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Journal articles on the topic 'Fault is of the sufferer'

Author: Grafiati

Published: 13 December 2022

Last updated: 31 July 2025

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1

Herada, Shella Novia. "When the Flower Wilts: Stigmas of Mental Illnesses in Indonesia." K@ta Kita 7, no. 3 (2019): 316–19. http://dx.doi.org/10.9744/katakita.7.3.316-319.

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In Indonesia, mental illnesses, or more specifically, depression, is still seen as a moral failure, a failure to conform in society due to a faulty moral upbringing. However, little spotlight is given towards the immediate family of a sufferer, how a sufferer places burdens on their family in terms of economy, psychology, and social life, in addition to the burden of sympathy as the result of having to put the needs of someone else above onself. To depict such suffering and help make it more visible, I created a story, written from the perspective of someone close to a sufferer, to show how th

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Dwi Permana, Alvin, Mamik Tri Wedawati, and Muhammad Dhika Arif Rizqan. "Love and Belonging Needs in John Green’s The Fault in Our Stars." Udayana Journal of Social Sciences and Humanities (UJoSSH) 5, no. 1 (2021): 21. http://dx.doi.org/10.24843/ujossh.2021.v05.i01.p03.

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The anxiety of being treated differently unlike others is one of the myriad uncomfortable feelings which may be understood by cancer sufferer. The present study aimed to expose the needs of two cancer sufferers who loved each other. They are the main characters of the Fault in Our Stars namely Hazel and Augustus. Therefore, the researchers addressed two questions: How are the love and belonging needs of Hazel and Augustus portrayed in John Green's The Fault in Our Stars? And what are the impacts of fulfilling love and belonging needs toward Hazel and Augustus as it is portrayed in John Green’s

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Lakshmi A, Sowjanya, and Vanipriya Ch. "Communication induced checkpointing based fault tolerance mechanism using deep-learning in IoT applications." Indonesian Journal of Electrical Engineering and Computer Science 37, no. 3 (2025): 1785. https://doi.org/10.11591/ijeecs.v37.i3.pp1785-1796.

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Internet of things (IoT) is increasingly used in diverse environments such as healthcare, industry and agriculture. They carry a risk of adverse effects if they make decisions based on faulty information. Software faults, especially transient faults are a primary contributor to deficient decision-making. The existing fault tolerant mechanisms often suffer from checkpoint overheads as checkpoints are placed in all the nodes. This paper describes a novel communication induced checkpointing based fault tolerance mechanism (CIC-FTM) designed to efficiently recover from transient faults, while mini

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Sowjanya, Lakshmi A. Vanipriya Ch. "Communication induced checkpointing based fault tolerance mechanism using deep-learning in IoT applications." Indonesian Journal of Electrical Engineering and Computer Science 37, no. 3 (2025): 1785–96. https://doi.org/10.11591/ijeecs.v37.i3.pp1785-1796.

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Internet of things (IoT) is increasingly used in diverse environments such as healthcare, industry and agriculture. They carry a risk of adverse effects if they make decisions based on faulty information. Software faults, especially transient faults are a primary contributor to deficient decision-making. The existing fault tolerant mechanisms often suffer from checkpoint overheads as checkpoints are placed in all the nodes. This paper describes a novel communication induced checkpointing based fault tolerance mechanism (CIC-FTM) designed to efficiently recover from transient faults, while mini

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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 (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 transforma

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Arfeen, Zeeshan, Ehtisham Arshad, Raja Massod Lark, et al. "Advanced Fault Detection, Classification, and Analysis Framework for HV Transmission Lines using RT Synchronized Monitoring and Control Systems." UCP Journal of Engineering & Information Technology 2, no. 2 (2025): 41–51. https://doi.org/10.24312/ucp-jeit.02.02.436.

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The emergence of new technologies such as IoT, along with the merger of renewable energies, AI, smart grids, and non linear loads is enhancing the complexity of modern power systems and detecting fault as well as its correction much harder. Traditional methods suffer from inadequate speed, accuracy, less coverage, and latency that renders them highly ineffective in varying conditions. Reliable power transmission is vital for modern infrastructure, as faults on transmission lines can disrupt supply, damage equipment, and create safety risks. This paper presents a Fault Detection and Analysis Sy

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Dr.Amina, Bashir Dr.Muhammad Qasim Dr.Umaar Azhar. "CUTIS LAXA: VERY UNUSUAL THING OF CONNECTIVE MATTER SYNDROMES CONNECTED WITH IRREGULARITIES INTO FLEXIBLE MATTER." INDO AMERICAN JOURNAL OF PHARMACEUTICAL SCIENCES 05, no. 10 (2018): 10622–25. https://doi.org/10.5281/zenodo.1470019.

