测试科学与仪器2021，Vol.12Issue(2)：242-252,11.DOI:10.3969/j.issn.1674-8042.2021.02.014
基于电信号的改进VMD和DBN-DNN液压齿轮泵轮齿故障监测方法研究
Monitoring method of gear teeth failure of hydraulic gear pump based on improved VMD and DBN-DNN of electrical signal
摘要
Abstract
Abundant system operation state information is included in the electrical signal of the hydraulic system motor.How to accurately extract and classify the operation information of electrical signal is the key to realize the condition monitoring of hydraulic system.The early fault characteristics of hydraulic gear pump hidden in the motor current signal are weak and difficult to extract by traditional time-frequency analysis.Based on the correlation coefficient and artificial bee colony algorithm (ABC),the parameter optimization of variational mode decomposition (VMD)is realized in this paper.At the same time,the principle of maximum signal correlation coefficient and kurtosis value is adopted to determine the effective intrinsic mode function (IMF).Moreover,the permutation entropy(PE)and root mean square(RMS)of the effective IMF components are input into the deep belief network (DBN-DNN)as high-dimensional feature vectors.The operation state of gear pump is monitored.The results show that the weak characteristics of current signal of gear pump fault are accurately and stably extracted by this method.The running state of gear pump is monitored and the accuracy of gear fault diagnosis is improved.关键词
轮齿故障/状态监测/人工蜂群算法/变分模态分解法/深度信念网络Key words
gear teeth fault/status monitoring/artificial bee colony algorithm (ABC )/variational mode decomposition (VMD)/deep belief network (DBN-DNN)引用本文复制引用
杨莎,谷立臣,石媛,耿宝龙,刘佳敏,赵宝建,仵浩宇..基于电信号的改进VMD和DBN-DNN液压齿轮泵轮齿故障监测方法研究[J].测试科学与仪器,2021,12(2):242-252,11.基金项目
National Natural Science Foundation of China(No.51675399) （No.51675399）
