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首页> 外文期刊>IEEE Transactions on Industry Applications >Reducing unscheduled plant maintenance delays-field test of a new method to predict electric motor failure
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Reducing unscheduled plant maintenance delays-field test of a new method to predict electric motor failure

机译:减少计划外的工厂维护延迟-一种预测电动机故障的新方法的现场测试

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摘要

Most electric motor predictive maintenance methods have drawbacks that limit their effectiveness in the mining environment. The US Bureau of Mines (USBM) is developing an alternative approach to detect winding insulation breakdown in advance of complete motor failure. In order to evaluate the analysis algorithms necessary for this approach, the USBM has designed and installed a system to monitor 120 electric motors in a coal preparation plant. The computer-based experimental system continuously gathers, stores, and analyzes electrical parameters for each motor. The results are then correlated to data from conventional motor maintenance methods and in-service failures to determine if the analysis algorithms can detect signs of insulation deterioration and impending failure. This paper explains the online testing approach used in this research, and describes monitoring system design and implementation. At this writing, data analysis is underway, but conclusive results are not yet available.
机译:大多数电动机预测性维护方法都存在一些缺点,这些缺点限制了它们在采矿环境中的有效性。美国矿业局(USBM)正在开发一种替代方法,以在电动机完全故障之前检测绕组绝缘故障。为了评估此方法所需的分析算法,USBM设计并安装了一个系统来监控选煤厂中的120台电动机。基于计算机的实验系统不断收集,存储和分析每个电动机的电气参数。然后将结果与常规电动机维护方法和在役故障中的数据相关联,以确定分析算法是否可以检测到绝缘劣化和即将发生故障的迹象。本文介绍了此研究中使用的在线测试方法,并介绍了监视系统的设计和实现。在撰写本文时,数据分析正在进行中,但尚无最终结果。

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