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1
Chu, Kenny Sau Kang, Kuew Wai Chew, Yoong Choon Chang, and Stella Morris. "An Open-Circuit Fault Diagnosis System Based on Neural Networks in the Inverter of Three-Phase Permanent Magnet Synchronous Motor (PMSM)." World Electric Vehicle Journal 15, no. 2 (February 16, 2024): 71. http://dx.doi.org/10.3390/wevj15020071.
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Three-phase motors find extensive applications in various industries. Open-circuit faults are a common occurrence in inverters, and the open-circuit fault diagnosis system plays a crucial role in identifying and addressing these faults to enhance the safety of motor operations. Nevertheless, the current open-circuit fault diagnosis system faces challenges in precisely detecting specific faulty switches. The proposed work presents a neural network-based open-circuit fault diagnosis system for identifying faulty power switches in inverter-driven motor systems. The system leverages trained phase-to-phase voltage data from the motor to recognize the type and location of faults in each phase with high accuracy. Employing separate neural networks for each of the three phases in a three-phase permanent magnet synchronous motor, the system achieves an outstanding overall fault detection accuracy of approximately 99.8%, with CNN and CNN-LSTM architectures demonstrating superior performance. This work makes two key contributions: (1) implementing neural networks to significantly improve the accuracy of locating faulty switches in open-circuit fault scenarios, and (2) identifying the optimal neural network architecture for effective fault diagnosis within the proposed system.
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Chen, Chaobo, Ying Yang, Binbin Zhang, and Song Gao. "The Diagnostic Method for Open-Circuit Faults in Inverters Based on Extended State Observer." Mathematical Problems in Engineering 2021 (April 26, 2021): 1–11. http://dx.doi.org/10.1155/2021/5526173.
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To reduce the influence of unknown disturbance on open-circuit fault diagnosis of inverters in the motor drive system, an open-circuit fault diagnosis method, which is based on extended state observer, is proposed for inverters. A mixed logic dynamic model of the inverters is established by analyzing the current flow path when the system works normally and there are open-circuit faults. A voltage extended state observer is designed for the mixed logic dynamic model. The open-circuit faults are detected according to the phase voltage residual between the observed voltage and the actual voltage. The position of the faulty switches is determined by querying the voltage residual information table. Finally, the simulation results show that the method can effectively reduce the influence of the unknown interference on the inverter faults diagnosis, improve the fault diagnosis rate, and verify the effectiveness and feasibility of the method.
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Vu, Hoang-Giang, and Hamed Yahoui. "Intermittent open-circuit fault diagnosis of inverters based on DC-link electromagnetic field signal." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 4 (August 1, 2024): 3885. http://dx.doi.org/10.11591/ijece.v14i4.pp3885-3893.
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For the objective of improving the reliability of converters in electric drives, research on a method for early detection of intermittent open-circuit faults of power valves is reported in this article. Intermittent open circuit condition is the incipient form of power valve open-circuit fault in power converters. Prompt detection of this fault allows for timely remediation of permanent open circuit defects that is a commonly subsequent process. This study introduces an investigation of this fault, which occurs in the voltage source inverter of induction motor drives. Intermittent faults are created through interference with the control pulse of the power valve. Wavelet transform with the Mexican hat mother function is utilized for signal processing. Appropriate ranges of the scale are selected to obtain a high magnitude of the wavelet coefficient at faulty instants. The analysis for the direct current recorded at the DC-link in simulation and the electromagnetic signal measured at the DC-bus of the inverter can be effectively used for the fault diagnosis.
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Morel, Cristina, Baptiste Le Gueux, Sébastien Rivero, and Saad Chahba. "Currents Analysis of a Brushless Motor with Inverter Faults—Part II: Diagnostic Method for Open-Circuit Fault Isolation." Actuators 12, no. 6 (June 2, 2023): 230. http://dx.doi.org/10.3390/act12060230.
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In this paper, a brushless motor with a three-phase inverter is investigated under healthy and multiple open-circuit faults. The occurrence of faults in an inverter will lead to atypical characteristics in the current measurements. This is why many usual entropies and multiscale entropies have been proposed to evaluate the complexity of the output currents by quantifying such dynamic changes. Among this multitude of entropies, only some are able to differentiate between healthy and faulty open-circuit conditions. In addition, another selection is made between these entropies in order to improve diagnostic speed. After the fault detection based on the mean values, the open-circuit faults are localized based on the fault diagnostic method. The simulation results ensure the ability of these entropies to detect and locate open-circuit faults. Moreover, they are able to achieve fault diagnostics for a single switch, double switches, three switches, and even four switches. The diagnostic time to detect and to isolate faults is between 10.85 ms and 13.67 ms. Then, in order to prove the ability of the fault diagnostic method, a load variation is performed under the rated speed conditions of the brushless motor. The validity of the method is analyzed under different speed values for a constant torque. Finally, the fault diagnostic method is independent from power levels.
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Cheng, Guanyuan, and Shaojian Song. "Fault Detection and Identification in MMCs Based on DSCNNs." Energies 16, no. 8 (April 13, 2023): 3427. http://dx.doi.org/10.3390/en16083427.
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Fault detection and location is one of the critical issues in engineering applications of modular multilevel converters (MMCs). At present, MMC fault diagnosis based on neural networks can only locate the open-circuit fault of a single submodule. To solve this problem, this paper proposes a fault detection and localization strategy based on a depthwise separable convolutional (DSC) neural network. By inputting the bridge arm circulating current and the submodule capacitor voltage into two serially connected neural networks, not only can this method achieve the classification of submodule open-circuit faults, submodule block short-circuit faults, and bridge arm inductance faults in MMCs, but it can also locate the switch where open-circuit faults occur. The simulation experimental results show that the proposed method achieves fault classification and locates multiple submodule open-circuit faults in the same bridge arm. This method achieves accuracies of ≥99% and 87.7% for the single-point and multi-point open-circuit fault localization in MMCs, respectively, which is better than some benchmark achievements in the current literature in terms of detection accuracy, and speed, and it has fewer model parameters and better real-time performance.
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Zdiri, Mohamed Ali, Badii Bouzidi, and Hsan Hadj Abdallah. "Performance investigation of an advanced diagnostic method for SSTPI-fed IM drives under single and multiple open IGBT faults." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 38, no. 2 (March 4, 2019): 616–41. http://dx.doi.org/10.1108/compel-04-2018-0181.
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Purpose This paper aims to analyze and investigate the performance of an improved fault detection and identification (FDI) method based on multiple criteria, applied to six-switch three-phase inverter (SSTPI)-fed induction motor (IM) drives under both single and multiple open insulated-gate bipolar transistors(IGBT) faults. Design/methodology/approach This paper proposes an advanced diagnostic method for both single and multiple open IGBT faults dedicated to SSTPI-fed IM drives considering five distinct faulty operating conditions as follows: a single IGBT open-circuit fault, a single-phase open-circuit fault, a non-crossed double fault in two different legs, a crossed double fault in two different legs and a three-IGBT open-circuit fault. This is achieved because of the introduction of a new diagnosis variable provided using the information of the slope of the current vector in (α-β) frame. The proposed FDI method is based on the synthesis and the analysis, under both healthy and faulty operations, of the behaviors of the introduced diagnosis variable, the three motor phase currents and their normalized average values. Doing so, the developed FDI method allows a best compromise of fast detection and precision localization of IGBT open-circuit fault of the inverter. Findings Simulation works, carried out considering the implementation of the direct rotor flux oriented control in an IM fed by the conventional SSTPI, have proved the high performance of the advanced FDI method in terms of fast fault detection associated with a high robustness against false alarms, against speed and load torque fast variations and against the oscillations of the DC-bus voltage in the case of both healthy and faulty operations. Research limitations/implications This work should be extended considering the validation of the obtained simulation results through experiments. Originality/value Different from other FDI methods, which suffer from a low diagnostic effectiveness for low load levels and false alarms during transient operation, this method offers the potentialities to overcome these drawbacks because of the introduction of the new diagnosis variable. This latter, combined with the information provided from the three motor phase currents and their normalized average values allow a more efficient detection and identification of IGBT open-circuit fault.
