基于AO-VMD和IAO-SVM的齿轮箱故障诊断  

Fault Diagnosis of Gearboxes Based on AO-VMD and IAO-SVM

作　　者：王博 南新元[1] Wang Bo;Nan Xinyuan(School of Electrical Engineering,Xinjiang University,Urumqi 830047,China)

机构地区：[1]新疆大学电气工程学院,新疆乌鲁木齐830047

出　　处：《机械传动》2023年第5期143-149,共7页Journal of Mechanical Transmission

摘　　要：针对提高变分模态分解(Variational Mode Decomposition,VMD)的自适应性、优选本征模态分量(Intrinsic Mode Function,IMF)及多故障分类的问题,提出一种天鹰优化器(Aquila Optimizer,AO)优化VMD、综合评价模型优选IMF、改进天鹰优化器(Improved Aquila Optimizer,IAO)优化支持向量机(Support Vector Machine,SVM)的齿轮箱故障诊断方法。首先,采用AO优化VMD的参数并分解原始信号;其次,构建基于相关系数、峭度、包络熵、能量熵的CRITIC-TOPSIS综合评价模型,优选IMF,提取能量熵建立特征向量;最后,将其输入IAO-SVM识别故障类型。通过实验验证所提出方法的有效性。Aiming at the problems of improving the adaptability of variational mode decomposition(VMD)and in order to optimize the intrinsic mode function(IMF)and multi-fault classification,a gearbox fault diagno⁃sis method is proposed,with which the Aquila optimizer(AO)optimizes VMD,the comprehensive evaluation model optimizes IMF,and improves the Aquila optimizer optimization support vector machine(IAO-SVM).First⁃ly,AO is used to optimize the parameters of VMD and decompose the original signal.Secondly,a CRITIC-TOP⁃SIS comprehensive evaluation model based on correlation coefficient,kurtosis,envelope entropy,energy entropy is constructed to optimize IMF,and energy entropy is extracted to establish feature vectors.Finally,it is input in⁃to IAO-SVM to identify faults.The effectiveness of this method is verified by experiments.

关 键 词：天鹰优化器 变分模态分解 综合评价模型 改进天鹰优化器 支持向量机 

分 类 号：TH132.41[机械工程—机械制造及自动化]