概率神经网络在车辆齿轮箱典型故障诊断中的应用*

doi:10.19562/j.chinasae.qcgc.2020.07.018

Abstract

Abstract: In order to enhance the diagnosis efficiency and accuracy of the typical faults of automotive gearbox, a fault diagnosis method of gearbox based on probabilistic neural network (PNN) is proposed. The vibration signals of the gearbox under normal state, tooth root cracks and broken tooth are collected through an experiment on a gearbox. After data processing, the sample data are obtained and input into PNN model. The results of cross-validation and comparison with the BP neural network (BPNN) show that PNN can accurately identify the typical faults of the gearbox and has higher diagnostic accuracy and faster diagnostic speed compared with BPNN.

Key words: gearbox, fault diagnosis, probabilistic neural network, pattern recognition

Zhang Yangyang, Jia Yunxian, Wu Weiyi, Su Xiaobo, Shi Xiaowen. Application of Probabilistic Neural Network to Typical Fault Diagnosis of Vehicle Gearbox[J].Automotive Engineering, 2020, 42(7): 972-977.

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Application of Probabilistic Neural Network to Typical Fault Diagnosis of Vehicle Gearbox

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