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Kherif, Omar, Tahar Zebbadji, Youcef Gherbi, Mohamed Larbi Azzouze, and Madjid Teguar. "Simplified Diagnosis Method for CHBMIs under Open-circuit Switch or Battery Failure." ENP Engineering Science Journal 1, no. 2 (December 31, 2021): 17–25. http://dx.doi.org/10.53907/enpesj.v1i2.23.
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This paper deals with the diagnosis of cascaded H-bridge multilevel inverters controlled by a sinusoidal level-shifted pulse-width modulation technique. For this purpose, the behaviour of 3, 5, 7 and 9-level inverters is studied for regular and faulty operation modes. Three types of recurring faults are considered, namely open-circuit of a switch, damaged and disconnected battery. Under a single fault, the output voltage signals are presented where the impact of each fault is discussed. In order to detect, identify and locate the three types of fault, a signal processing method is proposed, elaborating the output voltage of inverters with and without fault. The obtained results are convincing for the considered cases. The study shows no real correlation between the selected features from one to the other type of fault. Indeed, each fault type has its own trajectory with respect to the evolution of the output voltage characteristics. Thus, localizing the faulty component within the multilevel inverter can be made with no ambiguity. Such findings obviously solve a large part of problems associated with the presence of faults in multilevel inverters. They can help improving the reliability of the inverter in such way it continues working.
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T., Daniel Raj. "SHE-PWM Cascaded Ml Inverters Structure with Fault Tolerance Over Open Circuit Faults." Journal of Advanced Research in Dynamical and Control Systems 12, no. 01-Special Issue (February 13, 2020): 348–58. http://dx.doi.org/10.5373/jardcs/v12sp1/20201081.
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Singh, Vikram, Anamika Yadav, and Shubhrata Gupta. "Open circuit fault diagnosis and fault classification in multi-level inverter using fuzzy inference system." Serbian Journal of Electrical Engineering 20, no. 2 (2023): 163–89. http://dx.doi.org/10.2298/sjee2302163s.
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Multi-level inverters (MLIs) have been successfully used to integrated the renewable energy sources (RES) into microgrids. However, the operation of MLI is affected when an open circuit fault (OCF) or a short circuit fault occurs. Among these kinds of faults, there is a high prevalence of open circuit faults in MLI. Any fault in MLI must be identified and classified as soon as possible to maintain the reliability of the power supply. This work is focused on developing a Fuzzy Inference System (FIS) for detecting and classifying the open circuit faults in Cascaded H-Bridge Multi-Level Inverter (CHMLI), thereby improving the fault diagnosis accuracy and efficiency. In CHMLI, the gate pulse is generated by pulse width modulation (PWM) technique. The Mamdani Fuzzy Logic Controller (FLC) identifies and categorizes the different OCFs. Fuzzy logic rules are designed for detecting and classifying open circuit faults simultaneously using the fundamental Discrete Fourier components of voltage and current. Several combinations of open circuit faults have been studied in different switches of the MLI, along with the effect of fault inception angle. Furthermore, the test results support the feasibility of the proposed fuzzy-based fault diagnosis and classification scheme in a practical context. A real-time simulation obtained with the help of FPGA-based OPAL-RT 4510 demonstrates the robustness and effectiveness of the designed topology. All types and fault locations are considered in multiple cases of switch failure.
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Hyon, Byong Jo, Dae Yeon Hwang, Pooreum Jang, Yong-Su Noh, and Jin-Hong Kim. "Offline Fault Diagnosis for 2-Level Inverter: Short-Circuit and Open-Circuit Detection." Electronics 13, no. 9 (April 26, 2024): 1672. http://dx.doi.org/10.3390/electronics13091672.
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Fault detection is very important to improve the reliability of power conversion devices. Faults of power semiconductors can be broadly divided into shorts and opens and are further classified into two types depending on whether there is an internal problem with the switch or anti-parallel diode. In this paper, fault-diagnosis methods for short-circuit and open-circuit states are proposed, respectively. A method of classifying and diagnosing faults by applying a gate signal to each switch is proposed to diagnose short-circuit conditions. This method uses only current magnitude information, which reduces the amount of required information and reduces diagnostic failures due to angle errors and current noise. A method is proposed to detect a faulty switch by applying a voltage vector and comparing the current angle with a lookup table to diagnose an open state. An iterative diagnostic algorithm is proposed to prevent diagnostic failure due to angle error and current noise. The effectiveness of the proposed diagnosis method is verified through experiments and simulations.
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Cao, Fan, Haifeng Lu, Yonggang Meng, and Dawei Gao. "Sensorless Fault-Tolerant Control of Dual Three-Phase Permanent Magnet Synchronous Motor." World Electric Vehicle Journal 12, no. 4 (October 11, 2021): 183. http://dx.doi.org/10.3390/wevj12040183.
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Dual three-phase permanent magnet synchronous motors (DTPMSM) are used in the steer-by-wire system of electric vehicles that require high reliability. Multiple faults should be considered for the steering system, such as open-circuit faults and speed sensor faults. However, the current speed sensorless control methods of the dual three-phase motor are mainly derived from the promotion of the three-phase motor. They fail when an open-circuit fault occurs, leading to the failure of fault-tolerant control. Researchers have noticed this problem and proposed many methods, but they are very complicated and computationally intensive. This paper proposes one type of improved model reference adaptive system (MRAS). By adding certain fault-related restraints to the output of the adjustable model, speed sensorless control can automatically fit the open-circuit fault and estimate accurately even if an open-circuit fault occurs, which makes sure the whole system continues to operate. Simulation results are presented that contain normal operation, open-circuit fault operation, fault-tolerant control operation, and the whole process from start to fault-tolerant operation. The results show that no matter what period the motor is in, the improved speed sensor can accurately estimate the motor speed and position. The improved model reference adaptive system is significant for improving the reliability of the motor steering system and ensuring the safety of people and property.
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Morel, Cristina, and Ahmad Akrad. "Open-Circuit Fault Detection and Location in AC-DC-AC Converters Based on Entropy Analysis." Energies 16, no. 4 (February 16, 2023): 1959. http://dx.doi.org/10.3390/en16041959.
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Inverters and converters contain more and more power electronics switches which may subsequently affect their reliability. Therefore, fault detection and location are essential to improve their reliability and to ensure continuous operation. In this paper, an AC−DC−AC converter with three-phase inverter is investigated under permanent, single and multiple open-circuit fault scenarios. Many entropies and multiscale entropies are then proposed to evaluate the complexity of the output currents by quantifying their entropies over a range of temporal scales. Among the multitude of entropies, only some entropies are able to differentiate healthy from open-circuit faulty conditions. Moreover, the simulation results show that these entropies are able to detect and locate the arms of the bridge with open-circuit faults.
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Gmati, Badii, Amine Ben Rhouma, Houda Meddeb, and Sejir Khojet El Khil. "Diagnosis of Multiple Open-Circuit Faults in Three-Phase Induction Machine Drive Systems Based on Bidirectional Long Short-Term Memory Algorithm." World Electric Vehicle Journal 15, no. 2 (February 5, 2024): 53. http://dx.doi.org/10.3390/wevj15020053.
