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34 articles for “Fault Diagnosis”
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Detection of Stator Winding Faults Using Finite Element Analysis (FEA) in BLDC Motors
Abstract: Detection of eccentricity faults has been feasible using physical and vibrational parameters. The Brushless DC motor is undergoes various kinds of stresses including mechanical, electrical, thermal, and environmental. These stresses increase the probability of occurrences of stator faults with various severity levels. The well maintained BLDC motor and correct operations decrease the probability of occurrences of faults. These faults are of three types as damage in laminations, damage in frame …
Published in Trends in Mechanical Engineering & Technology · Vol. 8, Issue 3, 2018 · pp. 82–90 Read article
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Detection of Eccentricity Fault for Induction Motor
Abstract: The study shows that 80% of faults are because of eccentricity in induction motors, advancing numerous research endeavors still gave to the eccentricity in these motors. In this paper, an asynchronous motor under static and dynamic eccentricities with various load levels is modeled utilizing using finite element method (FEM) as FEM is utilized as an intense numerical technique for analysis of defective induction motors. The simulation outcomes demonstrate that due …
Published in Trends in Electrical Engineering · Vol. 8, Issue 2, 2018 · pp. 19–32 Read article
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Fault Tolerant Inverter for BLDC Drives
Abstract: In this study, fault tolerant inverter for BLDC drives is used for aerospace application. In such application, the human intervention is limited. So, the fault tolerant control of BLDC motor is of great importance for its continuous operating capacity even under the faulty situation. Over voltage and over current phenomenon occur in system due to switching faults, so a fault isolation and system reconfiguration method is presented. This method can …
Published in Journal of Power Electronics and Power Systems · Vol. 8, Issue 3, 2018 · pp. 31–38 Read article
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Faults Detection Techniques of Three Phase Induction Motor: A Review
Abstract: Induction motors are the most commonly used machines in industries. It is very robust, inexpensive and easy to maintain. Induction motors appear to various faults during their operation. Accurate fault identification is the prime industrial need to reduce breakdown, maintenance and revenue losses. Therefore, an early fault detection is needed for the protection of the motor against electrical and mechanical failures for continuing their operation safely. The main perspective of …
Published in Journal of Control & Instrumentation · Vol. 9, Issue 1, 2018 · pp. 45–49 Read article
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Machine Learning Based Optical Fiber Fault Detection and Localization Using OTDR Signals
Abstract: Optical fiber networks provide high bandwidth, low transmission loss, and immunity to electromagnetic interference, making them fundamental to modern communication infrastructure. However, fiber faults caused by cable cuts, excessive bending, connector degradation, splicing defects, and physical disturbances can significantly affect network reliability. Optical time-domain reflectometry (OTDR) is widely used for identifying and locating such faults, but conventional OTDR interpretation often depends on threshold-based signal processing and manual analysis. This study …
Published in Trends in Opto-electro & Optical Communication · Vol. 16, Issue 2, 2026 · pp. 41–52 Read article
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Log Identification and Monitoring System Using Generative AI
Abstract: In contemporary software ecosystems, application and infrastructure logs play a vital role in ensuring system reliability, performance optimization, fault diagnosis, and security compliance. As applications become increasingly distributed and cloud native, the volume, velocity, and variety of generated log data have grown dramatically. This rapid expansion makes traditional manual log inspection inefficient, error-prone, and largely impractical. To address these challenges, this paper proposes an artificial intelligence (AI) driven log monitoring …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 08–16 Read article
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Performance Analysis And Battery Management System Optimization In Electric Vehicles
Abstract: The rapid electrification of the automotive industry has led to an increased need for battery management systems that are not only efficient and safe but also intelligent. BMS is the device that guarantees the best use of the battery, prolongs its life, and allows its safe operation even under different environmental and load conditions. Through the synthesis of literature and industry practices, this paper acts as a tribute to the …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 Read article
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DGA Analysis of Transformer Oil with Experimental Investigation: An Effective Tool of Condition Monitoring for Power Transformer
Abstract: Dissolved Gas Analysis (DGA) is usually performed for power transformer condition based maintenance activities. The DGA has become a very popular technique for the monitoring the overall health of a power transformer. It is possible to distinguish faults such as partial discharge, over-heating, and arcing in a great variety of oil filled power transformers. A number of samples must be taken over a period of time to discern trends and …
Published in Journal of Power Electronics and Power Systems · Vol. 5, Issue 2, 2015 · pp. 9–16 Read article
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Detecting Winding Movement by Fuzzy Logic for Frequency Response of Power Transformer
Abstract: Power transformers are basically one of the most efficient devices that are used in Power Plant or in any substation. Its maintenance is bit some tedious but has to be done to diagnose any severe fault that may damage the transformer. Sweep Frequency Response Analysis (SFRA) is used to detect any winding or core deformation in transformer that would arise during transportation, due to severe short circuits or due to …
Published in Journal of Power Electronics and Power Systems · Vol. 5, Issue 3, 2015 · pp. 25–34 Read article
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Fault Investigation of Rolling Element Bearing using Soft Computing
Abstract: AbstractRolling element bearing is the most significant mechanical component of any rotating machinery and used in vast applications from the surgical machine tool to aircraft etc. In the present research, an experimental investigation has been done using vibration analysis, continuous wavelet transform (CWT), and soft computing, i.e., support vector machine (SVM) and k-nearest neighbor (k-NN) for fault detection and diagnosis of rolling element bearing. Vibration signatures in the time domain …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 6, Issue 1, 2019 · pp. 8–22 Read article
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Brief Review of Fault Detection and Classification in Induction Motor
Abstract: Induction motors are operating as the support system for each industry. But like every different machine, due to serious duty cycles, poor operating atmosphere, installation and manufacturing factors, they gradually slow down or sometimes fail. That is why, diagnosis methods that are competent to sense the motor failures are necessary in order to increase the safety and the performances of with increasing needs for reliability and efficiency, the field of …
Published in Journal of Experimental & Applied Mechanics · Vol. 10, Issue 1, 2019 · pp. 1–6 Read article
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Implementation of OBD-II Vehicle Diagnosis System for Improved Safety
Abstract: A car is no more a luxurious belonging of a person rather it has become an integral part of a modern family. One always prefers a car for safe transfer to one’s destination at low cost, with comfort and predictable travel outcome. The approach here presents a new car-data collection platform based on existing network infrastructure, internet, to collect driving data of vehicles remotely. Firstly, the vehicle data is monitored …
Published in Recent Trends in Electronics Communication Systems · Vol. 4, Issue 1, 2017 · pp. 17–21 Read article
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Fault Diagnostic Method of Transformers based on Hybrid ANN and Expert System
Abstract: Transformers are major equipments power system which affects not only the electrical energy availability of the area supplied, but also the economical operation of utilities. The most important concern about incipient faults in power transformer is that they may reduce the electrical and mechanical stress of the insulation. This proposed hybrid system utilizes dissolved gas in oil analysis techniques to diagnose for fault condition of power transformers. The Roger’s Four …
Published in Journal of Mechatronics and Automation · Vol. 1, Issue 1, 2014 · pp. 27–32 Read article
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Defect Diagnosis and Modelling for A Rotating Machine Running at A Steady Pace
Abstract: Rotary equipment, such as gears, shafts, pumps, and bearings, are widely used across various rotary machine in industries, often operating under different loading conditions. The fluctuations in loading can lead to fatigue failures in rotating components, significantly affecting machinery performance. To investigate the behavior of such rotating equipment under diverse operational scenarios, a numerical model has been created. This approach can replace costly and often challenging experimental methods. However, it …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 154–164 Read article