沥青混合料水-温-光损伤超声波评价及预测方法

发布时间：2018-04-24 14:24

本文选题：道路工程 + 沥青混合料　；参考：《长安大学学报(自然科学版)》2014年06期

【摘要】：通过室内水-温-光循环试验,将降水、高温和日照3种环境因素对沥青混合料的损伤进行模拟。利用超声波检测技术,测定不同温度、不同含水量的沥青混合料试件在水-温-光循环过程中超声波参数性质的变化,从而对其损伤进行初步判断。通过试件劈裂强度与冻融劈裂强度的衰减来定义其损伤,并应用支持向量机理论,建立波速与沥青混合料损伤程度的回归预测模型,形成了沥青混合料水-温-光损伤无损检测方法。研究结果表明:利用超声波形及频谱的特性变化,可以对水-温-光循环过程中不同形式的沥青混合料的损伤程度进行初步判断;借助支持向量机理论对沥青混合料水-温-光损伤进行超声波评价,相关系数最大值为0.97,最小值为0.90,预测平均误差为4.53%,表现出较高的精度及稳定性。
[Abstract]:The damage of asphalt mixture was simulated by three kinds of environmental factors, precipitation, high temperature and sunshine, through indoor water-temperature-light cycle test. Ultrasonic testing technique is used to determine the changes of ultrasonic parameters of asphalt mixture specimens with different temperature and moisture content during water-temperature-light cycling, and the damage of asphalt mixture is preliminarily judged. The damage is defined by the attenuation of splitting strength and freeze-thaw splitting strength, and the regression prediction model of wave velocity and damage degree of asphalt mixture is established by using support vector machine theory. A non-destructive detection method for water-temperature-light damage of asphalt mixture was developed. The results show that the damage degree of different types of asphalt mixture can be preliminarily judged by using the characteristic changes of ultrasonic shape and frequency spectrum in the process of water-temperature-light cycling. Based on the support vector machine (SVM) theory, the ultrasonic evaluation of water-temperature-light damage of asphalt mixture shows that the maximum correlation coefficient is 0.97, the minimum value is 0.90, and the average prediction error is 4.53, which shows high accuracy and stability.
【作者单位】：吉林大学交通学院;
【基金】：国家自然科学基金项目(51278222) 吉林大学研究生创新基金资助项目(20121079)
【分类号】：U414

【参考文献】