Study On Monitoring And Fault Diagnosing Of Steam Turbine Generator Sets

With the rapid development of economy, power system in our country aims more and more at super high voltage, great capacity and multi-generator interlinking system. Large-scale generator units of 200MW, 300MW and above have dominated our country's power net, which consequently leads to the increasing demand of monitoring and malfunction diagnosis of Steam Turbine Generator of great capacity. For the complexity of equipment malfunction and the complexity of relations between equipment and omens of malfunction, multi malfunctions always arise simultaneously. However, the problem of multi malfunctions diagnosis has not been solved yet at present. Therefore, it is of great significance for the safe and stable running of generator units to study technologies of comprehensive malfunction diagnosis, and it is also a leading study in the field of electric engineering and other inter-disciplines. On the basis of summing up and referring to the studies on monitoring and malfunction diagnosing of Steam Turbine Generator Sets by other scholars, this dissertation puts stress on Temperature abnormity of vibration of steam turbine, Artificial Neural Network technology. Through testifying the above by some existing vibrating malfunctions in Steam Turbine Generator Sets, this dissertation has reached some valuable conclusions and achieved some reliable and practical approaches which enriches and promotes the development of the malfunction diagnosis theory of large-scale Steam Turbine Generator, The paper discussed malfunction diagnosis theory of Fuzzy Set Theory .Artificial Neural Network, Particle Swarm Optimize ,Genetic Algorithms...