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<em>Cutis laxa very mixed collection of connective matter syndromes connected with irregularities into flexible matter. The situation might remain autosomal receding (Category 1 also Category 2), autosomal leading, X-allied receding or else developed. Innate mistakes of elastin mixture plus physical flaws of extracellular medium proteins main towards reduced springiness and dismissed, drooping casing into exaggerated sufferers. This includes skin membrane, lungs, endocrine structure, stomach zones, circulatory scheme plus genitourinary zones. Medical appearances of cutis laxa be influenced by

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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 (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 op

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Xia, Linlin, Jingyu Cong, Xun Xu, Yiping Gao, and Shufeng Zhang. "H-infinity adaptive observer enhancements for vehicle chassis dynamics-based navigation sensor fault construction." International Journal of Advanced Robotic Systems 17, no. 2 (2020): 172988142090421. http://dx.doi.org/10.1177/1729881420904215.

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The issues of chassis dynamics-based navigation sensor fault and state estimation in land vehicles are specialized in this study. Owing to the essential attributes of robust theory-based observers, an H-infinity adaptive observer is proposed to implement the fault reconstructions of faulty sensors, offering a reference to vehicles for further favorable control decision-making. This observer fuses a linear matrix inequality convex optimization strategy, with the dynamics of land vehicles established mathematically, the consequent problems associated with augmented descriptor system state-space

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Ling, Haoyu, Manlu Liu, and Yi Fang. "Deep Edge-Based Fault Detection for Solar Panels." Sensors 24, no. 16 (2024): 5348. http://dx.doi.org/10.3390/s24165348.

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Solar panels may suffer from faults, which could yield high temperature and significantly degrade their power generation. To detect faults of solar panels in large photovoltaic plants, drones with infrared cameras have been implemented. Drones may capture a huge number of infrared images. It is not realistic to manually analyze such a huge number of infrared images. To solve this problem, we develop a Deep Edge-Based Fault Detection (DEBFD) method, which applies convolutional neural networks (CNNs) for edge detection and object detection according to the captured infrared images. Particularly,

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Naito, Shohei, Ken Xiansheng Hao, Shigeki Senna, et al. "Investigation of Damages in Immediate Vicinity of Co-Seismic Faults During the 2016 Kumamoto Earthquake." Journal of Disaster Research 12, no. 5 (2017): 899–915. http://dx.doi.org/10.20965/jdr.2017.p0899.

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In the 2016 Kumamoto earthquake, the Futagawa fault zone and the Hinagu fault zone were active in some sections, causing severe damage in neighboring areas along the faults. We conducted a detailed investigation of the surface earthquake fault, building damage, and site amplification of shallow ground within about 1 km of the neighboring areas of the fault. The focus was mainly on Kawayou district, Minamiaso village and Miyazono district, Mashiki town, and locations that suffered particularly severe building damage. We explored the relationship between local strong motion and building damage c

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Lou, Yihuai, Bo Zhang, Ruiqi Wang, Tengfei Lin, and Danping Cao. "Seismic fault attribute estimation using a local fault model." GEOPHYSICS 84, no. 4 (2019): O73—O80. http://dx.doi.org/10.1190/geo2018-0678.1.

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Faults in the subsurface can be an avenue of, or a barrier to, hydrocarbon flow and pressure communication. Manual interpretation of discontinuities on 3D seismic amplitude volume is the most common way to define faults within a reservoir. Unfortunately, 3D seismic fault interpretation can be a time-consuming and tedious task. Seismic attributes such as coherence help define faults, but suffer from “staircase” artifacts and nonfault-related stratigraphic discontinuities. We assume that each sample of the seismic data is located at a potential fault plane. The hypothesized fault divides the sei

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Kabir Chakraborty, Sanchari De, Tamanna Saha, and Purnima Nama. "Fault location prediction under line-to-ground fault in transmission line using artificial neural network." World Journal of Advanced Engineering Technology and Sciences 15, no. 2 (2025): 857–66. https://doi.org/10.30574/wjaets.2025.15.2.0552.

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The electrical power system occasionally suffers from failures, often caused by the faults occurring within the system. Accurate fault location prediction is important to ensure the reliable operation of the power system and to minimize the downtime during the occurrence of fault conditions. While traditional methods of fault location detection remain effective for specific scenarios, Artificial Neural Network (ANN) provide a more versatile, efficient, and cost-effective approach to fault location detection. This study focuses on predicting fault positions under line-to-ground (L-G) fault usin

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14

Xie, Xuyang, Zichun Yang, Lei Zhang, et al. "An improved Autogram and MOMEDA method to detect weak compound fault in rolling bearings." Mathematical Biosciences and Engineering 19, no. 10 (2022): 10424–44. http://dx.doi.org/10.3934/mbe.2022488.

