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Development of a tube ball mill mathematical model for mill condition and safety monitoring

机译:用于轧机状态和安全监测的管球磨机数学模型的开发

摘要

The PhD research project is to examine if it is possible to minimize the mill faults and fires in the Tube Ball mill operation by using a model based approach. The research outcome proves that the risks of mill fault can be monitored and alerted by implementing the model based on-line condition monitoring software that developed through the PhD project. udCoal fired power stations nowadays regularly use coal with higher volatile contents and Biomass materials to satisfy the government regulations on sustainable and renewable energy. This greatly increases the risks of explosions or fires in milling plants. However, there are no acceptable measurement methods available at the present and it is difficult to identify if there will be a fire in the mill. Therefore, the project is carried out from the study mill mathematical model to mill condition monitoring.udMonitoring the mill operation conditions only based on currently available on-site measurement without requiring any extra hardware is a cost effective solution and will pose a great challenge. A mathematical model of coal mills is developed using computational intelligent algorithms for prediction of potential mill faults.
机译:博士研究项目旨在研究是否可以通过使用基于模型的方法来最大程度地减少管式球磨机运行中的轧机故障和火灾。研究结果证明,通过实施基于通过博士项目开发的在线状态监控软件的模型,可以监控和警告轧机故障的风险。 ud如今,燃煤发电厂定期使用挥发分含量更高的煤炭和生物质材料来满足政府关于可持续和可再生能源的规定。这大大增加了铣削厂爆炸或火灾的风险。但是,目前没有可接受的测量方法,很难确定磨机是否会着火。因此,该项目是从研究轧机数学模型到监测轧机状态的过程。 ud仅基于当前可用的现场测量来监测轧机的运行状态,而无需任何额外的硬件,这是一种经济高效的解决方案,将带来巨大的挑战。使用计算智能算法开发了磨煤机的数学模型,用于预测磨煤机潜在的故障。

著录项

  • 作者

    Zachariades Paschalis;

  • 作者单位
  • 年度 2015
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  • 原文格式 PDF
  • 正文语种 English
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