Study On The Intelligent Diagnosis System Of Mechanical Equipment Fault

With the development of science and technology, mechanical equipment is having the tendency of large scale, serialization, high-speed, light-duty, centralization, automation, big power and big load. This not only enhances the productivity but also reduces the cost. But once the machinery fault happened, the loss is large. There were disastrous accidents and casualties and the influence are large. So on one hand, the higher need is put forward in speed, content, efficiency, safe side of rotating machinery, on the other hand, it is important to develop advanced state inspect and diagnosis technology.In this thesis, the rotor system of rotating machine and the motor are studied. The development of mechanical fault diagnosis technology and the research overview, research goal and research significance of intelligent fault diagnosis technology used in the field of equipment are described and the shortcomings of it are discussed. The fault diagnosis mechanism, fault types and diagnosis methods of equipment are also discussed. The methods of intelligent fault diagnosis based on knowledge and intelligent fault diagnosis based on neural networks are discussed, too. And the intelligent diagnosis system of mechanical equipment fault is completed by the integrated programme method based on Visual Basic, Matlab and Access and run with example.The intelligent diagnosis system of mechanical equipment fault has four subsystems including rotating machine fault diagnosis system, motor fault diagnosis system, bearing fault diagnosis system and reciprocating machine fault diagnosis system. In this thesis, establishing the first two systems is main study work, and the establishing processes are discussed. In the rotating machine fault diagnosis system, the intelligent fault diagnosis methods based on knowledge and based on neural networks are available, and they are independent, also interactive. The diagnosis system is a visual system, has visual interfaces. The fault type, causing reason and the measure of solving problem can be gained by the rotating machinediagnosis system with one of the intelligent fault diagnosis methods based on knowledge and based on neural networks or together. And the motor fault diagnosis system, it is established with different diagnosis methods. And the different tree-like knowledge bases are built with it. And the expert system is established, too.In this thesis, the rotating machine fault diagnosis system and the motor fault diagnosis system of the intelligent diagnosis system of mechanical equipment fault are validated by cases.