IEEE AccessThis paper is motivated by the growing penetration of renewable power plants in electrical systems worldwide and the scarcity of studies evaluating fault detection, classification, and localization tasks when applied within wind farms, i.e., their ...
Moises J. B. B. Davi +2 more
doaj +1 more source
Neural Architecture Search for Bearing Fault Classification
Proceedings of the 16th International Conference on Agents and Artificial IntelligenceIn this research, we address bearing fault classification by evaluating three neural network models: 1D Convolutional Neural Network (1D-CNN), CNN-Visual Geometry Group (CNN-VGG), and Long Short-Term Memory (LSTM). Utilizing vibration data, our approach incorporates data augmentation to address the limited availability of fault class data.
Edicson Santiago Bonilla Diaz +6 more
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Fault Classification in Predictive Maintenance
, 2023 Abstract In the field of predictive maintenance, “smart condition monitoring” extends beyond merely assessing the present state of manufacturing equipment. In today's landscape, businesses and research endeavors strive for deeper insights into equipment conditions, seeking to uncover potential causes behind issues or anticipate the remaining ...
Guenter Roehrich, Davide Raffaele
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Fault Detection and Classification in MMC-HVDC Systems using Learning Methods [PDF]
, 2020 In this paper we explore learning methods to improve the performance of the open16 circuit fault diagnosis of modular multilevel converters (MMCs). Two deep learning methods, namely, Convolutional Neural Networks (CNN) and Auto Encoder based Deep Neural ...
Darwish, M +10 more
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Two-Stage Fault Classification Algorithm for Real Fault Data in Transmission Lines
IEEE AccessFault classification in power transmission lines is important in distance relaying for identifying the accurate phases implicated in the fault occurrence.
Se-Heon Lim +4 more
doaj +1 more source
Advanced Bearing-Fault Diagnosis and Classification Using Mel-Scalograms and FOX-Optimized ANN [PDF]
Accurate and reliable bearing-fault diagnosis is important for ensuring the efficiency and safety of industrial machinery. This paper presents a novel method for bearing-fault diagnosis using Mel-transformed scalograms obtained from vibrational signals ...
Muhammad Umar +8 more
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FisPro based interpretable fuzzy inference system for dual circuit extra high voltage transmission line fault classification and fault distance estimation [PDF]
Journal of Fuzzy Extension and ApplicationsAccurate fault classification and precise fault distance estimation play a critical role in reliable, stable and optimal operation of electrical power systems.
A Naresh Kumar +7 more
doaj +1 more source
From model, signal to knowledge: a data-driven perspective of fault detection and diagnosis [PDF]
, 2013 This review paper is to give a full picture of fault detection and diagnosis (FDD) in complex systems from the perspective of data processing. As a matter of fact, an FDD system is a data-processing system on the basis of information redundancy, in which
Dai, Xuewu, Gao, Zhiwei
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Rough set based gas turbine fault isolation study [PDF]
, 2010 Gas path fault isolation is one of the key techniques in Engine Health Management systems. In order to accomplish gas path fault isolation successfully for a gas turbine engine, both an accurate off-design performance model and an effective fault ...
Wang, Lihui.
core
Fault Diagnosis of Reciprocating Compressors Using Revelance Vector Machines with A Genetic Algorithm Based on Vibration Data [PDF]
This paper focuses on the development of an advanced fault classifier for monitoring reciprocating compressors (RC) based on vibration signals. Many feature parameters can be used for fault diagnosis, here the classifier is developed based on a relevance
Gu, Fengshou +3 more
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