首页 | 本学科首页   官方微博 | 高级检索  
     

大型回转机电设备采煤机故障智能诊断的研究
引用本文:侯小红,熊晓燕.大型回转机电设备采煤机故障智能诊断的研究[J].煤矿机械,2005(12):149-151.
作者姓名:侯小红  熊晓燕
作者单位:太原理工大学,太原,030024
摘    要:采煤机是一个集机械、电气和液压为一体的大型复杂系统,工作环境恶劣。如果出现故障将会导致整个采煤工作的中断,造成巨大的经济损失。因此建立一个智能化监测系统。全面、综合地反映它的真实运行状态,并预告其故障发生发展的趋势是非常必要的。介绍了采用多传感器对采煤机的运行状态进行监测,通过小波包对监测信号进行分析,得到其特征频率信息,以达到对其早期故障的预测。

关 键 词:采煤机  早期故障预测  小波包
文章编号:1003-0794(2005)12-0149-03
收稿时间:2005-07-30
修稿时间:2005年7月30日

Research of Early Intelligent Diagnosis for Faults in Coal Excavator
HOU Xiao-hong,XIONG Xiao-yan.Research of Early Intelligent Diagnosis for Faults in Coal Excavator[J].Coal Mine Machinery,2005(12):149-151.
Authors:HOU Xiao-hong  XIONG Xiao-yan
Affiliation:Taiyuan University of Technology, Tianyuan 030024, China
Abstract:Coal excavator is a complicated system that consists of machinery,electric and hydraulic drive,etc.It works in adverse circumstances.Its stop by faults will cause whole mine system to break down.So it is necessary to set up a complete fault intelligent diagnosis system to accurately describe intact state,forecast its faults and diagnose them.The paper introduces a method of using multisensor to detect running state and using the wavelet packet transform to analyse the signals.In the ends the character frequency information can be found and coal excavator's fault forecast achieved.
Keywords:coal excavator  fault forecast  wavelet packet
本文献已被 CNKI 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号