A Knowledge-Based Diagnosis System for Automobile Engines
Zheng Xiaojun, Yang Shuzi, Zhou Anfa, Hanmin Shi · 2005
A newly developed knowledge-based diagnosis system for automobile engines is described in this paper. The system is based on the Hierarchy Diagnostic Principle, suggested by the authors [1]. On this principle, a complex diagnostic task can be divided into several simple ones and then solved step by step. Both deep and shallow knowledge are used in the system, and or- ganized in two different knowledge bases: (1) a static knowledge base, which uses frames to describe the structure, symptom and fault information of the system to be diagnosed; (2) a dynamic knowledge base, which uses production rules and special functions to describe various dynamic information for diagnosing the locations and causes of a system fault. The system employs a hierarchy and portioning architecture which has two levels; a meta-level and a object level. The knowledge base of the object-level system, according to the fault types and structure hierarchy of the system to be diagnosed, is divided into several independent knowledge sources which are controlled by the meta-level system. The knowledge sources communicate with each other through a working memory called "black-board".