Intelligent fault diagnosis using an unsupervised sparse feature learning method
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Michael Pecht | Chun Cheng | Weiping Wang | Haining Liu | Michael G. Pecht | Chun Cheng | Haining Liu | Weiping Wang
[1] Shunming Li,et al. Batch-normalized deep neural networks for achieving fast intelligent fault diagnosis of machines , 2019, Neurocomputing.
[2] Xin Li,et al. An early fault diagnosis method of gear based on improved symplectic geometry mode decomposition , 2020 .
[3] F. A. Miles,et al. Vergence eye movements in response to binocular disparity without depth perception , 1997, Nature.
[4] Mohd Salman Leong,et al. Challenges and Opportunities of Deep Learning Models for Machinery Fault Detection and Diagnosis: A Review , 2019, IEEE Access.
[5] Yu Xue,et al. Text classification based on deep belief network and softmax regression , 2016, Neural Computing and Applications.
[6] Xiaolong Zhu,et al. Time-Shift Multiscale Fuzzy Entropy and Laplacian Support Vector Machine Based Rolling Bearing Fault Diagnosis , 2018, Entropy.
[7] Sanjay H Upadhyay,et al. A review on signal processing techniques utilized in the fault diagnosis of rolling element bearings , 2016 .
[8] Hee-Jun Kang,et al. A survey on Deep Learning based bearing fault diagnosis , 2019, Neurocomputing.
[9] Shunming Li,et al. General normalized sparse filtering: A novel unsupervised learning method for rotating machinery fault diagnosis , 2019, Mechanical Systems and Signal Processing.
[10] Y. V. Venkatesh,et al. Facial expression recognition using radial encoding of local Gabor features and classifier synthesis , 2012, Pattern Recognit..
[11] S. Harsha,et al. Statistical and frequency analysis of vibrations signals of roller bearings using empirical mode decomposition , 2019, Proceedings of the Institution of Mechanical Engineers, Part K: Journal of Multi-body Dynamics.
[12] Kai Wang,et al. Fault Diagnosis for Rolling Bearings Based on Composite Multiscale Fine-Sorted Dispersion Entropy and SVM With Hybrid Mutation SCA-HHO Algorithm Optimization , 2020, IEEE Access.
[13] Shunming Li,et al. A novel supervised sparse feature extraction method and its application on rotating machine fault diagnosis , 2018, Neurocomputing.
[14] K. Loparo,et al. Bearing fault diagnosis based on wavelet transform and fuzzy inference , 2004 .
[15] Erkki Oja,et al. Independent component analysis: algorithms and applications , 2000, Neural Networks.
[16] Feng Jia,et al. An Intelligent Fault Diagnosis Method Using Unsupervised Feature Learning Towards Mechanical Big Data , 2016, IEEE Transactions on Industrial Electronics.
[17] S. L. Shimi,et al. Condition Monitoring and Fault Diagnosis of Induction Motors: A Review , 2018, Archives of Computational Methods in Engineering.
[18] Liang Gao,et al. A New Deep Transfer Learning Based on Sparse Auto-Encoder for Fault Diagnosis , 2019, IEEE Transactions on Systems, Man, and Cybernetics: Systems.
[19] Minqiang Xu,et al. A Review of Early Fault Diagnosis Approaches and Their Applications in Rotating Machinery , 2019, Entropy.
[20] Elmar Eisemann,et al. Approximated and User Steerable tSNE for Progressive Visual Analytics , 2015, IEEE Transactions on Visualization and Computer Graphics.
[21] Jianzhong Zhou,et al. Fault Diagnosis for Rolling Element Bearings Based on Feature Space Reconstruction and Multiscale Permutation Entropy , 2019, Entropy.
[22] Xinyu Shao,et al. Sensor Data-Driven Bearing Fault Diagnosis Based on Deep Convolutional Neural Networks and S-Transform , 2019, Sensors.
[23] Lu Yang,et al. Sparse representation and learning in visual recognition: Theory and applications , 2013, Signal Process..
[24] N. P. Angelo,et al. On the application of Gabor filtering in supervised image classification , 2003 .
[25] Liang Guo,et al. A neural network constructed by deep learning technique and its application to intelligent fault diagnosis of machines , 2018, Neurocomputing.
[26] Xin Zhou,et al. Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data , 2016 .
[27] Yide Wang,et al. A Sparse Autoencoder and Softmax Regression Based Diagnosis Method for the Attachment on the Blades of Marine Current Turbine , 2018, Sensors.
[28] Jinjiang Wang,et al. Deep Boltzmann machine based condition prediction for smart manufacturing , 2018, Journal of Ambient Intelligence and Humanized Computing.
[29] Jing Lin,et al. Hierarchical discriminating sparse coding for weak fault feature extraction of rolling bearings , 2018, Reliab. Eng. Syst. Saf..
[30] Hee-Jun Kang,et al. Bearing Defect Classification Based on Individual Wavelet Local Fisher Discriminant Analysis with Particle Swarm Optimization , 2016, IEEE Transactions on Industrial Informatics.
[31] Qing Li,et al. Bearings fault detection using wavelet transform and generalized Gaussian density modeling , 2020 .
[32] Jorge Nocedal,et al. On the limited memory BFGS method for large scale optimization , 1989, Math. Program..