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<abstract> <p>When weak compound fault occurs in rolling bearing, the faint fault features suffer from serious noise interference, and different type faults are coupled together, making it a great challenge to separate the fault features. To solve the problems, a novel weak compound fault diagnosis method for rolling bearing based on improved Autogram and multipoint optimal minimum entropy deconvolution adjusted (MOMEDA) is proposed. Firstly, the kurtosis index in Autogram is modified with multi-scale permutation entropy, and improved Autogram finds the optimal resonance frequency

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Tian, Yingying, and Fanglai Zhu. "Fault estimation and observer-based fault-tolerant controller in finite frequency domain." Transactions of the Institute of Measurement and Control 40, no. 5 (2017): 1659–68. http://dx.doi.org/10.1177/0142331216688617.

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In this paper, the problems of finite-frequency fault estimation (FE) and fault tolerant controller design are investigated for a class of systems subjected to both sensor and actuator faults. To begin with, by introducing an expanded state vector, the original system is transformed into a descriptor system, and then an unknown input proportional-integral observer (PI) is developed to provide state and FE, which avoids the overdesign problems occurring in the entire frequency domain. After this, based on reconstructed information, an observer-based fault-tolerant controller is designed to stab

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Zhao, Jianwen, Yiwen Du, Yaxin Luo, and Yubing Zhang. "The exponential function coefficient characteristic of the fault voltage forward traveling wave and protection method for microgrid." Engineering Research Express 7, no. 1 (2025): 015315. https://doi.org/10.1088/2631-8695/ada484.

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Abstract Existing microgrid protection methods suffer from false action or non-action due to the difficulty of wave head extraction. The time-domain expressions of voltage forward traveling wave for internal faults or external faults in microgrid are derived in this paper, and the exponential function coefficient characteristic of the fault voltage forward traveling wave is obtained: the maximum value of exponential function coefficient for the internal fault is greater than that of the external fault. Based on this, a novel microgrid protection method is proposed, which uses the exponential f

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17

Wu, Weixiang, Xusen Wan, Jinbao Zhang, and Shi Cheng. "Research on a Random Mask Infection Countermeasure against Double Fault Attacks." Applied Sciences 13, no. 22 (2023): 12530. http://dx.doi.org/10.3390/app132212530.

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The infection countermeasure, in which the main idea is to prevent adversaries from exploiting faulty ciphertexts to break the key by spreading the induced fault, is a very effective countermeasure against fault attacks. However, most existing infection countermeasures struggle to defend against double-fault attacks effectively due to the single-fault assumption. By analyzing the principle of infection mechanism and adding different random Boolean masks in the two encryption paths, this paper proposes a measure called a random mask infection countermeasure to defend against double-fault attack

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18

Zhang, Feige, Shesheng Gao, Wenjuan Zhang, Guo Li, and Chao Zhang. "Current Sensor Fault-Tolerant Control Strategy for Speed-Sensorless Control of Induction Motors Based on Sequential Probability Ratio Test." Electronics 13, no. 13 (2024): 2476. http://dx.doi.org/10.3390/electronics13132476.

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In the speed-sensorless vector control of induction motors (IMs), the speed estimation accuracy suffers from the deteriorated current measurement caused by the current sensor faults, such as open circuit in one phase, DC bias, and odd harmonics. In this paper, a novel speed estimation strategy based on the current sensor fault-tolerant control is proposed to improve the speed estimation accuracy under the current sensor faults. First, to detect the current sensor faults in real time, the sequential probability ratio test is introduced to the system by using the innovations of the extended Kalm

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19

Zhao, Qi, Kuan Li, Jinlong Tan, Lu Zhang, and Shuobo Zhang. "Pole-to-Pole Fault Current Impact Factors Analysis Based on Equivalent Impedance for Modular Multilevel Converter High-Voltage Direct Current System." Electronics 14, no. 4 (2025): 694. https://doi.org/10.3390/electronics14040694.

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The fault current in MMC HVDC systems suffers from a quick rising rate and no zero-cross problems, which makes it hard to cut off and has become the main problem when promoting MMC dc systems. Among the different types of faults, the pole-to-pole fault is the most serious one. Hence, to clarify the discharging mechanism during pole-to-pole faults and determine the influential factors, this paper proposes a simplified modeling method for MMC HVDC fault current impact factors analysis. The proposed method uses the simplified MMC circuit when faults happen, and the frequency domain model is then

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20

Abdullahi, Adeleke, Noor Azah Samsudin, Mohd Rasidi Ibrahim, Muhammad Syariff Aripin, Shamsul Kamal Ahmad Khalid, and Zulaiha Ali Othman. "Towards IR4.0 implementation in e-manufacturing: artificial intelligence application in steel plate fault detection." Indonesian Journal of Electrical Engineering and Computer Science 20, no. 1 (2020): 430. http://dx.doi.org/10.11591/ijeecs.v20.i1.pp430-436.

