摘要
为实现对电机及水泵等大型旋转设备的在线监测及故障诊断,利用LabVIEW开发了实时监测与故障诊断系统。系统对电机电流、压力和温度数据进行潜在趋势分析;对振动数据,可通过经验模式分解(EMD)、Hilbert包络谱以及Teager能量算子方法进行分析。与传统的故障诊断系统相比,该系统的优势为在测点指标未超标的情况下,可提前预报测点的异常情况,且Teager能量算子的引入,极大地提高了冲击类故障的信噪比,更加有利于发现轴承等旋转部件早期微弱的故障。
In order to realize online state monitoring and fault diagnosis of large rotating equipment such as motors and water pumps,a real⁃time monitoring and fault diagnosis system was developed using LabVIEW.The system performed potential trend a⁃nalysis on motor current,pressure and temperature data.Vibration data can be analyzed by empirical mode decomposition(EMD),Hilbert envelope spectrum and Teager energy operator methods.Compared with the traditional fault diagnosis system,the advantage of this system is that it can predict the abnormal condition of the measuring point in advance when the measuring point index does not exceed the standard,and the introduction of Teager energy operator greatly improves the signal⁃to⁃noise ratio of im⁃pact faults,which is more conducive to finding early weak failures of rotating parts such as bearings.
作者
阳震
严保康
路鹏程
陆翔宇
YANG Zhen;YAN Bao-kang;LU Peng-cheng;LU Xiang-yu(School of Information Science and Engineering,Wuhan University of Science and Technology,Wuhan 430081,China)
出处
《仪表技术与传感器》
CSCD
北大核心
2021年第12期92-96,共5页
Instrument Technique and Sensor
基金
湖北省自然科学基金项目(2019CFB133)
国家自然科学基金项目(51975433)。
