Rolling bearing fault diagnosis based on channel attention multi-scale convolution-BiLSTM network

Yuqing Li; Jie Ma

doi:10.1109/ddcls61622.2024.10606566

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Rolling bearing fault diagnosis based on channel attention multi-scale convolution-BiLSTM network

Yuqing Li Jie Ma

Year: 2024 Pages: 61-66

DOI: 10.1109/ddcls61622.2024.10606566

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Keywords:

Convolution (computer science) Bearing (navigation) Fault (geology) Computer science Channel (broadcasting) Scale (ratio) Artificial intelligence Pattern recognition (psychology) Computer network Geology Artificial neural network Cartography Seismology Geography

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Topics

Machine Fault Diagnosis Techniques

Physical Sciences → Engineering → Control and Systems Engineering

Gear and Bearing Dynamics Analysis

Physical Sciences → Engineering → Mechanical Engineering

Fault Detection and Control Systems

Physical Sciences → Engineering → Control and Systems Engineering

Rolling bearing fault diagnosis based on channel attention multi-scale convolution-BiLSTM network

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