Based On The Key Technologies Of Remote Diagnostics Of The Whole It

With the advancement of modern science and technology, the equipments tend to be larger, faster as well as more roboticized and complicated, which makes technology of state monitoring and fault diagnosis more and more important. But the traditional fault diagnosis of machinery is based on the analysis of the signal coming from single channel from which the character information about the machinery action is picked up. Although using individual information can reflect the machinery faults sometimes, in many instances the diagnosis result is irresponsible. Commonly the vibration information of one rotor's section is picked up from two radial sensors and a axes sensor,one section's channels belong to same dimension,so inevitably each other of them exists certain relation, accordingly these information fusion at data level through full information technology can farthest show the section's informations the diagnosis result sometimes is unilateral on the basis of rotor's one section. Therefore it is necessary to recognize faults according to the rotor's multi-sections information.Combining with the rotor space vibration and the field practical situation.and making use of the rotor two ends, The thesis founds a model of data level and character level and decision level mixture fusion,and the key techniques to realize the model are the full information and integration Probabilistic Neural Network. The thesis applys Full-spectrum and Holospectrum and Vector-spectrum to the diagnosis model,and compare the diagnosis result of the three methods,finally the conclusion is that the Vector-spectrum is the best of the full information.The Vector-spectrum of full information continues a series of analysis methods because of its good information processing way. The thesis discusses several important analysis methods to fault diagnosis: Vector power spectrum and Vector-cepstrum and Vector-Wigner that used to analysis stationary signals,and combines these methods width system model to diagnose faults as well as validates the methods veracity.After the rigorous study of the theory, using the C++ Builder5.0 as the developing tool, a full information fault diagnosis system was visualized, which based on the mode ofBrowser/Server and can run on the Internet. Also the full information and the Vector-spectrum's continued methods are visualized,and the diagnosis conclusion is exact and reliable.