Logistic chaotic detection algorithm for bird damage tripping probability of 10kV distribution lines

Bird damage trip data may contain a lot of noise and outliers, which requires the detection algorithm to have strong data processing ability to accurately extract useful information from complex data. However, current detection algorithms may need to be improved in terms of data processing capabilities. Therefore, the Logistic chaotic detection algorithm of bird damage tripping probability of 10kV distribution line is designed. The fault current of 10kV distribution line is extracted, and the hierarchical model of bird hazard risk assessment based on geographical characteristics and tower structure characteristics is established. By using Logistic chaotic time series, the abnormal data component is extracted to realize the detection of bird damage tripping probability of 10kV distribution line. The experimental results show that the predicted results of the design method fit the real situation, the average relative error is reduced by 10%, and the average detection time is gradually reduced from 0.71 seconds in 10 iterations to 0.48 seconds in 50 iterations.