Nonlinear Diversified Processes Monitoring

Abstract EN

The paper proposed a new method to classify and establish the monitoring model for diversified processes data with multiscale.

The advantages of the proposed approach are listed as follows.

(1) The issues of diversified processes data with multiscale are considered and the fault monitoring effect is enhanced.

(2) From a new perspective, the common and specific characteristic subspaces are extracted to help simplify the structure of the monitoring model.

(3) It makes the correlation between the common subspace itself and input-output dataset of each mode as close as possible.

The effect of the proposed method has been shown in the Experiment Results section.