李擎, 郑德玲, 孟文博, 童新海, 谢四江. 一种新的加热炉状态识别算法[J]. 工程科学学报, 2002, 24(3): 364-368. DOI: 10.13374/j.issn1001-053x.2002.03.078
引用本文: 李擎, 郑德玲, 孟文博, 童新海, 谢四江. 一种新的加热炉状态识别算法[J]. 工程科学学报, 2002, 24(3): 364-368. DOI: 10.13374/j.issn1001-053x.2002.03.078
LI Qing, ZHENG Deling, MENG Wenbo, TONG Xinhai, XIE Sijiang. A New kind of Algorithm for State Recognition of Heating Furnace[J]. Chinese Journal of Engineering, 2002, 24(3): 364-368. DOI: 10.13374/j.issn1001-053x.2002.03.078
Citation: LI Qing, ZHENG Deling, MENG Wenbo, TONG Xinhai, XIE Sijiang. A New kind of Algorithm for State Recognition of Heating Furnace[J]. Chinese Journal of Engineering, 2002, 24(3): 364-368. DOI: 10.13374/j.issn1001-053x.2002.03.078

一种新的加热炉状态识别算法

A New kind of Algorithm for State Recognition of Heating Furnace

  • 摘要: 最小距离法是一种应用非常广泛的状态识别算法,但其在使用过程中要求待识别样本必须符合类内距离较小、类间距离较大这一前提条件,否则将会造成识别错误.针对最小距离法存在的问题,提出了一种基于人工神经网络的改进最小距离法,并将该方法应用于加热炉工况的状态识别.结果表明,该方法具有识别速度快、识别率高的优点,完全能够满足工业生产过程的需要.

     

    Abstract: MDM(Minimum Distance Method) is a very familiar algorithm in state recognition. But it has a presupposition, that is, the distance within one class is short and the distance between classes is long. When this presupposition is not satisfied, a mistake is made. In order to overcome the shortcomings of MDM, an im-proved minimum distance method based on ANN(Artificial Neural Networks) is presented. The simulation re-sults demonstrate that this method has two advantages, that is, the rate of recognition is fast and the accuracy of recognition is high.

     

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