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水电机组状态监测及故障诊断研究

Study on Condition Monitoring and Fault Diagnosis of Hydroelectric Unit

【作者】 徐东海

【导师】 吴玉林;

【作者基本信息】 清华大学 , 动力工程及工程热物理, 2003, 硕士

【摘要】 水电以其在电力行业调峰的重要作用以及巨大的潜在资源,越来越受到人们的重视?随着电力市场的发展,提高水电自身的竞争力已成为行业追求的目标?提高水电机组运行稳定性,发展故障诊断相关的研究技术和实测手段,实施状态检修,是电力改革的必然要求?本文就水轮机组状态监测与故障诊断问题进行探讨,建立了一套对机组进行状态监测的方法,并在此基础上开发了水电机组在线监测及故障诊断系统,为水电厂开展状态检修及故障诊断奠定了基础?本论文基于状态检修的概念及其发展现状,针对贵州东风发电厂3号机组进行在线监测,分析水电站机组运行稳定性及能量问题,探讨故障诊断的实施,从工程应用的角度探讨状态检修和故障诊断的发展方向?本文对实际并网运行的机组实施全面的在线实时监测,将信号处理技术,水电机组测量技术,以及网络技术结合起来应用于工业现场,为运行?检修提供帮助?同时针对水轮发电机组的一般故障及东风水力发电厂3#机组的特性,总结了一套故障诊断数据库,在此基础上对机组进行初步的故障诊断以辅助电厂进行检修决策?

【Abstract】 Hydroelectric power is attached importance for its hump modulation and huge potential resource. Along with the development of power system, increasing the competitive power of hydroelectric plant becomes the hydropower trade’s aim. Enhancement of the operation stability of hydroelectric unit, development of the fault diagnose technology, and actualization of condition monitoring are the requirement of the reform of power system.The thesis studies on the condition monitoring and fault diagnose, and finds a method to monitor the hydroelectric unit. Based on this method, it develops a condition monitoring and fault diagnose system for hydroelectric unit.The system on-line monitors the No.3 unit of Guizhou Dongfeng Hydropower Plant and analyzes the operation stability and energy characteristics of the unit. It explores the way of actualization of condition monitoring and fault diagnose from the view of engineering. The system uses signal processing, monitoring technology and network, so it can monitor the unit on-line and real-time to help operation and servicing worker.The thesis sets up a diagnose knowledge base, which considers the normal fault of hydroelectric unit and the characteristics of the No.3 unit of Guizhou Dongfeng Hydropower Plant. With this condition, the system can diagnose the elementary fault of the unit to assist in operation and servicing.

【关键词】 水电机组状态检修故障诊断
【Key words】 Hydroelectric unitCondition monitoringDiagnose
  • 【网络出版投稿人】 清华大学
  • 【网络出版年期】2004年 03期
  • 【分类号】TV738
  • 【被引频次】10
  • 【下载频次】703
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