基于数据流的矿山机电配套设备故障诊断模型

Fault diagnosis model of mine electromechanical auxiliary equipment based on data flow

矿山开采工作对于机电设备的依赖度较高,为了提高矿山机电设备的故障诊断率,保证其稳定运行,构建了基于数据流的矿山机电配套设备故障诊断模型。采用低功耗和体积小的信号处理器采集矿山机电设备故障信号,基于数据流检测故障信号,并划分普通信号和故障信号,依据划分结果建立配套设备故障诊断模型,实现矿山机电配套设备故障诊断。实验结果证明,构建的设备故障诊断模型诊断准确率较高。

Mining work is highly dependent on electromechanical equipment.In order to improve the fault diagnosis rate of mine electromechanical equipment and ensure its stable operation,a fault diagnosis model of mine electromechanical equipment based on data flow was constructed.The signal processor with low power consumption and small size was used to collect the fault signal of mine electromechanical equipment,detected the fault signal based on the data stream,and divided the common signal and fault signal,and established the fault diagnosis model of the auxiliary equipment according to the division result,so as to realize the fault diagnosis of the mine electromechanical equipment.The experimental results showed that the fault diagnosis accuracy of the constructed model was high.