AN IMPLEMENTATION ARCHITECTURE OF KNOWLEDGE-BASED SYSTEM FOR ENGINE DIAGNOSIS

Abstract

Abstract The diagnostic task is a problem in which one is given a set of symptoms or manifestations observed from a diagnosed system and is required to find a parsimonious set of disorders in a given layer of the system. These disorders may produce (or explain) directly or indirectly (e.g., through disorder propagation) those symptoms by using his knowledge about the domain. The diagnostic problem solving for a complex system is proved to be particularly difficult because of the lack of efficient techniques on knowledge organization and knowledge integration at present for the problem. In this paper we address issues of expertise models and present a novel strategy for integrating multiple knowledge sources in the diagnostic problem solving of complex systems. More importantly, a Knowledge-Based System for Engine Diagnosis (KBSED) is introduced in this article. The KBSED is a knowledge-based information-processing system, integrating fault diagnosis, state detection, and recognition, with repair consultation for automobile engines without whole-block disassembly. An implementation architecture for this system is described, including hierarchical diagnosis, knowledge exploitation, knowledge control structure, and other techniques related to the diagnosis. Finally, the system structure and function of KBSED is described in detail.