Fuzzy decision fusion system for fault classification with analytic hierarchy process approach

- A fuzzy decision fusion system is developed for the purpose of fault classification.
- The analytic hierarchy process (AHP) approach is introduced for model evaluation priority determination.
- Different weights are given for different classifiers in the model ensemble system.
- The superiority of the developed method is tested on a benchmark process.

Performance of the most existing fault detection and classification methods can only be guaranteed when each of their own assumptions are met. In other words, a method works well in one condition may not perform well in another. In this paper, a new analytic hierarchy process (AHP) based fuzzy decision fusion system is proposed to tackle the fault classification problem. The AHP approach is introduced to determine the priorities of different classifiers, which are further utilized as the weights in ensemble system. Comparing to conventional equal weighted fusion system, the proposed fuzzy fusion system is able to provide more rational and convincing fault classification result. Effectiveness of the proposed fuzzy fusion system with model evaluation is verified through the Tennessee Eastman (TE) benchmark process.