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Availability and continuous operation under critical conditions are very important in electric machine drive systems. Such systems may suffer from several types of failures that affect the electric machine or the associated voltage source inverter. Therefore, fault diagnosis and fault tolerance are highly required. This paper presents a new robust deep learning-based approach to diagnose multiple open-circuit faults in three-phase, two-level voltage source inverters for induction-motor drive applications. The proposed approach uses fault-diagnosis variables obtained from the sigmoid transformation of the motor stator currents. The open-circuit fault-diagnosis variables are then introduced to a bidirectional long short-term memory algorithm to detect the faulty switch(es). Several simulation and experimental results are presented to show the proposed fault-diagnosis algorithm’s effectiveness and robustness.
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Chen, Yin, Zhenli Tang, Xiaofeng Weng, Min He, Sheng Zhou, Ziqiang Liu, and Tao Jin. "A Diagnostic Method for Open-Circuit Faults in DC Charging Stations Based on Improved S-Transform and LightGBM." Energies 17, no. 2 (January 13, 2024): 404. http://dx.doi.org/10.3390/en17020404.
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The open-circuit fault in electric vehicle charging stations not only impacts the power quality of the electrical grid but also poses a threat to charging safety. Therefore, it is of great significance to study open-circuit fault diagnosis for ensuring the safe and stable operation of power grids and reducing the maintenance cost of charging stations. This paper addresses the multidimensional characteristics of open-circuit fault signals in charging stations and proposes a fault diagnosis method based on an improved S-transform and LightGBM. The method first utilizes improved incomplete S-transform and principal component analysis (PCA) to extract features of front- and back-stage faults separately. Subsequently, LightGBM is employed to classify the extracted features, ultimately achieving fault diagnosis. Simulation results demonstrate the method’s effectiveness in feature extraction, achieving an average diagnostic accuracy of 97.04% on the test dataset, along with notable noise resistance and real-time performance. Additionally, we designed an experimental platform for diagnosing open-circuit faults in DC charging station and collected experimental fault data. The results further validate the effectiveness of the proposed method.
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Huang, Chen, Lidan Zhou, Zujia Cao, and Gang Yao. "Fault-Tolerant Control Strategy with Asymmetric Phase Currents for Single to Four-Phase Open-Circuit Faults of Six-Phase PMSM." Energies 14, no. 11 (May 28, 2021): 3163. http://dx.doi.org/10.3390/en14113163.
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Multi-phase motors and generators are regarded with great fault tolerance capability, especially on open-circuit faults. Various mathematics analytical methods are applied for their fault control. In this paper, a fault-tolerant control strategy with asymmetric phase current for the open-circuit faults with arbitrary phases in the six-phase PMSM (six-phase permanent magnetic synchronous motor, 6P-PMSM) system, is proposed for better electrical and dynamical performance of the machine. An innovative mathematical model for PMSM under one to four-phase-open circuit faults are established considering the asymmetry of the machine. Combining with time-varying relations in machines’ working conditions, targeted decoupling transformation matrixes of every kind of open-circuit faults are settled by voltage equations under different faults. Modified control strategy with a connection between the neutral point and the inverter’s DC side is presented, which aims at increasing the system redundancy and reducing the amplitude of phase currents. Besides, improved control loops with two layers are put forward as well, with which the PMSM system acquires fewer harmonics in phase current and smoother electromagnetic torque. Simulation and experimental results of open-circuit faults are provided for verification of the theoretical analysis.
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You, Li, Zaixun Ling, Yibo Cui, Wanli Cai, and Shunfan He. "Open Circuit Fault Detection of T-Type Grid Connected Inverters Using Fast S Transform and Random Forest." Entropy 25, no. 5 (May 10, 2023): 778. http://dx.doi.org/10.3390/e25050778.
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To detect open circuit faults of grid-connected T-type inverters, this paper proposed a real-time method based on fast S transform and random forest. The three-phase fault currents of the inverter were used as the inputs of the new method and no additional sensors were needed. Some fault current harmonics and direct current components were selected as the fault features. Then, fast S transform was used to extract the features of fault currents, and random forest was used to recognize the features and the fault type, as well as locate the faulted switches. The simulation and experiments showed that the new method could detect open-circuit faults with low computation complexity and the detection accuracy was 100%. The real-time and accurate open circuit fault detection method was proven effective for grid-connected T-type inverter monitoring.
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Rahman, Ungku Mohamed Ismail Adrian Ungku Abdul, Wan Noraishah Wan Abdul Munim, Hang Seng Che, Mahdi Tousizadeh, and Khairul Safuan Muhammad. "Fault tolerance of asymmetrical six-phase induction machine during single open circuit fault to three open circuit faults using GUI." International Journal of Power Electronics and Drive Systems (IJPEDS) 11, no. 2 (June 1, 2020): 611. http://dx.doi.org/10.11591/ijpeds.v11.i2.pp611-617.
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The fault tolerance of multiphase drive is favourable in the industry for its reliability and safety reasons. However, from the educational point of view, the post-fault capability of six-phase machine is still unclear. This paper presents the fault tolerance of asymmetrical six-phase induction machine (A6-IM) under one to three open-circuit faults using Graphical User Interface (GUI). In this study, the capability of A6-IM has been interpreted through a simple and user-friendly GUI helping students to have a better understanding on the current limits of A6-IM. The optimization of post-fault current references is based on maximum torque (MT) and minimum loss (ML). This work provides GUI highlighting the post-fault derating of A6-IM with single isolated neutral (1N) in two different modes namely MT and ML for educational purposes.
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Xu, Hao, Jinghong Zhao, Lv Yang, Hansi Chen, Xiangyu Luo, and Shuheng Zhang. "Research on Open Circuit Fault Modeling and Fault Tolerant Control Strategy of Five-Phase Induction Motor." Processes 10, no. 9 (September 18, 2022): 1891. http://dx.doi.org/10.3390/pr10091891.
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Five-phase induction motors have the advantages of high reliability and strong fault-tolerant performance, so it’s open circuit fault model and fault-tolerant control strategy are widely studied. Based on the normal operation of the five-phase induction motor, the mathematical model of the five-phase induction motor under the conditions of single-phase open circuits, adjacent two-phase open circuits, and non-adjacent two-phase open circuits are established by using the reduced order decoupling transformation. Based on the principle of constant magnetic potential, the relationship between magnetic potential and each phase current is analyzed by using the symmetrical component method (MSC). The fault-tolerant control strategy of a five-phase induction motor with the above three open-circuit faults is designed. Through simulation and prototype experiments, the phase current and speed conversion under three open-circuit faults are analyzed. The results show that after the open-circuit fault of a five-phase motor, the residual phase current is no longer balanced, the motor speed is decreased, and the vibration is increased significantly. After fault-tolerant control, the residual phase current is balanced, the rated speed can be reached, and the vibration of the motor is reduced. Thus, the validity and correctness of the fault-tolerant control strategy for a five-phase induction motor are verified.
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Mehta, Pavan, Subhanarayan Sahoo, and Harsh Dhiman. "Open Circuit Fault Diagnosis in Five-Level Cascaded H-Bridge Inverter." International Transactions on Electrical Energy Systems 2022 (April 20, 2022): 1–13. http://dx.doi.org/10.1155/2022/8588215.
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The development of power electronic converter, especially multilevel converter, is remarkable for several decades. The complex switching and increased power of semiconductor devices are prime reasons for faults in multilevel inverters and have raised question about reliability. To improve the reliability, a cost-effective solution in terms of fault diagnosis is essential. In this context, this study proposed an open circuit fault (OCF) diagnosis technique for a switching device in a five-level cascaded H-bridge multilevel inverter using fuzzy logic control. The OCF features like output voltage total harmonic distortion (THD) and normalized average output voltage are fuzzed as input variables of the fuzzy logic controller. These input variables are divided into various triangular antecedent membership function (MF). The output produced by the fuzzy controller as consequent MFs is divided into different levels to identify the faulty switch. In order to make a complete fault-tolerant structure, a reduced modulation index-based postfault control is suggested to get a balanced output voltage. The MATLAB/Simulink results and prototype results are the evidence to support the proposed fault diagnosis technique.
