Qualitative Fault Detection and Hazard Analysis Based on Signed Directed Graphs for Large-Scale Complex Systems

Abstract

Nowadays in modern industries, the scale and complexity of process systems are increased continuously. These systems are subject to low productivity, system faults or even hazards because of various conditions such as mis-operation, equipment quality change, external disturbance, and control system failure. In these systems, many elements are interacted, so a local fault can be propagated and probably spread to a wide range. Thus it is of great importance to find the possible root causes and consequences according to the current symptom promptly. Compared with the classic fault detection for local systems, the fault detection for large-scale complex systems concerns more about the fault propagation in the overall systems. And this demand is much close to hazard analysis for the system risks, which is a kind of qualitative analysis in most cases prior to quantitative analysis. The signed directed graph (SDG) model is a kind of qualitative graphical models to describe the process variables and their cause-effect relations in continuous systems, denoting the process variables as nodes while causal relations as directed arcs. The signs of nodes and arc correspond to variable deviations and causal directions individually. The SDG obtained by flowsheets, empirical knowledge and mathematical models is an expression of deep knowledge. Based on the graph search, fault propagation paths can be obtained and thus certainly be helpful for the analysis of root causes and sequences (Yang & Xiao, 2005a). And with development of the computer-aided technology, graph theory has been implemented successfully by some graph editors, some of which, like Graphviz (2009), can transform text description into graphs easily. Hence the SDG technology can be easily combined with the other design, analysis and management tools. The SDG definition and its application in fault diagnosis were firstly presented by Iri et al. (1979). Ever since then, many scholars have contributed to this area, including modeling, inference, software development and applications. Many efforts have been particularly made to implement the methods and to overcome the disadvantages, such as spurious solutions. Here we recognize some representatives among them. Kramer & Palowitch (1987) 3