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Journal articles on the topic 'Condition monitoring; 3-phase induction motors'
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1
Hsueh, Ittangihala, Wu, Chang, and Kuo. "Condition Monitor System for Rotation Machine by CNN with Recurrence Plot." Energies 12, no. 17 (August 21, 2019): 3221. http://dx.doi.org/10.3390/en12173221.
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Induction motors face various stresses under operating conditions leading to some failure modes. Hence, health monitoring for motors becomes essential. In this paper, we introduce an effective framework for fault diagnosis of 3-phase induction motors. The proposed framework mainly consists of two parts. The first part explains the preprocessing method, in which the time-series data signals are converted into two-dimensional (2D) images. The preprocessing method generates recurrence plots (RP), which represent the transformation of time-series data such as 3-phase current signals into 2D texture images. The second part of the paper explains how the proposed convolutional neural network (CNN) extracts the robust features to diagnose the induction motor’s fault conditions by classifying the images. The generated RP images are considered as input for the proposed CNN in the texture image recognition task. The proposed framework is tested on the dataset collected from different 3-phase induction motors working with different failure modes. The experimental results of the proposed framework show its competitive performance over traditional methodologies and other machine learning methods.
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Laadjal, Khaled, Mohamed Sahraoui, Abdeldjalil Alloui, and Antonio J. Marques Cardoso. "Three-Phase Induction Motors Online Protection against Unbalanced Supply Voltages." Machines 9, no. 9 (September 20, 2021): 203. http://dx.doi.org/10.3390/machines9090203.
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Three-phase induction motors (IMs) are the main workhorse in industry due to their many advantages as compared to other types of industrial motors. However, the efficiency and lifetime of IMs can be considerably affected by some operating conditions, in particular those related to unbalanced supply voltages (USV), which is quite a common condition in industrial plants. Therefore, early detection and a precise severity estimation of the USV for all working conditions can prevent major breakdowns and increase reliability and safety of industrial facilities. This paper proposes a reliable method allowing for a precise and online detection of the USV condition, by monitoring a pertinent indicator calculated using the voltage symmetrical components. The effectiveness of the proposed method is validated experimentally for several different working conditions, and a comparison with other indicators available in the literature is also performed.
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Kashirskikh, Veniamin, Valery Zavyalov, Irina Semykina, and Valery Borovtsov. "The Computer System for Monitoring of Induction Motors Condition of Mining Machinery." E3S Web of Conferences 105 (2019): 03023. http://dx.doi.org/10.1051/e3sconf/201910503023.
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The possibility of carrying out monitoring of parameters and variables of the induction electric motor (IM) working as a part of the electric mining machinery drive is considered. Monitoring is carried out on the working inventory in real time by means of the computer system on the basis of the IM mathematical model, mathematical estimation methods and also information which is contained in easily measured phase tension and IM stator currents. As a result IM indicators are defined difficult or cannot be measured in the mining machinery operation course. These are the active and induced windings resistances of a stator and a rotor, a magnetic linkage, an angular frequency of a rotor rotation and the electromagnetic moment. Algorithms of dynamic IM identification and the software are developed for carrying out monitoring. Theoretical provisions and conclusions are confirmed with results of the pilot studies. Information received during monitoring can be used for perfecting of the electric drive.
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Shnibha, R., A. Albarbar, A. Abouhnik, and G. Ibrahim. "A More Reliable Method for Monitoring the Condition of Three-Phase Induction Motors Based on Their Vibrations." ISRN Mechanical Engineering 2012 (October 18, 2012): 1–9. http://dx.doi.org/10.5402/2012/230314.
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This paper is concerned with accurate, early, and reliable fault diagnosis using an enhanced vibration measurement technique based on short-time Fourier transform. The novelty of this work lies in detecting very low-phase imbalance-related faults. The energy contained within specified frequency bands centred on the rotor frequency and power supply frequency, and their sideband zones were calculated. The technique was firstly demonstrated by simulated signals and then verified by experimental measurements taken from two different-sized test rigs. The first one comprised a 1.1 kW variable speed three-phase induction motor with varying output load (no load, 25%, 50%, 75%, and 100% load). Two types of common faults were introduced: imbalance in one phase as the electrical fault and misalignment of load as the mechanical fault. The second test rig had a 3 kW three-phase induction motor again with varying load, and here the two seeded faults were: phase imbalance and one broken rotor bar. The measured energy levels in the test conditions were found to be affected by type of fault and fault severity. It is concluded that the proposed method offers a potentially reliable and computationally inexpensive condition monitoring tool which can be implemented with real-time monitoring systems.
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Mustafa, Mohammed Obaid. "Broken rotor bars fault detection in induction motors based on current envelope and neural network." Eastern-European Journal of Enterprise Technologies 3, no. 2 (111) (June 30, 2021): 88–95. http://dx.doi.org/10.15587/1729-4061.2021.227315.
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The growing demand for dependable manufacturing techniques has sped up research into condition monitoring and fault diagnosis of critical motor parts. On the other hand, in modern industry, machine maintenance is becoming increasingly necessary. An insufficient maintenance strategy can result in unnecessarily high downtime or accidental machine failure, resulting in significant financial and even human life losses. Downtime and repair costs rise as a result of failure. Furthermore, developing an online condition monitoring method may be one solution to come up for the problem. Early detection of faults is very vital since they grow quickly and can cause further problems to the motor. This paper proposes an effective strategy for the classification of broken rotor bars (BRBs) for induction motors (IMs) that uses a new approach based on Artificial Neural Network (ANN) and stator current envelope. The stator current envelope is extracted using the cubic spline interpolation process. This is based on the idea that the amplitude-modulated motor current signal can be revealed using the motor current envelope. The stator current envelope is used to select seven features, which will be used as input for the neural network. Five IM conditions were experimentally used in this study, including a part of BRB, 1 BRB, 2 BRBs and 3 BRBs. The new feature extraction and selection approach achieves a higher level of accuracy than the conventional method for motor fault classification, according to the experimental results. Indeed, the results are impressive, and it is capable of detecting the exact number of broken rotor bars under full load conditions
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Lucas, M., and W. T. Thomson. "A study of the natural vibratory response of stator structures to improve condition monitoring strategies for induction motors." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 212, no. 1 (January 1, 1998): 57–68. http://dx.doi.org/10.1243/0954406981521042.
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On-line condition monitoring is widely used to detect failure mechanisms in large highvoltage three-phase induction motors. The high-voltage winding is installed in a complex, stator core structure which vibrates due to electromagnetic forces. Insulation degradation can be diagnosed via on-line monitoring of partial discharges but the fundamental cause is often mechanical damage due to stator vibration. This paper presents results of an investigation into the natural vibratory response of the complete stator assembly. Results from finite element models of complex stator assemblies, including the frames, are supported by experimental measurements. These include freely suspended stator cores as in previous studies, and also now introduce the much more realistic condition of the complete stator assembly securely bolted on to a solid baseplate. The knowledge gathered in this study will aid the application of a vibration monitoring strategy to detect stator core vibration which can lead to winding insulation damage.
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Prakash, Chandra, and Rakesh Kumar Saini. "Crop Field Monitoring Platform: IoT-Based Monitoring and Controlling of Crop Field and Induction Motor Protection from Voltage Fluctuation." International Innovative Research Journal of Engineering and Technology 6, no. 2 (December 30, 2020): CS—1—CS—7. http://dx.doi.org/10.32595/iirjet.org/v6i2.2020.136.
