Research on Intelligent Fault Diagnosis Model for Complicated Equipment

摘要

Through studying intelligent fault diagnosis methods, an intelligent fault diagnosis model is proposed for complicated equipments. The model is composed of two modules: data module and knowledge module. The data module includes data acquisition, the valid information extraction and data memory three parts. In data module, neural network information fusion method is adopted to acquire, extract and analyze fault feature information. Knowledge representation, knowledge using and knowledge acquirement are banded together organically by knowledge module. Utilize fuzzy logic and expert system as executive institution of diagnosis adjudging to diagnose cause of equipment fault and to evaluate the equipment running situation. The improved learning mechanism is used to improve the capability of system. The investigation shows that the model is tried and flexibility. It provides a new method to intelligent fault diagnosis and has important meaning of realism, theories and stratagem for equipment guarantee.