A novel first-principles-based diagnostic system called PRODIAG is proposed
for on-line detection and identification of faulty components during incip
ient off-normal process conditions. The concepts of qualitative physics rea
soning and function-oriented diagnostics are employed in the design of PROD
IAG and result in two unique capabilities not found in other plant-level di
agnostic systems. First, PRODIAG is fully portable as it requires only modi
fication of the input files containing the appropriate process schematics i
nformation to be able to diagnose single-component failures in different pr
ocesses/plants. Second, PRODIAG detects unanticipated faults. Hence, it doe
s not require the prespecification and formulation of rules to cover every
conceivable fault scenario, and unlike traditional approaches, it is nor li
kely to misdiagnose unforeseen events. PRODIAG's approach is to map process
symptoms Into component faults through a three-step mapping procedure with
a knowledge base containing three distinct types of information: qualitati
ve macroscopic balance equation rules, functional classification of process
components, and the process piping and instrumentation diagram. The concep
ts introduced in the proposed diagnostic system are described, and an illus
trative example shows how they are used in plant-level diagnostics.