Dynamic Measurement Algorithm of Electrical Equipment Parameters Based on BP Neural Network

The field of large-scale measurement is gradually developing towards high precision and intelligence. The application of dynamic measurement error theory and technology helps to improve the measurement accuracy and reduce cost of large-scale metrology, and promote its development. Therefore, it is of great significance to study the separation and calibration technology of dynamic measurement errors. The main purpose of this paper is to study the dynamic measurement algorithm of electrical equipment parameters based on BP neural network. This paper mainly studies and analyzes the application of BP neural network model in dynamic measurement, and analyzes and researches the arrangement scheme of cooling fan in the same power station and the starting method of GSY cooling fan. In the experiment of simulation verification, summarizing the experimental results, it can be seen that the multi-point grounding method for the isolated-phase closed busbar of the IOOOMW generator set has significant advantages compared with the single-point grounding method in terms of safety and economy priority program.