非线性调频模式分解及在机械设备故障诊断中的应用  

Nonlinear Chirp Mode Decomposition and its Application in Mechanical Fault Diagnosis

作　　者：林青云 魏连友 叶杰凯 易灿灿[2] LIN Qing-yun;WEI Lian-you;YE Jie-kai;Yi Can-can(Lishui Special Equipment Testing Institute,Zhejiang Lishui 323000,China;Wuhan University of Science and Technology,Hubei Wuhan 430081,China)

机构地区：[1]丽水市特种设备检测院,浙江丽水323000 [2]武汉科技大学,湖北武汉430081

出　　处：《机械设计与制造》2021年第5期77-81,共5页Machinery Design & Manufacture

基　　金：国家自然科学基金(51475339);丽水市自筹类公益性技术应用研究计划(201806);国家自然科学基金(批准号:51805382);丽水市自筹类公益性技术应用研究计划(2019SJZC03)。

摘　　要：由于机械设备传动系统中的关键零部件如轴承的振动信号具有典型非平稳的特征,将非线调频模式分解算法引入到机械设备故障诊断中,实现了对轴承等关键零部件早期微弱故障的特征识别。该方法在变模式分解理论的基础上,利用解调算子,将宽带信号变为窄带信号,实现了复杂信号的多尺度分解,同时使得多组分信号具有较高的时频分辨率。利用该方法对具有时频交叉干扰特性的仿真信号和故障实验台的实测轴承信号进行了分析,结果表明提出的方法在复杂信号模式分解和故障特征识别方面具有明显的优势。Since the vibration signals of key parts in the transmission system of mechanical equipment,such as bearings,have typical non-stationary characteristics,the nonlinear chirp mode decomposition algorithm is introduced into the fault diagnosis of mechanical equipment in this paper.It is designed to achieve the early weak fault identification of bearing and other parts.Based on the theory of variable mode decomposition,this method uses demodulation operator to change broadband signal into narrowband signal.Thus,the multiscale decomposition of complex signal is realized and the resolution of time frequency presentations is enhanced.The method is used to analyze the simulation signal with the characteristics of time-frequency cross interference and the measured bearing signal of the fault test bench.The results show that the proposed method has obvious advantages in complex signal modes decomposition and fault feature identification.

关 键 词：非线性调频 模式分解 故障诊断 特征识别 

分 类 号：TH16[机械工程—机械制造及自动化] U462.1[机械工程—车辆工程]