| 引用本文: | 周兴林,李庆丰,祝媛媛,肖神清.粗集料纹理粗糙度表征的高差相关函数方法[J].哈尔滨工业大学学报,2019,51(9):157.DOI:10.11918/j.issn.0367-6234.201805163 |
| ZHOU Xinglin,LI Qingfeng,ZHU Yuanyuan,XIAO Shenqing.Height difference correlation function method for texture roughness characterization of coarse aggregate[J].Journal of Harbin Institute of Technology,2019,51(9):157.DOI:10.11918/j.issn.0367-6234.201805163 |
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| 摘要: |
| 为全面描述粗集料的粗糙程度,引入高差相关函数进行粗集料表面纹理多参数表征. 首先借助触针轮廓仪获取集料表面纹理轮廓曲线,消除数据误差. 然后,计算粗集料高差相关函数,对函数进行分段拟合,计算表面纹理曲线的自相似特征参数(D,ξ∥,ξSymbol^A@)作为评价指标,分析粗集料表面纹理的粗糙程度. 结果表明:粗集料表面纹理在一定范围内具有两段变维特性,微观纹理和宏观纹理的尺度界线为100~200 μm；不同集料表面宏观纹理分形维数D1均在1.3左右,微观纹理分形维数D2均在1.05左右,分形维数对粗糙度不敏感；水平截止波长ξ∥和幅度期望值ξSymbol^A@分别反映了粗集料表面微凸体的水平波长期望值和垂直幅度期望值,水平截止波长ξ∥反映最大微凸体的大小,其中白云岩和闪长岩较小,晶体结构较大的花岗岩较大. 幅度期望值ξSymbol^A@从大到小依次为闪长岩、黄砂岩、花岗岩1、辉绿岩、花岗岩2、白云岩,符合实际情况,幅度期望值ξSymbol^A@可定量描述集料整体的粗糙程度. 自相似特征参数可全面描述粗集料表面纹理的粗糙程度. |
| 关键词: 道路工程 粗糙度表征 高差相关函数 粗集料 分形维数 |
| DOI：10.11918/j.issn.0367-6234.201805163 |
| 分类号:U416 |
| 文献标识码:A |
| 基金项目:国家自然科学基金(0,9,51827812) |
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| Height difference correlation function method for texture roughness characterization of coarse aggregate |
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ZHOU Xinglin1,LI Qingfeng1,ZHU Yuanyuan1,XIAO Shenqing2
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(1.School of Automobile and Traffic Engineering, Wuhan University of Science and Technology, Wuhan 430065, China; 2. School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150090, China)
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| Abstract: |
| To fully describe the roughness of coarse aggregate, the height difference correlation function was introduced to characterize the surface texture of coarse aggregate with multi-parameters. First, the needle profiler was applied to obtain the texture profile curve of the aggregate surface and eliminate the error in data acquisition. Then, the height difference correlation function of the coarse aggregate was calculated, and the curve was fitted with piecewise fitting. The self-similar feature parameters (D, ξ∥, ξSymbol^A@) of the surface texture curve were calculated as evaluation indexes to analyze the roughness of the surface texture of the coarse aggregate. Results show that the surface texture of the coarse aggregate had two sections of variable dimension within a certain range, and the scale boundary between the micro texture and the macro texture was 100-200 μm. The fractal dimension D1 of the macro texture of different aggregates was about 1.3, and the fractal dimension D2 of the micro texture was about 1.05, which revealed that the fractal dimension was insensitive to roughness. The horizontal cutoff wavelength ξ∥ and the amplitude expectation value ξSymbol^A@ reflected the expected values of the horizontal wavelength and the vertical amplitude of the micro-convex surface of the coarse aggregate, respectively. The horizontal cutoff wavelength ξ∥ reflected the size of the largest microbump. The dolomite and the diorite were smaller, while the granite with larger crystal structure had a maximum value. The amplitude expectation value ξSymbol^A@ was diorite, yellow sandstone, granite 1, diabase, granite 2, and dolomite in descending order, which was in line with the actual situation. The amplitude expectation value could quantitatively describe the overall roughness of the aggregate. The self-similar feature parameters could fully describe the roughness of the surface texture of the coarse aggregate. |
| Key words: road engineering roughness characterization height difference correlation function coarse aggregate fractal dimension |
