Power distribution switch mechanical fault feature extraction method based on CEEMDAN and weighted time-frequency entropy

The invention relates to the technical field of power distribution networks, and specifically relates to a power distribution switch mechanical fault feature extraction method based on CEEMDAN and weighted time-frequency entropy. The method comprises the following steps of: step 1, acquiring a vibration signal through an acceleration or speed signal data acquisition system; step 2, decomposing thevibration signal through a CEEMDAN method to obtain IMF components of each order of the vibration signal; step 3, obtaining instantaneous frequencies respectively corresponding to each order of IMF components through Hilbert transformation; step 4, carrying out equal frequency band division on the IMF component through a band-pass filtering method in combination with the instantaneous frequency to construct a time-frequency matrix with a specified bandwidth; and step 5, performing equal interval division on the time-frequency matrix in the time domain direction to obtain a block time-frequency matrix, and solving the