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

For the incipient fault diagnosis in complex industrial processes, a fault diagnosis method is proposed based on data preprocessing and reconstructed contribution plot. In order to overcome the influence of non-Gaussian distribution data on the accuracy of fault detection, the original sample data is preprocessed based on the data change rate, and the principal component analysis model for fault diagnosis is established. In order to improve the accuracy of fault identification, an average residual difference reconstructed contribution plot is used to identify the fault. Through the projection of normal sample data and fault data in the residual subspace, the residual difference vector is obtained and the reconstruction contribution value is calculated. The simulation results of fault diagnosis on Tennessee-Eastman (TE) process show that the proposed method has good diagnostic performance.