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Training based, moving digital filter method for real time heat flux function estimation

机译:基于训练的移动数字滤波方法实时估算热通量函数

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In this paper the neural networks is utilized to estimate the "filter coefficients" needed to estimate heat flux in a particular system. In developing the training phase of the network inspiration is drawn from the Burgraff's exact solution of the IHCP as well as the filter method. Thus, the estimation phase neither requires any temperature field nor the sensitivity coefficients calculations. The neural network used in this work is a 2-layer perceptron. It is shown via classical triangular heat flux test cases that the method can yield very accurate, very efficient as well as stable estimations. (c) 2006 Elsevier Ltd. All rights reserved.
机译:在本文中,神经网络用于估计特定系统中估计热通量所需的“滤波器系数”。在开发网络的训练阶段时,灵感来自Burgraff对IHCP的精确解决方案以及过滤方法。因此,估计阶段既不需要任何温度场,也不需要灵敏度系数计算。在这项工作中使用的神经网络是2层感知器。通过经典的三角热通量测试案例表明,该方法可以产生非常准确,非常有效以及稳定的估计。 (c)2006 Elsevier Ltd.保留所有权利。

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