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Xiong, Shibo, Yuxuan Pei, Weikang Wang, Wenwei Liu, Peng Zhang, and Yang Liu. "An Open-Circuit Fault Diagnosis Method for LLC Converters." Energies 17, no. 4 (February 8, 2024): 817. http://dx.doi.org/10.3390/en17040817.
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In electrified transportation systems, power system failures can lead to greater disasters. Therefore, the reliability of converters in transportation systems has been a concern. Fault-tolerant techniques are widely applied to ensure that converters can continue to supply loads under fault conditions. Fault diagnosis as a prerequisite for fault tolerance has also become a research hotspot. This paper proposes a fast method for fault diagnosis of high-frequency LLC converters. The proposed fault diagnosis method is based on the observation of the voltage across the resonant capacitor to determine and locate the faulty power switch, providing a basis for fault tolerance. This diagnosis method requires a voltage sensor, which is also necessary for some control methods. When applying these control methods, the proposed fault diagnosis method can be used without additional sensors, beneficial for cost reduction. A full-bridge LLC converter controlled by a digital signal processor was used as an experimental platform to verify the effectiveness and speed of the proposed diagnostic method. The results show that the proposed fault diagnosis method can achieve the fast diagnosis of high-frequency LLC converters in a short time and with only minimal computational resources.
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Wang, Falin, Gang Yuan, Chaoyang Guo, and Zhinong Li. "Research on fault diagnosis method of aviation cable based on improved Adaboost." Advances in Mechanical Engineering 14, no. 9 (September 2022): 168781322211257. http://dx.doi.org/10.1177/16878132221125762.
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In order to solve the problems of short circuit, open circuit and insulation faults in aviation cables, a fault diagnosis method based on BP-Adaboost algorithm is proposed in this paper. The BP neural network is used as the weak classifier in the Adaboost algorithm, and many weak classifiers are composed a strong classifier with stronger classification performance to diagnose fault categories. The BP-Adaboost fault diagnosis model is established, and the BP-Adaboost algorithm is improved to adapt to the multi-classification faults of cables, so as to identify the short circuit, open circuit, and insulation faults in the aircraft cable as well as normal working conditions. The accuracy of classification is analyzed; the results of the algorithm are analyzed by Matlab software, and the analysis results show that the improved BP-Adaboost algorithm has a relatively good classification performance for multi-class aviation cable fault diagnosis. Finally, the feasibility of the algorithm proposed is verified through an example combined with cable fault detection equipment.
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Puthiyapurayil, Muhammed Ramees Mullali Kunnontakath, Mohamed Nadir Nasirudeen, Yashkumar A. Saywan, Md Waseem Ahmad, and Hasmat Malik. "A Review of Open-Circuit Switch Fault Diagnostic Methods for Neutral Point Clamped Inverter." Electronics 11, no. 19 (October 2, 2022): 3169. http://dx.doi.org/10.3390/electronics11193169.
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Due to numerous advantages, a neutral point clamped (NPC) inverter is a preferred choice for high-power applications and renewable technology. The reliability of the NPC inverter is a major concerning factor during the assessment of system performance as power semiconductor switches are vulnerable to abnormal conditions. Open-circuit (OC) switch faults are not as dangerous as short circuit (SC) faults but eventually have enough potential to cause cascaded failure to other components in the system and thus need to be supervised carefully. The OC faults result in a distortion of voltage and current signals in the NPC converter. Based on these signals, over the past few years, many efforts have been made to identify and localize the OC switch fault to the switch level in the NPC topology. In this paper, a review of different OC switch fault diagnostic methods is provided. Starting from the NPC inverter operation under healthy and faulty conditions, the various possible and unavailable switching states along with the deviation in pole voltage under different switch fault conditions is discussed. Then, based on the approach used for system-based fault detection, the OC fault detection methods are classified. The various OC methods are further discussed on the basis of signal, i.e., current, voltage or a combination of both signals used as a signature for fault detection. Emphasis is given to the principle involved, diagnostic variables utilized, the implementation approach and the diagnostic time required. Finally, the approaches are tabulated so as to provide a quick reference for NPC fault diagnostics.
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Nedjah, Nadia, Jalber Dinelli Luna Galindo, Luiza de Macedo Mourelle, and Fernanda Duarte Vilela Reis de Oliveira. "Fault Diagnosis in Analog Circuits Using Swarm Intelligence." Biomimetics 8, no. 5 (August 25, 2023): 388. http://dx.doi.org/10.3390/biomimetics8050388.
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Open or short-circuit faults, as well as discrete parameter faults, are the most commonly used models in the simulation prior to testing methodology. However, since analog circuits exhibit continuous responses to input signals, faults in specific circuit elements may not fully capture all potential component faults. Consequently, diagnosing faults in analog circuits requires three key aspects: identifying faulty components, determining faulty element values, and considering circuit tolerance constraints. To tackle this problem, a methodology is proposed and implemented for fault diagnosis using swarm intelligence. The investigated optimization techniques are Particle Swarm Optimization (PSO) and the Bat Algorithm (BA). In this methodology, the nonlinear equations of the tested circuit are employed to calculate its parameters. The primary objective is to identify the specific circuit component that could potentially exhibit the fault by comparing the responses obtained from the actual circuit and the responses obtained through the optimization process. Two circuits are used as case studies to evaluate the performance of the proposed methodologies: the Tow–Thomas Biquad filter (case study 1) and the Butterworth filter (case study 2). The proposed methodologies are able to identify or at least reduce the number of possible faulty components. Four main performance metrics are extracted: accuracy, precision, sensitivity, and specificity. The BA technique demonstrates superior performance by utilizing the maximum combination of accessible nodes in the tested circuit, with an average accuracy of 95.5%, while PSO achieved only 93.9%. Additionally, the BA technique outperforms in terms of execution time, with an average time reduction of 7.95% reduction for the faultless circuit and an 8.12% reduction for the faulty cases. Compared to the machine-learning-based approach, using BA with the proposed methodology achieves similar accuracy rates but does not require any datasets nor any time-demanding training to proceed with circuit diagnostic.
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Khelif, Mohamed Amine, Azeddine Bendiabdellah, and Bilal Djamal Eddine Cherif. "A Combined RMS-MEAN Value Approach for an Inverter Open-Circuit Fault Detection." Periodica Polytechnica Electrical Engineering and Computer Science 63, no. 3 (April 5, 2019): 169–77. http://dx.doi.org/10.3311/ppee.13605.
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Currently, with the power electronics evolution, a major research axis is oriented towards the diagnosis of converters supplying induction machines. Indeed, a converter such as the inverter is susceptible to have structural failures such as faulty leg and/or open-circuit IGBT faults. In this paper, the detection of the faulty leg and the localization of the open-circuit switch of an inverter are investigated. The fault detection technique used in this work is based essentially upon the monitoring of the root mean square (RMS) value and the calculation of the mean value of the three-phase currents. In the first part of the paper work, the faulty leg is detected by monitoring the RMS value of the three-phase currents and comparing them to the nominal value of the phase current. The second part, the open-circuit IGBT fault is localized simply by knowing the polarity of the calculated mean value current of the faulty phase. The work is first accomplished using simulation work and then the obtained simulation results are validated by experimental work conducted in our LDEE laboratory to illustrate the effectiveness, simplicity and rapidity of the proposed technique.
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Pei, Tingting, and Xiaohong Hao. "A Fault Detection Method for Photovoltaic Systems Based on Voltage and Current Observation and Evaluation." Energies 12, no. 9 (May 6, 2019): 1712. http://dx.doi.org/10.3390/en12091712.
