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为了能及时准确的发现采煤机电机故障,快速做出电机故障诊断决策,减小损失,针对采煤机电动机中常见的滚动轴承故障,在对采煤机机械故障信号进行深入分析的基础上,提出一种基于正交小波的采煤机电机故障诊断方法。利用小波变换在特征分析过程中所得到的小波熵值、峭度值以及平滑指数三大特征参数,通过对参数的比较分析,得到不同参数下电机滚动轴承故障的不同类型,并设计开发了基于小波分析的采煤机电机故障诊断专家系统。实验结果表明,故障诊断系统能正确判断故障部位及类型,并给出针对性维修策略,大大减少了故障诊断时间,具有较好实际应用价值。
In order to timely and accurately detect the fault of shearer motor and make the diagnosis decision of motor fault quickly to reduce the loss, aiming at the common rolling bearing fault in shearer motor, based on the deep analysis of the mechanical fault signal of shearer, A fault diagnosis method of shearer motor based on orthogonal wavelet is proposed. Based on wavelet transform, the three characteristic parameters of wavelet entropy, kurtosis and smoothing index obtained in the process of feature analysis are compared. Based on the comparison and analysis of parameters, different types of motor rolling bearing faults with different parameters are obtained. Shearer motor fault diagnosis expert system based on wavelet analysis. The experimental results show that the fault diagnosis system can correctly determine the fault location and type, and give a targeted maintenance strategy, greatly reducing the fault diagnosis time, with good practical value.