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Introducing the meaning, research status, and developing trend of the Mine Ventilator fault diagnosis, and analyzing the vibration and fault mechanics of Ventilator etc. Expert System (ES) and Neural Network (NN), the most rapidly developing branches of Artificial Intelligence, are playing more and more important roles in some fields with the technical development of calculator. There are some shortages of knowledge acquisition and inefficiency in ES, and explanation function in NN. So, this thesis combines ES with NN to cover the shortages. In this thesis, studying Ventilator Fault Diagnosis Combined Expert System, analyzing the structure and method of ES, studying modified BP algorithmic, taking CLIPS as inner core and combining it with NN to construct Ventilator Fault Diagnosis Expert System on the base of the vibration and fault characteristics of Ventilator, and realizing ventilator’s intelligence diagnosis.
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