Automata generated test plans for fault diagnosis in sequential material- and energy-transfer operations

Hardware failures are inevitable random events that occur in the operation life of a batch chemical plant. Based on the piping and instrumentation diagram (P&ID) of the given process and the sequential function chart (SFC) of its normal operating procedure, a system automaton and the corresponding “diagnoser” can be built to identify all observable fault propagation traces and, also, their root cause(s). Since the fault origin(s) of a trace may not be unique, there is a need to develop a nonconventional means to further enhance diagnostic performance. For this purpose, a novel approach is proposed in this study to synthesize the test plan of every undiagnosable trace on the basis of discrete-event system (DES) theory. In particular, all components at the failure-induced initial states and the required control specifications are first modeled systematically with automata and, then, an optimal supervisor (test plan) can be assembled accordingly so as to achieve the operation goal of differentiating the fault origins as much as possible. This proposed strategy has been tested successfully in a series of examples and the results of selected case studies are reported in this paper.