Based On Neural Network Construction Machinery Hydraulic Fault Diagnosis Expert System

The hydraulic system has such advantages as small volume, light weight, big power, working steadily and stepless speed regulating on wide range, is widely used in the motive force, control and executive system of the engineering machinery. However, the ocular of hydraulic system's working condition is bad. It is difficult to obtain the parameter of hydraulic system. The fault of hydraulic system has pilosity nature, uncertainty and disguise. The fault sign and the fault reason of hydraulic system have complex non-linear mapping relations, therefore it cannot use the simple functional relation to describe. This has brought the difficulty for the classics fault diagnosis technology. The intelligent diagnosis technology base on ANN and ES can solove the above problem well and the diagnosis result is more accurate and reliable.This paper has analyzed that various diagnosis technology and method in hydraulic fault diagnosis fields. Aimed at the fault's characteristic of the hydraulic system, it has established the model and structure of hydraulic system fault diagnosis system based on ANNES. The system is made up by memory system of knowledge, studying system, reasoning machine, explaining device and human-computer interaction interface. This paper provides the detailed structure and establishing method of every part.ANNES has merged the advantage that the formidable adaptive learning ability of ANN and explicit knowledge expression of ES, simplified the process of ANN study data gaining and ES inference rule building. The working course of ANNES is: ?Establishes the knowledge library at first; ?At studying system obtaining knowledge, it only requires experts to offer example (or instance) and corresponding solving. The system uses the neural network studying algorithms to train samples. Throught adaptive algorithm of network, the system constantly revise right value's distribute so as to meet goal. Distribute the heuristic knowledge and the experience knowledge to network interconnection and right value. ?The reasoning machine carries on reasoning according to the knowledge that involve in knowledge base and fact that users offer. ?Through front computation of nerve network, the output port obtains the output vector. ?The explanation module of ES is explained to user.At last, this paper has realized grab hydraulic system based on ANNES intelligent diagnosis, it has proven this fault diagnosis method feasibility.