Fault diagnosis knowledge acquiring system

Abstract

The invention discloses a fault diagnosis knowledge acquiring system, which comprises a semi-automatic knowledge acquiring module, an automatic knowledge acquiring module, an automatic knowledge base maintaining module, a knowledge base, a fault tree information base and a case base. The automatic knowledge acquiring module summarizes and concludes a new rule from a large number of cases stored in the case base according to the rough set theory and stores the acquired rule in the knowledge base, thus realizing automatic expansion of the knowledge base. The automatic knowledge base maintainingmodule realizes a function of automatically maintaining the knowledge base by using the character set closure and rule implication method, and the functional module can perform redundancy and circulation rule check on a rule base and provide the check result to the domain experts for judgment and processing. The invention acquires the known knowledge by using a fault tree, thereby not only indicating the logic relation in knowledge but also providing convenience for the user to maintain.

Description

technical field [0001] The invention belongs to the field of artificial intelligence, and relates to fault diagnosis technology, knowledge acquisition technology, fault tree technology, rough set theory, and fault diagnosis knowledge acquisition technology. Specifically, it refers to a fault diagnosis knowledge acquisition system. Background technique [0002] Fault diagnosis technology has become an important means to ensure the safe and reliable operation of equipment. At the same time, fault diagnosis methods based on expert systems have been widely used, but the acquisition of complete diagnostic knowledge is the bottleneck of fault diagnosis expert systems. The knowledge of fault diagnosis expert system can be divided into two categories, one is known knowledge, such as expert experience, maintenance manual knowledge, etc.; the other is new knowledge that needs to be summarized and induced in the system's own operation practice. For the known knowledge, it is necessary ...

AI Technical Summary

Problems solved by technology

In this way, with the expansion of the knowledge base of the expert system and the increasing number of rules, there may be problems such as redundancy and circulation among the rules, which will inevitably affect the diagnosis process of the expert system and reduce the performance of the expert system.

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