Fault Isolation of Nonlinear Processes Based on Fault Directions and Features

In this brief, a new fault isolation method is proposed. The disadvantages of the conventional contribution plot method are: 1) the fault cannot be identified accurately due to process control and recycle loops in process flowsheets. To overcome this disadvantage, the fault-relevant-independent components (ICs) are extracted in this brief, which clearly represent different fault feature and 2) the conventional fault identification method is not available for the nonlinear process. In this brief, the nonlinear fault direction information is extracted. Then, the fault isolation method in the nonlinear process is proposed, where the historical fault information is used to build the model. The proposed method is applied to a simple nonlinear process and the electro-fused magnesia process. Compared with IC analysis (ICA) method and kernel ICA method, the results clearly show the effectiveness of the proposed method.