The invention provides a mutual
inductor operation and maintenance method based on an improved K-means
algorithm, and the method comprises the steps: collecting the
operation time and an
operation time ratio difference sequence of a mutual
inductor, calculating the reliability of the mutual
inductor through three-parameter Weibull distribution, and evaluating the stability of the mutual inductor through ADF statistics; the reliability and the stability are used as key indexes, a mutual inductor
data set is constructed,
kernel density estimation (KDE) and a
local outlier factor (LOF) are adopted to optimize initial cluster center selection of a K-means
algorithm, and particularly, by calculating a cluster center variation coefficient and a local reachable density, it is ensured that the
dispersity and the density of cluster center distribution are reasonable. After a mutual inductor
data set is subjected to clustering analysis through an improved K-means
algorithm, the reliability and stability mean value of each cluster is calculated, weights are given according to user requirements, comprehensive scores are calculated, and the comprehensive scores are divided into five grades to evaluate the state of the mutual inductor. And finally, different operation and maintenance strategies are made according to the
evaluation result, and the accuracy and reliability of the operation and maintenance of the mutual inductor are improved.