张明社, 李小昱, 雷廷武, 王为, 张征. 用基于人工神经网络的数据融合法测量水流泥沙含量[J]. 农业工程学报, 2002, 18(4): 41-43.
    引用本文: 张明社, 李小昱, 雷廷武, 王为, 张征. 用基于人工神经网络的数据融合法测量水流泥沙含量[J]. 农业工程学报, 2002, 18(4): 41-43.
    Zhang Mingshe, Li Xiaoyu, Lei Tingwu, Wang Wei, Zhang Zheng. Data Fused Method Based on Artificial Neural Network to Measure Sediment Concentration in Flow-Water[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2002, 18(4): 41-43.
    Citation: Zhang Mingshe, Li Xiaoyu, Lei Tingwu, Wang Wei, Zhang Zheng. Data Fused Method Based on Artificial Neural Network to Measure Sediment Concentration in Flow-Water[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2002, 18(4): 41-43.

    用基于人工神经网络的数据融合法测量水流泥沙含量

    Data Fused Method Based on Artificial Neural Network to Measure Sediment Concentration in Flow-Water

    • 摘要: 在采用电容传感器测量泥沙含量的过程中,电容传感器的输出值受环境温度的影响较大,为消除温度对测量数据的影响,提出了采用人工神经网络法对传感器进行数据融合处理的方法,该方法以传感器的泥沙含量值与温度值作为网络的输入,通过对网络的训练达到消除非目标参量——温度的影响。试验结果表明该方法收敛速度快,输出稳定性可显著提高,能够有效地消除温度带来的影响。

       

      Abstract: In the process of measuring the sediment concentration in flow-water, the temperature will greatly influence the testing results. A new method, based on artificial neural network under MATLAB environment is designed to fuse the two-sensor information. The neural network used the capacitance sensor and the temperature sensor output as input. After the network is trained, it can make the sensor eliminate the temperature influence and improve the target parameter input. The simulation results show that the fusion results are stable and precise enough with this method.

       

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