基于电容等效模型的路面覆盖物检测系统研究
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1.南京信息工程大学江苏省大气环境与装备技术协同创新中心南京210044; 2.南京信息工程大学集成电路学院南京210044

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TP212;TN206

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国家重点研发计划(2022YFB3205900)项目资助


Research on road covering detection system based on capacitance equivalent model
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1.Jiangsu Collaborative Innovation Centre for Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing 210044, China; 2.School of Integrated Circuits, Nanjing University of Information Science & Technology, Nanjing 210044, China

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    摘要:

    针对传统电容式路面覆盖物检测方法在低温下辨识能力弱、区分度不高的问题,基于电容器的串联等效模型,从电介质极化原理出发,研究了电容器和覆盖物存在的介电损耗和弛豫现象,分析了覆盖物和检测频率对电容器等效串联电容和等效串联电阻的影响,设计并搭建了电容器高通滤波电路,通过比较高通滤波电路输出与输入信号的幅度衰减比和相位偏移,间接测量电容器等效串联电容和等效串联电阻的变化,实现覆盖物类型的识别。在恒温箱中进行样本测试,实验结果表明,当温度在10 ℃~60 ℃时,干燥时的相位差大于30°,衰减比例小于0.8;积水时的相位差在10°以内,衰减比例接近1。当温度在-30 ℃~0 ℃时,干燥、结冰和积雪时的衰减比例存在交叉。相位差随着温度缓慢变化,干燥时平均相位差大于40°,结冰时平均相位差小于30°,而积雪时的平均相位差介于二者之间。利用温度、相位差和衰减比例构建神经网络分类模型,部署到单片机后进行实测。实测数据表明在0 ℃~60 ℃之间,干燥和积水的区分准确率达到95%;在-30 ℃~0 ℃之间,干燥、结冰和积雪的区分准确率达到83%,能够满足路面覆盖物检测的需求。

    Abstract:

    In response to the problem that the traditional capacitive road covering detection method has weak identification ability and low discrimination at low temperatures,the dielectric loss and relaxation phenomena of capacitors and covers are studied based on the series equivalent model of the capacitor and starting from the principle of dielectric polarization. The effects of covers and detection frequency on the equivalent series capacitance and equivalent series resistance of the capacitor was analyzed and a capacitor high-pass filter circuit was designed and built. By comparing the amplitude attenuation ratio and phase difference between the output and input signals of the high pass filtering circuit, the changes in equivalent series capacitance and equivalent series resistance of capacitors can be indirectly measured to achieve the identification of the type of covering material. The sample was tested in the incubator. The experimental results show that when the temperature is between 10 ℃ and 60 ℃, the phase difference during drying is greater than 30°, and the decay ratio is less than 0.8. The phase difference is less than 10°, and the decay ratio is close to 1. When the temperature is between -30 ℃ and 0 ℃, the decay ratio of dry, freezing and snow cover is crossed. The phase difference varies slowly with temperature, with an average phase difference of more than 40° when dry, less than 30° when frozen, and somewhere in between when covered with snow. The neural network classification model is constructed by using temperature, phase difference and decay ratio, which is deployed to the single chip computer and measured. Measured data show that the method achieves an accuracy of 95% in distinguishing between dry and stagnant water between 0 ℃ and 60 ℃, and the accuracy of distinguishing between dry, frozen, and snow cover is about 83% in the range of -30℃ and 0℃, which can meet the needs of road covering detection.

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周家涛,李敏,沙秩生,张加宏,曹越洋.基于电容等效模型的路面覆盖物检测系统研究[J].电子测量与仪器学报,2025,39(6):51-64

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  • 在线发布日期: 2025-09-16
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