Design of an Efficient Intelligent Instrument Fault Diagnosis Expert System

An efficient approach is proposed to develop the efficient expert system for intelligent instrument fault diagnosis. According to the characteristics of intelligent instrument faults, the hybrid inference method combined with the rule-based reasoning and the case-based reasoning is adopted. In the rule-based reasoning, a hierarchical search method is proposed, and the diagnostic priority of each rule in a specified search level is determined based on a fuzzy multi-attribute group decision making method. According to such an inference strategy, the knowledge base in this expert system is optimally designed in SQL Server database technology, and an efficient expert system for intelligent instrument fault diagnosis is developed in VS.Net. In actual use, the expert system shows higher diagnosis efficiency than its first version.