Fault diagnosis of diesel generator set based on optimized NRS and complex network

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Journal of Vibration and Shock ›› 2020, Vol. 39 ›› Issue (4) : 246-251.

JI Zhe1， FU Zhongqian2， ZHANG Songtao1

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Abstract

In order to solve the problem of complex fault identification in diesel generator set fault diagnosis, a fault diagnosis method combining variational modal decomposition, optimal neighborhood rough set and community hierarchical clustering was designed.The variational mode decomposition method was used to decompose the collected acoustic signals and form the initial feature set.Considering the influence of redundant features, an optimized neighborhood rough set was used to filter features to achieve the goal of attribute reduction.The fault diagnosis network was established by the community structure in the complex network, and the community structure was found by designing the association criterion function, and the fault diagnosis classification was realized at the same time.The experimental results show that the fault diagnosis rate of the proposed method reaches 99.17%, and its validity and superiority is fully confirmed.

Key words

diesel generator set / acoustic signal / neighborhood rough set / complex network / fault diagnosis

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JI Zhe1， FU Zhongqian2， ZHANG Songtao1. Fault diagnosis of diesel generator set based on optimized NRS and complex network[J]. Journal of Vibration and Shock, 2020, 39(4): 246-251

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