基于CUM3-CNN的柴油机高压油路故障诊断

常春,梅检民,赵慧敏,沈 虹,王双朋

振动与冲击 ›› 2023, Vol. 42 ›› Issue (3) : 174-180.

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振动与冲击 ›› 2023, Vol. 42 ›› Issue (3) : 174-180.
论文

基于CUM3-CNN的柴油机高压油路故障诊断

  • 常春,梅检民,赵慧敏,沈 虹,王双朋
作者信息 +

Fault diagnosis of diesel engine high pressure oil circuit based on CUM3-CNN

  • CHANG Chun, MEI Jianmin, ZHAO Huimin, SHEN Hong, WANG Shuangpeng
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文章历史 +

摘要

针对柴油机故障诊断中噪声干扰强、人工确定特征主观影响大、自动识别准确率低的问题,提出了一种利用卷积神经网络识别振动信号三阶累积量灰度图的柴油机故障诊断方法。首先利用三阶累积量抑制高斯噪声的先天特点对缸盖振动信号进行分析,生成抑制噪声后的灰度图像,作为卷积神经网络的输入;用具有动量的随机梯度下降优化算法和学习率退火方法训练卷积神经网络,通过遗传算法优化训练参数,用训练好的网络对柴油机高压油路的5种工况进行故障诊断。实验结果表明,三阶累积量生成的灰度图像既能有效抑制噪声又能全面表现特征信息;用学习率退火方法和遗传算法改进优化的卷积神经网络有良好的泛化能力,相比于传统方法具有更高的准确率和抗噪能力。

Abstract

Aiming at the problems of strong noise interference, high subjective influence of artificial identification characteristics and low accuracy of automatic identification in diesel engine fault diagnosis,a diesel engine fault diagnosis method using convolutional neural network to identify the cumulant grayscale image of vibration signal was proposed. Firstly, using the innate characteristics of third-order cumulants to suppress Gaussian noise, the vibration signal of cylinder head was analyzed, and the grayscale image was generated as input of convolution neural network. Stochastic gradient descent with momentum algorithm and learning rate annealing method were used to train the convolutional neural network, and genetic algorithm was used to optimize training parameters, then the trained network was used to diagnose the faults of five working conditions of diesel engine high pressure oil circuit. The experimental results show that the grayscale images generated by third-order cumulants can suppress the noise effectively and display the characteristic information comprehensively. The method of learning rate annealing and genetic algorithm to improve the optimized convolutional neural network has good generalization ability, and has higher accuracy and anti-noise ability than the traditional method.

关键词

柴油机 / 故障诊断 / 三阶累积量 / 卷积神经网络

Key words

diesel engine / fault diagnosis / third-order cumulant / convolution neural network

引用本文

导出引用
常春,梅检民,赵慧敏,沈 虹,王双朋. 基于CUM3-CNN的柴油机高压油路故障诊断[J]. 振动与冲击, 2023, 42(3): 174-180
CHANG Chun, MEI Jianmin, ZHAO Huimin, SHEN Hong, WANG Shuangpeng. Fault diagnosis of diesel engine high pressure oil circuit based on CUM3-CNN[J]. Journal of Vibration and Shock, 2023, 42(3): 174-180

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