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The impassable use of technologies contributes to on condition that the accurate amount of water needed by plants. Agricultural country like India, where more than 70% of rural population depends on farming and contributes around 18% to the GDP. Despite of having modern facilities, farmers are still using traditional methods for irrigation. The main reason is the lack of knowledge and the cost of resources are too high which cannot bear by the farmers. It is mostly seen that the farmer uses ground water for irrigation. The management of ground water for irrigation is essential, while contributing to environmental sustainability. Here the word management is to irrigate more and more using the least water. IoT technologies can be a better option to achieve this goal. IoT technology is used in management of ground water for irrigation in the agriculture. But the commonality of the same thing has been found in all systems i.e., the farmer has to buy lots of equipments to apply the smart irrigation. This paper implements a gadget that provide information of the crop situation like degree the resistance or conductivity across the soil matrix among two contacts are basically junk, soil disease sensor regulates while the seeds will germinate, and how rapid your flowers will develop in step with those data, microcontroller take the motion in form of induction motor gets ON/OFF, when it's far required. This paper is also aim to shield 3 phase induction motor from inrush currents on the spreading device like fluctuations and single phasing.
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Adam, Putri Ramadhani, Purwanto Gendroyono, and Nur Hanifah Yuninda. "MONITORING SUPLAI TEGANGAN PADA MOTOR INDUKSI TIGA FASA MENGGUNAKAN MIKROKONTROLER ARDUINO DAN SENSOR TEGANGAN ZMPT101B." Journal of Electrical Vocational Education and Technology 5, no. 2 (December 16, 2020): 37–43. http://dx.doi.org/10.21009/jevet.0052.06.
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ABSTRACT
The purpose of this study is to create a three-phase induction motor voltage monitoring system based on Arduino Uno microcontroller using a ZMPT101B voltage sensor. In addition, this study aims to determine the percentage of source voltage unbalance entering the 3 phase induction motor based on the National Standard for Electric Power System and Equipment ANSI Std C84.1-1995, NEMA Std MGI.2009 from the results of monitoring equipment that has been was made. The research method used by the author is a laboratory experimental method which includes manipulation, control, and observation.
The results showed that the value of the percentage of voltage unbalance, the average for the morning the value is still below 1%. As for the value of the percentage of voltage unbalance in the afternoon and evening, the value is already above 1%. If according to the standard, the percentage of voltage unbalance permitted without derating (decreasing power) based on NEMA is 1%. Meanwhile, the maximum percentage of allowable voltage unbalance is 5%. So, the results of the research data of the three times the safest condition is in the morning. Meanwhile, research data taken during the afternoon and evening conditions are still safe but there will be a decrease in power. In addition, the comparison of the ZMPT101B voltage sensor with a digital AVO meter when detecting the voltage has an average error of 0.07% for the first ZMPT101B voltage sensor, 0.28% for the second ZMPT101B voltage sensor and 0.15% for the sensor the third voltage ZMPT101B. So that it can be said that the voltage monitoring system that is made in accordance with the provisions and can be applied as learning by students of Electrical Engineering Education.
ABSTRAK
Penelitian ini bertujuan untuk membuat sistem monitoring suplai tegangan motor induksi tiga fasa berbasis mikrokontroler Arduino Uno menggunakan sensor tegangan ZMPT101B. Selain itu, dalam penelitian ini bertujuan untuk mengetahui persentase ketidakseimbangan tegangan sumber yang masuk pada motor induksi 3 fasa berdasarkan standar The National Standard for Electric Power System and Equipment ANSI Std C84.1-1995, NEMA Std MGI.2009 dari hasil monitoring alat yang telah dibuat. Metode penelitian yang digunakan penulis yaitu metode eksperimen laboratorium yang meliputi manipulasi, pengendalian, dan pengamatan.
Hasil penelitian menunjukkan bahwa nilai persentase ketidakseimbangan tegangan, rata rata untuk di waktu pagi nilainya masih di bawah 1 %. Sedangkan untuk nilai persentase ketidakseimbangan tegangan di waktu siang dan sore hari nilainya sudah di atas 1 %. Jika sesuai dengan standar, persentase ketidakseimbangan tegangan yang diijinkan tanpa melakukan derating (penurunan daya) berdasarkan NEMA adalah 1 %. Sedangkan, maksimum persentase ketidakseimbangan tegangan yang diijinkan adalah 5 %. Maka, hasil dari data penelitian ketiga waktu tersebut yang paling aman kondisinya adalah di waktu pagi hari. Sedangkan, data penelitian yang diambil saat siang dan sore hari kondisinya masih aman tetapi akan ada penurunan daya. Selain itu, Perbandingan sensor tegangan ZMPT101B dengan alat ukur AVO meter digital saat mendeteksi tegangan memiliki error rata-rata yaitu 0,07 % untuk sensor tegangan ZMPT101B yang pertama, 0,28 % untuk sensor tegangan ZMPT101B yang kedua dan 0,15 % untuk sensor tegangan ZMPT101B yang ketiga. Sehingga dapat dikatakan bahwa sistem monitoring tegangan yang dibuat sesuai dengan ketentuan dan bisa diaplikasikan sebagai pembelajaran mahasiswa Pendidikan Teknik Elektro.
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Sinha, Ashish Kumar, Sukanta Das, and Tarun Kumar Chatterjee. "Empirical relation for broken bar determination in SCIM." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 37, no. 1 (January 2, 2018): 242–65. http://dx.doi.org/10.1108/compel-11-2016-0515.
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Purpose Condition monitoring of squirrel cage induction motors (SCIMs) is indispensible for achieving fault-free working environment. As broken rotor bars (BRBs) are one of the more frequent faults in a SCIM especially where direct-on-line starting is indispensible, as in underground mines, a priori knowledge of fault severity in terms of the number of BRBs assists in effective fault monitoring. In this regard, this paper aims to propose a unique empirical relation to facilitate the determination of number of BRB. Design/methodology/approach Fast Fourier transform is used to obtain fault sideband amplitudes under varying number of BRBs and load torque for 5.5 kW, 7.5 kW, 10 kW, three-phase, 415 V, 50 Hz SCIMs in MATLAB/Simulink. The nature of variation is decided by an appropriate curve fitting technique for comprehending a unique empirical relation. The proposed empirical relation is validated by bootstrapping and z-test. Furthermore, hardware validation is done using 1 kW laboratory prototype with Labview interface. Findings The analytical study reveals the dependence of lower and upper sideband amplitudes on the number of BRBs, load torque and machine rating. Therefore, fault severity in terms of number of BRBs is accurately calculated using the proposed empirical relation if load torque, machine rating and amplitudes of lower and upper sidebands are known. Originality/value The unique empirical relation proposed in the present work provides accurate knowledge of fault severity in terms of the number of BRBs. This facilitates maintenance scheduling which shall reduce effective downtime and improve production.
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Ciancetta, Fabrizio, Edoardo Fiorucci, Antonio Ometto, Andrea Fioravanti, Simone Mari, and Maria-Anna Segreto. "A Low-Cost IoT Sensors Network for Monitoring Three-Phase Induction Motor Mechanical Power Adopting an Indirect Measuring Method." Sensors 21, no. 3 (January 23, 2021): 754. http://dx.doi.org/10.3390/s21030754.
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Three-phase induction motors are widely diffused in the industrial environment. Many times, the rated power of three-phase induction motors is not properly chosen causing incorrect operating conditions from an energetic point of view. Monitoring the mechanical dimension of a new motor is helpful, should an existing motor need to be replaced. This paper presents an IoT sensors network for monitoring the mechanical power produced by three-phase induction motors, adopting an indirect measuring method. The proposed technique can be easily adopted to monitor the mechanical power using only one line of current transducer, reducing the cost of the monitoring system. The proposed indirect measurement technique has been implemented on a low-cost IoT system, based on a Photon Particle SoC. The results show that the proposed IoT system can estimate the mechanical power with a relative error of within 8%.
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Sari Hartati, Prof Rukmi, Ida Bagus Gede Manuaba, and I. Made Mataram. "Induction Motor Monitoring System Base on Fuzzy Logic Controller." Journal of Electrical, Electronics and Informatics 4, no. 1 (February 29, 2020): 15. http://dx.doi.org/10.24843/jeei.2020.v04.i01.p03.
