Turbine Generator Unit Vibration Monitoring And Fault Diagnosis

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.