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An automatic data acquisition system for on-line training of artificial neural network-based air handling unit modeling

机译:基于人工神经网络的空气处理机组建模在线训练自动数据采集系统

摘要

Air-conditioning systems are highly non-linear. A conventional air-conditioning control cannot achieve thermal comfort environments all the times. Artificial neural networks have been proven to be successfully applicable in this area. However, they required on-line field data to re-tune themselves. In this paper, a fully automatic data acquisition system was developed for this purpose. The system consisted of a real air-handling unit, thermal sensors, data acquisition boards and a computer with an acquisition program. Substantial experiments were carried out to capture the operating characteristics of the real air-conditioning plant. With the help of the acquisition system, a neural network-based model was built which could accurately predict the behaviors of the plant. A practical optimal control is thus possible. The methodology in this paper, the proposed acquisition system with the neural network under on-line training, can be applied in other areas for better control performances.
机译:空调系统是高度非线性的。传统的空调控制不能一直实现热舒适环境。人工神经网络已被证明可成功应用于这一领域。但是,他们需要在线现场数据来重新调整自身。在本文中,为此目的开发了一种全自动数据采集系统。该系统由一个实际的空气处理单元,热传感器,数据采集板和带有采集程序的计算机组成。进行了大量实验以捕获实际空调设备的运行特性。在采集系统的帮助下,建立了基于神经网络的模型,该模型可以准确地预测植物的行为。因此可行的最佳控制是可能的。本文中的方法,即所提出的带有神经网络的在线培训的采集系统,可以应用于其他领域以获得更好的控制性能。

著录项

  • 作者

    Tse WL; Chan WL;

  • 作者单位
  • 年度 2005
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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