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Fault Monitoring Method Based on Mutual Information and Relative Principal Component Analysis

Due to the influence of dimension standardization in traditional PCA, each variable is in a relatively equal position and loses relative difference. While RPCA is able to solve the problem, it is not easy to calculate the weight for each variable. In order to solve it, in this paper, a kind of fault diagnosis method based on Mutual Information and Relative Principal Component Analysis (MI-RPCA) is proposed. Firstly, select the key variable of the device as quality variable. Secondly, calculate the mutual information between the process variable and the quality variable separately. Mutual information provides a general measure of dependence between two variables. And then, the proportion factor is determined by scaling the mutual information values between the variables. Finally, experiment on centrifugal compressor show that the proposed method performs better in fault detection compared with the traditional PCA method.