摘要
水轮发电机组是大型机电能量转换装置,其运行状态关系到水电厂能否安全、经济的供电。近百年来,以统计理论为基础,按计划定期进行小修、中修、大修的维修体制,普遍存在着过维修和不足维修现象,特别是近年来随着水轮发电机组的巨型化,这种维护体制更加暴露出严重的弊端。因此,实现有效的机组状态监测和故障诊断,提高维修的针对性,不仅对电力工业,而且对整个国民经济都有重要的影响。
本文论述水轮发电机组故障诊断和在线监测的重要意义,分析故障诊断的研究现状及发展趋势,并对故障诊断的应用前景做进一步分析。在概述水轮机的状态监测和故障诊断系统的基础上,在研究了故障诊断常用的方法后,提出使用模糊专家系统对设备进行诊断分析,从而将人工智能技术与故障诊断技术相结合,实现更精确的故障诊断,根据水轮发电机组振动故障特点,提出了一种基于模糊逻辑、神经网络与专家系统的混合智能诊断方法。本文中给出基于模糊神经网络的水轮发电机组故障诊断专家系统,实例仿真结果验证了模糊神经网络用于水轮发电机组振动故障诊断专家系统的合理性与可行性。完成了水轮发电机组状态监测与故障诊断系统的软件开发,实现了数据采集和信号分析功能、实时状态监测的功能、振动分析功能、故障诊断功能等功能,并就软件实现的关键技术展开了论述。
Hydroelectric generating sets are large apparatus, which converts hydraulic energy into electric power, and their running conditions determine whether the hydro-plant can supply electric power safely and economically. During the past century, the servicing system based on statistics theory carries out the minor repair, medium repair and heavy repair at the regular intervals has the shortcomings of superfluous or lacking repair generally. Especially with the hydroelectric enerating set becoming more and larger, the shortcomings are more obviously. Therefore, the effective system of state monitoring and fault diagnose for HGS, to improve the repair pertinence and enhance the security and reliability of HGS, not only have important effect to power industry and but also to entire national economy.
This dissertation illustrates the importance of turbine generator unit fault diagnosis, and analysis the existing research states and developing trend of fault diagnosis as well as the application prospect of fault diagnosis in details. Based on introducing condition monitoring and diagnose system for hydroelectric generator set, several commonly methods for fault diagnostic are discussed, and a fuzzy expert system model is established which is used in fault diagnosis of turbine generator units, which combines the AI technology and fault diagnose technology to realize the precise fault diagnose. Based on the characters of hydroelectric generating vibration, it puts forward a mix intelligence diagnose based on fuzzy logic, neutral network and expert system. This paper gives a hydroelectric generating fault diagnose expert system based on fuzzy neutral network and stimulants its rationality and operational. It achieves the software development of hydroelectric generating fault diagnosis and online monition to impellents data collecting and signal analysis, on-line status monition, vibrating analysis and fault diagnose and study the key technologies.
引文
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