| The water treatment technology possesses a broad knowledge, including both qualitative analysis and quantitative calculation. To satisfy different requirements of project and dealing with a problem specially, developing an expert system with basic but skilled knowledge of water treatment technology is necessary.In this work, we analyzed the structure and composition of an expert system as well as the development process, aiming at the actuality of the water treatment expert system. Based on the summarization of water treatment technology and the shortage of the present water treatment expert system, new water treatment knowledge content was re-stipulated and a new method to acquire the knowledge was proposed in this thesis. Furthermore, the production rules were employed to develop the water treatment knowledge base. The main data structure and the design ideas used to build the knowledge base and perform the implement of the inference process were introduced in detail. According to the uncertain characteristic of the water treatment factors, fuzzy rules and definite rules were compared with the method of fuzzy mathematics in the water treatment expert system. A fuzzy matching strategy and fuzzy reasoning method that could be employed in the field of water treatment were summarized.Vs.net and database design language were employed to develop the water treatment expert system, including membrane fouling diagnosis and consultation. The most correlated membership value could be obtained by comparing the membership functions value and the threshold value in the monitoring process. The accuracy of the system operation was proved by the specific tests.At last, the knowledge enrollment was found to have a direct impacted on the accuracy of the conclusion results. Thus, taking into account the survival of the expert system, the algorithm of the reasoning mechanism must be improved and the capacity of the knowledge base should be increased in the future.
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