Abstract
It is difficult to use a single diagnosis theory or method to monitor and diagnose the whole condition of a large complicated system. To realize real-time condition monitoring and fault diagnosis of a large automatic production line in a steel factory, according to the structure and fault diagnosis characteristics of the production line system, a hybrid fault diagnosis expert system based on knowledge and neural network has been researched and built. This paper introduces the basic composition of the hybrid expert system, and gives the rule examples of the expert system based on knowledge, and emphatically introduces knowledge expression and knowledge acquisition and fault diagnosis inference of the fault diagnosis expert system based on neural network. Finally, fault diagnosis examples based on neural network are given. Research results show that a hybrid expert system is very effective to monitor and diagnose a large complicated modern production process.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
