一种采煤机状态预测方法研究

Research on a State Prediction Method of Coal Mining Machine

针对采煤机测量数据处理困难,无法准确表征其运行状态,设计了一种采煤机预测方法。通过分析了采煤机常见的运行故障和状态数据采集方法,建立了运行状态数据处理模型,实现采煤机运行状态实时预测,以某煤矿实际工程为例,取牵引部电机电流、牵引部电机温度、牵引部电机转速三种监测数据各2 000条作为实验数据进行状态预测,结果表明该模型真实值和预测结果拟合程度达到93%以上,各数据的状态预警准确率均达到90%以上,准确率较高,满足实际工程需求。

Aiming at the difficulty of processing the measurement data of coal mining machine and the inability to accurately characterise its operation status,a prediction method for coal mining machine is designed.It analyses the common operating faults and state data acquisition methods of coal mining machine,establishes an operating state data processing model,and realizes real-time prediction of the operating state of coal mining machine.Taking an actual project of a coal mine as an example,it takes the three kinds of monitoring data of the motor current of the haulage section,the temperature of the motor of the haulage section,and the motor speed of the haulage section,each of which has 2,000 pieces,as the experimental data for the state prediction,and the results show that the fitting degree of the real value of this model and the prediction result is more than 93%.reaches more than 93%,and the state warning accuracy of each data reaches more than 90%,which is high and meets the actual engineering requirements.