Robust fault diagnosis based on clustered symptom trees

Abstract This study suggests a new methodology for fault diagnosis, based on the signed digraph (SDG), in developing the fault-diagnostic system of a boiler plant. The suggested methodology uses a new model, the clustered symptom tree (CST). The CST utilizes the advantage of the SDG to represent the causal relationship between process variables and/or the propagation paths of faults in a simple and graphical way, and is therefore easy to understand. It also covers the problems, such as symptom variation, that conventional SDG-based methods cannot handle. The advantages of the presented method were confirmed through case studies.