基于QICA的工作模态参数识别技术及其应用研究  

Research of the Operational Modal Parameter Identification Technology and Application based on QICA

作　　者：张睿[1,2] 何常德[1,2] 黄晋英[3] 张永梅[4] 薛晨阳[1,2] 张文栋[1,2] 

机构地区：[1]中北大学电子测试国家重点实验室,山西太原030051 [2]中北大学仪器科学与动态测试教育部重点实验室,山西太原030051 [3]中北大学机械与动力工程学院,山西太原030051 [4]北方工业大学信息工程学院,北京100144

出　　处：《机械传动》2015年第5期169-173,共5页Journal of Mechanical Transmission

摘　　要：针对目前基于振动信号的工作模态参数识别方法存在抗噪能力低,参数识别主观经验性较强,识别精度差和识别方法较复杂等问题,研究了一种基于量子优化ICA的工作模态参数识别技术(Operational Model Analysis,OMA),通过齿轮箱LMS模态实验证明,QICA模态参数识别技术操作简单,能够有效排除噪声干扰。最后以QICA识别的齿轮箱五种工况模态频率作为故障诊断特征参量,分析对比各工况下的模态频率的变化,进行了齿轮箱故障诊断。Aiming at the major difficulties of OMA method based on vibration signals such as low noise-robust ability,high subjective experience and poor accuracy in identifying parameters and more complex recognition method,a new method of OMA on the basis of QICA is studied.Through the LMS modal experimental data algorithm analysis,the QICA modal parameter identification technology operates simply,and can effectively eliminate noise interference.Finally,regards taking of gearbox modal frequency of the five kinds of working condition recognized by the QICA as characteristic parameter of fault diagnosis,the changes of any kind of model frequency on gearbox fault working condition are compared and analyzed,and the goal of the fault identification is achieved.

关 键 词：齿轮箱 量子独立分量分析 故障诊断 

分 类 号：TH132.41[机械工程—机械制造及自动化] TH165.3