基于VMD和BPNN-GA的齿轮裂纹故障诊断  

Fault Diagnosis of Gear Crack Based on VMD and BPNN-GA

作　　者：王二化[1] 刘忠杰[1] 刘颉 WANG Er-hua;LIU Zhong-jie;LIU Jie(Changzhou City Lab of Intelligent Technology for Advanced Manufacturing Equipment,Changzhou College of Information Technology,Jiangsu Changzhou 213164,China;School of Hydropower and Information Engineering,Huazhong University of Science and Technology,Hubei Wuhan 430074,China)

机构地区：[1]常州信息职业技术学院常州市高端制造装备智能化技术重点实验室,江苏常州213164 [2]华中科技大学水电与数字化工程学院,湖北武汉430074

出　　处：《机械设计与制造》2022年第10期208-211,217,共5页Machinery Design & Manufacture

基　　金：国家973项目:难加工航空零件数字化制造的基础研究(2011CB706803);常州市高端制造装备智能化技术重点实验室(CM20183004);江苏省青蓝工程中青年学术带头人,2020年江苏高校“青蓝工程”优秀青年骨干教师项目资助;常州信息职业技术学院“1+1+1”协同培育工程建设项目。

摘　　要：齿轮裂纹是机械传动机构容易出现的故障之一,严重的裂纹直接影响齿轮的使用寿命及整个传动系统的安全。基于变分模态分解(Variational Mode Decomposition,VMD)和改进的BP神经网络模型(BPNN),本文提出了一种齿轮裂纹故障诊断方法。首先对齿轮箱振动信号进行VMD分解,得到内禀模式函数(Intrinsic Mode Function,IMF);然后计算各个IMF的均方根和峭度,并选择与齿轮裂纹长度密切相关的IMF的峭度和均方根作为故障特征;最后通过基于遗传算法(Genetic Algorithm,GA)的BPNN模型对得到的齿轮裂纹故障特征进行分类。结果表明,这里提出的故障诊断方法能够准确识别无裂纹、1/4裂纹、1/2裂纹和3/4裂纹的齿轮,在识别精度和计算效率方面具有优异的综合性能。Gear crack is one of the faults of mechanical transmission mechanism,which directly affects the service life of gear and the safety of the whole transmission system.Based on the empirical mode decomposition(VMD)and the improved BP neural network model(BPNN),a fault diagnosis method of gear crack is proposed in this paper.Firstly,the vibration signal of gearbox is decomposed by VMD to get the intrinsic mode component IMF;then,the RMS and kurtosis of each IMF component are calculated,and the RMS and kurtosis of the intrinsic mode component closely related to the crack length of the gear are selected as the fault characteristics;finally,based on genetic algorithm genetic algorithm The BPNN model of algorithm(GA)is used to classify the fault features of gear cracks.The results show that the fault diagnosis method proposed in this paper can accurately identify the gears without crack,1/4 crack,1/2 crack and 3/4 crack,and has excellent comprehensive performance in recognition accuracy and calculation efficiency.

关 键 词：齿轮裂纹 故障诊断 变分模态分解 BP神经网络 遗传算法 

分 类 号：TH16[机械工程—机械制造及自动化] TM341[电气工程—电机] TM351