中南大学学报（自然科学版）2026，Vol.57Issue(5)：2135-2145,11.DOI:10.11817/j.issn.1672-7207.2026.05.019
考虑温度效应和率效应的沥青混合料Ⅰ型断裂声发射信号表征
Characterization of acoustic emission signals in mode Ⅰ fracture of asphalt mixtures considering temperature and rate effects
摘要
Abstract
To investigate the effects of temperature and loading rate on acoustic emission(AE)signals during Mode I fracture of asphalt mixtures,the semi-circular bending(SCB)tests on AC10 and AC16 mixtures at varied temperatures and loading rates were conducted.The fracture process was simultaneously monitored using AE technology.Through analysis of fracture energy,tensile stiffness index(TSI)and AE parameters,the macroscopic fracture performance and damage evolution patterns of the mixtures were evaluated.Based on the data of risetime-amplitude ratio and average frequency(RA-AF),three clustering methods,i.e.,K-means clustering algorithm,Gaussian mixture model(GMM)and GMM combined with support vector machine(GMM+SVM)were applied to quantify the proportions of tensile and shear cracking modes.The results indicate that increasing temperature significantly reduces fracture energy in AC16 but increases in AC10.Higher loading rates causes AC10 fracture energy to initially increase and then decrease,while consistently elevates TSI.AE cumulative energy and counts decrease with the increase of the temperature but increase with the increase of the loading rates.K-means and GMM+SVM yield highly consistent proportions of tensile cracking and shear cracking,whereas GMM underestimates this proportion of tensile cracking.At 2 mm/min loading rate,all methods detect the highest tensile cracking ratio.Incorporating SVM can optimize GMM cluster boundaries and enhance cracking mode differentiation accuracy.关键词
沥青混合料/声发射/温度效应/率效应/聚类分析Key words
asphalt mixture/acoustic emission/temperature effect/loading rate effect/cluster analysis分类
交通工程引用本文复制引用
宋卫民,闫文龙,吴昊,陈小宝,梁远奇..考虑温度效应和率效应的沥青混合料Ⅰ型断裂声发射信号表征[J].中南大学学报（自然科学版）,2026,57(5):2135-2145,11.基金项目
国家自然科学基金资助项目(52478291) （52478291）
湖南省自然科学基金资助项目(2024JJ5437)(Project(52478291)supported by the National Natural Science Foundation of China （2024JJ5437）
Project(2024JJ5437)supported by the Natural Science Foundation of Hunan Province) （2024JJ5437）
