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A process monitoring system based on the Kohonen self-organizing maps

机译:基于Kohonen自组织图的过程监控系统

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Process monitoring and fault diagnosis have been studied widely in recent years, and the number of industrial applications with encouraging results has grown rapidly. In the case of complex processes a computer-aided monitoring enhances operators possibilities to run the process economically. In this paper, a fault diagnosis system will be described and some application results from the Outokumpu Harjavalta smelter will be discussed. The system monitors process states using neural networks (Kohonen self-organizing maps, SOMs) in conjunction with heuristic rules, which are also used to detect equipment malfunctions.
机译:近年来,对过程监视和故障诊断进行了广泛的研究,并且工业应用的数量迅速增长。对于复杂的过程,计算机辅助的监视功能可以提高操作员经济地运行过程的可能性。在本文中,将描述一个故障诊断系统,并讨论奥托昆普Harjavalta冶炼厂的一些应用结果。该系统使用神经网络(Kohonen自组织图,SOM)结合启发式规则来监视过程状态,启发式规则也可用于检测设备故障。

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