The Study Of Intelligent Fault Diagnosis Technology Based On Fuzzy Neural Network

In the field of engineering and technology,fault diagnosis technology has been playing an important role to ensure the proper functioning of equipment and the smooth conduct.Fault diagnosis technology for research and applications,which has not only theoretical value,but also a very obvious and direct economic benefits. Today,with the continuous development of science and technology,industrial equipment in production is in the increasingly large,complex,high-speed and automation.The equipment progress on the technology,on the one hand,increased production speed,efficiency,capacity and strength by a big margin,but on the other hand,increasing loss due to system downtime and failure also followed by a simultaneous.The restrained relationship has put forward higher requirements for the fault diagnosis and predicting technique,the traditional diagnostic methods have been unable to meet this demand.In this trend,along with the progress of computer technology and artificial intelligence technology,diagnostic techniques have been into the intelligent phase.Based on fuzzy theory and BP neural network which are more mature in the theory,in this paper fuzzy theory and BP neural network in the application of fault diagnosis are discussed and a smart fault diagnosis structure which by BP neural network mainly and fuzzy theory as a useful complement is presented.First of all, fault diagnosis system receives all kinds of operating parameters which are as input for the BP neural network after the fuzzication processing,and then takes full advantage of the trained neural network which has the capable of memory and association to identify the failures,and last get the final diagnosis results in the output layer.In this paper,firstly the development background of fault diagnosis is showed and the significance of fault diagnosis is explained and the development process and status in quo of fault diagnosis is analysed;then elaborate on the basic theory of artificial neural networks and focus on the BP neural network model which has a relatively well development in artificial neural networks;followed by a brief introduction of fuzzy theory and discussing the fuzzy theory and neural networks combined with the form of various and among which choose a simple and effective combination form for research;finally the compared simulation research of the example of fault diagnosis of marine diesel engine has illustrated the effectiveness of this method.