基于BP神经网络的炉膛三维温度检测方法研究

Yang Yu, Jinxing Chen
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引用次数: 3

摘要

针对大型锅炉燃烧火焰变化的多样性,以便实时掌握炉膛火焰的状态。本文介绍了BP神经网络吸收火焰图像温度的基本方法,对BP神经网络模型进行了深入的研究讨论,并提出了一种改进的BP神经网络方法,对于三维温度场的计算方法,比传统的优化方法有许多优点。仿真研究和实验结果表明,采用BP神经网络对加热炉内三维温度场进行测试是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Research on Method of Detection for Three-Dimensional Temperature of the Furnace Based on BP Neural Network
In view of the variety of the changes of burning flame in large-scale boiler, in order to master the status of the furnace flame in real time. In this paper, it introduces the BP neural network absorb the basic method of flame-picture's temperature, to study thoroughly discussed about the BP neural network model, and puts forward an improved BP neural network method, as for the method to calculate three-dimensional temperature field, which has many advantages to the traditional optimization method. Taking the BP neural network using to test the three-dimensional temperature field in the furnace is feasible by the simulation studies and the experimental results.
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