煤矿通风机故障信号特征提取方法优化研究  

Research on Optimization of Fault Signal Feature Extraction Method for Coal Mine Ventilator

作　　者：赵建斌 Zhao Jianbin(China Coal Research Institute,Beijing 100013,China)

机构地区：[1]煤炭科学技术研究院有限公司,北京100013

出　　处：《煤矿机械》2024年第11期169-171,共3页Coal Mine Machinery

基　　金：煤炭科学技术研究院有限公司科技发展基金项目(技术创新基金)(2022CX-I-07)。

摘　　要：通风机作为煤矿通风系统的核心部分,是煤矿安全高效生产的前提条件,主通风机的运行状态与煤矿的安全生产息息相关,但是由于振动信号的非平稳性,无法准确地对其故障信号特征进行提取。为解决以上问题,分别针对转速波动工况和变转速工况采用不同的提取方法进行分解,最后将两者结合,达到精准提取煤矿主通风机故障信号特征的目的,为煤矿通风系统的安全监控与故障预警智能系统的建立提供理论基础。As the core part of the coal mine ventilation system,the fan is a prerequisite for safe and efficient production of coal mines.The operating state of the main fan is closely related to the safe production of coal mines.However,due to the non-stationarity of the vibration signal,it is impossible to accurately extract the fault signal characteristics.In order to solve the above problem,the different extraction methods were used to decompose the speed fluctuation condition and the variable speed condition respectively.Finally,two methods were combined to achieve the purpose of accurately extracting the fault signal characteristics of the main fan in coal mine,which provides a theoretical basis for the establishment of safety monitoring and fault warning intelligent system of coal mine ventilation system.

关 键 词：煤矿通风 通风故障 故障诊断 特征提取 

分 类 号：TD724[矿业工程—矿井通风与安全]