The Application Research Of Fuzzy Clustering Diagnose For Transformer In Neijiang Power System

Transformer is one of the pivot equipment of power system, its reliability of operation has a direct influence on the safely function of the whole power system. In order to ensure the stability of the power system, we must enhance the monitor and diagnosis towards transformer. On the base of investigation the status of the on-line monitoring technology .of gases dissolved in transformer oil at home and abroad, and analysis of the elements that can affect the generally experimental results of dissolved gases and the diagnoses technology. The conclusion that dissolved gases in gas composition and content of transformer could embody the inside of the transformer's situation about "the insulation fault effectively is concluded.In the research of power equipment fault diagnosis based dissolved gases in transformer oil, the fault type increase clearly with the fault development. Traditional way is inability to faults diagnose of electrical equipment such as transformer that the fault reason, phenomenon and principle are indeterminacy etc. This paper takes the dissolved gases in gas as the characteristic quantity, according to the relationship between the component of the dissolved gases in oil and the category of transformer's fault, makes use of the thoughts of fuzzy mathematics, raise a fuzzy clustering theory which takes the dissolved gases in gas as the characteristic quantity, use to diagnose the inside insulation fault of transformer.Through instance analysis of fuzzy clustering diagnose which the characteristics is dissolved gases analysis and it's practical application analysis on transformers of NeiJiang power station, the diagnose result of transformer fault using fuzzy clustering theory and the result of hanging core check almost correspondence match, diagnose result has better accuracy. Through the case study during the operation on spot, it proved the effective of this method:...