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Squirrel cage induction motor is an AC electric motor that is most widely used in industry. This type of motor is chosen because it does not have a commutation brush, and its construction is strong, so it can withstand large, easy flow surges for repair and maintenance. The problem that often occurs is the imbalance of supply voltage which causes motor efficiency to decrease. An imbalance of voltage will result in a current not equal. As a result of phase currents that are much larger than other phases result in an increase in temperature and speed on the motor. This research was conducted to monitor the induction motor so that it can determine the condition of the motor when receiving a voltage imbalance.
The method used in the induction motor condition monitoring system is the fuzzy logic method. Parameters that can be monitored are categorized into three conditions: normal (good) motor condition, damage (serious) and serious damage.
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Alawady, A. A., M. F. M. Yousof, N. Azis, and M. A. Talib. "Phase to phase fault detection of 3-phase induction motor using FRA technique." International Journal of Power Electronics and Drive Systems (IJPEDS) 11, no. 3 (September 1, 2020): 1241. http://dx.doi.org/10.11591/ijpeds.v11.i3.pp1241-1248.
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The purpose for preparing this paper is to innovate a new method to detection and diagnosis the three-phase induction motor electrical failures, especially the failures that occur in Stator winding. Stator winding breakdown largely contributes to induction motor failures. To understand internal fault in induction motors winding, four cases studies of different three-phase induction motors (TPIM) were analysed according to two conditions: normal winding condition and windings shorted between two phases. In this paper, the measurement of frequency response analysis (FRA) on the stator winding with inter-phase short is presented. Additionally, Frequency Response Analysis (FRA) interpretation technique classify and quantify the fault is also proposed. For interpretation of the FRA, a statistical indicator, which is NCEPRI algorithm is used for comparison the measured responses.
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Podduturi, Sai Sharath. "Condition Monitoring of Three Phase Induction Motor using Current Signature Analysis." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 20, 2021): 1946–55. http://dx.doi.org/10.22214/ijraset.2021.35491.
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In this paper we are going to see how Gabor transform is used to analyze the signal and to determine the inner and outer race of bearing faults by monitoring the condition of Induction motor using Motor Current Signature Analysis. Among the various faults bearing faults is the major problem, which cause a huge damage to induction motor, when unnoticed at developing stage. So, monitoring of bearing faults is very important and it can done by several conditions monitoring methods like thermal monitoring, vibration monitoring and more but these methods require expensive sensors or specified tools, whereas current monitoring methods doesn’t require any additional tools. Usually, this condition monitoring is used to detect the various faults like bearing faults, load faults by MCSA. If the fault is present in the motor, the frequency spectrum of the line current is different from healthy ones, the Gabor analysis detects the fault signature generated in the induction motor, by using mathematical expressions and calculate the RMS and Standard deviation values, these fault values are different from healthy ones. Through this we can identify faults.
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NISTOR, C. G., G. SCUTARU, R. CAMPEANU, and M. CERNAT. "Noise and Vibration Monitoring for Premium Efficiency IE 3 Three-Phase Induction Motors." Advances in Electrical and Computer Engineering 15, no. 3 (2015): 117–22. http://dx.doi.org/10.4316/aece.2015.03017.
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Abitha, Memala W., and V. Rajini. "Virtual Instrumentation Based Analysis of Induction Motor." Advanced Materials Research 984-985 (July 2014): 970–76. http://dx.doi.org/10.4028/www.scientific.net/amr.984-985.970.
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The three phase induction motor is a popularly used machine in many of the industries, which is well known for its robustness, reliability, cost effectiveness, efficient and safe operation. The unnoticed manufacturing failure, mistakes during repair work, exceeding life time may be some of the causes of the induction motor failure, which may lead to the unknown shut down time of the industry. The condition monitoring plays important role as it has the influence on the production of materials and profit. In our work, the induction motor is modelled using stationary reference frame and analysed for single phasing stator fault. The techniques used in detecting the single phasing (open circuit) failures are Park’s vector approach and Fast Fourier Transform (FFT). Park’s vector approach is used for detecting the faults occurring at various phases and FFT is used for detecting the faults of the induction motor working under no load and varying loading conditions.
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Enany, T. A., W. I. Wahba, and M. A. Moustafa Hassan. "A Remote and Sensorless Stator Winding Temperature Estimation Method for Thermal Protection for Induction Motor." International Journal of System Dynamics Applications 3, no. 3 (July 2014): 53–72. http://dx.doi.org/10.4018/ijsda.2014070103.
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Three-phase induction motors are the “workhorses” of industry; they are the most widely used electrical machine; because of its simple structure and high reliability. This paper proposes a new technique to model the stator winding of the induction motor in Matlab Simulink® software. This simulation of the induction motor would have the thermal behavior of its stator winding; to study the induction motor temperature estimation using motor parameter-based method. The modified model is used to validate a remote and Sensorless stator winding temperature estimation technique; therefore a thermal protection is obtained for soft-starter-connected to induction motors. The soft-starter is used to inject a DC signal in the induction motor terminal voltage and current. The stator winding resistance/temperature is estimated from DC signal injection by changing the gate drive signals of the Thyristor in the soft starter. The level of the injected DC signal is adjusted by the value of the delay angle. The accuracy of stator winding temperature estimation increased with the increase of DC signal level; however the pulsation of the output torque increased also. The thermal behavior is simulated utilizing a thermal resistor block from the Matlab Simscape™ software. It is used to replace the fixed resistor value of the induction motor model in the Matlab Simulink. The thermal monitoring scheme has been validated from the simulation results of a 7.5 kW induction motor under various loading conditions.
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Jannati, Mohammad, and Tole Sutikno. "Modelling of a 3-Phase Induction Motor Under Open-Phase Fault Using Matlab/Simulink." International Journal of Power Electronics and Drive Systems (IJPEDS) 7, no. 4 (December 1, 2016): 1146. http://dx.doi.org/10.11591/ijpeds.v7.i4.pp1146-1152.
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The d-q model of Induction Motors (IMs) has been effectively used as an efficient method to analyze the performance of the induction machines. This study presents a step by step Matlab/Simulink implementation of a star-connected 3-phase IM under open-phase fault (faulty 3-phase IM) using d-q model. The presented technique in this paper can be simply implemented in one block and can be made available for control purposes. The simulated results provide to show the behavior of the star-connected 3-phase IM under open-phase fault condition.
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Alsayid, Basim. "Experimental Investigation and Analysis of Induction Motors Operation under Single-Phasing Condition." مجلة جامعة فلسطين التقنية خضوري للأبحاث 8, no. 2 (September 1, 2020): 90–99. http://dx.doi.org/10.53671/ptukrj.v8i2.94.
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A three-phase induction motor will continue to operate when a disturbance of some sort causes the source voltages of the motor to become unbalanced. When an induction motor is operated at unbalanced voltage supply the performance characteristics like efficiency, power factor, input power, output power and losses are affected. The single-phasing occurs when one phase fails as a result of a fuse blowing, protective device opening on one phase of the motor, open phase on one terminal of the motor or other causes. This paper will analyze the operation of a 3-phase induction motor under normal balanced source voltages first, then under single phasing experimentally in order to follow a comparative approach.
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Alsayid, Basim. "Experimental Investigation and Analysis of Induction Motors Operation under Single-Phasing Condition." مجلة جامعة فلسطين التقنية للأبحاث 8, no. 2 (September 1, 2020): 90–99. http://dx.doi.org/10.53671/pturj.v8i2.94.
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A three-phase induction motor will continue to operate when a disturbance of some sort causes the source voltages of the motor to become unbalanced. When an induction motor is operated at unbalanced voltage supply the performance characteristics like efficiency, power factor, input power, output power and losses are affected. The single-phasing occurs when one phase fails as a result of a fuse blowing, protective device opening on one phase of the motor, open phase on one terminal of the motor or other causes. This paper will analyze the operation of a 3-phase induction motor under normal balanced source voltages first, then under single phasing experimentally in order to follow a comparative approach.
