关键词:

故障诊断, 化工过程, 主成分分析法, 人工免疫系统, 混合系统

Abstract:

Fault diagnosis is an important method to insure the safety and stability of chemical processes.Principle component analysis (PCA), one of the typical diagnostic methods, has been widely used in various chemical fault detections.However, PCA is not good at fault diagnosis of complex chemical processes.Artificial immune system (AIS) is an adaptive system inspired by theoretical immunology and observes immune functions, principles and models.Based on the principles of self/non-self discrimination in the immune system, fault diagnosis by using AIS is feasible.The ability of self-learning and self-adaptation makes AIS able to evolve during the online applications.A hybrid diagnostic system combining PCA and AIS was proposed in this paper for early fault diagnosis of chemical processes.A dynamic chemical simulation model was built with Honeywell’s UniSim platform, and the efficiency of the diagnostic system was validated.

Key words:

故障诊断, 化工过程, 主成分分析法, 人工免疫系统, 混合系统