[1] Yang Zhenbo, Jia Minping,. GA-1DLCNN method and its applicationin bearing fault diagnosis [J]. Journal of Southeast University (English Edition), 2019, 35 (1): 36-42. [doi:10.3969/j.issn.1003-7985.2019.01.006]

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

35

Issue:

2019 1

Page:

36-42

Research Field:

Mechanical Engineering

Publishing date:

2019-03-30

Info

Title:

GA-1DLCNN method and its applicationin bearing fault diagnosis

Author(s):

Yang Zhenbo;  Jia Minping

School of Mechanical Engineering, Southeast University, Nanjing 211189, China

Keywords:

one-dimensional convolution neural network;  large-size convolution kernel;  hyper-parameter optimization;  genetic algorithm

PACS:

TH17

DOI:

10.3969/j.issn.1003-7985.2019.01.006

Abstract:

Due to the fact that the vibration signal of the rotating machine is one-dimensional and the large-scale convolution kernel can obtain a better perception field, on the basis of the classical convolution neural network model(LetNet-5), one-dimensional large-kernel convolution neural network(1DLCNN)is designed. Since the hyper-parameters of 1DLCNN have a greater impact on network performance, the genetic algorithm(GA)is used to optimize the hyper-parameters, and the method of optimizing the parameters of 1DLCNN by the genetic algorithm is named GA-1DLCNN. The experimental results show that the optimal network model based on the GA-1DLCNN method can achieve 99.9% fault diagnosis accuracy, which is much higher than those of other traditional fault diagnosis methods. In addition, the 1DLCNN is compared with one-dimencional small-kernel convolution neural network(1DSCNN)and the classical two-dimensional convolution neural network model. The input sample lengths are set to be 128, 256, 512, 1 024, and 2 048, respectively, and the final diagnostic accuracy results and the visual scatter plot show that the effect of 1DLCNN is optimal.

References:

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Memo

Memo:

Biographies: Yang Zhenbo(1995—), male, graduate; Jia Minping(corresponding author), male, doctor, professor, mpjia@seu.edu.cn.
Foundation item: The National Natural Science Foundation of China(No.51675098).
Citation: Yang Zhenbo, Jia Minping.GA-1DLCNN method and its application in bearing fault diagnosis[J].Journal of Southeast University(English Edition), 2019, 35(1):36-42.DOI:10.3969/j.issn.1003-7985.2019.01.006.

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