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Photovoltaic (PV) power generation systems work chronically in various climatic outdoor conditions, therefore, faults may occur within the PV arrays in PV systems. Online fault detection for the PV arrays are important to improve the system’s reliability, safety and efficiency. In view of this, a fault-detection method based on voltage and current observation and evaluation is presented in this paper to detect common PV array faults, such as open-circuit, short-circuit, degradation and shading faults. In order to develop this detection method, fault characteristic quantities (e.g., the open-circuit voltage, short-circuit current, voltage and current at the maximum power point (MPP) of the PV array) are identified first to define the voltage and current indicators; then, the fault-detection thresholds are defined by utilizing voltage and current indicators according to the characteristic information of various faults; finally, voltage and current indicators evaluated at real-time voltage and current data are compared with the corresponding thresholds to detect potential faults and fault types. The performances of the proposed method are simulated verifying by setting eight different fault patterns in the PV array. Simulation experimental results show the effectiveness of the proposed method, especially the capacities of distinguishing the degradation faults, partial shading faults and variable shading faults.
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Cheng, Shu, Jundong Zhao, Chunyang Chen, Kaidi Li, Xun Wu, Tianjian Yu, and Yongsheng Yu. "An open-circuit fault-diagnosis method for inverters based on phase current." Transportation Safety and Environment 2, no. 2 (June 2020): 148–60. http://dx.doi.org/10.1093/tse/tdaa008.
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Abstract The inverter is an indispensable part of a power electronics system. Its safety and stability are important indicators for evaluating the reliability of the system. Inverter faults are usually caused by operating faults in the switch elements. This paper therefore proposes a non-intrusive fault-diagnosis method for open-circuit faults in inverter semiconductor power switches. This method requires only a current signal. It is simple and economical. Faults can be diagnosed quickly using the proposed algorithm. First, the phase current waveforms before and after the open-circuit fault are analysed based on the mathematical model. Then, based on the analysis of the phase currents, the fault features are extracted and the fault is located using the proposed integration algorithm. Finally, the effectiveness and reliability of the proposed fault-diagnosis method are verified using a hardware-in-the-loop experiment.
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Zhang, Li, Chenyang Dong, Yucheng Wang, and Sai Han. "Research on Fault-Tolerant Field-Oriented Control of a Five-Phase Permanent Magnet Motor Based on Disturbance Adaption." Energies 15, no. 9 (May 8, 2022): 3436. http://dx.doi.org/10.3390/en15093436.
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To ensure the high-quality output performance of the five-phase fault-tolerant permanent magnet synchronous motor (FTPMSM) drive system under normal and open-circuit faults and achieve the minimal reconfiguration of the FTPMSM control drive system under various open-circuit faults, in this paper, a fault-tolerant field-oriented control (FOC) strategy based on disturbance adaption is proposed. The speed-loop and current-loop steady-healthy controllers are designed to effectively suppress the torque ripples caused by open-circuit faults and improve the robustness of the drive system to load disturbance and motor parameter variation under fault operation. Moreover, the additional zero-sequence current controller can be omitted. In addition, the modified reduced-order coordinate transformation matrices are proposed to weaken the influence of oscillating neutral. Finally, the fault-tolerant FOC system of the FTPMSM is established, and its experiment is conducted. The experimental results verify the feasibility and effectiveness of the proposed control strategy.
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Wen, Li, and Gongquan Tan. "Fault Diagnosis Method for Photovoltaic Arrays Based on Support Vector Machines." Academic Journal of Science and Technology 9, no. 3 (March 12, 2024): 142–45. http://dx.doi.org/10.54097/cw6sp715.
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A fault diagnosis method for photovoltaic arrays based on Support Vector Machines (SVM) is proposed to address four typical faults of photovoltaic arrays (short-circuit, open-circuit, aging, shadowing). MATLAB is used to simulate the faults in the photovoltaic array, obtaining four characteristic parameters under different faults: short-circuit current (Isc), open-circuit voltage (Uoc), current at the maximum power point (Im), and voltage at the maximum power point (Um). These parameters are used as training samples to establish a classification model through the SVM algorithm for training and verification. Simulation results show that this method can accurately diagnose the typical faults of the photovoltaic array, and the fault diagnosis accuracy is high.
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K Abdul Razak, R., K. S Muhammad, R. Baharom, and A. M I Mamat. "Open-Circuit Fault Detection Technique for Fault-Tolerant Bridgeless Boost Rectifier." International Journal of Engineering & Technology 7, no. 3.15 (August 13, 2018): 168. http://dx.doi.org/10.14419/ijet.v7i3.15.17523.
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Unexpected failure in one of the switches in a converter will lessen the performance of a system and may even prompt to a system failure. Therefore, to reduce the failure rate and to prevent unscheduled shutdown, a real-time fault detection is necessary. In this paper, a new technique to identify the exact location of the faulty switch based on single-phase bridgeless boost converter is proposed. The faulty switch is detected by analyzing the boost inductor current, switching mode and cycle of the input power supply. The information of the faulty switch will be used to redirect the current to any available path. Therefore, an uninterruptable and reliable power supply could be developed. The analysis of the proposed fault detection scheme is done by using PSIM simulation software.
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Veerendra, Arigela Satya, Akeel A. Shah, Mohd Rusllim Mohamed, Chavali Punya Sekhar, and Puiki Leung. "Wavelet Transform Based Fault Identification and Reconfiguration for a Reduced Switch Multilevel Inverter Fed Induction Motor Drive." Electronics 10, no. 9 (April 25, 2021): 1023. http://dx.doi.org/10.3390/electronics10091023.
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The multilevel inverter-based drive system is greatly affected by several faults occurring on switching elements. A faulty switch in the inverter can potentially lead to more losses, extensive downtime and reduced reliability. In this paper, a novel fault identification and reconfiguration process is proposed by using discrete wavelet transform and auxiliary switching cells. Here, the discrete wavelet transform exploits a multiresolution analysis with a feature extraction methodology for fault identification and subsequently for reconfiguration. For increasing the reliability, auxiliary switching cells are integrated to replace faulty cells in a proposed reduced-switch 5-level multilevel inverter topology. The novel reconfiguration scheme compensates open circuit and short circuit faults. The complexity of the proposed system is lower relative to existing methods. This proposed technique effectively identifies and classifies faults using the multiresolution analysis. Furthermore, the measured current and voltage values during fault reconfiguration are close to those under healthy conditions. The performance is verified using the MATLAB/Simulink platform and a hardware model.
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Fadzail, N. F., S. Mat Zali, M. A. Khairudin, and N. H. Hanafi. "Stator winding fault detection of induction generator based wind turbine using ANN." Indonesian Journal of Electrical Engineering and Computer Science 19, no. 1 (July 1, 2020): 126. http://dx.doi.org/10.11591/ijeecs.v19.i1.pp126-133.
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This paper presents a stator winding faults detection in induction generator based wind turbines by using artificial neural network (ANN). Stator winding faults of induction generators are the most common fault found in wind turbines. This fault may lead to wind turbine failure. Therefore, fault detection in induction generator based wind turbines is vital to increase the reliability of wind turbines. In this project, the mathematical model of induction generator based wind turbine was developed in MATLAB Simulink. The value of impedance in the induction generators was changed to simulate the inter-turn short circuit and open circuit faults. The simulated responses of the induction generators were used as inputs in the ANN model for fault detection procedures. A set of data was taken under different conditions, i.e. normal condition, inter-turn short circuit and open circuit faults as inputs for the ANN model. The target outputs of the ANN model were set as ‘0’ or ‘1’, based on the fault conditions. Results obtained showed that the ANN model can detect different types of faults based on the output values of the ANN model. In conclusion, the stator winding faults detection procedure for induction generator based wind turbines by using ANN was successfully developed.
