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双电源二次激励法是本文提出的一种利用温型粘土砂导电特性参数，快速预测其组分的新方法。利用人工神经网络（ＡＮＮｓ）研究型砂有效粘土含量和含水量与型砂交流电导率、直流电导率、直流电导率变化率之间的复杂关系，通过ＢＰ算法建立了信息参数与预测参数之间的非线性映照关系。实验结果表明，双电源二次激励法与人工神经网络相结合，可以实现型砂有效粘土含量和含水量的快速在线预测。
The double-power secondary excitation method is a new method proposed in this paper to predict its composition rapidly using the conductivity characteristics of warm-type clay sand. The artificial neural network (ANNs) was used to study the complex relationship between effective clay content and water content in sand and sand, AC conductivity, DC conductivity and DC conductivity. The relationship between information parameters and predicted parameters was established by BP algorithm. Linear mapping relationship. The experimental results show that the dual-power secondary excitation method combined with the artificial neural network can realize the rapid on-line prediction of effective clay content and water content in sand.