摘要
对起重机负载电机进行了研究,采用西门子公司的S7-200SMART PLC采集负载电机的机械振动信号,通过工业Wi-Fi无线模块以无线数据包的形式将采集的数据汇总到上位机LabVIEW监测平台;上位机的LabVIEW监测平台对电动机振动信号进行相关性和频谱分析,将实时振动数据频谱信号和已知常见负载电机的轴承外圈故障、轴承内环故障和滚子故障3种典型的故障状态频谱信号进行相关性运算,得到实时信号与已知状态的相关系数;提出了以相关系数作为故障诊断判定阈值的方法进行故障诊断,实现了对起重机状态进行监测以及监控信息发布。
This paper proposes the use of Siemens S7-200 Smart PLC to collect mechanical vibration signals of rolling bearings for the crane load motor by Phoenix industrial Wi- Fi wireless module to send the collected data in the form of wireless packet data summary to the PC monitoring center. The correlation and spectrum analysis of the motor vibration signal are carried out by the LabVIEW monitoring platform of the host computer. The real-time vibration data spectrum signal and three typical fault state spectrum signals of known common bearing outer ring failure, inner ring fault and roller failure are carried out by correlation method. The correlation coefficient is used as the fault diagnosis threshold to diagnose the fault, and the state of the crane is monitored and the information of the monitoring is released.
出处
《计算机测量与控制》
2017年第7期43-46,50,共5页
Computer Measurement &Control
基金
国家自然科学基金(51209134)
关键词
起重机
状态监控
相关性原理
工业无线
故障诊断
crane
condition monitoring
industrial wireless
correlation
fault diagnosis
