Research On The Integrated Compressor Intelligent Fault Diagnosis Expert System Based On RBR And CBR

The article analyzes the characteristic and limitation of the applied fault diagnosis method. Based on that, a new integrated diagnosis method based on RBR (rule-based reasoning) and CBR (case-based reasoning) is presented in this paper. The design plan, integrated mechanism and key technology of the integrated diagnosis method have been developed.A Rough sets data mining method for rule acquisition is selected to over come the shortages of some knowledge attaining methods existed before. The basic algorithm is improved by using attribute reduction and heuristic value reduction, which can simplify the calculation and enhance the efficiency of seeking the reduction in some extent. Rough sets theory can gathers the existing diagnoses data and obtains the diagnosis rule efficiently and quickly through handle incomplete and inconsistent data availably.According to the demand of fault diagnosis expert system and the characteristic of compressor fault diagnosis, the compressor fault case is classified by characteristic and detail on the foundation of characteristic-based case expression. The multi-layered structure of the case database of the system is formed in accordance with the structure of the key characteristic which is abstracted from fault cases. The strategy of layering index and characteristic classification have reduced the complexity of case expression, the management and construction of case database, it also have enhanced the index speed and efficiency dramatically.Based on the research above, this paper introduces an integrated fault diagnosis expert system integrated with rule-based reasoning and case-based reasoning. The integrated system can not only make use of the field knowledge but can take advantage of diagnose experience in the past, There by,it is mutually complementary to improve the accuracy and identification capability of the diagnosis System.