Fault diagnosis with between mode similarity analysis reconstruction for multimode processes

- Specific change of variables from one mode to another is gotten based on BMSA.
- Fault amplitude and fault directions of each subspace are calculated based on the relationship between fault data and normal data.
- The veracity of fault diagnosis is improved as the accurate calculation of fault amplitude and fault directions.

In this paper, a new approach on between mode similarity analysis (BMSA) reconstruction is proposed. Compared with the traditional method, similarity between different modes, higher-order and independent statistics are considered to separate independent subspaces, which contain increased subspace, decreased subspace, unchanged subspace and residual subspace. And further, the fault amplitude and fault directions are accurately extracted from the independent components to realize fault reconstruction, thus fault feature is highlighted, and the diagnosis performance is improved. Fault diagnosis indices are developed based on BMSA reconstruction for various fault alarms. The proposed method is applied to penicillin fermentation process, and is compared to traditional multiple modeling method. Experiment results show that the proposed method can more accurately diagnose fault than traditional multiple modeling method.