Stochastic qualitative reasoning and its application to diagnosis of air conditioning system

The simulation technique on qualitative models is one of the powerful tools for the fault diagnosis. However, since a qualitative model is expressed with simple causal relations, enormous number of behaviors are possible even pruning off improbable behaviors by some real measured values patterns. Therefore, it is hard to apply it to practical scale system as it is. To cope with this problem, a stochastic qualitative reasoning is proposed in this paper. In this method, all of the behaviors have existence probabilities. The behaviors with relatively small probability are eliminated. We have applied this method to diagnosis of the air conditioning system. If a trouble is reported, the qualitative models of the target system in normal and failure are simulated and compared with the real measured values in the target plant. Agreement degrees with the model and the measured values are calculated with existence probabilities, and the cause of failure is found out. Through this application, we have confirmed the effectiveness of the method.<
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