Study On New Technology Of Fault Diagnosis For Electrical Equipment Based On Intelligence Information Fusion

Along with the scale of electric power system extends continuously and the amount of large transformer substation increases gradually, the electric equipment's request of reliability and technical level in the large transformer substation also rises increasingly. At present the national power company just generalizes energetically the electric power equipments'condition monitoring and reliability centered maintenance everywhere. The electric power equipments condition monitoring and fault diagnosis is to find fault rule by all kinds of technical method aimed at equipment's prophase and latency fault. The diagnosis of this kind of fault is one of investigative hot spot in electric power system. This problem and the fault judgment after instantaneous protect action are two aspects of one problem. The relay protection can't solve hidden and latency prophase fault. So it is important to study the electric power equipments'condition monitoring and fault diagnosis. The electrical equipments'condition monitoring and fault diagnosis is not only the base of condition maintenance pattern but also according with the demand that electric running pattern of unattended operation in transformer substation. It is needful to adding an on-line monitoring and diagnosis expert system as assistant decision-making means no matter what general transformer substation or unattended operation transformer substation. This can advance monitoring and controlling capacity. It is needful to add the electrical equipments'on-line monitoring and fault diagnosis in order to realize unattended operation indeed. In this way transformer substation synthesized automatization will be much more perfect and availability. So it will impel the transformer substation's synthesized automatization if we can fuse the electrical equipments'on-line monitoring and fault diagnosis based on synthesized automatization such as measure, control, signal, protection and so on. It is important to promote transformer substation's synthesized automatization level in China. The intelligentized technology applying in electrical equipments'fault diagnosis is expounded in this paper. The paper introduces the development history and present study condition of electrical equipments'fault diagnosis systematically. This paper also introduces the development trend of on-line monitoring in the future. Then studied and solved method has put forward in this paper. The main content to study is definite. The paper has broken the localization of normal fault diagnosis'method in order to solve the main technical problem in the electrical equipments'fault diagnosis. The different type math model and realized theory of transformer's insulated fault diagnosis applying neural network method are compared. All kinds of study arithmetic based on BP neural network have studied. The influence on network's constringency of different study arithmetic has compared detailed. Aimed at the shortcoming of BP network-hidden layer structure's uncertainty, the different hidden layer amounts have simulated in this paper. This paper has put forward fault diagnosis model and method based on radial basis function network, probabilistic neural network and learning vector quantization neural network. By compared the capability and nicety of different type neural network, the appropriate neural network model applying in transformer's fault diagnosis make sure. The paper has put forward a kind of fuzzy mathematical diagnosis method based on transformer insulated fault diagnosis in order to solve complicated relation of electrical equipments'fault omen and fault reason and fault mechanism. The fuzzy phenomenon subset and subjection degree function corresponding with different fault type are established. Thereby fuzzy synthesized judge of fault type carry on. Author has combined advantage and fuzzy reasoning method. It has overcome the problem of difficult to determine fuzzy regulation in transformer fault diagnosis. Making use of from the orientation nerve network of from study function, pass the study of the nerve network made sure the misty rule to belong to with faintness degree. ANFIS model of transformer fault diagnosis has established. This model has realized the electric power equipment fault diagnosis. It reflects actual running state of transformer. Author has established information fusion model applied in on-line monitoring and fault diagnosis according to information fusion principle. This paper has put forward the method of electric power equipment fault diagnosis applying D-S proof theories for the first time. D-S fusion model and method has fused neural network and fuzzy reasoning diagnosis result again. It makes diagnosed information more definite. It has improved diagnosis accuracy. Author has put forward the fault diagnosis method synthesized many artificial intelligence models such as the nerve network, fuzzy mathematics, adaptive neural fuzzy inference system and information fusion. Then many intelligence information fusion judgments are come into being to diagnose electric power equipment fault. The author has developed the fault diagnosis expert system in transformer substation leading the expert system into the electric power equipments'fault diagnosis. This paperhas described detailed the fault diagnosis expert system'repository and database. Then diagnosed example of breaker and transformer is given in the end. This paper has summarized actuality and development trend. Then the thought of many parameters integer design taken the transformer substation as on-line monitoring object has been put forward in this paper based on the request and object of electrical equipments'on-line monitoring in transformer substation. The concentrative on-line monitoring scheme aimed at large-scale and medium-sized transformer substation is designed. Moreover the structure of synthesized on-line monitoring system that can synthesize many types of electrical equipment such as transformer, breaker, mutual inductance and capacitance device and so on has expounded in this paper. This paper has finished the design of collectivity scheme and hardware circuit. The testing and debugging of hardware circuit has come through. The above research results are summarized finally. The further investigative direction is put forward in the end.