机械与电子2024，Vol.42Issue(3)：76-80,5.
基于WSN的旋转机械设备故障时频监测方法
Time Frequency Monitoring Method of Rotating Machinery Equipment Fault Based on WSN
孙留存 1胡从川 1钱大龙1
作者信息
- 1. 中国绿发投资集团有限公司,北京 100020
- 折叠
摘要
Abstract
Due to the complex structure and vibration source of rotating machinery equipment,the threshold set by single fault experience cannot accurately decompose multi-modal faults.In order to im-prove the fault monitoring effect,a time-frequency monitoring method for rotating machinery equipment faults based on WSN is proposed.The time-frequency signal of fault is decomposed by the collective em-pirical mode,the vibration signal at different times is decomposed,the energy of the IMF component is cal-culated,and the normalized energy index and the IMF matrix singular spectrum entropy index are com-bined to complete the decomposition of the fault time-frequency signal of rotating machinery equipment.According to the results of feature decomposition,the trained immune RBF neural network is used to mo-nitor the faults of rotating machinery.The experimental results show that this method can shorten the mo-nitoring time and improve the fault monitoring accuracy.关键词
集合经验模态/旋转机械设备/故障监测/时频监测/主成分分析/RBF神经网络Key words
set empirical mode/rotating mechanical equipment/fault monitoring/time frequency moni-toring/principal component analysis/RBF neural network分类
机械制造引用本文复制引用
孙留存,胡从川,钱大龙..基于WSN的旋转机械设备故障时频监测方法[J].机械与电子,2024,42(3):76-80,5.
