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Knowledge-based genetic algorithms data fusion and its application in mine mixed-gas detection

机译:基于知识的遗传算法数据融合及其在矿井瓦斯检测中的应用

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摘要

Considering that the high concentration of mine gas and hydrogen will disturb the output of electrochemical carbon monoxide sensor, this paper integrates gas sensor array with data fusion Algorithm. The output signals of three sensors are trained by BP neural network to get the mathematical model of information fusion for the analysis of mixed gas of methane, hydrogen and carbon monoxide. The experiment shows that the information fusion could correct the crossed sensitivity error, and improve the accuracy of carbon monoxide, therefore achieve quantitative analysis mixed gas of coal mine.
机译:考虑到矿井瓦斯和氢气中的高浓度会干扰电化学一氧化碳传感器的输出,本文将气体传感器阵列与数据融合算法集成在一起。通过BP神经网络训练三个传感器的输出信号,得到信息融合的数学模型,用于分析甲烷,氢气和一氧化碳的混合气体。实验表明,信息融合可以纠正交叉灵敏度误差,提高一氧化碳的准确度,从而实现对煤矿混合气的定量分析。

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