Fault diagnosis of rolling bearings under variable conditions based on unsupervised domain adaptation method

Jianhua Zhong; Cong Lin; Yang Gao; Jianfeng Zhong; Shuncong Zhong

doi:10.1016/j.ymssp.2024.111430

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Fault diagnosis of rolling bearings under variable conditions based on unsupervised domain adaptation method

Jianhua Zhong Cong Lin Yang Gao Jianfeng Zhong Shuncong Zhong Jianfeng Zhong Shuncong Zhong

Year: 2024 Journal: Mechanical Systems and Signal Processing Vol: 215 Pages: 111430-111430 Publisher: Elsevier BV

DOI: 10.1016/j.ymssp.2024.111430

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Keywords:

Computer science Pattern recognition (psychology) Feature (linguistics) Artificial intelligence Fault (geology) Convolutional neural network Domain (mathematical analysis) Interpretability Feature extraction Bearing (navigation) Data mining Mathematics

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Machine Fault Diagnosis Techniques

Physical Sciences → Engineering → Control and Systems Engineering

Imbalanced Data Classification Techniques

Physical Sciences → Computer Science → Artificial Intelligence

Oil and Gas Production Techniques

Physical Sciences → Engineering → Ocean Engineering

Fault diagnosis of rolling bearings under variable conditions based on unsupervised domain adaptation method

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