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A zero-shot fault semantics learning model for compound fault diagnosis
Expert Systems With Applications, 2023Juan Xu, Xu Ding, Ruqiang Yan
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Compound fault diagnosis for industrial robots based on dual-transformer networks [PDF]
Journal of Manufacturing Systems, 2023 The accurate diagnosis of the compound fault of industrial robots can be highly beneficial to maintenance management. In the actual noisy working environment of industrial robots, the mixed and feeble failure features are easy to be overwhelmed, which ...
Chong Chen, Chao Liu
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WavCapsNet: An Interpretable Intelligent Compound Fault Diagnosis Method by Backward Tracking
IEEE Transactions on Instrumentation and Measurement, 2023Weihua Li, Hao Lan, Junbin Chen
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Zero-shot learning compound fault diagnosis of bearings
2021 International Joint Conference on Neural Networks (IJCNN), 2021The compound fault signal of bearings is coupled and complex, thereby compound fault diagnosis is a difficult problem in bearing fault diagnosis. The existing deep learning models can extract fault features when there are a large number of labeled compound fault samples.
Juan Xu 0002 +4 more
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Multiple Enhanced Sparse Decomposition for Gearbox Compound Fault Diagnosis
IEEE Transactions on Instrumentation and Measurement, 2020The vibration monitoring of gearboxes is an effective means of ensuring the long-term safe operation of rotating machinery. A gearbox may have more than one fault in actual applications. Therefore, gearbox compound fault diagnosis should be investigated.
Ning Li 0020 +4 more
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A Novel Compound Neural Network for Fault Diagnosis
2006 2nd IEEE/ASME International Conference on Mechatronics and Embedded Systems and Applications, 2006Independent Component Analysis (ICA) is a powerful tool for redundancy reduction and nongaussian data analysis. And, Artificial Neural Network (ANN), especially the Self-Organizing Map (SOM) based on unsupervised learning is a kind of excellent method for pattern clustering and recognition. By combining ICA with ANN, we proposed a novel compound neural
Jiao Weidong, Yang Shixi, Yan Gongbiao
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A compound fault diagnosis model for gearboxes using correlation information between single faults
Measurement Science and Technology, 2023Abstract Gearboxes are key components of rotating machinery. Performing intelligent fault diagnosis of gearboxes with condition-based monitoring information helps to make reliable decisions on equipment operation and maintenance. Besides single faults, compound faults also are common failure forms of gearboxes.
Ming Zeng +3 more
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Compound fault diagnosis based on probability box theory
2017 9th International Conference on Modelling, Identification and Control (ICMIC), 2017In view of compound fault of rolling bearing in mechanical transmission system, the fault signal was decomposed by probability box modeling method to obtain the different probability box models. The original data with abundant statistical information was taken as the research object.
Tang Hong +3 more
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The application of compound networks in fault diagnosis of power transformer
2008 China International Conference on Electricity Distribution, 2008Using the concepts of typical gas's concentration and cumulative frequency in analysis of the reliability data for dealing with the pretreatment of data of DGA, two new normalized methods which named characteristic normalization and mix normalization are presented in this paper. The Fisher rule to evaluate the results of the two pretreatment methods is
Wei-zheng Zhang +4 more
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A New ICA-SOM Based Method for Compound Faults Diagnosis
2006 6th World Congress on Intelligent Control and Automation, 2006Compound faults diagnosis is an important but difficult task in diagnostics. When several faults arise at the same time, vibration measurements by sensors show themselves as a complex integrated symptom, not as a simple and linear combination of several single faults, which makes it difficult to detect compound faults correctly.
null Weidong Jiao +3 more
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