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Parimalasundar, E., R. Senthil Kumar, V. S. Chandrika, and K. Suresh. "Fault diagnosis in a five-level multilevel inverter using an artificial neural network approach." Electrical Engineering & Electromechanics, no. 1 (January 4, 2023): 31–39. http://dx.doi.org/10.20998/2074-272x.2023.1.05.
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Introduction. Cascaded H-bridge multilevel inverters (CHB-MLI) are becoming increasingly used in applications such as distribution systems, electrical traction systems, high voltage direct conversion systems, and many others. Despite the fact that multilevel inverters contain a large number of control switches, detecting a malfunction takes a significant amount of time. In the fault switch configurations diode included for freewheeling operation during open-fault condition. During short circuit fault conditions are carried out by the fuse, which can reveal the freewheeling current direction. The fault category can be identified independently and also failure of power switches harmed by the functioning and reliability of CHB-MLI. This paper investigates the effects and performance of open and short switching faults of multilevel inverters. Output voltage characteristics of 5 level MLI are frequently determined from distinctive switch faults with modulation index value of 0.85 is used during simulation analysis. In the simulation experiment for the modulation index value of 0.85, one second open and short circuit faults are created for the place of faulty switch. Fault is identified automatically by means of artificial neural network (ANN) technique using sinusoidal pulse width modulation based on distorted total harmonic distortion (THD) and managed by its own. The novelty of the proposed work consists of a fast Fourier transform (FFT) and ANN to identify faulty switch. Purpose. The proposed architecture is to identify faulty switch during open and short failures, which has to be reduced THD and make the system in reliable operation. Methods. The proposed topology is to be design and evaluate using MATLAB/Simulink platform. Results. Using the FFT and ANN approaches, the normal and faulty conditions of the MLI are explored, and the faulty switch is detected based on voltage changing patterns in the output. Practical value. The proposed topology has been very supportive for implementing non-conventional energy sources based multilevel inverter, which is connected to large demand in grid.
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Aswad, Raya A. K., and Bassim M. H. Jassim. "Impact of Induction Motor Faults on the Basic Parameters' Values." Journal of Engineering 26, no. 12 (December 1, 2020): 66–80. http://dx.doi.org/10.31026/j.eng.2020.12.04.
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Unlike fault diagnosis approaches based on the direct analysis of current and voltage signals, this paper proposes a diagnosis of induction motor faults through monitoring the variations in motor's parameters when it is subjected to an open circuit or short circuit faults. These parameters include stator and rotor resistances, self-inductances, and mutual inductance. The genetic algorithm and the trust-region method are used for the estimation process. Simulation results confirm the efficiency of both the genetic algorithm and the trust-region method in estimating the motor parameters; however, better performance in terms of estimation time is obtained when the trust-region method is adopted. The results also show the possibility of extracting fault signatures from the motor's parameter values because each type of the mentioned faults has a different impact on these parameters. Under a 10% short circuit fault condition, the mutual inductance and rotor resistance deviate by almost 10% from their original values to lower values. While the stator resistance noticeably reduces by up to 20% during the open circuit fault condition.
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E, Parimalasundar, Jayakumar S, Ravikumar R, and Suresh K. "Investigation analysis of open circuit and short circuit fault on cascaded H-bridged multilevel inverter using artificial neural network approach." International Journal of Electrical and Electronics Research 10, no. 2 (June 6, 2022): 320–26. http://dx.doi.org/10.37391/ijeer.100243.
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Cascaded H-bridge multilevel inverters are becoming increasingly used in applications such as distribution systems, electrical traction systems, high voltage direct conversion systems, and many others. Despite the fact that multilevel inverters contain a large number of control switches, detecting a malfunction takes a significant amount of time. In the fault switch configurations diode included for freewheeling operation during open-fault condition. During short circuit fault conditions are carried out by the fuse, which can reveal the freewheeling current direction. The fault category can be identified independently and also failure of power switches harmed by the functioning and reliability of cascaded H-bridge multilevel inverters. This paper investigates the effects and performance of open and short switching faults of multilevel inverters. Output voltage characteristics of five level MLI are frequently determined from distinctive switch faults with modulation index value of 0.85 is used during simulation analysis. In the simulation study, with the modulation index value of 0.85, one second open and short circuit faults are generated for the location of the defective switch. Fault is identified automatically by means of artificial neural network technique using sinusoidal pulse width modulation based on distorted total harmonic distortion and managed by its own. The proposed topology is to be design and evaluate using MATLAB/Simulink platform.
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Zhang, Zi Yang, Jun Sheng Shi, Jing Yu Zhang, Xu Qing Wu, and Ming Li. "Study on Fault Detection for Photovoltaic Array Using Infrared Image." Advanced Materials Research 512-515 (May 2012): 280–84. http://dx.doi.org/10.4028/www.scientific.net/amr.512-515.280.
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This paper provides proof of concept for a technique that uses high resolution thermal infrared imager to detect faults for outdoor operation photovoltaic array. An experimental study focused on two situations was tested: abnormal emitting heat of monocrystalline silicon solar cells (hot spot); open circuit fault of photovoltaic array. Experimental results show that the infrared image could clearly give prominence to the faulty solar cell or PV array. The back surface temperature of solar cell with hot spot is higher than normal ones with 13.2°C in mean value，and the back surface temperature of open circuit PV array is higher than normal ones with 2.8°C in mean value.
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Vandris, Evstratios, and Gerald Sobelman. "Switch-level Differential Fault Simulation of MOS VLSI Circuits." VLSI Design 4, no. 3 (January 1, 1996): 217–29. http://dx.doi.org/10.1155/1996/34084.
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A new switch-level fault simulation method for MOS circuits is presented that combines compiled switch-level simulation techniques and functional fault modeling of transistor faults with the new fault simulation algorithm of differential fault simulation. The fault simulator models both node stuck-at-0, stuck-at-1 faults and transistor stuck-on, stuck-open faults. Prior to simulation, the switch-level circuit components are compiled into functional models. The effect of transistor faults on the function of the circuit components is modeled by functional fault models that execute very fast during simulation. Every compiled circuit component is assigned a dominance attribute, which abstracts relative strength information in the circuit. Dominance is used during simulation to resolve the X-state due to fighting pull-up and pull-down transistor paths and also to deduce transistor fault detectability and fault equivalencies prior to simulation. The differential fault simulation algorithm developed for gate-level circuits is adapted for use at the switch-level. Differential fault simulation provides excellent performance with minimum memory requirements, although it incurs a higher overhead at the switch-level than at the gate-level due to the dynamic memory properties of MOS circuits.
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Touaiti, Bilel, Hechmi Ben Azza, Mongi Moujahed, and Mohamed Jemli. "Fault-Tolerant Voltage Source Converter for Wind-Driven Doubly Fed Induction Generator Connected to a DC Load." Journal of Circuits, Systems and Computers 27, no. 10 (May 24, 2018): 1850153. http://dx.doi.org/10.1142/s0218126618501530.
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This paper presents a fault-tolerant Voltage Source Converter (VSC) for Field Oriented Control (FOC) of a stand-alone Doubly Fed Induction Generator (DFIG) connected to a DC load. In the proposed topology, the stator of the DFIG is connected to a DC load through a diode rectifier, while the rotor is connected to the DC load through a VSC. This topology allows the integration of DFIG in the hybrid system with other sources of production and storage, such as photovoltaic system, connected to the same DC bus. The fault-tolerant VSC consists in incorporating a fourth leg to replace the faulted leg. A fault detection scheme for switch device open-circuit faults is proposed in this study. The novelty of this method consists in analyzing the rotor currents within normal and faulty operating modes. Simulation results are presented for a 3.7[Formula: see text]kW DFIG-DC system with single open-circuit faults that validate the methods presented in this study. The effectiveness of the proposed fault detection method has been validated experimentally by using dSpace DS1104 control board based on TMS320F240 real time Digital Signal Processor (DSP).
