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Application ofT2Control Charts and Hidden Markov Models in Condition-Based Maintenance at Thermoelectric Power Plants

机译:T2控制图和隐马尔可夫模型在火电厂状态维护中的应用

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An innovative approach to condition-based maintenance of coal grinding subsystems at thermoelectric power plants is proposed in the paper. Coal mill grinding tables become worn over time and need to be replaced through time-based maintenance, after a certain number of service hours. At times such replacement is necessary earlier or later than prescribed, depending on the quality of the coal and of the grinding table itself. Considerable financial losses are incurred when the entire coal grinding subsystem is shut down and the grinding table found to not actually require replacement. The only way to determine whether replacement is necessary is to shut down and open the entire subsystem for visual inspection. The proposed algorithm supports condition-based maintenance and involves the application ofT2control charts to distinct acoustic signal parameters in the frequency domain and the construction of Hidden Markov Models whose observations are coded samples from the control charts. In the present research, the acoustic signals were collected by coal mill monitoring at the thermoelectric power plant “Kostolac” in Serbia. The proposed approach provides information about the current condition of the grinding table.
机译:本文提出了一种基于条件的热电厂磨煤子系统维护的创新方法。磨煤机磨床随着时间的流逝而磨损,需要在一定数量的服务小时后通过基于时间的维护进行更换。有时,根据煤炭和磨床本身的质量,有必要在规定的时间之前或之后进行这种更换。当关闭整个磨煤子系统并且发现磨床实际上不需要更换时,会造成可观的财务损失。确定是否需要更换的唯一方法是关闭并打开整个子系统以进行目视检查。所提出的算法支持基于状态的维护,并涉及将T2控制图应用于频域中不同的声信号参数,以及构造隐马尔可夫模型的构造,其观测值是来自控制图的编码样本。在本研究中,声学信号是通过塞尔维亚热电厂“ Kostolac”的磨煤机监控收集的。所提出的方法提供了有关磨床当前状态的信息。

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