Fault diagnosis based on granular matrix-SDG and its application

Abstract

The hierarchical fault diagnosis based on granular matrix and Signed Directed Graph (SDG) is presented in the paper. Granular Computing (GrC) theory can be introduced into SDG-based fault diagnosis to optimize the decision table. The rules of fault diagnosis are reasoned out through searching the associated path of the SDG model. The redundant nodes of the failure diagnosis rules are reduced by the attribute reduction algorithm based on granular matrix, which can simplify the solution of failure diagnosis, avoid the setting of the redundant sensor, and decrease the complexity of collocating sensor network. Compared with the traditional failure diagnosis based on SDG, the designed scheme and an experimental example of a hot nitric acid cooling failure diagnosis system show that the hierarchical fault diagnosis based on granular matrix and SDG in the paper is not only feasibly and effectively, but also valuable in practice.