| In recent years, the intelligent fault diagnosis technology has become a hot spot in research of fault diagnosis. This technique mainly includes complex system (equipment, components) management, state monitoring and fault diagnosis. The goal of this technique is to build up the fault prevention and maintenance system, and it has been used widely in various fields. Intelligent technology makes the fault diagnosis more scientific, more reasonable, and more accurate. It greatly enriches the knowledge in the field of failure mechanisms. The intelligent fault diagnosis technology consists of expert system, fuzzy fault diagnosis, neural network, information fusion and petri net, etc.Currently, many mathematical methods and some reasoning method in expert system have reached a very high level in intelligent fault diagnosis technology, but there are some key issues need to be addressed, such as knowledge representation and reasoning, knowledge learning, intelligent identification, information fusion,etc. Intelligent fault diagnosis system combines the diagnosis theory and expert experience knowledge, and it is realized by the computer software programming. In the realization process of intelligent fault diagnosis system, the fault diagnosis expert is often not the developer, and the excellent software programmer is not fault diagnosis expert. So that, whether or not the intelligent diagnosis system reflects real expert intelligence, it determines the pros and cons of the system. And the promotion of the system, the application scope and effect are dependent on the clear and efficient diagnosis. Petri net has many characteristics, so that it not only can simply and conveniently represent expert knowledge, the organizational structure and the process of diagnosis, but also can optimize the expert knowledge and the reasoning rules. In addition, petri net can be easily combined with other techniques and theories, such as fuzzy reasoning, neural network and object-oriented programming etc. In short, petri net makes the fault diagnosis expert, the system developers and the users of the system closely related. It reflects the whole process from theory to intelligence, and then to application. This paper mainly studied the following aspects.Firstly, researches on the technology of petri net. The modeling method of petri net is researched based on the theory of petri net and the fuzzy production rules. Focused on the fault diagnosis reasoning strategy, such as graphics-based reasoning approach and matrix-operation-based reasoning approach. Integrated uses the extreme value method and the summation method to realize the application of graphics-based reasoning approach (graphics-based reverse reasoning approach) in fault diagnosis.Secondly, researches on the technology of intelligent petri net. Researched on the weighted fuzzy petri net and self-learning fuzzy petri net, analyzed the advantages and disadvantages, such as using the single BP neural network to train weights, thresholds and other parameters. The theory of neural network ensemble was introduced, then put forward a method combined with dynamic selective ensemble method and fault diagnosis petri net.Thirdly, researches on the optimization of PSO algorithm. Based on the optimization of PSO algorithm put forward a new improved PSO optimization algorithm. Researched on the fusion technology of PSO algorithm and neural network, then put forward a new integrated learning optimized method of neural network based on the improved PSO algorithm, and this method is applied to intelligent petri net.Lastly, designed and realized the remote intelligent fault diagnosis system based on petri net.It was used for fault diagnosis of steam turbine unit. Researched on some computer network technologies, such as data-shaping technology, data compression technology, data transmission technology and server-push technology, etc. These computer network technologies were used to solve practical problems, which are usually encountered during remote diagnosis. |
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