Optimization of Deep Belief Network Based on Sparrow Search Algorithm for Rolling Bearing Fault Diagnosis
Donghao Xu,
Cheng Li
Abstract:This study addresses the randomness of training parameters in the Deep Belief Network (DBN) and proposes an optimization method for rolling bearing fault diagnosis based on the Sparrow Search Algorithm (SSA). SSA is employed to globally optimize the structural and training parameters of the DBN network, effectively resolving the challenge of parameter determination. Simultaneously, vibration signals are extracted from multiple dimensions to capture different types of fault features. These features are derived … Show more
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