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<span>Fault detection is the task of discovering patterns of a certain fault in industrial manufacturing. Early detection of fault is an essential task in industrial manufacturing. Traditionally, faults are detected by human experts. However, this method suffers from cost and time. In this era of Industrial revolution IR 4.0, machine learning (ML) methods and techniques are developed to solve fault detection problem. In this study, three standard ML models: LR, NB, and SVM are developed for the classification problem. The experimental dataset used in this study consists of steel plates f

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Adeleke, Abdullahi, Azah Samsudin Noor, Rasidi Ibrahim Mohd, Syariff Aripin Muhammad, Kamal Ahmad Khalid Shamsul, and Ali Othman Zulaiha. "Towards IR4.0 implementation in e-manufacturing: artificial intelligence application in steel plate fault detection." Indonesian Journal of Electrical Engineering and Computer Science 20, no. 1 (2022): 430–36. https://doi.org/10.11591/ijeecs.v20.i1.pp430-436.

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Fault detection is the task of discovering patterns of a certain fault in industrial manufacturing. Early detection of fault is an essential task in industrial manufacturing. Traditionally, faults are detected by human experts. However, this method suffers from cost and time. In this era of Industrial revolution IR 4.0, machine learning (ML) methods and techniques are developed to solve fault detection problem. In this study, three standard ML models: LR, NB, and SVM are developed for the classification problem. The experimental dataset used in this study consists of steel plates faults. The d

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Kim, Donguk, Minseok Jeon, Doha Hwang, and Hakjoo Oh. "PAFL: Enhancing Fault Localizers by Leveraging Project-Specific Fault Patterns." Proceedings of the ACM on Programming Languages 9, OOPSLA1 (2025): 1378–405. https://doi.org/10.1145/3720526.

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We present PAFL, a new technique for enhancing existing fault localization methods by leveraging project-specific fault patterns. We observed that each software project has its own challenges and suffers from recurring fault patterns associated with those challenges. However, existing fault localization techniques use a universal localization strategy without considering those repetitive faults. To address this limitation, our technique, called project-aware fault localization (PAFL), enables existing fault localizers to leverage project-specific fault patterns. Given a buggy version of a proj

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Tang, Tao, Chun Huang, Zhenxing Li, and Xiuguang Yuan. "Identifying Faulty Feeder for Single-Phase High Impedance Fault in Resonant Grounding Distribution System." Energies 12, no. 4 (2019): 598. http://dx.doi.org/10.3390/en12040598.

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The identification of faulty feeder for single-phase high impedance faults (HIFs), especially in resonant grounding distribution system (RGDS), has always been a challenge, and existing faulty feeder identification techniques for HIFs suffer from some drawbacks. For this problem, the fault transient characteristic of single-phase HIF is analyzed and a faulty feeder identification method for HIF is proposed. The analysis shows that the transient zero-sequence current of each feeder is seen as a linear relationship between bus transient zero-sequence voltage and bus transient zero-sequence volta

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SHAKIL, D. JAMADAR, SHRAVANKUMAR AKIREDDY, and ANITHA CHIRRA. "A NOVEL LOGIC TO STATOR SINGLE PHASE - TO - GROUND FAULT FOR POWER-FORMER." JournalNX - A Multidisciplinary Peer Reviewed Journal 3, no. 3 (2017): 53–57. https://doi.org/10.5281/zenodo.1462659.

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The stator single-phase to ground fault is one of the most common fault that a Generator will suffer. If such fault is neglected then there are chances of converting it into phase to phase fault. So there is need to detect and isolate the faulty part from the rest of the system as early as possible. Because of this, protection is very important otherwise there is shortage of power in our system. The proposed approach detects the ground fault by analyzing the direction, magnitude, and energy of leakage current, which is the difference of zero-sequence current fault component between the neutral

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Lodhe, Abhay, Ashish Tandekar, Mayur Rokade, et al. "An Overview on Detection of Temporary Fault and Permanent Fault for 3 Phase Load." International Journal for Research in Applied Science and Engineering Technology 11, no. 4 (2023): 2951–53. http://dx.doi.org/10.22214/ijraset.2023.50820.

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Abstract: To Maintain reliability in Power System it is important to protect the 3 phase devices like inductive, resistive, etc against various faults occurring in it. This fault should be identified and analysed quickly for their remedies. The Project Aim is to develops an Automatic Tripping mechanism for the three-phase system. In the case of a temporary fault, the output of the project resets automatically within second. While in event of Permanent fault condition the permanent Trip. Due to these faults, the power system may suffer from considerable damage. This can lead to disturbance in p

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Desta, Berhanu Zelalem, Mengesha M. Wogari, and Stanislaw M. Gubanski. "Investigation on Pollution-Induced Flashovers of In-Service Insulators in Ethiopian Power Transmission Lines." Energies 17, no. 9 (2024): 2007. http://dx.doi.org/10.3390/en17092007.

