国产欧美精品一区二区,中文字幕专区在线亚洲,国产精品美女网站在线观看,艾秋果冻传媒2021精品,在线免费一区二区,久久久久久青草大香综合精品,日韩美aaa特级毛片,欧美成人精品午夜免费影视

Insulated Gate Bipolar Transistor (IGBT) and other electronic components are widely used in the transport and energy sector, its health status for equipment safety and effectiveness is essential. Based on the analysis of the structure and failure mechanism of the IGBT, the peak of the collector-transmitter voltage is selected as the failure characteristic parameter combining with the accelerated degradation experiment data from NASA Ames Center. Then a prediction method based on the Deep Belief Network (DBN) is proposed for the analysis and prediction of the trend of the IGBT. Comparing with the Levenberg-Marquardt (LM) algorithm model, the experimental results show that the proposed three hidden layer DBN model has better prediction performance and higher prediction accuracy than LM model.