在线电机诊断的特征分析

I. Culbert, J. Letal
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引用次数: 1

摘要

异步电动机定子电流特征分析是诊断转子鼠笼绕组缺陷和气隙偏心问题的一种行之有效的方法。使用该技术,可以识别特定频率电流分量,作为保持架绕组缺陷以及定子和转子之间不均匀间隙的指示。由于这些数据通常是定期收集的,因此尽早识别这些组件非常重要。然后可以更频繁地监测这些可趋势参数,以避免在使用中出现故障。随着新的处理技术的应用,识别这些关键的电流特征频率成分和它们所指示的恶化趋势的能力得到了提高。这使得维护活动可以更早地安排,并在故障之前执行,避免昂贵的电机部件损坏和计划外停机。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Signature analysis for on-line motor diagnostics
Stator current signature analysis on induction motors is a proven method for diagnosing rotor squirrel cage winding defects and air gap eccentricity problems. With this technology, specific frequency current components can be identified as an indication of cage winding defects as well as a non-uniform gap between the stator and rotor. Because this data is generally collected periodically, it is important to identify these components as early as possible. These trendable parameters can then be monitored more often to avoid inservice failure. With the application of new processing technologies, the ability to identify these critical current signature frequency components and trend the deterioration they indicate has improved. This allows for maintenance activities to be scheduled earlier and performed prior to failure avoiding costly motor component damage and unplanned downtime.
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