免费看大片a-亚洲精品中文字幕乱码三区91-久久久在线视频-中文字幕免费高清在线观看-狼人狠狠干-www婷婷-欧美第一视频-国产中文字字幕乱码无限-色呦呦在线播放-男女羞羞无遮挡-成人男女视频-久久传媒-久久草精品-久久久精品综合-国产免费二区-四虎影院一区二区-国产操人-操操操爽爽爽-色就是色网站-久久77777-神马伦理影视-91手机在线看片-黄视频国产-中文字幕第100页-视频免费1区二区三区

    Abstract: Accurate prediction of the residual electrical life of AC contactors is of great significance in ensuring the safety of the electrical system. Through accelerated electrical lifetime testing of AC contactors, completing electrical lifespan data of test samples were acquired.Wavelet transform method was employed to determine the starting and ending moments of arcing in the breaking phase of an AC contactor,and the arcing time, arcing energy and average arcing power in the time domain of the arcing signal were calculated accordingly. Extracting root mean square, standard deviation, skewness, and form factor feature parameters in the statistical domain, and then the fusion of the time domain and statistical domain feature parameters during arcing is selected by the method of mutual information, and the voltage standard deviation,voltage root mean square, average arcing power, and the arcing energy feature parameters are selected and used as inputs to the gate recurrent unit(GRU), temporal convolutional network(TCN), improved TCN prediction models to complete the prediction task. By comparing the fitting degree of the prediction results of the three models with the actual electric lifetime values of AC contactors and the evaluation indexes of the prediction results, it is obtained that the prediction results of the improved TCN model have a higher fitting degree with the actual electric life values, higher prediction accuracy, and the best performance among the three models.

    Key words: AC contactor; electrical lifetime; wavelet transform; improved TCN model; mutual information