Hybrid fault diagnosis based on model-based and case-based reasoning method

Model-Based diagnosis describing internal structure and behavior of a system is deep knowledge which can obtain the diagnosis knowledge easily, but the large amount of calculation is its disadvantage. Case-based reasoning diagnosis relies on historical experience and the diagnostic efficiency is relatively high, but knowledge acquisition is the bottleneck. Therefore, according to the advantages and disadvantages of the two methods, this paper proposes using the model-based approach to achieve the case knowledge acquisition, and then complete the process of fault diagnosis by case-based reasoning. This approach which can improve the diagnosis efficiency not only learned the advantages of high accuracy and avoided the difficult problem of knowledge acquisition but also inherited the high-speed characteristics of case-based reasoning.