摘要
通过分析煤矿机械齿轮和轴承故障类型与原因后,将振动信号作为检测故障的依据,以频域分析法作为判断煤矿机械故障类型的方法,简化了分析过程。利用数据挖掘技术快速获取有用的知识和模型,有效提高了系统整合大量数据的能力,建立了数据仓库用来存放可用于支持决策的数据,及时发现设备的微小变化并预测故障部位,减少了煤矿机械故障发生概率。
After analyzing the types and causes of faults in coal mine mechanical gears and bearings,the vibration signal is used as the basis for detecting faults, and the frequency domain analysis method is used as a method to judge the type of coal mine mechanical faults, which simplifies the analysis process. Data mining technology is used to quickly obtain useful knowledge and models, which has effectively improved the system′s ability to integrate large amounts of data. A data warehouse has been established to store data that can be used to support decision-making. The system can timely find small changes in equipment and predict fault locations, which can reduce the probability of mechanical failure.
作者
刘婷
LIU Ting(Jining Polytechnic,Jining 272037,China)
出处
《煤炭技术》
CAS
2018年第9期307-309,共3页
Coal Technology
关键词
煤矿机械故障
齿轮
轴承
频域分析法
振动信号
coal mine machinery failure
gears
bearing
frequency domain analysis method
vibration signal
