The Design And Implement On Expert System Of Fault Diagnosis For Ventilator Rotating Machine

Nowadays, fault diagnosis of rotating machine is one of the quickly developed emerging technologies at home and abroad. Research and application on monitoring and analyzing system of the large rotating machine is significant to avoid substantive economic loss and disastrous accident. Expert system is a branch of artificial intelligence. Actually, it is a computer software system based on knowledge, owning much expert's knowledge and experience in one field and using knowledge like expert to make intelligent decision by reasoning. Expert system can diagnose fault of the large rotating machine more accurate, promote change of maintenance way from prevention to forecast and extend machine's life. It creates a great societal and economical benefit.In this paper, ventilator rotating machine is the object of research, and the basic theorem for expert system of fault diagnosis to ventilator rotating machine is researched. Combining fisher's discriminant analysis, rough set, fuzzy and ant algorithm, technology of knowledge auto-reason has been presented, which can change the traditional fault diagnosis expert system for ventilator machine to automatic diagnosis.The system of ventilator fault diagnosis has been presented that includes two parts: the fore is an online simple monitor and the end is an expert system of automatic diagnosis. The implementation of online simple monitor contains fisher's discriminant analysis and other monitor technology; the expert system of automatic diagnosis uses rough set, characteristic knowledge, fuzzy and ant algorithm. Finally, the actual data is applied to test the expert system of fault auto-diagnosis. The result is that the expert system of fault auto-diagnosis can discriminate ventilator machine in good state from bad state and explain the reason of fault.