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28 articles for “Faults Classification”
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Enhancing Smart Grid Resilience Through AI-Based Fault Classification
Abstract: Traditional power grids can be developed into smart grids, and they are comprised of the latest information and communication technologies (ICTs), which are based on establishing the relationship between the conventional electricity systems along with the usage of smart meters and distributed generation. This dynamic improves energy efficiency and the integration of renewables. Well, the dynamic and reversible power injection from Distributed Energy Resources (DERs) creates substantial operational problems. These …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 10–15 Read article
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Fault Dealing through Software Fault Tolerance in Automated Dose Packaging System
Abstract: Each industry is highly influenced by latest computer technology. Computer system has quickly become an important and vital element in any growing industry. Each industry is depending on certain computer base applications and systems to achieve high accuracy and reliability. This paper focuses on automated dose packaging system. Such system needs supportive computer system which assists to have desired outcomes at any circumstances. Faulty environment may cause unexpected damage to …
Published in Journal of Computer Technology & Applications · Vol. 9, Issue 1, 2018 · pp. 1–5 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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Bearing Defect Diagnosis: An Approach for Manufacturing Industries Using Wavelet Transform Based Features
Abstract: To maintain reliability in the manufacturing units, industries have concentrated their attention on the condition based maintenance. Fault detection and diagnosis are the two of three condition based maintenance mainstays. Bearing is one of the most important and essential components of the rotating machines. Hence, the researchers have shown their interest in bearing fault detection and diagnosis from the last few years. They mainly use bearing vibration as fault characteristics …
Published in Journal of Microelectronics and Solid State Devices · Vol. 4, Issue 1, 2017 · pp. 15–21 Read article
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An Efficient Method of Fault Analysis using Artificial Neural Network
Abstract: In the power system, there are many techniques to identify and classify the faults. So, it is utmost important to choose the suitable technique. In this paper, a novel technique based on ANN have been proposed. When abnormal conditions occur in the system, the purposed method identifies and classify the fault to protect the system from the faults and stop from the big hazards. Simulation of purposed Simulink model have …
Published in Current Trends in Signal Processing Read article
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An Efficient Method of Fault Analysis using Artificial Neural Network
Abstract: In the power system, there are many techniques to identify and classify the faults. So, it is utmost important to choose the suitable technique. In this paper, a novel technique based on ANN have been proposed. When abnormal conditions occur in the system, the purposed method identifies and classify the fault to protect the system from the faults and stop from the big hazards. Simulation of purposed Simulink model have …
Published in Current Trends in Signal Processing · Vol. 11, Issue 1, 2021 · pp. 9–25 Read article
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Transformer Health Monitoring System
Abstract: Rising demands for reliable and efficient power distribution in modern electric control grid increasingly call up for robust monitoring systems for critical substructure. Being a vital part of the power conduction system, transformer are subjected to mechanical, electrical, and environmental stresses, which, if not properly controlled, can cause failures. In this project, we propose a Transformer Health Monitoring System (THMS) using machine learning (ML) models and real-time monitoring method to …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 1–9 Read article
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An Efficient Fault Detection and Localization System for Three-Phase Transmission Line using Arduino and Artificial Neural Networks
Abstract: This paper presents an efficient fault detection and localization system for a three-phase transmission line using Arduino and artificial neural networks. Theproposed system is designed to detect and localize faults in real-time, reducing the downtime and improving the reliability of the power system. The system consists of three main components: the fault detection unit, the fault classification unit, and the fault localization unit. The fault detection unit uses Arduino microcontroller …
Published in Recent Trends in Electronics Communication Systems · Vol. 9, Issue 3, 2022 · pp. 35–42 Read article
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Feature Extraction and Analysis of Bearing Faults: A Review
Abstract: One of the most important steps in identifying bearing problems is feature extraction. In order to provide a more meaningful dataset, it entails locating and extracting pertinent features from raw bearing vibration signals. Tasks involving categorization and prediction can then make use of these attributes. In many practical applications, such as monitoring rotating machinery or electronic components, the raw signals collected (e.g., vibration, current, temperature) are often complex, high-dimensional, and …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 20–28 Read article
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Boosting Gesture Recognition with Software Fault Tolerance
Abstract: User interface is always a key important issue of any application. Graphic user interface is one of the convenient and conventional ways to use application but the current trades of user interface are very popular with emotional user interface (EUI). Automation, changing technology and shortest path to operate command are certain reasons of popularity of EUI. In any EUI, the gesture recognition is core important part. Faults may occur anywhere …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 6, Issue 1, 2018 · pp. 1–5 Read article
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IOT and algorithmic intelligent motor health monitoring as well as maintenance prediction
Abstract: Manufacturing, transportation, and energy systems rely largely on industrial electric motors, and their untimely failure can result in expensive downtime, safety hazards, and decreased operational efficiency. The majority of traditional motor maintenance procedures rely on reactive methods or routine inspections, which frequently miss early-stage problems and lead to needless maintenance or unexpected breakdowns. This project offers an Intelligent Motor Health Monitoring and Predictive Maintenance System that combines Internet of Things …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 28–37 Read article
