基于冲击脉冲传感器监测技术的矿用胶带机自动化机械监测研究  

Research on automatic mechanical monitoring of mining belt conveyor based on impact pulse sensor monitoring technology

作　　者：张少华 Zhang Shaohua(CHN Energy Xinjiang Zhundong Energy Co.,Ltd.,Urumqi Xinjiang 830001,China)

机构地区：[1]国能新疆准东能源有限责任公司,新疆乌鲁木齐830001

出　　处：《煤化工》2024年第2期78-81,共4页Coal Chemical Industry

摘　　要：针对传统矿用胶带机轴承故障监测存在的数据偏差、数据误差、故障诊断准确性低等问题,构建了一种基于冲击脉冲传感器的胶带机轴承故障监测模型,然后利用模型方法验证实际应用效果。结果表明:迭代至100次时,与长短期记忆网络、时间卷积神经网络相比,模型方法的准确度分别高出0.08和0.13,且模型方法的收敛速度更快,损失函数降低更小,说明模型方法在矿用胶带机轴承故障监测过程中,具有较高的准确性和可行性;将模型方法应用于煤矿胶带机的实时监测中,可准确获取早期故障信号。Aiming at the problems of data deviation,data error and low accuracy of fault diagnosis in traditional mining belt conveyor bearing fault monitoring,a belt conveyor bearing fault monitoring model based on the impact pulse sensor was constructed.And then the modeling method was used to verify the actual application effect.The results showed that when iterated to 100 times,compared with long short-term memory network and time convolutional neural network,the accuracy of the modeling method was 0.08 and 0.13 higher,respectively,the convergence speed of the modeling method was faster and the loss function was smaller,indicating that the modeling method had high accuracy and feasibility in the bearing fault monitoring process of the mining belt conveyor.The model method could be applied to the real-time monitoring of the coal mine belt conveyor,and the early fault signal could be accurately obtained.

关 键 词：冲击脉冲传感器 模型方法 矿用胶带机 轴承 故障监测 

分 类 号：TD634[矿业工程—矿山机电]