Small fault detection method of instruments based on independent component subspace algorithm and ensemble strategy

Abstract

To solve the problem of small fault detection of instruments in process industry,independent components were extracted by Independent Component Analysis(ICA) from instruments recorded data.And independent component subspaces were established according to the contribution matrix.Fault detection model was constructed in each independent component subspace with statistical variables.A proper ensemble strategy was chosen by combining all the fault detection results.Finally,the instrument with fault was located by contribution algorithm.The simulation results with TE(Tennessee Eastman) process show that this method has higher precision on small fault detection and more flexibility with proper ensemble strategy.