多元信号融合的在线监测与故障诊断系统开发  

Development of Online Monitoring and Fault Diagnosis System Based on Multivariate Signal Fusion

作　　者：李林峰 吕勇 袁锐[1,2] Li Linfeng;Lv Yong;Yuan Rui(The Key Laboratory of Metallurgical Equipment and Control of Education Ministry,School of Machinery and Automation,Wuhan University of Science and Technology,Wuhan 430081;Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering,School of Machinery and Automation,Wuhan University of Science and Technology,Wuhan 430081)

机构地区：[1]武汉科技大学机械自动化学院冶金装备及其控制教育部重点实验室,湖北武汉430081 [2]武汉科技大学机械自动化学院机械传动与制造工程湖北省重点实验室,湖北武汉430081

出　　处：《冶金设备》2022年第5期1-7,共7页Metallurgical Equipment

基　　金：国家自然科学基金面上项目(51875416);湖北省自然科学基金创新群体项目(2020CFA033)。

摘　　要：冶金设备是冶金工业中的关键,对其振动信号的监测与故障诊断是保证安全生产的重要环节。本文旨在开发一种在线监测与故障诊断系统,该系统利用多传感器采集多元振动信号,以避免局部故障信息的丢失;针对报警数据,应用基于多元经验模式分解(MEMD)的多元信号融合算法分解提取故障特征频率,实现了故障诊断的功能。本文根据高速线材轧制生产线实际工况,提出系统整体设计方案;阐述了系统所应用的多元信号融合的故障诊断方法;在此基础上,开发系统软件,并开展试验验证。结果表明,所开发的系统在冶金设备的状态监测和故障诊断中具有实际应用价值。Metallurgical equipment is crucial to metallurgical industry. Monitoring and fault diagnosis of its vibration signal is an important link to ensure safe production. This paper aims to develop an online monitoring and fault diagnosis system, which uses multiple sensors to collect multivariate vibration signals to avoid the loss of local fault information;The multivariate signal fusion algorithm based on multivariate empirical mode decomposition is applied to decompose the fault characteristic frequency to realize fault diagnosis. Referring to the actual working conditions, this paper puts forward the overall design scheme of the system. And the fault diagnosis algorithm of multivariate signal fusion applied in the system is described. On this basis, the system software is developed and tested. The results show that the developed system has practical application value in condition monitoring and fault diagnosis of metallurgical equipment.

关 键 词：机械状态监测 故障诊断 多元信号融合 LABVIEW PYTHON 

分 类 号：TP277[自动化与计算机技术—检测技术与自动化装置] TH165.3[自动化与计算机技术—控制科学与工程]