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Sun, Min, Huaxing Zhao, Bo Chen, Wei Zeng, and Zaineng Yang. "Fault Diagnosis Strategy for Solar Cells Based on Reverse Derivation of I-V Curve." Journal of Physics: Conference Series 2564, no. 1 (August 1, 2023): 012018. http://dx.doi.org/10.1088/1742-6596/2564/1/012018.
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Abstract This paper proposes a fault diagnosis strategy for solar cells based on the reverse derivation of the I-V curve. This strategy does not require real-time monitoring of the surface irradiance and average temperature of the solar cell during operation. It only needs to calculate(establish) the I-V curve library under different irradiance and solar cell temperature in advance, then measure the open circuit voltage and short circuit current of the photovoltaic module during operation. And the measured voltage and current at the maximum power point can determine whether the solar cell is faulty. The possible faults of various solar cells are simulated by setting up experimental equipment, and the method is used for fault diagnosis. Experimental results show that the proposed method can effectively monitor various faults of solar cells. The method improves the accuracy of fault detection of the solar cell, enhances the reliability and economical benefits of the photovoltaic power station, and realizes online fault detection of the solar cell.
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Khadar, Saad, Abdellah Kouzou, Mohamed Mounir Rezzaoui, and Ahmed Hafaifa. "Sensorless Control Technique of Open-End Winding Five Phase Induction Motor under Partial Stator Winding Short-Circuit." Periodica Polytechnica Electrical Engineering and Computer Science 64, no. 1 (September 13, 2019): 2–19. http://dx.doi.org/10.3311/ppee.14306.
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Open-end winding induction machines are gaining more attention in the last years due to their attractive advantages in the industrial applications, where high reliability is required. However, despite their inherit robustness, they are subjected to various electrical or mechanical faults that can ultimately reduce the motor efficiency and later leads to full failure. This paper proposes a method of modeling the five phase induction machine with open end stator winding taking into consideration the short-circuit fault between turns. The fault modeling is based on the theory of electromagnetic coupling of electrical circuits. In addition, a sliding mode observer is used to estimate the speed rotor. The idea of proposed backstepping strategy is used in this paper to allow to the studied machine to continue its operating state under short circuit fault between turns. The proposed sensorless control strategy is evaluated in terms of the healthy and faulty performances through the simulation results presented in this paper. The obtained results prove that the proposed sensorless control technique allows to the open-end winding five phase induction machine to continue its operation mode under the specified fault of partial short-circuit of the stator winding. This can be a very practical situation in the industrial applications, especially in the case where the maintenance is not easy and the operation of the industrial process should not be interrupted suddenly.
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Niu, Dao Sen, Xiao Dong Liu, Shou Qun Sun, and Yang Liu. "Verification of Fault Control Measures Based on Fault Injection for MCU Control System." Applied Mechanics and Materials 484-485 (January 2014): 325–31. http://dx.doi.org/10.4028/www.scientific.net/amm.484-485.325.
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To verify the validity of fault control measures, a verification platform with software fault injection and hardware fault injection is developed to conduct fault diagnosis measures for MCU control system. For the faults occurring in the internal units of a controller, program debugger is employed to simulate software or hardware faults by varying the data; for the faults occurring in peripheral circuits, a circuit of fault-settings is employed to simulate hardware faults, i.e., open-/short-circuit and electrical level variation. This verification platform is applied to evaluate software measures to control the faults/errors in accordance with IEC60335/IEC60730/UL1998/CSA22.2.08, and a case of induction cooker is presented shows how it works. Experimental results show that the verification platform runs stably and accurately, and has a big value in practice.
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Johar, Harminder Singh, Abhijit Bhattacharya, and S. Srinivasa Rao. "Fault Tolerant Brushless DC Motor Drive for Aerospace Applications." Defence Science Journal 73, no. 06 (November 1, 2023): 749–56. http://dx.doi.org/10.14429/dsj.73.18898.
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This article brings out a Fault-tolerant BLDC motor drive for aerospace applications using the redundancy concept. In a way, it brings out a fault-tolerant strategy that can be used to continue the regular operation of a BLDC motor drive even after the occurrence of faults. As BLDC motors are used in critical and dangerous control areas like military services and space vehicles, a fault-tolerant drive is essential to maintain drive operation and provide desirable output. This article compares fault simulation results in the software model of a BLDC motor drive to those of fault simulation results in hardware for three main types of faults. Fault simulation is carried out for three types of faults, viz. inverter device open circuit fault, motor winding open circuit fault, and rotor position sensor (hall sensor) open-circuited fault. Fault tolerance is ensured by introducing a redundant drive (drive-2), which operates the complete drive at the advent of any of the faults mentioned above in the main (healthy) drive-1. A fault-tolerant (redundant) hardware comprising dual stator BLDC motor and redundant controllers is realized and operationalized. Fault simulation is carried out in this hardware, and these results are validated with the results of fault simulation in the MATLAB SIMULINK model. Software and hardware results are comparable and form a basis for developing fault-tolerant electro-mechanical actuation systems for high-reliability, high-cost applications, mainly aerospace.
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Akay, Ali, and Paul Lefley. "Open-Circuit Fault-Tolerant Control of Multi-Phase PM Machines by Compensating the d-q Axes Currents." Energies 14, no. 1 (January 1, 2021): 192. http://dx.doi.org/10.3390/en14010192.
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This paper presents a novel method to control sinusoidal distributed winding or sinusoidal back electromotive force (back-EMF) multi-phase permanent magnet (PM) machines under open-circuit fault conditions. In this study, five different fault conditions are considered: single-phase, adjacent double-phase, non-adjacent double-phase, adjacent three-phase, and non-adjacent three-phase open circuit conditions. New current sets for the remaining healthy phase under open-circuit fault conditions are obtained by compensating the direct-quadrature (d-q) axes currents. For this purpose, an iterative method has been used to get the new set of currents. D-q axes currents, due to faulty phase/phases, are shared to the healthy phases to obtain the same d-q axes currents as in the healthy condition. Therefore, the same torque is produced as in the healthy condition. The developed method is simulated in MATLAB/Simulink by using a d-q modelled sinusoidal back-EMF five-phase machine. A vector control block diagram has been designed to run the machine under healthy and faulty conditions. The machine model has been run successfully under fault tolerant conditions. Additionally, a finite element analysis (FEA) has been undertaken to simulate the five-phase PM model machine by using MagNet software. Open-circuit fault-tolerant control currents are fed into the coils of the machine model. Satisfactory torque results have been obtained. Because the model five-phase PM machine includes higher order back-EMF harmonics, especially the third harmonic, torque has ripple due to interaction between the fault-tolerant control currents and the higher order back-EMF harmonics.
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Geng, Qiang, Wenhao Du, Xuefeng Jin, Guozheng Zhang, and Zhanqing Zhou. "Online Fault Detection of Open-Circuit Faults in a DTP-PMSM Using Double DQ Current Prediction." World Electric Vehicle Journal 15, no. 5 (May 8, 2024): 204. http://dx.doi.org/10.3390/wevj15050204.
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This research proposes a strategy to diagnose open-phase faults (OPF) and open-switching faults (OSF) in dual three-phase permanent magnet synchronous motor (DTP-PMSM) inverters. The method is based on the dual d–q predictive current model and involves establishing a mathematical model and utilizing the finite control set model predictive current extraction technique to predict the motor current. It then analyzes the characteristics of the switching-tube current under both normal and fault conditions. Finally, a fault predictive current model is introduced and the residual is calculated based on the predicted fault current value and the actual measured current value to diagnose the inverter fault. The proposed method effectively overcomes misjudgment issues encountered in traditional open-circuit fault diagnosis of inverters. It enhances the system’s response speed during dynamic processes and strengthens the robustness of diagnosis algorithm parameters. The experimental results demonstrate that the proposed method can rapidly, effectively, and accurately diagnose open-circuit faults presented in this paper fastest within one-fifth of a current cycle. It achieves a diagnostic accuracy rate of 97% in the dual three-phase permanent magnet synchronous motor drive system.