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Fault Diagnosis of Air Compressor (AC) System using Local Mean Decomposition (LMD) and Logistic Regression (LR) Machine Learning Classifier
Abstract: This article presents a detailed and systematic procedure for performing fault diagnosis in an air compressor (AC) system by analyzing the audio signals generated during its operation. The analysis covers both normal (healthy) conditions and seven distinct types of faults, including bearing failure, flywheel malfunction, inlet valve leakage, outlet valve leakage, non-return valve failure, piston ring defect, and rider belt issues. To acquire the acoustic signals, the researchers utilized a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 416–427 Read article
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Fault Detection in Solar PV Systems Integrated with the Power Grid: Evaluating Logistic Regression through Confusion Matrix Analysis
Abstract: This paper proposes a method for failure detection in grid-integrated solar photovoltaic (PV) systems using logistic regression and real-time sensor data. The approach effectively classifies and identifies seven distinct fault types. The developed model demonstrates a high fault identification accuracy, ranging from 93% to 96.5% across various fault types and operational conditions. By leveraging logistic regression, the system utilizes key independent variables that significantly influence the classification process. Additionally, the …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 2, 2025 · pp. 45–52 Read article
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Recent Routing Protocols in UAV Networks: Classifications, Challenges, and Future Directions
Abstract: Routing protocols enable reliable communication in Unmanned Aerial Vehicle (UAV) networks, particularly Flying Ad-hoc Networks (FANETs), amid high-speed 3D mobility, dynamic topologies, and energy limits. Key challenges include intermittent links due to mobility, limited energy resources, variable network density, and the need to minimize end-to-end delay while maximizing throughput and fault tolerance. This paper classifies recent UAV routing protocols into topology-based routing protocols, position-based routing protocols, and hierarchical-based routing protocols. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 2, 2026 Read article
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Development of a Generative AI Model for Early Detection and Prevention of Electrical Faults in Thermal Power Plants
Abstract: Electrical faults in thermal power plants can lead to severe equipment damage, production downtime, and safety hazards if not detected in advance. This study presents the development of a Generative Artificial Intelligence (GenAI) model for the early detection and prevention of electrical faults using predictive analytics. The proposed framework integrates Generative Adversarial Networks (GANs) with deep learning (CNN) and machine learning algorithms (Random Forest, Logistic Regression) to enhance data diversity, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 45–54 Read article
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AI Powered Fault Detection in DC Motor using STM32
Abstract: This work presents the design and implementation of an embedded artificial intelligence system for real-time fault detection in a direct current (DC) motor using the STM32 Nucleo- F411RE microcontroller. The objective of the study is to develop a low-cost and efficient predictive maintenance solution capable of identifying abnormal motor behavior at an early stage. Vibration and temperature signals are acquired using an MPU6050 sensor and processed directly on the microcontroller …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 39–49 Read article
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To Diagnose the Broken Tooth Fault, Signal Processing Techniques and Machine Learning Technique are Applied
Abstract: The objective of this research is to study the diagnosis of broken tooth fault of spur gear using vibration signals with signal processing and machine learning techniques. In this study, experiment has been performed and analyse on the broken tooth fault and healthy spur gear conditions. This paper describes two approaches to signal processing techniques from acquired vibration signals, which are time-domain and frequency domain, involving statistical characteristics of vibration …
Published in Trends in Mechanical Engineering & Technology · Vol. 13, Issue 3, 2023 · pp. 45–53 Read article
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AI-Assisted Defect Detection in Polymer Composite Insulators Using an Optimised Ensemble Deep Learning Framework for Structural Health Monitoring
Abstract: Polymer composite insulators, particularly those made from silicone rubber and epoxy resins, are increasingly adopted in high-voltage transmission systems due to their superior electrical insulation, lightweight design, hydrophobicity, and environmental durability. Despite their advantages, these materials are susceptible to surface degradation, mechanical cracking, and flashover under prolonged exposure to environmental pollutants, thermal stress, and electrical aging. Accurate, real-time condition assessment of these composite insulators is critical for ensuring operational safety, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 253–261 Read article
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Power Quality Issues and Mitigation Strategies: A Review
Abstract: AbstractTo protect the power system recognition and arrangement of voltage (V) and current (I) issues are essential tasks. Most power quality (PQ) disturbances are unstable and ephemeral; the call for recognition and arrangement of voltages and current is proved. There are some intelligent system technologies which have dominance regarding fault analysis by using wavelet transform (WT), expert systems and artificial neural networks. As signals are classified in six classes: five …
Published in Current Trends in Signal Processing · Vol. 9, Issue 3, 2019 · pp. 23–27 Read article
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A review of the employing of Wavelet transforms and Classifier Artificial intelligence (AI) methods for detecting power transmission difficulties
Abstract: Power systems use large interconnections to transmit and distribute electric power. For power transmission, the same voltage levels are used for minimum transmission losses. During power transmission faults may occur due to natural events such as lightning, strong wind, fire etc. Faults may occur between phase conductors to ground or between the phase conductors. Transmission line protection has been performed using the comparison of voltages and currents and activates the …
Published in Journal of Power Electronics and Power Systems · Vol. 14, Issue 2, 2024 · pp. 36–41 Read article