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Power transmission lines in Ethiopia are experiencing an alarmingly high frequency of unexplained outages triggered by environmental factors, which significantly undermine the reliability of the country’s power system. This paper presents investigations aiming to identify those among the unexplained fault records that have been caused by pollution induced flashovers. An identification method is developed, which associates the contextual fault features, such as information about the characteristics of the fault, fault location, and time of day, as well as month of its occurrence with local mete

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Han, Jiaming, Zhong Yang, Qiuyan Zhang, et al. "A Method of Insulator Faults Detection in Aerial Images for High-Voltage Transmission Lines Inspection." Applied Sciences 9, no. 10 (2019): 2009. http://dx.doi.org/10.3390/app9102009.

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Insulator faults detection is an important task for high-voltage transmission line inspection. However, current methods often suffer from the lack of accuracy and robustness. Moreover, these methods can only detect one fault in the insulator string, but cannot detect a multi-fault. In this paper, a novel method is proposed for insulator one fault and multi-fault detection in UAV-based aerial images, the backgrounds of which usually contain much complex interference. The shapes of the insulators also vary obviously due to the changes in filming angle and distance. To reduce the impact of comple

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Nie, Lei, Yizhu Ren, Rouhui Wu, and Mengying Tan. "Sensor Fault Diagnosis, Isolation, and Accommodation for Heating, Ventilating, and Air Conditioning Systems Based on Soft Sensor." Actuators 12, no. 10 (2023): 389. http://dx.doi.org/10.3390/act12100389.

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Heating, Ventilating, and Air Conditioning (HVAC) systems often suffer from unscheduled maintenance or abnormal shutdown due to the fault of their interior sensor system. Traditional fault diagnosis methods for HVAC sensor systems primarily focus on sensor fault diagnosis and isolation, lacking fault accommodation. Therefore, to realize effective sensor fault detection, identification, and accommodation (SFDIA), a method for HVAC SFDIA based on the soft sensor is proposed. First, a diagnosis soft sensor with multi-variable input is constructed to estimate the output of the physical sensor bein

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Zhao, Hong Shan, Sha Sha Lian, and Ling Shao. "Fault Prediction of Pitch Actuator for Wind Turbines." Applied Mechanics and Materials 721 (December 2014): 397–401. http://dx.doi.org/10.4028/www.scientific.net/amm.721.397.

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Hydraulic pitch-controlled system is one of the components of wind turbines which are frequently prone to faults. Early fault prediction of the pitch control system can improve the operation reliability effectively and reduce the unnecessary loss. Wind turbines suffer much environmental interference; moreover, data-based fault prediction is vulnerable to occur false alarms by the impact of these factors. And it is difficult to implement the fault isolation. So this paper presents a fault prediction method for the pitch-controlled system, which is based on the mathematical model of wind turbine

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Abdelrhman, Ahmed M., M. Salman Leong, Lim Meng Hee, and Wai Keng Ngui. "A Comparative Study of Reassigned Conventional Wavelet Transform for Machinery Faults Detection." Applied Mechanics and Materials 773-774 (July 2015): 90–94. http://dx.doi.org/10.4028/www.scientific.net/amm.773-774.90.

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Application of Fast Fourier Transform (FFT) in machinery faults detection is known to be only effective if fault is of repetitive in nature and considering severe. While minor and transient faults are usually remain undetected based on vibration spectrum analysis. Wavelet analysis is relatively new technique which is still suffered from inadequately in its time-frequency resolution. In this paper, ahmedrabak_time wavelet is proposed based on the wavelet reassignment technique for Morlet mother wavelet. The proposed wavelet analysis is compared to the conventional wavelet analysis for machinery

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Cartocci, Nicholas, Marcello R. Napolitano, Francesco Crocetti, Gabriele Costante, Paolo Valigi, and Mario L. Fravolini. "Data-Driven Fault Diagnosis Techniques: Non-Linear Directional Residual vs. Machine-Learning-Based Methods." Sensors 22, no. 7 (2022): 2635. http://dx.doi.org/10.3390/s22072635.

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Linear dependence of variables is a commonly used assumption in most diagnostic systems for which many robust methodologies have been developed over the years. In case the system nonlinearities are relevant, fault diagnosis methods, relying on the assumption of linearity, might potentially provide unsatisfactory results in terms of false alarms and missed detections. In recent years, many authors have proposed machine learning (ML) techniques to improve fault diagnosis performance to mitigate this problem. Although very powerful, these techniques require faulty data samples that are representa

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Borja-Jaimes, Vicente, Antonio Coronel-Escamilla, Ricardo Fabricio Escobar-Jiménez, et al. "Fractional-Order Sliding Mode Observer for Actuator Fault Estimation in a Quadrotor UAV." Mathematics 12, no. 8 (2024): 1247. http://dx.doi.org/10.3390/math12081247.