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Jiang, Yaoxi, Hongchun Shu, and Mengli Liao. "Fault-Tolerant Control Strategy for Sub-Modules Open-Circuit Fault of Modular Multilevel Converter." Electronics 12, no. 5 (February 22, 2023): 1080. http://dx.doi.org/10.3390/electronics12051080.
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Modular multilevel converter (MMC) is a key device of high-voltage-direct circuit (HVDC) transmission system, the sub-module detection technology of which will directly influence the damage severity, and even the reliability of the whole system. In this paper, the open-circuit fault characteristics of an insulated gate bipolar transistor (IGBT) in a sub-module are analyzed, and a fault-tolerant optimal control strategy is proposed for the redundant hot-reserved MMC based on nearest-level modulation (NLM). A fault sub-module diagnosis and location strategy based on the deviation distance of the capacitor voltages is presented. After the faulty sub-module is removed, due to the asymmetric operation of the MMC, odd-order circulating currents are introduced in the faulty phase, in which the fundamental-frequency circulating current is the major component; the fundamental-frequency voltage related to the redundancy rate is injected into the faulty phase, which effectively suppresses the fundamental-frequency circulating current and harmonics in the faulty phase. The proposed method combines fault detection and fault ride-through steps, so it has the features of high reliability and high compatibility. Based on the Matlab/Simulink simulation model, the effectiveness of the proposed strategy is verified.
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Wang, Song, Shuang Wang, Ying Cui, Jie Long, Fuqiang Ren, Shengchang Ji, and Shuhong Wang. "An Experimental Study of the Sweep Frequency Impedance Method on the Winding Deformation of an Onsite Power Transformer." Energies 13, no. 14 (July 8, 2020): 3511. http://dx.doi.org/10.3390/en13143511.
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Power transformers are one of the most important devices in electrical networks. The safety operation of the transformers directly affects the reliability of the power system. To diagnose the internal deformation of the transformer as soon as possible is of great significance. As a new technique, sweep frequency impedance (SFI) method has been used to detect the short-circuit fault of the transformer winding. However, the SFI method is still in the early stage and more experimental tests are needed to further demonstrate its accuracy in the detection of other types of winding faults. Therefore, in this paper, the SFI method is investigated to diagnose an open-circuit fault of an onsite transformer. By deeply analyzing the SFI curves and SFI values at power frequency obtained by the SFI test, the open-circuit fault of this transformer winding is determined. Meanwhile, the accuracy of the diagnostic results based on the SFI method is validated by introducing the results of the short-circuit impedance (SCI) and winding resistance measurements. The application of the SFI method on the detection of the open-circuit fault within the transformer winding not only enrich the SFI method research but also provide valuable practical guidance significance for the fault detection.
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Fadzail, Noor Fazliana, Samila Mat Zali, and Ernie Che Mid. "Multiple faults detection in doubly-fed induction generator wind turbine using artificial neural network." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 3 (June 1, 2024): 3342. http://dx.doi.org/10.11591/ijece.v14i3.pp3342-3349.
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The development of fault detection methods in wind turbine (WT), especially for single fault detection, is continuously increasing. However, the rapid growth of fault detection in WT leads to another challenge where multiple faults can occur. The single fault detection method in WT is no longer reliable, especially when multiple faults occur simultaneously. Therefore, multiple faults detection in doubly-fed induction generators (DFIG) WT was proposed using an artificial neural networks (ANN) model. These multiple faults include internal and external stator faults happening simultaneously. Internal stator faults cover inter-turn short circuit faults and open circuit faults, while external stator faults cover loss of excitation and external short circuit faults. The performance of the developed multiple faults detection model was measured using accuracy and the root mean square error (RMSE) value. The results show that the developed model performs well with high accuracy and a low RMSE value. Thus, the developed model can accurately detect the coexistence of multiple faults in DFIG WT.
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Murillo-Soto, Luis D., and Carlos Meza. "Automated Fault Management System in a Photovoltaic Array: A Reconfiguration-Based Approach." Energies 14, no. 9 (April 23, 2021): 2397. http://dx.doi.org/10.3390/en14092397.
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This work proposes an automated reconfiguration system to manage two types of faults in any position inside the solar arrays. The faults studied are the short-circuit to ground and the open wires in the string. These faults were selected because they severely affect power production. By identifying the affected panels and isolating the faulty one, it is possible to recover part of the power loss. Among other types of faults that the system can detect and locate are: diode short-circuit, internal open-circuit, and the degradation of the internal parasitic serial resistance. The reconfiguration system can detect, locate the above faults, and switch the distributed commutators to recover most of the power loss. Moreover, the system can return automatically to the previous state when the fault has been repaired. A SIMULINK model has been built to prove this automatic system, and a simulated numerical experiment has been executed to test the system response to the faults mentioned. The results show that the recovery of power is more than 90%, and the diagnosis accuracy and sensitivity are both 100% for this numerical experiment.
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Yang, Zhan She, and Xian Min Ma. "The Extraction of Fault Feature Vector in Inverter Open Base on Matlab/Simulink." Advanced Materials Research 846-847 (November 2013): 706–9. http://dx.doi.org/10.4028/www.scientific.net/amr.846-847.706.
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Fault is classified when the thyristor open in three phase bridge rectifier circuit in this paper,Circuit simulation model is established based on Matlab/Simulink,and for a variety of open circuit fault is simulinked,extracted all kinds of fault feature vector, provided the theory of mathematical basis for intelligent fault diagnosis.
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Bolbolnia, Rouhollah, Karim Abbaszadeh, and Mojtaba Nasiri. "Diagnosis and Fault-Tolerant Control of Six-Phase Wind Turbine under Multiple Open-Switch Faults." Mathematical Problems in Engineering 2021 (October 7, 2021): 1–16. http://dx.doi.org/10.1155/2021/9999918.
Full textAbstract:
A new open-switch fault diagnosis method is proposed in this paper for the six-phase AC-DC converter based on the difference between the phase current and the corresponding reference using an adaptive threshold. The single and multiple open-switch faults are detected without any additional equipment and complicated calculations since the proposed fault detection method is integrated with the hysteresis controller. The proposed fault-tolerant technique reduces the value of overcurrent and total harmonic distortion on the side phases of the faulty one, by changing the switching signal of one switch in its opposite phase in some regions. This technique is performed without adding any legs, switches, or triode for alternating currents to the circuit. Finally, the proposed fault-tolerant technique is evaluated by MATLAB simulation and the results show its effectiveness.
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Hayroman, Muhammad Hakiem, Rahimi Baharom, Wan Noraishah Wan Abdul Munim, and Khairul Safuan Muhammad. "Computer simulation of open-circuit fault-tolerant boost rectifier based on SPMC." International Journal of Power Electronics and Drive Systems (IJPEDS) 15, no. 2 (June 1, 2024): 1031. http://dx.doi.org/10.11591/ijpeds.v15.i2.pp1031-1044.
Full textAbstract:
This paper presents a computer simulation of an open-circuit fault-tolerant boost rectifier based on a single-phase matrix converter using MATLAB/ Simulink. The proposed converter employs a fault identification technique to identify the faulty switch by generating a binary code extracted from the output voltage, magnitude of inductor current, and cycle of the input power supply. Upon identifying the faulty switch, the current is redirected to any available path through operational switches by controlling the switching devices. The aim is to ensure uninterrupted power supply from the source to the load. The paper includes a detailed analysis of the fault identification technique and the options for rerouting the current path. The outcomes of this paper are simulated using MATLAB/Simulink.