Signed Directed Graph and Qualitative Trend Analysis Based Fault Diagnosis in Chemical Industry

In the past 30 years, signed directed graph (SDG), one of the qualitative simulation technologies, has been widely applied for chemical fault diagnosis. However, SDG based fault diagnosis, as any other qualitative method, has poor diagnostic resolution. In this paper, a new method that combines SDG with qualitative trend analysis (QTA) is presented to improve the resolution. In the method, a bidirectional inference algorithm based on assumption and verification is used to find all the possible fault causes and their corresponding consistent paths in the SDG model. Then an improved QTA algorithm is used to extract and analyze the trends of nodes on the consistent paths found in the previous step. New consistency rules based on qualitative trends are used to find the real causes from the candidate causes. The resolution can be improved. This method combines the completeness feature of SDG with the good diagnostic resolution feature of QTA. The implementation of SDG-QTA based fault diagnosis is done using the integrated SDG modeling, inference and post-processing software platform. Its application is illustrated on an atmospheric distillation tower unit of a simulation platform. The result shows its good applicability and efficiency.