A study on fault diagnosis for chemical processes using hybrid approach of quantitative and qualitative method

정성적, 정량적 기법의 혼합 전략을 통한 화학공정의 이상진단에 관한 연구

This paper presents a fault detection and diagnosis methodologies based on weighted symptom model and pattern matching between the coming fault propagation trend and the simulated one. At the first step, backward chaining is used to find the possible cause candidates for the faults. The weighted symptom model(WSM) is used to generate those candidates. The weight is determined from dynamic simulation. Using WSMs, the methodology can generate the cause candidates and rank them according to the probability. Secondly, the fault propagation trends identified from the partial or complete sequence of measurements are compared to the standard fault propagation trends stored a priori. A pattern matching algorithm based on a number of triangular episodes is used to effectively match those trends. The standard trends have been generated using dynamic simulation and stored a priori. The proposed methodology has been illustrated using two case studies and showed satisfactory diagnostic resolution.