Process Fault Analysis using Digraph Method

Abstract

Fault detection in chemical processes and their isolation is becoming a pressing demand due to rising concerns regarding safety. An undetected fault can often get out of control and cause massive losses to an industry in terms of infrastructure and personnel. . When a fault is detected the next steps comprise of identifying the root of the fault, determining the extent to which the system functioning can be maintained despite the fault and to find a repair or solution to the fault. Traditional methods of fault diagnosis include real time analysis of faults or/and sequential testing procedures but none guarantee an early detection; thus confusion is inevitable in case of multiple faults. Due to these limitations, the digraph method of fault detection has been an area of interest lately. The foundations of this method are developed based on human reasoning and analytical skills and later the prepared model is validated with the help of simulation. The advantages of this method being the relative simplicity of the model to be referred in the case of a fault and the fast diagnosis of root of fault; this process has been applied to three processes in this paper and its effectiveness observed.
The three processes that have been studied are: Jacketed Continuous Stirred Tank Reactor, Binary Distillation Column and Drum Boiler. Mechanism of each process was studied in detail; their mathematical modelling was done for the purpose of simulation using MATLAB. Using the working principle of each process and theoretical knowledge, digraph was developed for each process. The variables were denoted by nodes and the relationship among them by continuous and dashed lines. Once the digraph was developed, simulation of each process was carried out and the results compared to the digraph in order to validate it.
The disadvantage of the digraph method is that fault detection is only qualitative which reduces the resolution of fault detection. Also a variable value may fluctuate due to the action of control loops giving compensatory variables (CV) or inverse variables (IV) and the fault diagnostic system should be efficient enough to monitor or predict such changes as well.