Electrical Ejection Engine Fault Diagnosis Expert System Based On Artificial Intelligence

Expert system is a branch of artificial intelligence, which is most active, has board application prospects. It can resolve the engineering problem which is reasoning and complicated. While expert system is applied to the automobile electrical fuel injection engine fault diagnosis, we can make use of the experiential knowledge of the diagnostician enough, and therefore could improve efficiency.For increasing complexion in the automobile electrical fuel injection engine fault diagnosis, this system collected much knowledge and experience in maintain field. It simulates expert actual operation in the process of diagnosing the automobile electrical fuel injection engine fault. This system combined the data structure of the fault tree and the principle of relationship database to complete the express of knowledge. The knowledge base was built and the inference engine of ascertain fault diagnose was realized. The automobile electrical fuel injection engine fault diagnosis expert system was developed on the platform of Visual C++ and Access 2000. The main function of the system includes: fault code diagnosing function, fault phenomena diagnosing function, sensor diagnosing function, oscilloscope diagnosing function, data maintenace function and experience diagnosing function. This system adopts the means of modularization. The knowledge database built in this way can be expanded in future. The system knowledge can be expanded by increasing function module, and so it is helpful for maintenance engineer to can maintain electrical ejection engine fault orientation and diagnose conveniently, quickly and truly. Therefore, the system can improve the efficiency, increase the reliability and reduce the cost of maintenance.This paper mainly focuses on the creation of knowledge base, production rule based diagnosis mechanism. With the basic technology, such as artificial intelligence, database and software engineering, a target system comes into being in reality. It can solve the practical issues intelligently in fault diagnosing. Therefore, it is valuable in both theoretical field and engineering field.