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钢铁企业生产过程复杂、生产工艺繁琐、生产设备众多。生产设备一旦出现故障就会影响企业的经济效益,如何实现低成本、高效率的故障检测是每家钢铁企业函待解决的难题。人工智能技术发展迅速,广泛的应用到钢铁企业设备故障的检测中来,特别是专家系统、神经网络和模糊集理论。本文在分析人工智能检测设备故障必要性基础上,详细论述专家系统、神经网络和模糊集理论在钢铁企业设备故障中的应用现状。
The steel production process is complicated, the production process is cumbersome, and the production equipment is numerous. Once the production equipment failure will affect the economic efficiency of enterprises, how to achieve low-cost, high efficiency fault detection is what each steel company to be addressed to solve the problem. The rapid development of artificial intelligence technology, widely used in the detection of equipment failures in steel enterprises, especially the expert system, neural network and fuzzy set theory. Based on the analysis of the necessity of artificial intelligence detection equipment failure, this paper discusses in detail the application status of expert system, neural network and fuzzy set theory in the equipment failure of steel enterprises.