基于SPM的多变量连续过程在线故障预测方法

Fault prediction for a class of unknown-model multivariate continuous processes with a hidden fault was studied,and a solution was given based on statistical process monitoring(SPM)approach.A principle component analysis(PCA)model using sample data under normal state was built,then the characteristic value for fault prediction was constructed,and time series analysis and prediction were applied to the characteristic value to predict the remaining useful life(RUL)of the system.Aiming at the linear time invariant system,a characteristic value was proposed and the prediction error of RUL was analyzed under some assumptions for system structure and hidden fault.A case study on a CSTR showed the efficiency of the proposed approach.