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Fulzele, Asmita G., V. G. Arajpure, P. P. Holay, and N. M. Patil. "Condition monitoring of shaft of single-phase induction motor using optical sensor." Mechanical Systems and Signal Processing 29 (May 2012): 428–35. http://dx.doi.org/10.1016/j.ymssp.2011.12.002.
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Sinan Cabuk, Ali. "Data acquisition system for induction motors with arduino." International Conference on Technics, Technologies and Education, ICTTE 2019 (2019): 256–62. http://dx.doi.org/10.15547/ictte.2019.04.090.
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Data acquisition systems have been used for many years in order to conduct analyses to increase efficiency, measure performance and detect failures in electrical motors.High costs and not being of modular use have prevented these systems from being commonly used. Various methods were developed for data acquisition from electrical machines. This paper presents data acquisition analysing and monitoring system using Arduino platform. Vibration, temperature and current values of a 3 phase induction motor are obtained by this data acquisition system via USB port. A system compatiable with all sorts of settings and of low cost was obtained as a result of using Arduino where data processing is conducted on a computer. Values obtained from the data collection system used in this study were found to be supportive to the values shown by the measurement devices from 3 phase induction motor.
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Patel, R. K., and V. K. Giri. "Condition monitoring of induction motor bearing based on bearing damage index." Archives of Electrical Engineering 66, no. 1 (March 1, 2017): 105–19. http://dx.doi.org/10.1515/aee-2017-0008.
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Abstract The rolling element bearings are used broadly in many machinery applications. It is used to support the load and preserve the clearance between stationary and rotating machinery elements. Unfortunately, rolling element bearings are exceedingly prone to premature failures. Vibration signal analysis has been widely used in the faults detection of rotating machinery and can be broadly classified as being a stationary or non-stationary signal. In the case of the faulty rolling element bearing the vibration signal is not strictly phase locked to the rotational speed of the shaft and become “transient” in nature. The purpose of this paper is to briefly discuss the identification of an Inner Raceway Fault (IRF) and an Outer Raceway Fault (ORF) with the different fault severity levels. The conventional statistical analysis was only able to detect the existence of a fault but unable to discriminate between IRF and ORF. In the present work, a detection technique named as bearing damage index (BDI) has been proposed. The proposed BDI technique uses wavelet packet node energy coefficient analysis method. The well-known combination of Hilbert transform (HT) and Fast Fourier Transform (FFT) has been carried out in order to identify the IRF and ORF faults. The results show that wavelet packet node energy coefficients are not only sensitive to detect the faults in bearing but at the same time they are able to detect the severity level of the fault. The proposed bearing damage index method for fault identification may be considered as an ‘index’ representing the health condition of rotating machines.
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Hussein, H. A. Taha, M. E. Ammar, and M. A. Moustafa Hassan. "Three Phase Induction Motor's Stator Turns Fault Analysis Based on Artificial Intelligence." International Journal of System Dynamics Applications 6, no. 3 (July 2017): 1–19. http://dx.doi.org/10.4018/ijsda.2017070101.
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This article presents a method for fault detection and diagnosis of stator inter-turn short circuit in three phase induction machines. The technique is based on modelling the motor in the dq frame for both health and fault cases to facilitate recognition of motor current. Using an Adaptive Neuro-Fuzzy Inference System (ANFIS) to provide an efficient fault diagnosis tool. An artificial intelligence network determines the fault severity values using the stator current history. The performance of the developed fault analysis method is investigated using Matlab/Simulink® software. Stator turns faults are detected through current monitoring of a 2 Hp three phase induction motor under various loading conditions. Fault history is calculated under various loading conditions, and a wide range of fault severity.
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Sreejeth, Mini, Parmod Kumar, and Madhusudan Singh. "Distributed Drives Monitoring and Control: A Laboratory Setup." Journal of Engineering 2013 (2013): 1–10. http://dx.doi.org/10.1155/2013/924928.
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A laboratory setup of distributed drives system comprising a three-phase induction motor (IM) drive and a permanent magnet synchronous motor (PMSM) drive is modeled, designed, and developed for the monitoring and control of the individual drives. The integrated operation of IM and PMSM drives system has been analyzed under different operating conditions, and their performance has been monitored through supervisory control and data acquisition (SCADA) system. The necessary SCADA graphical user interface (GUI) has also been created for the display of drive parameters. The performances of IM and PMSM under parametric variations are predicted through sensitivity analysis. An integrated operation of the drives is demonstrated through experimental and simulation results.
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Reljic, Dejan, Josif Tomic, and Zeljko Kanovic. "Application of the Goertzel’s algorithm in the airgap mixed eccentricity fault detection." Serbian Journal of Electrical Engineering 12, no. 1 (2015): 17–32. http://dx.doi.org/10.2298/sjee1501017r.
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In this paper, a suitable method for the on-line detection of the airgap mixed eccentricity fault in a three-phase cage induction motor has been proposed. The method is based on a Motor Current Signature Analysis (MCSA) approach, a technique that is often used for an induction motor condition monitoring and fault diagnosis. It is based on the spectral analysis of the stator line current signal and the frequency identification of specific components, which are created as a result of motor faults. The most commonly used method for the current signal spectral analysis is based on the Fast Fourier transform (FFT). However, due to the complexity and memory demands, the FFT algorithm is not always suitable for real-time systems. Instead of the whole spectrum analysis, this paper suggests only the spectral analysis on the expected airgap fault frequencies employing the Goertzel?s algorithm to predict the magnitude of these frequency components. The method is simple and can be implemented in real-time airgap mixed eccentricity monitoring systems without much computational effort. A low-cost data acquisition system, supported by the LabView software, has been used for the hardware and software implementation of the proposed method. The method has been validated by the laboratory experiments on both the line-connected and the inverter-fed three-phase fourpole cage induction motor operated at the rated frequency and under constant load at a few different values. In addition, the results of the proposed method have been verified through the motor?s vibration signal analysis.
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Sudhakar, I., S. AdiNarayana, and M. AnilPrakash. "Condition Monitoring of a 3-Ø Induction Motor by Vibration Spectrum anaylsis using Fft Analyser- A Case Study." Materials Today: Proceedings 4, no. 2 (2017): 1099–105. http://dx.doi.org/10.1016/j.matpr.2017.01.125.
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Treetrong, Juggrapong. "Application of Signal Processing for Motor Condition Monitoring Based on Filtered-Signals and Eliminated-Signals." Advanced Materials Research 378-379 (October 2011): 557–60. http://dx.doi.org/10.4028/www.scientific.net/amr.378-379.557.
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This paper proposes new procedures of motor fault detection. The proposed methods are based on filtered-signals and eliminated-signals. Generally, the raw stator phase currents collected from the motors are firstly filtered in order to get rid of measurement noises. If the new signals are called “Filtered-Signals” and the signals eliminated from the raw stator phase currents are called “Eliminated-Signals”. The first proposed procedure is to detect the motor faults by spectrum of PSD slope from the filtered-signals. The second proposed procedure is to detect the motor faults by spectrum of the eliminated-signals. The both methods are tested on 3 different motor conditions: healthy, stator fault, and rotor fault motor at full load condition. The experiments show that the both methods can differentiate conditions clearly and they also can indicate the levels of fault severity. Thus, it can be effective when the both methods are applied simultaneously to analyze the faults
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de Carvalho, Daniel P., Fernando B. Silva, Wagner E. Vanço, Felipe A. da Silva Gonçalves, Carlos A. Bissochi, Raul V. A. Monteiro, Geraldo C. Guimarães, and Darizon A. de Andrade. "A method for real-time wireless monitoring of the efficiency and conditions of three-phase induction motor operation." Electric Power Systems Research 157 (April 2018): 70–82. http://dx.doi.org/10.1016/j.epsr.2017.12.009.
