Detection of air-gap eccentricity faults in synchronous machines

同步电机气隙偏心故障的检测

• 批准号: 238253-2006
• 负责人: Nandi, Subhasis
• 金额: $ 1.6万
• 依托单位: University of Victoria
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2007
• 资助国家: 加拿大
• 起止时间: 2007-01-01 至 2008-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=364090
• 关键词: Detection; air; gap; eccentricity; faults

Recently, research related to on-line electric machine fault diagnosis (also known as Condition Based Monitoring (CBM)) has generated considerable interest. Fault prognosis, particularly at the incipient stage, can reduce machine downtime and maintenance considerably. Air-gap eccentricity faults occur in electrical machines when the air-gap between stator and rotor is no longer uniform. An air-gap eccentricity can be broadly classified into two types, namely, the static air-gap eccentricity and the dynamic air-gap eccentricity. Static and dynamic eccentricities tend to co-exist. Unless detected early, eccentricity may result in stator to rotor rub, causing a major breakdown of the machine due to core and winding damage. Normally, eccentricity related faults are associated with large machines. The detection and monitoring techniques available for eccentricity have been mostly restricted to induction machines because they usually have very small airgap. However, early and quick detection techniques of eccentricity for synchronous machines can also lead to their design with much smaller airgap. This will substantially reduce the cost of the machine due to a decrease in magneto motive force (MMF) requirements. It will also reduce short circuit currents and hence circuit breaker size and cost. It is therefore imperative that diagnosis techniques, preferably non-invasive in nature, are developed to monitor and detect these faults in synchronous machines. It is expected that the results of the investigation will shed new light in understanding how to effectively detect eccentricity of synchronous machines. This will benefit numerous manufacturers and users of synchronous machines and will surely translate into increased profit and enhanced productivity for Canadian industry.

近年来，电机在线故障诊断（也称为基于状态的监测）的研究引起了人们的广泛关注。故障预测，特别是在早期阶段，可以大大减少机器停机时间和维护。当电机定子与转子之间的气隙不均匀时，就会发生气隙偏心故障。气隙偏心可大致分为静态气隙偏心和动态气隙偏心两种类型。静态和动态偏心倾向于共存。如果不及早发现，偏心可能会导致定子和转子摩擦，导致铁芯和绕组损坏，从而导致机器的重大故障。通常，与偏心相关的故障与大型机器有关。可用于偏心的检测和监测技术大多局限于感应电机，因为它们通常具有非常小的气隙。然而，早期和快速检测技术的偏心同步电机也可以导致他们的设计与更小的气隙。这将大大降低机器的成本，由于减少了磁动机（MMF）的要求。它还将减少短路电流，从而减少断路器的尺寸和成本。因此，必须开发诊断技术，最好是非侵入性的，以监测和检测同步电机中的这些故障。本文的研究结果将为如何有效地检测同步电机偏心提供新的思路。这将使同步机器的众多制造商和用户受益，并必将转化为增加利润和提高加拿大工业的生产力。