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Keyword

fault classification

Description: Fault classification is the assignment of detected failures to categories to support diagnosis, monitoring, or protection of engineered systems.
OpenAlex ID: keywords/fault-classification
Rolling element bearing diagnostics using the Case Western Reserve University data: A benchmark study
2015 · Wade A. Smith, Robert B. Randall · Mechanical Systems and Signal Processing · 2,737
Fault Detection Method based on Artificial Neural Network for 330kV Nigerian Transmission Line
2024 · Alhassan Musa Oruma, Ismaila Mahmud, et al. · International Journal of Innovative Science and Research Technology (IJISRT) · 1,767
Model-based fault-detection and diagnosis – status and applications
2005 · Rolf Isermann · Annual Reviews in Control · 1,580
Model-Based Fault Detection and Diagnosis - Status and Applications
2004 · Rolf Isermann · IFAC Proceedings Volumes · 1,262
Analysis of geological structures
1991 · Choice Reviews Online · 943
Deep Learning Algorithms for Bearing Fault Diagnostics—A Comprehensive Review
2020 · Shen Zhang, Shibo Zhang, et al. · IEEE Access · 915
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Multiscale Convolutional Neural Networks for Fault Diagnosis of Wind Turbine Gearbox
2018 · Guoqian Jiang, Haibo He, et al. · IEEE Transactions on Industrial Electronics · 894
Fault Tolerance: Principles and Practice
1990 · Peter Lee, Thomas Anderson · Newcastle University ePrints (Newcastle Univesity) · 781
Bearing fault diagnosis base on multi-scale CNN and LSTM model
2020 · Xiaohan Chen, Beike Zhang, et al. · Journal of Intelligent Manufacturing · 745
A sparse auto-encoder-based deep neural network approach for induction motor faults classification
2016 · Wenjun Sun, Siyu Shao, et al. · Measurement · 699
Fault diagnosis of rolling bearings with recurrent neural network-based autoencoders
2018 · Han Liu, Jianzhong Zhou, et al. · ISA Transactions · 608
A comprehensive review on convolutional neural network in machine fault diagnosis
2020 · Jinyang Jiao, Ming Zhao, et al. · Neurocomputing · 577
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Active fault database of Turkey
2016 · Ömer Emre, Tamer Y. Duman, et al. · Bulletin of Earthquake Engineering · 572
Fault detection and diagnosis methods for photovoltaic systems: A review
2018 · A. Mellit, G.M. Tina, et al. · Renewable and Sustainable Energy Reviews · 568
A novel fault diagnosis technique for photovoltaic systems based on artificial neural networks
2016 · W. Chine, A. Mellit, et al. · Renewable Energy · 543
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Rolling bearing fault diagnosis using an optimization deep belief network
2015 · Haidong Shao, Hongkai Jiang, et al. · Measurement Science and Technology · 517
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A novel optimized SVM classification algorithm with multi-domain feature and its application to fault diagnosis of rolling bearing
2018 · Xiaoan Yan, Minping Jia · Neurocomputing · 506
Inductive Fault Analysis of MOS Integrated Circuits
1985 · John Shen, W. Maly, et al. · IEEE Design & Test of Computers · 506
A deep learning method for bearing fault diagnosis based on Cyclic Spectral Coherence and Convolutional Neural Networks
2020 · Zhuyun Chen, Alexandre Mauricio, et al. · Mechanical Systems and Signal Processing · 474
Bearing Fault Detection by a Novel Condition-Monitoring Scheme Based on Statistical-Time Features and Neural Networks
2012 · Miguel Delgado Prieto, Giansalvo Cirrincione, et al. · IEEE Transactions on Industrial Electronics · 462
Preprocessing-Free Gear Fault Diagnosis Using Small Datasets With Deep Convolutional Neural Network-Based Transfer Learning
2018 · Pei Cao, Shengli Zhang, et al. · IEEE Access · 460
Intelligent Fault Detection Scheme for Microgrids With Wavelet-Based Deep Neural Networks
2017 · James J. Q. Yu, Yunhe Hou, et al. · IEEE Transactions on Smart Grid · 452
A review on fault detection and diagnosis techniques: basics and beyond
2020 · Anam Abid, Muhammad Tahir Khan, et al. · Artificial Intelligence Review · 439
An Improved Quantum-Inspired Differential Evolution Algorithm for Deep Belief Network
2020 · Wu Deng, Hailong Liu, et al. · IEEE Transactions on Instrumentation and Measurement · 430
Motor Bearing Fault Diagnosis Using Trace Ratio Linear Discriminant Analysis
2013 · Xiaohang Jin, Mingbo Zhao, et al. · IEEE Transactions on Industrial Electronics · 424
Works count: 18,350
Citation count: 223,000
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