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Tang, Jing, Jie Chen, Kan Dong, Yongheng Yang, Haichen Lv, and Zhigang Liu. "Modeling and Evaluation of Stator and Rotor Faults for Induction Motors." Energies 13, no. 1 (December 26, 2019): 133. http://dx.doi.org/10.3390/en13010133.
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The modeling of stator and rotor faults is the basis of the development of online monitoring techniques. To obtain reliable stator and rotor fault models, this paper focuses on dynamic modeling of the stator and rotor faults in real-time, which adopts a multiple-coupled-circuit method by using a winding function approach for inductance calculation. Firstly, the model of the induction machine with a healthy cage is introduced, where a rotor mesh that consists of a few rotor loops and an end ring loop is considered. Then, the stator inter-turn fault model is presented by adding an extra branch with short circuit resistance on the fault part of a stator phase winding. The broken rotor bar fault is then detailed by merging and removing the broken-bar-related loops. Finally, the discrete models under healthy and faulty conditions are developed by using the Tustin transformation for digital implementation. Moreover, the stator and rotor mutual inductances are derived as a function of the rotor position according to the turn and winding functions distribution. Simulations and experiments are performed on a 2.2-kW/380-V/50-Hz three-phase and four-pole induction motor to show the performance of the stator and rotor faults, where the saturation effect is considered in simulations by exploiting the measurements of a no load test. The simulation results are in close agreement with the experimental results. Furthermore, magnitudes of the characteristic frequencies of 2f1 in torque and (1 ± 2s)f1 in current are analyzed to evaluate the stator and rotor fault severity. Both indicate that the stator fault severity is related to the short circuit resistance. Further, the number of shorted turns and the number of continuous broken bars determines the rotor fault severity.
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O. Alwan, Hayder, and Qais S- Al-Sabbagh. "Designand application of data aquistion interface circuit." International Journal of Engineering & Technology 7, no. 2.6 (March 11, 2018): 247. http://dx.doi.org/10.14419/ijet.v7i2.6.10778.
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A commitment to condition monitoring involves the operators of plant in the conduct of a range of activities. These activities may be complicated in nature and indeed may often be performed automatically under computer control. They can, however, always be down into a relatively small number of easily identifiable functional tasks. This makes it much easier to identify the common elements of machine condition monitoring schemes. A proposed interface circuit design and application will be further explain in this paper, the implemented monitoring unit circuit also illustrated, see appendix A. Two scenarios presented in this paper, first ten turns assume to be shorted, and in the second thirty turns shorted to show the difference in the amplitude of frequencies at each case. This paper present. An improvement in three-phase squirrel-cage induction motor stator inter-turn fault detection and diagnosis based on a neural network approach is presented.
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Huang, Baoshan, Guojin Feng, Xiaoli Tang, James Xi Gu, Guanghua Xu, Robert Cattley, Fengshou Gu, and Andrew D. Ball. "A Performance Evaluation of Two Bispectrum Analysis Methods Applied to Electrical Current Signals for Monitoring Induction Motor-Driven Systems." Energies 12, no. 8 (April 15, 2019): 1438. http://dx.doi.org/10.3390/en12081438.
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This paper investigates the performance of the conventional bispectrum (CB) method and its new variant, the modulation signal bispectrum (MSB) method, in analysing the electrical current signals of induction machines for the condition monitoring of rotor systems driven by electrical motors. Current signal models which include the phases of the various electrical and magnetic quantities are explained first to show the theoretical relationships of spectral sidebands and their associated phases due to rotor faults. It then discusses the inefficiency of CB and the proficiency of MSB in characterising the sidebands based on simulated signals. Finally, these two methods are applied to analyse current signals measured from different rotor faults, including broken rotor bar (BRB), downstream gearbox wear progressions and various compressor faults, and the diagnostic results show that the MSB outperforms the CB method significantly in that it provides more accurate and sparse diagnostics, thanks to its unique capability of nonlinear modulation detection and random noise suppression.
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Barcelos, Andre S., and Antonio J. Marques Cardoso. "Current-Based Bearing Fault Diagnosis Using Deep Learning Algorithms." Energies 14, no. 9 (April 27, 2021): 2509. http://dx.doi.org/10.3390/en14092509.
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Artificial intelligence algorithms and vibration signature monitoring are recurrent approaches to perform early bearing damage identification in induction motors. This approach is unfeasible in most industrial applications because these machines are unable to perform their nominal functions under damaged conditions. In addition, many machines are installed at inaccessible sites or their housing prevents the setting of new sensors. Otherwise, current signature monitoring is available in most industrial machines because the devices that control, supply and protect these systems use the stator current. Another significant advantage is that the stator phases lose symmetry in bearing damaged conditions and, therefore, are multiple independent sources. Thus, this paper introduces a new approach based on fractional wavelet denoising and a deep learning algorithm to perform a bearing damage diagnosis from stator currents. Several convolutional neural networks extract features from multiple sources to perform supervised learning. An information fusion (IF) algorithm then creates a new feature set and performs the classification. Furthermore, this paper introduces a new method to achieve positive unlabeled learning. The flattened layer of several feature maps inputs the fuzzy c-means algorithm to perform a novelty detection instead of clusterization in a dynamic IF context. Experimental and on-site tests are reported with promising results.
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Nishat Toma, Rafia, Cheol-Hong Kim, and Jong-Myon Kim. "Bearing Fault Classification Using Ensemble Empirical Mode Decomposition and Convolutional Neural Network." Electronics 10, no. 11 (May 24, 2021): 1248. http://dx.doi.org/10.3390/electronics10111248.
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Condition monitoring is used to track the unavoidable phases of rolling element bearings in an induction motor (IM) to ensure reliable operation in domestic and industrial machinery. The convolutional neural network (CNN) has been used as an effective tool to recognize and classify multiple rolling bearing faults in recent times. Due to the nonlinear and nonstationary nature of vibration signals, it is quite difficult to achieve high classification accuracy when directly using the original signal as the input of a convolution neural network. To evaluate the fault characteristics, ensemble empirical mode decomposition (EEMD) is implemented to decompose the signal into multiple intrinsic mode functions (IMFs) in this work. Then, based on the kurtosis value, insignificant IMFs are filtered out and the original signal is reconstructed with the rest of the IMFs so that the reconstructed signal contains the fault characteristics. After that, the 1-D reconstructed vibration signal is converted into a 2-D image using a continuous wavelet transform with information from the damage frequency band. This also transfers the signal into a time-frequency domain and reduces the nonstationary effects of the vibration signal. Finally, the generated images of various fault conditions, which possess a discriminative pattern relative to the types of faults, are used to train an appropriate CNN model. Additionally, with the reconstructed signal, two different methods are used to create an image to compare with our proposed image creation approach. The vibration signal is collected from a self-designed testbed containing multiple bearings of different fault conditions. Two other conventional CNN architectures are compared with our proposed model. Based on the results obtained, it can be concluded that the image generated with fault signatures not only accurately classifies multiple faults with CNN but can also be considered as a reliable and stable method for the diagnosis of fault bearings.
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Venugopal, Chitra, and Thershen Govender. "Load power and energy management system using proteus visual design software." Indonesian Journal of Electrical Engineering and Computer Science 20, no. 2 (November 1, 2020): 1044. http://dx.doi.org/10.11591/ijeecs.v20.i2.pp1044-1052.
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At present, there is a serious energy crisis around the globe which impacts greatly on the power grid. A smart and user friendly energy management system can control the energy consumption. In this paper, load power and energy management system is developed and simulated using Proteus Visual Design software. The load analysis and measurement techniques are developed for single phase and three phase loads and implemented using Arduino Mega 2560 board. User friendly controls are developed using the visual design feature of the software to control the energy consumption. The load power management system is simulated by measuring the power consumed by various residential loads such as lights, fans, air-conditioners, heaters. The industrial loads are simulated by squirrel cage induction motor. The load analysis summary is displayed on the Arduino 2.8 inch TFT display shield in a table format. The simulaion model is created for future hardware implementation and is tested under various practical input conditions. The Proteus Visual Design software is chosen in this resesarch due to its advantages such as professional PCB layout package, availability of nearly 800 microcontrollers in the library package etc.The developed model successfully measured the energy consumption of several loads and assist the user in controlling the energy usage through automation control techniques. The accuracy of the results shows that the technique and the model developed in this research can be used by engineers, students and hobbyists who are working with energy monitoring systems and smart home applications directly. This is an ongoing project where in the next stage, the hardware design of the simulation model will be implemented and tested in real time application.
