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为了能及时准确地发现采煤机电动机故障,快速地对电机故障进行诊断处理、减小损失,针对采煤机电动机中常见的滚动轴承故障特点,提出了一种新的故障类型诊断方法.通过优化小波参数有效地提取故障信号的频段特征,再利用改进的专家系统对所获特征进行辨识,诊断出具体故障类型,给出预警信息和维修策略.研究结果表明:采煤机电动机故障诊断专家系统能够正确判断滚动轴承常见故障,满足现场实时监控和故障预警要求,而且诊断结论符合现场实际.
In order to find out the fault of shearer motor in time and accurately, diagnose the fault of motor quickly and reduce the loss, a new fault type diagnosis method is proposed according to the common faults of bearing in shearer motor.Through the optimization Wavelet parameters effectively extract the band characteristics of the fault signal, and then use the improved expert system to identify the characteristics obtained, diagnose the specific fault types, and give the warning information and maintenance strategy.The results show that: the fault diagnosis expert system Correctly determine the common faults of rolling bearings to meet the on-site real-time monitoring and fault warning requirements, and the diagnosis concluded in line with the actual site.