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In this paper, we present the design of a fractional-order sliding mode observer (FO-SMO) for actuator fault estimation in a quadrotor unmanned aerial vehicle (QUAV) system. Actuator faults can significantly compromise the stability and performance of QUAV systems; therefore, early detection and compensation are crucial. Sliding mode observers (SMOs) have recently demonstrated their accuracy in estimating faults in QUAV systems under matched uncertainties. However, existing SMOs encounter difficulties associated with chattering and sensitivity to initial conditions and noise. These challenges

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Ward, Steven N. "More on Mmax." Bulletin of the Seismological Society of America 87, no. 5 (1997): 1199–208. http://dx.doi.org/10.1785/bssa0870051199.

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Abstract M max the maximum magnitude earthquake that a fault is likely to suffer, plays an important role in earthquake hazard estimation. Although observational evidence summarized in plots of characteristic earthquake magnitude (Mchar) versus fault length indicate that smaller faults produce lower magnitude events, an argument has been made that any fault regardless of its length should have Mmax near magnitude 8. The rationale for this argument charges that the contrary observational evidence stems from historical catalogs of limited extent and that it largely excludes nonconventional earth

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Jayati, Holkar, and Vidhya Fulmali Prof. "INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY." International Journal of Engineering Sciences & Research Technology 5, no. 2 (2016): 863–71. https://doi.org/10.5281/zenodo.46534.

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The transmission line among the other electrical power technique component suffers from unexpected failure due to various random causes. The transmission line is quite large as it is open in the environment. The fault occurs on transmission line when two or more conductors come in contact with each other or ground. This paper presents a proposed model based on MATLAB/SIMULINK software to detect the fault on transmission line. The output of the system is used to train an artificial neural network to detect the transmission line faults. The fault detection has been achieved by using artificial n

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Du, Xinyu, Lichao Mai, and Hossein Sadjadi. "Fault Diagnostics and Prognostics for Vehicle Springs and Stablizer Bar." Annual Conference of the PHM Society 12, no. 1 (2020): 10. http://dx.doi.org/10.36001/phmconf.2020.v12i1.1129.

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Vehicle springs and stabilizer bar are critical suspension components impacting vehicle riding and handling experience. Diagnostics and prognostics of springs and stabilizer bar can improve customer perceived quality, reduce repair cost and increase up-time for fleet vehicles. It’s even more important for autonomous vehicles, since there is no human driver to sense fault symptoms. Currently, there is no production solution to automatically diagnose and prognose spring and stabilizer bar failures, and most research work is suffered by various noise factors. In this work, a novel solution based

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Liu, Zhizhong, Zhuo Zhao, Guangyu Huang, Fei Wang, Peng Wang, and Jiayue Liang. "Power Grid Faults Diagnosis Based on Improved Synchrosqueezing Wavelet Transform and ConvNeXt-v2 Network." Electronics 14, no. 2 (2025): 388. https://doi.org/10.3390/electronics14020388.

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The increasing demand on electrical power consumption all over the world makes the need for stable and reliable electrical power grids is indispensable. Meanwhile, power grid fault diagnosis based on fault recording data is an important technology to ensure the normal operation of the power grid. Despite the fact that dozens of studies have been put forward to detect electrical faults, these studies still suffer from several downsides, such as fuzzy characteristics of complex fault samples with small inter-class differences and large intra-class differences in different topology structures of

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Zhang, Xin Hui, Shi Liang Yang, Wei Kui Wang, Yun Liu, and Yan Wei. "Establishment of Aircraft Ammunition Fault Diagnosis Expert System Knowledge Base Based on FTA." Applied Mechanics and Materials 121-126 (October 2011): 3909–13. http://dx.doi.org/10.4028/www.scientific.net/amm.121-126.3909.

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Aircraft ammunitions inevitably suffer various faults during its storage, use and maintenance. The faults may result in disastrous consequences or make combat missions fail to meet related tactical and strategic requirements, so their diagnoses are significant for the safe and normal storage and use in combats. The diagnoses of the faults are complicated and difficult and always need the participation of experts who are small in quantity. Thus, this paper studies and develops the establishment of an aircraft ammunition fault diagnosis expert system knowledge base for the purposes of better col

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Hu, Anlin, Wenjiang Feng, Xudong Zhu, Junjie Wang, Yiping Ao, and Hao Feng. "MetaGAN: Metamorphic GAN-Based Augmentation for Improving Deep Learning-Based Multiple-Fault Localization Without Test Oracles." Electronics 14, no. 13 (2025): 2596. https://doi.org/10.3390/electronics14132596.