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Altman, Jessica K., Tsila Zuckerman, Olga Frankfurt, Selina M. Luger, Dale L. Bixby, Vamsi Kota, Micah M. Burch, et al. "Aspacytarabine (BST-236) Is Safe and Efficacious As a Single-Agent, First-Line Therapy for Patients with Acute Myeloid Leukemia Unfit for Standard Chemotherapy. Integrated Results from a Phase 1/2a and an Ongoing Phase 2b." Blood 134, Supplement_1 (November 13, 2019): 179. http://dx.doi.org/10.1182/blood-2019-124330.
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Introduction: Aspacytarabine (BST-236) is a prodrug of cytarabine, a backbone of acute myeloid leukemia (AML) therapy. Due to its unique pharmacokinetics and metabolism, treatment with aspacytarabine evades peak exposure to free cytarabine, which reduces non-hematological toxicity and enables delivery of high-dose cytarabine also to patients unfit for standard therapy. Data from a completed phase 1/2a and an ongoing phase 2b studies in AML patients unfit for standard therapy, including patients with AML secondary to therapy and myelodysplastic syndrome (MDS) with prior exposure to hypomethylating agents (HMA), demonstrate promising single-agent efficacy and safety of aspacytarabine as a potential first-line AML treatment for this challenging population. Aims: To evaluate the efficacy and safety of aspacytarabine in AML patients unfit for standard induction therapy. Methods: A completed phase 1/2a study and an ongoing phase 2b study evaluate the efficacy and safety of aspacytarabine as a single-agent therapeutic for AML. The phase 1/2a, dose-escalation study enrolled newly-diagnosed patients unfit for standard therapy and patients with relapsed/refractory AML. Patients were treated with 0.3-6 g/m2/d aspacytarabine in 6 dose-escalating cohorts. The ongoing multi-center phase 2b study expands the subgroup of newly-diagnosed AML patients unfit for standard therapy, to evaluate the efficacy and safety of aspacytarabine as a first-line therapy for this population. Secondary AML patients, treated with HMA, chemotherapy, or radiotherapy for a prior condition, are allowed. Patients in the phase 2b study are treated with the selected aspacytarabine dose of 4.5 g/m2/d, containing approximately 3 g/m2/d of cytarabine. Each aspacytarabine treatment course (induction and consolidation) consists of 6 1-hour daily intravenous infusions. Results: To date, 34 AML patients, median age 76 years, received at least 1 dose of aspacytarabine, including 30 patients unfit for standard induction therapy due to age or comorbidities. Overall, 25 patients completed 1 course of aspacytarabine, 4 patients completed 2 courses, 1 patient completed 3 courses, and 1 patient completed 4 courses of aspacytarabine. Three patients (in the phase 1/2a study) did not complete the first course. Aspacytarabine was safe and well-tolerated in repeated-course administration, including in older and unfit patients. Adverse events included mainly hematological "on-target" events with no drug-related mucositis or cerebellar toxicity. Twenty-one patients were newly-diagnosed with AML, either de novo or secondary to MDS or therapy. The patient population was characterized by older age (median 76 years, range 67-88 years), and the majority (67%) of patients had secondary AML, including 10 patients (48%) who were previously treated with HMA (median of 10 courses) or radiotherapy. The median baseline bone marrow blast percentage of this population was 75, and 43% and 48% had intermediate or adverse European LeukemiaNet (ELN) cytogenetic score, respectively. Despite these poor-prognostic characteristics, the 30-day mortality rate in the group of patients receiving ≥4.5 g/m2/d aspacytarabine was 7%. The combined complete remission (CR) rate of all doses was 33%, including 1 patient reaching a CR with partial platelet recovery (CRp). The CR rate in patients treated with at least 4.5 g/m2/d aspacytarabine is 36%, with median time for complete hematological recovery of 27 days (range 21-30) following induction and consolidation. Notably, among the 7 patients who reached a CR/CRp (median age 77), 3 secondary AML patients reached a CR, including 2 patients with prior exposure to HMA (5 and 10 courses) and 1 with prior exposure to radiotherapy (Table 1). Duration of response and overall survival follow up is ongoing and will be presented at the meeting. Conclusions: The accumulating clinical data suggest that aspacytarabine is safe and efficacious for the treatment of AML patients who are unfit for standard induction therapy, including patients with prior exposure to HMA, which may establish aspacytarabine as a new therapeutic backbone for AML, either as a single agent or in combination with targeted therapy. Disclosures Altman: Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Glycomimetics: Consultancy, Honoraria, Other: Data Safety and Monitoring Committee; Daiichi Sankyo: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Biosight: Other: US Lead; Novartis: Consultancy; Agios: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Cancer Expert Now: Consultancy; France Foundation: Speakers Bureau; prIME Oncology: Speakers Bureau; PeerView: Speakers Bureau; Theradex: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Luger:Seattle Genetics: Research Funding; Pfizer: Honoraria; Onconova: Research Funding; Kura: Research Funding; Jazz: Honoraria; Genetech: Research Funding; Daichi Sankyo: Honoraria; Cyslacel: Research Funding; Celgene: Research Funding; Biosight: Research Funding; Ariad: Research Funding; Agios: Honoraria. Kota:Takeda: Honoraria; Xcenda: Honoraria; Novartis: Honoraria; Amgen: Honoraria; Pfizer: Honoraria. Flaishon:BioSight Ltd.: Employment. Tessler:BioSight Ltd.: Employment. Gengrinovitch:BioSight Ltd.: Employment. Ben Yakar:BioSight Ltd.: Employment. Rowe:BioSight: Consultancy.
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Dulmovits, Brian M., Abena O. Appiah-Kubi, Julien Papoin, Michael Gould, Xiuli An, Narla Mohandas, Patrick G. Gallagher, Jeffrey M. Lipton, Johnson M. Liu, and Lionel Blanc. "Pomalidomide Modulates Transcription Networks Regulating Human Erythropoiesis and Globin Switching: Implications for Treatment of Hemoglobinopathies." Blood 124, no. 21 (December 6, 2014): 1375. http://dx.doi.org/10.1182/blood.v124.21.1375.1375.
