Research And Application On Intelligent Diagnosis Of Abnormalities About Working Case Of Copper Refining Furnace

Copper refining process in copper refining furnace involves chemical reactions, fluid flow and transmission of both heat and mass. It is characterized by properties such as multi-variables and non-linear, couple changes with great inertia. Therefore, the abnormities of copper refining furnace sometimes happen. A good abnormity diagnosis expert system can realize the abnormity diagnosis of c copper refining furnace and give an alarm based on its status messages, which will be useful for operation personnel to do corresponding measurements that will enhance the dependability and security of copper refining furnace and competition capacity of the production in the world.In order to realize diagnosis of abnormities or potential abnormities about copper refining furnace fleetly and high effectively, in this paper, abnormity diagnosis expert system about work case of copper refining process was designed based on fuzzy theory and expert system technology, and main works and innovations are expressed as follows:(1) Some operation parameters of copper refining furnace were analyzed theoretically and simulated, which offers a solid base for the abnormity diagnosis expert system to select some key operation parameters;(2) Abnormity diagnosis characteristic of copper refining furnace were analyzed, the working state parameters of copper refining furnace were manipulated by the fuzzy theory;(3) The abnormity diagnosis knowledge of copper refining furnace was expressed by synthetic knowledge method, knowledge base with more bases and more classes was organized, furthermore, a series of measurements about management and maintenance was adopted, which establish a solid base that is benefit for the abnormity diagnosis expert systems with high efficiency quick reasoning and diagnosing.(4) Due to assumed abnormity aggregate educed from a new fuzzy diagnosis model, the inference strategy was designed based on the hybrid reasoning mechanism with backward reasoning of the abnormity type diagnosis and forward reasoning of the factors giving rise to abnormity and eliminating its measures.(5) An uncertainty reasoning method and a fuzzy matching strategy were put...