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Modern electronic information system software is becoming increasingly complex, making manual debugging prohibitively expensive and necessitating automated fault localization (FL) methods to prioritize suspicious code segments. While Single-Fault Localization (SFL) methods, such as spectrum-based fault localization (SBFL) and Deep Learning-Based Fault Localization (DLFL), have demonstrated promising results in localizing individual faults, extending these methods to multiple-fault scenarios remains challenging. Deep Learning–Based Fault Localization (DLFL) methods combine metamorphic testing a

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Zhu, Yong, Tao Zhou, Shengnan Tang, and Shouqi Yuan. "Failure Analysis and Intelligent Identification of Critical Friction Pairs of an Axial Piston Pump." Journal of Marine Science and Engineering 11, no. 3 (2023): 616. http://dx.doi.org/10.3390/jmse11030616.

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Hydraulic axial piston pumps are the power source of fluid power systems and have important applications in many fields. They have a compact structure, high efficiency, large transmission power, and excellent flow variable performance. However, the crucial components of pumps easily suffer from different faults. It is therefore important to investigate a precise fault identification method to maintain reliability of the system. The use of deep models in feature learning, data mining, automatic identification, and classification has led to the development of novel fault diagnosis methods. In th

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Liu, Shuchen, Jan-Jöran Gehrt, Dirk Abel, and René Zweigel. "Identification of Multi-Faults in GNSS Signals using RSIVIA under Dual Constellation." Acta Cybernetica 25, no. 1 (2021): 69–84. http://dx.doi.org/10.14232/actacyb.285315.

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This publication presents the development of integrity monitoring and fault detection and exclusion (FDE) of pseudorange measurements, which are used to aid a tightly-coupled navigation filter. This filter is based on an inertial measurement unit (IMU) and is aided by signals of global navigation satellite system (GNSS). Particularly, the GNSS signals include global positioning system (GPS) and Galileo. By using GNSS signals, navigation systems suffer from signal interferences resulting in large pseudorange errors. Further, a higher number of satellites with dual-constellation increases the po

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Misra, Sajal, Satish Kumar, Sameer Sayyad, et al. "Fault Detection in Induction Motor Using Time Domain and Spectral Imaging-Based Transfer Learning Approach on Vibration Data." Sensors 22, no. 21 (2022): 8210. http://dx.doi.org/10.3390/s22218210.

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The induction motor plays a vital role in industrial drive systems due to its robustness and easy maintenance but at the same time, it suffers electrical faults, mainly rotor faults such as broken rotor bars. Early shortcoming identification is needed to lessen support expenses and hinder high costs by using failure detection frameworks that give features extraction and pattern grouping of the issue to distinguish the failure in an induction motor using classification models. In this paper, the open-source dataset of the rotor with the broken bars in a three-phase induction motor available on

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Gaurav Goyal. "AI-Driven Fault Detection and Diagnosis in Smart Grids for Enhanced Power System Reliability." Journal of Information Systems Engineering and Management 10, no. 42s (2025): 845–59. https://doi.org/10.52783/jisem.v10i42s.8203.

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The increasing complexity and demand for reliable power supply in modern electrical grids necessitate advanced monitoring and fault detection mechanisms. Traditional fault detection methods often suffer from inefficiencies, slow response times, and a lack of predictive capabilities AI-powered fault detection and diagnosis (FDD) have become crucial for improving the reliability of smart grid power systems. This study examines the impact of AI on fault identification, classification, and diagnosis, utilizing machine learning (ML) and deep learning (DL) methodologies to enhance grid performance.

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Abdi Monfared, Omid, Aref Doroudi, and Amin Darvishi. "Diagnosis of rotor broken bars faults in squirrel cage induction motor using continuous wavelet transform." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 38, no. 1 (2019): 167–82. http://dx.doi.org/10.1108/compel-11-2017-0487.

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Purpose Squirrel cage induction motors suffer from several faults such as rotor broken bar. One of the powerful methods to detect induction motor faults is the line current signature analysis. This paper aims to present a novel algorithm based on continuous wavelet transform (CWT) to diagnose a rotor broken bar fault. Design/methodology/approach The proposed CWT has high flexibility in monitoring any frequency of interest in a waveform. Based on this transform, stator current frequency spectrum is analyzed to diagnose the rotor broken bar fault. The algorithm distinguishes the healthy motor fr

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Yanti, Risma, and Vera Kristiana. "AN ANALYSIS OF THE MAIN CHARACTER OF STRUGGLING AGAINST CANCER IN THE NOVEL “THE FAULT IN OUR STARS”." PHILOLOGY Journal of English Language and Literature 1, no. 2 (2021): 107–12. http://dx.doi.org/10.32696/pjell.v1i2.836.

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This thesis contained an analysis of the main character's struggle against cancer in the novel entitled The fault in our stars by John Green. The method used in this research wasa qualitative method. The main objective of this research was to find out the main character's struggles against cancer in the novel The fault in our stars by Jhon Green. The results of the data analysis found 1.) What is the main character's struggles against cancer in the novel “The fault in our stars” 2.) What is the impact of the main character’sstruggles against cancer to the other characters in the novel “The fau

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Koh, C. K. H., J. Shi, W. J. Williams, and J. Ni. "Multiple Fault Detection and Isolation Using the Haar Transform, Part 1: Theory." Journal of Manufacturing Science and Engineering 121, no. 2 (1999): 290–94. http://dx.doi.org/10.1115/1.2831218.