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Abstract Sickle cell disease (SCD) represents a major challenge in hematology, with approximately 100,000 Americans afflicted and the annual number of newborns with SCD set to rise over the next 40 years worldwide. Current treatment approaches rely on increasing levels of fetal hemoglobin (HbF) to prevent painful vaso-occlusive crises and hemolysis secondary to red cell sickling. Hydroxyurea remains the only pharmacologic intervention approved for SCD; however, it has limited efficacy and carries significant side effects such as myelosuppression. Thus, there is a critical need to develop drugs that enhance HbF production without similar dose limiting side effects. Second generation immunomodulatory drugs, such as pomalidomide, are a class of emerging HbF inducers both in vitro and in vivo. Recent work from our laboratory revealed that hydroxyurea and pomalidomide differentially regulate HbF production in CD34+ cells undergoing erythroid differentiation using a 3-phase culture system. Pomalidomide, but not hydroxyurea, was found to decrease BCL11A expression through a yet to be defined mechanism. In the present study, we sought to characterize erythropoiesis and the expression of key transcription factor networks in this 3-phase culture system to determine the mechanisms underlying pomalidomide’s effect. Following a four day expansion period, isolated CD34+ cells from the peripheral blood of SCD or normal individuals were differentiated along erythroid lineage in the presence of pomalidomide (1μM) or DMSO (vehicle) for 14 days. As an additional control, CD34+ cells were also treated with hydroxyurea (10μM). Proliferation and erythroid differentiation were assessed at 7, 11 and 14 days of culture. Although a 50% decrease in cell growth was noted in cells treated with hydroxyurea, no such decrement was found in control, DMSO and pomalidomide-treated cells. Moreover, pomalidomide produced a transient delay in erythroid differentiation between days 6 and 11 of culture phenotypically documented by flow cytometric analysis using glycophorin-A, α-4 integrin and band 3 as surface markers monitoring erythroid differentiation as well as morphologically by May-Grunwald Giemsa staining. In contrast, cells treated with hydroxyurea demonstrated accelerated differentiation, compared to the control cultures. However, by day 14 of culture, no significant difference was observed under any condition, suggesting that the delayed cells eventually finished terminal differentiation. In terms of HbF induction, we confirmed elevated production in the cultures with pomalidomide by measuring the number of F-cells by flow cytometry. We also evaluated the production of γ-globin chains by qRT-PCR and western blot at D4 and D11 and found a dramatic increase in the production of γ-globin, in both SCD and normal samples treated with pomalidomide. We posited that pomalidomide might foster changes in transcription factors known to play a role in both erythropoiesis and globin switching. To this end, we evaluated the expression kinetics of BCL11A, SOX6, KLF1, MI2β, GATA1 and FOG1 via qRT-PCR and western blot analyses. In DMSO-treated cultures the above transcription factors were maximally expressed between days 6-8, and their levels diminished during the remainder of the culture. Conversely, pomalidomide markedly decreased BCL11A, SOX6, KLF1 and MI2β between days 4 and 6 in cultures of both SCD and normal samples. In line with our results, MI2β acts as a positive regulator of BCL11A and KLF1, and previous studies have shown that its knock down in CD34 cells leads to decreased levels of BCL11A and KLF1. Western blot analyses confirmed the qRT-PCR data. Further, the divergent expression patterns correlated temporally with the differentiation delay suggesting that pomalidomide modulates expression of members of the BCL11Atranscription factor complex, thereby augmenting γ-globin production. Taken together, these data provide evidence that pomalidomide influences erythropoiesis by modulating transcription factor expression in CD34+ cells differentiated in the 3-phase culture system, leading to a decrease in BCL11A and activation of γ-globin production. Importantly, further exploration of these pathways that function to regulate erythropoiesis and promote HbF silencing, may help elucidate the mechanism of action of pomalidomide as well as identify additional druggable molecules. Disclosures No relevant conflicts of interest to declare.
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Norman, Armando Henrique. "Medical ethics and screening: on what evidence should we support ourselves?" Revista Brasileira de Medicina de Família e Comunidade 9, no. 31 (May 4, 2014): 108–10. http://dx.doi.org/10.5712/rbmfc9(31)933.
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If screening had been a drug, it would have been withdrawn from the market. Thus, which country will be first to stop mammography screening? (Peter C. Gøtzsche) 1This issue of RBMFC addresses the subject of medical ethics, the backbone that should guide both the demands in health services and health technologies provision, as well as the practice of family and community physicians. As a stimulus for reflection, the Debate section tackles the “Preventive mandatory mammography” policy in Uruguay, while in the Section Essays, Jamoulle and Gomez discuss the concept of quaternary prevention: action that aims to offer ethically acceptable alternatives to patients in order to prevent the excess of medical interventions.2 Despite considerable technological and social transformations that directly affect people’s health, ethics in medicine continues to morally shape health problems and health policy decisions with implications for patients, physicians and health institutions.In a practical analytical and easy to understand guidance for health professionals, Gillon3 discusses the four principles and scope of medical ethics: autonomy, beneficence, non-maleficence and justice. The latter encompasses the distributive justice, individual right justice and legal justice. These four principles provide a baseline for dialogue across different cultures, religious beliefs and political positions, as these principles are considered to be prima facie: a duty which is compulsory on all occasions unless it is in conflict with equal or stronger duties.4 Thus, based on these four principles that underlie ethics in medicine and consequently the application of the quaternary prevention, cancer screening programme will be critically analysed as a preventative strategy.Screening programmes entails the use of an initial selective tool or a sieve phase (i.e. mammography) to separate asymptomatic persons within the target population, that will need to undergo a classificatory or diagnostic phase - which involves a ‘gold standard’ for defining a disease (i.e. anatomopathology) – to finally offer patients a definitive preventive treatment for the condition screened.5 Since this type of intervention is performed on healthy individuals, the ethical requirements in the cases of screening programmes are very high, because the risks of damage are not balanced against real suffering (a clinically manifested disease), but are anchored in a potential future of illness and death. In this case, the principle of non-maleficence (do not harm) prevails over the principle of beneficence (the desire to promote the patients’ wellbeing), since asymptomatic persons, who perceive themselves as healthy, may have their health perception shaken indefinitely due to a biomedical intervention. The most often cited damages in the literature are psychological (due to the uncertainties of false positives, false assurance of false negatives, and borderline conditions that require a closer monitoring such as Cervical Intraepithelial Neoplasia - CIN I, II, III), as well as the physical consequences resulting from treatment itself, such as impotence or urinary incontinence, in the case of screening and treatment of prostate cancer.Since in the screening and/or health check ups the intervention is usually a ‘mirage-guided’ or ‘probability-guided’, it can result in ‘damage without the potential benefits’,6 as in the case of invasive procedures (to clarify ‘images’ or ‘positive’ exam results produced in the selective or sieving phase) which can result in complications, but the biopsy turnout to be normal. For instance, colonoscopy, laparoscopy, biopsies (liver, kidney, prostate), in which those procedures may end up producing complications (intestinal perforation, anaesthesia complications, major artery perforation, sepsis) with the potential to scale up into hospital readmission, with stress for patients and families and/or an even worse scenario: patients’ death with a benign finding. Therefore, screening programmes intrinsically carry the potential to convert healthy people into sick individuals at the population level, and consequently are highly iatrogenic and could be summarized as follows: “For many are called, but few are chosen…,” but many will need to suffer for to very few be cured.This is particularly true in the case of breast cancer screening with mammography, which renders physiopathologically insignificant cancers (overdiagnosis) exposing previously healthy women to significant damages due to radiotherapy. Gotzsche et al.7 highlighted important risks of adverse effects as consequence of radiotherapy, such as heart failure (27%) from circulatory cardiac damage and/or induction of lung cancer (78%). Furthermore, a recently published systematic review in the British Medical Journal8 on the adverse effects of cancer screening, found that only a third of randomized controlled clinical trials was concerned in measuring and controlling for potential harms of screening intervention. This article is very important because it has a direct effect upon the practice of health professionals, who cannot address security parameters on cancer screening interventions with their patients, since there is an information selection bias that emphasizes only the positive aspects of screening, for lack of controlling and monitoring of potential harms in most screening clinical trials.From an ethical stance, this context of uncertainty undermines the patients’ autonomy, creating false empowerment, since women do not have a more complete view on the potential harms and benefits of breast cancer screening programmes.9 To truly empower women and strengthen their autonomy for deciding upon interventions that directly affect their health, there is a need for information to be more transparent and also to reveal potential harms of the interventions. Moreover, the language used for the dissemination of information should be neutral, of simple understanding, culturally accessible, so that the users of the health system can better decide about their own health.3From the perspective of public health, distributive ethic justice, and limited healthcare budget - that any health system faces - screening programmes diverts financial resources - which should primarily be allocated to the treatment and care of sick individuals - towards healthy people, with the potential to produce new real patients, due to the damage of the interventions on healthy bodies, generating more costs to the health system and society in general.Fortunately, screening programmes are increasingly losing their strength, especially in Europe. For instance, the Swiss Medical Board10 found no scientific rational for the maintenance of breast screening programmes in light of current available scientific evidence. In Denmark, the rate of mortality attributable to breast cancer have not reduced due to the implementation of systematic breast cancer screening programme with mammography over 17 years follow up,11 however, it has produced an overdiagnosis rate of 33%.12 Similar trends in mortality over the last 30 years were also observed in the United States,13 as well as in Canada, the accumulated 25 years monitoring of the effects of breast cancer screening, did not render reduction in mortality from breast cancer, but resulted in 22% of overdiagnosis.14 Thus, to Peter C. Gotzsche,1 one of the world ‘s leading authorities on the subject, the best method we have to reduce the occurrence of breast cancer is to stop screening with mammography.From an ethical and scientific point of view,10 screening programmes should be discontinued or restricted to high-risk groups or very specific situations, and the focus of prevention should be redirected towards interventions on early-symptomatic patients, since breast cancer treatment has improved considerably in recent decades, and this is likely to be the responsible for improving the quality of life of affected women.1 The Canadian Task Force15 on preventive health care in their last update (2011) regarded as weak recommendation the breast cancer screening with mammography every 2-3 years in age group 50-69 years-old, because they considered the evidence for screening only of moderate quality. The Brazilian Ministry of Health16 also acted correctly in limiting the financial incentives for breast cancer screening for the age group 50-69 years.Therefore, ‘there is nothing wrong saying no to mammography’,9 because when acting upon asymptomatic healthy people, the principle of non-maleficence should override the principle of beneficence. Thus, the challenge left for family and community doctors is to individualize each case in this ‘sea of uncertainty’, sharing with their patients the often hidden potential harms attributed to cancer screening in order to operationalize in daily practice the concept of quaternary prevention.
