Fault identification method of power network equipment based on fusion neural network model.

This paper studies a fault identification method and system of power grid equipment based on the fusion neural network model. The method includes: obtaining several power parameters representing the operation status of power grid equipment in the line of power grid equipment to be identified as eigenvalues and pre-processing; The pre-processed eigenvalues are input into the pre-established fusion neural network model to obtain the fault probability of the power grid equipment line to be identified. In view of the fact that the fault identification of power grid equipment is easily affected by the noise of signal transmission, this paper proposes a fault identification method and system of power grid equipment based on the fusion neural network model, which makes full use of the advantages of artificial intelligence, gives full play to the role of big data of power grid equipment operation, excavates the correlation between operation data and fault characteristics, and comprehensively diagnoses power grid equipment through multi-dimensional information, It can effectively reduce the impact of signal transmission noise or error on the accuracy of fault identification and improve the safety of power grid equipment operation.