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Most manufacturing processes involve several process variables which interact with one another to produce a resultant action on the part. A fault is said to occur when any of these process variables deviate beyond their specified limits. An alarm is triggered when this happens. Low cost and less sophisticated detection schemes based on threshold bounds on the original measurements (without feature extraction) often suffer from high false alarm and missed detection rates when the process measurements are not properly conditioned. They are unable to detect frequency or phase shifted fault signal

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M.S., Ms Bidave. "Railway Track Fault Detection and Automation System." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem31792.

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The Railway Track Fault Detection and Automation System (RTFDAS) represents a significant leap forward in the realm of railway infrastructure maintenance and management. Traditional methods of track inspection often suffer from limitations such as manual labor, periodic assessments, and the potential for human error, leading to safety hazards and operational disruptions. In response, the RTFDAS leverages cutting-edge technology, sophisticated algorithms, and automation capabilities to enable proactive fault detection and streamlined maintenance processes. This paper presents a comprehensive ov

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Zaki, Mohamed I., Tamer F. Megahed, and Sobhy M. Abdelkader. "Efficient Smart Grid Fault-Identification Approach with Photovoltaic- Distributed Generators Based on Monitoring of Current/Voltage Signals." Renewable Energy and Power Quality Journal 20 (September 2022): 161–66. http://dx.doi.org/10.24084/repqj20.252.

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A Smart grid fault-identification is a critical aspect of the protection relaying system with the integration of renewable energy based on photovoltaic-distributed generators. With increasing the distributed generators usage in smart grids, the conventional relaying techniques suffer from maloperation owing to the risk of changing fault current levels. Therefore, in this paper, a discrete wavelet transform (DWT) and the statistical cross-alienation coefficients-based method is proposed to detect and classify different types of faults considering the dynamic response of photovoltaic. The propos

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Yang, Yunfan, and Caiping Xi. "Rolling Bearing Fault Diagnosis Based on MFDFA-SPS and ELM." Mathematical Problems in Engineering 2022 (July 18, 2022): 1–17. http://dx.doi.org/10.1155/2022/4034477.

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Rolling bearings, as important parts on supporting rotating shafts, frequently suffer from fatigue failures. If these rolling bearing failures are not found in time, it will have a huge impact on the whole mechanical system’s operating safety and operating life. To improve the diagnosis of different faults as well as different degrees of faults, a fault diagnosis method based on the multifractal detrended fluctuation analysis (MFDFA) method-singularity power spectrum (SPS) with extreme learning machine (ELM) is proposed. First, MFDFA and SPS analyses are performed on vibration acceleration sig

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Li, Ting, Ting Yang, Yuyan Cao, Rong Xie, and Xinmin Wang. "Adaptive Robust Fault-Tolerant Synchronization Control for a Dual Redundant Hydraulic Actuation System with Common-Mode Fault." Mathematical Problems in Engineering 2018 (October 4, 2018): 1–14. http://dx.doi.org/10.1155/2018/6570104.

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This paper investigates the fault-tolerant synchronization control (FTSC) problem for a dual redundant hydraulic actuation system (DRHAS), which works on active/active (A/A) mode and suffers from a kind of common-mode fault (CMF), i.e., internal leakage faults occurring in both hydraulic actuator (HA) channels simultaneously due to a common cause. Firstly, in order to follow the position command and synchronize the force outputs of the two channels, a desired trajectory generator derived from the dynamics of the control surface is employed. Then, considering model uncertainties and nonlinear d

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Falcucci, Emanuela, Maria Eliana Poli, Fabrizio Galadini, Giancarlo Scardia, Giovanni Paiero, and Adriano Zanferrari. "First evidence of active transpressive surface faulting at the front of the eastern Southern Alps, northeastern Italy: insight on the 1511 earthquake seismotectonics." Solid Earth 9, no. 4 (2018): 911–22. http://dx.doi.org/10.5194/se-9-911-2018.

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Abstract. We investigated the eastern corner of northeastern Italy, where a system of NW–SE-trending dextral strike-slip faults of western Slovenia intersects the south-verging fold and thrust belt of the eastern Southern Alps. The area suffered the largest earthquakes of the region, among which are the 1511 (Mw 6.3) event and the two major shocks of the 1976 seismic sequence, with Mw = 6.4 and 6.1. The Colle Villano thrust and the Borgo Faris–Cividale strike-slip fault have been here first analyzed by interpreting industrial seismic lines and then by performing morphotectonic and paleoseismol

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