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Sheikh, Muhammad Aman, Nursyarizal Mohd Nor, and Taib Ibrahim. "A NEW METHOD FOR DETECTION OF UNBALANCE VOLTAGE SUPPLY IN THREE PHASE INDUCTION MOTOR." Jurnal Teknologi 78, no. 5-8 (May 25, 2016). http://dx.doi.org/10.11113/jt.v78.8740.
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Induction motors are associated with various techno-economic advantages; therefore these are widely used in residential, commercial and industrial systems. Cost effective and reliable process of condition monitoring of induction motor is very important. It is found that unbalance voltage supply is one of the major factors that produce uneven heating due to reverse current and leads to inter-turn short circuit. The issue regarding unbalanced voltage supply has attracted the attention of researcher and engineers in recent past. In this paper, a new effective non-invasive (online) method is proposed that only use rotor harmonic current signature for the detection of unbalance voltage supply instead of main line current signature. This is a sensor-less and online approach that accomplishes the reliable and accurate analysis of the induction motors. Moreover, it allows a continuous real time tracking without disturbing the normal operation and guarantees the overall production process. Additionally, this method recognizes the unbalance and estimate the severity of the unbalance in the voltage source. The effects of unbalance voltage supply are investigated through experiments. In order to perform the analysis and detect the asymmetry due to unbalance voltage, an experimental set up is designed that can accurately repeat the measurements. In the proposed work, unbalance voltage supply is diagnosed through experimental hardware setup. To validate the propose methods an experiment is performed that confirm that motor operating under unbalance voltage supply give a significant rise in the rotor harmonic while under balance voltage supply there is so such a rise in the rotor harmonic.
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Işık, Mehmet Fatih, Mustafa Reşit Haboğlu, and Büşra Yartaşı. "Smart Phone Based Energy Monitoring System for 3 Phase Induction Motors." International Journal of Electronics and Electrical Engineering, 2017, 90–93. http://dx.doi.org/10.18178/ijeee.5.1.90-93.
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Prabowo, Sohih Ajie, Wakhyu Dwiono, and Arif Johar Taufiq. "The Analysis Of 3 Phase 1 HP Induction Motor Efficiency In Under Voltage And Over Voltage Condition With PSIM Simulation." Jurnal Riset Rekayasa Elektro 1, no. 2 (January 22, 2020). http://dx.doi.org/10.30595/jrre.v1i2.5232.
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Three phase induction is the most common motor and is widely used in various industrial equipment because of all the advantages. To get the best performance, the quality of powersupply of induction motors needs to be maintained. One of the problems that arise in power quality is under voltage or over voltage. In this study the calculation and analysis of efficiency using the segregated loss method of 3 phase induction motors connected to stars and delta on the under voltage and over voltage conditions of the rating voltage, and at the rating voltage, the motor used is a 3 Phase 1 HP 4 pole induction motor with voltage rating of 380 volts. The method used is the segregated loss method, this method is a method to get the value of the efficiency of the induction motor by finding and separating the value of loss and loss, the method used refers to IEEE 112. Simulation using PSIM software as a hypothesis and comparison, variables taken are speed, current, inter-phase voltage and input power. Based on the results of calculations from all experiments show that the induction motor will produce better efficiency at loads approaching its capacity, and under voltage and over voltage conditions affect the efficiency value with a small difference in each change in voltage conditions. Efficiency values in all star motor voltage conditions range between 44% - 52% and in delta connection motor ranges between 39% - 42%. Simulations carried out using PSIM software produce higher efficiency than the test results with a range of values of 67% -78%, where the value is calculated from the simulation results and ignoring core losses.
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Jin, Chao, Agusmian P. Ompusunggu, Zongchang Liu, Hossein D. Ardakani, Fredrik Petré, and Jay Lee. "Envelope Analysis on Vibration Signals for Stator Winding Fault Early Detection in 3-Phase Induction Motors." International Journal of Prognostics and Health Management 6, no. 1 (November 1, 2020). http://dx.doi.org/10.36001/ijphm.2015.v6i1.2239.
Full textAbstract:
This paper brings up a novel method for detecting induction motor stator winding faults at an early stage. The contribution of the work comes from the delicate handling of motorvibration by applying envelope analysis, which makes it possible to capture electrical short-circuit signature in mechanical signals, even if the magnitude of the fault is fairly incipient. Conventional induction motor condition-based maintenance methods usually involve current and voltage measurements, which could be expensive to collect, and vibration-based analysis is often only capable of detecting the fault when it is already quite significant. In contrast, the solution presented in this study provides a refreshing perspective by applying time synchronous averaging to remove the discrete frequency component, and amplitude demodulation to further enhance the signal with the help of kurtogram. Experimental results on a three-phase induction motor show that the method is also able to distinguish different fault severity levels.
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Gangsar, Purushottam, and Rajiv Tiwari. "Online Diagnostics of Mechanical and Electrical Faults in Induction Motor Using Multiclass Support Vector Machine Algorithms Based on Frequency Domain Vibration and Current Signals." ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg 5, no. 3 (June 10, 2019). http://dx.doi.org/10.1115/1.4043268.
Full textAbstract:
This paper demonstrates the development of a flexible fault diagnosis methodology that can detect up to ten different faults in the induction motor (IM), simultaneously. The major IM electrical faults, such as the broken rotor bar (BRB), phase unbalance (PUF), and stator winding fault (SWF), and mechanical faults, such as bearing fault (BF), unbalanced rotor (UR), bowed rotor (BR), and misaligned rotor (MR), are considered with different fault severities for the diagnosis. The experiments are conducted with three varying loads and seven different speeds, and the frequency domain vibration and current data are acquired at a relatively low sampling rate of 1 kHz. Several statistical features are extracted and then the best feature-set is selected using the wrapper model. Thereafter, a data classification tool based on the support vector machine (SVM) is used for the fault characterization. Initially, a multi-fault diagnosis is performed by training and testing the SVM at the same operating conditions (i.e., load and speed). The performance of the classifier is found to be very good at all IM operating conditions. The main focus of this study lies in overcoming the fault diagnosis, where the data are unavailable at required operating conditions. This is accomplished by employing interpolation and extrapolation strategies for different loads and speeds. The proposed methodology not only solves practical problem of unavailability of data at different operating conditions but also shows good performance and takes low computation time, which are vital requirements of an online intelligent condition monitoring system.