路面材料介电特性的遗传反演方法应用研究

Research and Application of Backcalculation for Pavement Permittivity by Genetic Algorithm

路面雷达GPR因其快速、无损、高效的特点,已经广泛用于公路建设的施工质量控制、养护管理及路况评价和隐患调查.但因其厚度测试精度不高而经常需要取心标定,针对此技术现状,利用遗传算法的优化方法,建立了路面材料介电常数的遗传反演方法,实现了结构层介电常数的反演和厚度分析.通过与芯样厚度的对比发现,该方法得到的结构层厚度精度高于传统方法,能够有效减少或避免路面雷达测试过程中铅心标定的要求.

The pavement layer thickness accuracy measured from Ground Penetrating Radar（GPR） is not satisfied under any conditions,and the coring calibration must be done.Using Genetic Algorithm（GA）,an inverse method is presented to back-calculate pavement permittivity and analyze layer thickness used the GPR waveform reflected by pavement structure.The experiment shows it can get more accurate thickness analyzed by the inverse approach.When the method is used in GPR data analysis,the traditional coring calibration will be reduced or avoided.