The goal of this research project is to develop computer algorithms that can detect and interpret faults in operating chemical plants, to be used by plant personnel making operating decisions during plant upsets. Expert systems will be developed which allow the accumulated experience, judgment, and heuristics of process engineers and operators to be incorporated into an automated reasoning system. The expert system would apply this knowledge in real time by accessing plant measurements through the process control computer. This system will be designed in modular form so that complex plants can be decomposed and computer logic for individual units be developed separately (and recombined in subsequent iterations). The specific problems that will be addressed in this project include: (1) theoretical development of new algorithms for disturbance location and discrimination which account for realistic factors such as noisy and time-varying data; (2) the development of a theory and methodology of diagnosis based on uncertain reasoning techniques, to replace the current theory based on Boolean logic; (3) research on expert system architectures for integration of heuristic and model-based inferences; (4) basic research leading to development of guidelines for optimal process instrumentation to increase the effectiveness of the new diagnostic systems; (5) a theoretical study of qualitative fault simulation to provide accurate qualitative predictions of the effects of malfunctions on plant operations; and (6) the implementation of theoretical ideas in more complex and realistic simulations, to test methodology, and to give further insight on how to improve and extend the current diagnostic system.

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Massachusetts Institute of Technology
United States
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