| 基于神经网络的瓦斯传感器的非线性校正 |
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| 引用本文： | 刘刚,刘学仁,蔡十华.基于神经网络的瓦斯传感器的非线性校正[J].工矿自动化,2006(6):1-4. |
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| 作者姓名： | 刘刚 刘学仁 蔡十华 |
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| 作者单位： | 江西师范大学物理与通信电子学院,江西,南昌,330022 |
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| 基金项目： | 江西师范大学青年成长基金资助项目(2005ZR18) |
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| 摘 要： | 文章提出了一种基于改进型BP神经网络的瓦斯传感器的非线性调校方法,该方法利用神经网络良好的非线性映射能力逼近反非线性函数,从而完成非线性校正。仿真结果表明:与传统的分段线性方法和BP算法相比,改进型BP神经网络收敛速度快、逼近精度高,准确度由原来分段线性校正的±5.02%提高到现在的±0.130%,且易于动态调校。
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| 关 键 词： | 煤矿 瓦斯传感器 神经网络 非线性校正 |
| 文章编号： | 1671-251X（2006）06-0001-04 |
| 收稿时间： | 2006-09-11 |
| 修稿时间： | 2006年9月11日 |
The Nonlinear Correction of Methane Sensor Based on Neural Network |
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| LIU Gang,LIU Xue-ren,CAI Shi-hua.The Nonlinear Correction of Methane Sensor Based on Neural Network[J].Industry and Automation,2006(6):1-4. |
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| Authors: | LIU Gang LIU Xue-ren CAI Shi-hua |
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| Abstract: | The nonlinear correction method of methane sensor based on improved BP neural network was introduced,which approached inverse nonlinear function to finish the nonlinear correction by use of nonlinear mapping ability of neural network.The experimental results showed that the improved neural network has quick convergence rate and high approaching precision, the accuracy of the sensor could be greatly increased from(±5.02%) to(±0.130%) compared with traditional method of piecewise linear and BP algorithm. |
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| Keywords: | coal mine methane sensor neural network nonlinear correction |
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