VKCNN: An interpretable variational kernel convolutional neural network for rolling bearing fault diagnosis

Guangyi Chen; Guping Tang; Z. K. Zhu

doi:10.1016/j.aei.2024.102705

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VKCNN: An interpretable variational kernel convolutional neural network for rolling bearing fault diagnosis

Guangyi Chen Guping Tang Z. K. Zhu

Year: 2024 Journal: Advanced Engineering Informatics Vol: 62 Pages: 102705-102705 Publisher: Elsevier BV

DOI: 10.1016/j.aei.2024.102705

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Keywords:

Convolutional neural network Bearing (navigation) Kernel (algebra) Artificial intelligence Fault (geology) Artificial neural network Computer science Pattern recognition (psychology) Engineering Machine learning Mathematics Geology Discrete mathematics

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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

Engineering Diagnostics and Reliability

Physical Sciences → Engineering → Mechanics of Materials

VKCNN: An interpretable variational kernel convolutional neural network for rolling bearing fault diagnosis

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