对大型电机和发电机的电气绕组进行基于状态的维护

G. Stone, J. Kapler
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引用次数: 5

摘要

许多纸浆和造纸厂正在转向基于状态的维护(CBM),也称为预测性维护,用于发电机和电动机等主要设备。在电力行业赞助的研究中,已经开发出新的工具来帮助电机和发电机操作员在这些机器的电气绕组上实施CBM。其中一项技术涉及开发一个专家系统,该系统分析所有常见的在线和离线测试以及运行数据,以估计绕组故障风险的总体指标。在第二项开发中,开发了一种可供工厂人员使用的在线局部放电测量系统,该系统可以检测额定4kv及以上定子绕组中可能发生的大多数劣化机制。本文回顾了这两个领域的发展,它们严重依赖于复杂的软件技术,并讨论了它们在实现CBM中的应用。本文主要研究定子绕组。首先简要讨论了定子绕组最容易发生的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Condition-based maintenance for the electrical windings of large motors and generators
Many pulp and paper mills are moving toward condition-based maintenance (CBM), also known as predictive maintenance, for major equipment such as generators and motors. In research sponsored by the electric utility industry, new tools have been developed to help motor and generator operators implement CBM on the electrical windings in such machines. One technology involved the development of an expert system which analyzes all common online and offline tests together with operating data to estimate an overall indicator of the risk of winding failure. In a second development, an online partial discharge measurement system which can be used by plant personnel has been developed which can detect most of the deterioration mechanisms that can occur in stator windings rated 4 kV and above. This paper reviews the development of these two areas, which rely heavily on sophisticated software technologies, and discusses their application to implement CBM. The paper concentrates on stator windings. A short discussion of what problems are most likely to occur in stator windings is first presented.
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