王春水,何声馨,张二亮,李大磊.喷砂表面的多尺度分析与表征[J].表面技术,2015,44(6):127-132.
WANG Chun-shui,HE Sheng-xin,ZHANG Er-liang,LI Da-lei.Analysis and Characterization of Sandblasted Surfaces Using Multi-scale Analysis[J].Surface Technology,2015,44(6):127-132 |
| 喷砂表面的多尺度分析与表征 |
| Analysis and Characterization of Sandblasted Surfaces Using Multi-scale Analysis |
| 投稿时间：2015-01-16 修订日期：2015-06-20 |
| DOI：10.16490/j.cnki.issn.1001-3660.2015.06.024 |
| 中文关键词: 喷砂 三维粗糙度 多尺度分析 回归分析 |
| 英文关键词:sandblasting 3D roughness multi-scale analysis regression analysis |
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| Author | Institution |
| WANG Chun-shui | School of Mechanical Engineering, Zhengzhou University, Zhengzhou 450001, China |
| HE Sheng-xin | School of Mechanical Engineering, Zhengzhou University, Zhengzhou 450001, China |
| ZHANG Er-liang | School of Mechanical Engineering, Zhengzhou University, Zhengzhou 450001, China |
| LI Da-lei | School of Mechanical Engineering, Zhengzhou University, Zhengzhou 450001, China |
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| 中文摘要: |
| 目的 对喷砂表面的复杂轮廓特征进行分析和表征,以选取能表征最佳工艺参数的三维粗糙度参数。 方法 以喷砂工作距离为变量对 AISI 304L 不锈钢试样进行喷砂处理,对喷砂处理后试样的表面形貌开展多尺度分析,选取 5 个评价尺度,每个评价尺度下采用 12 个常用的三维粗糙度参数进行表面形貌表征;分析各个粗糙度参数对于评价尺度的变化规律,同时进一步考虑喷砂工作距离对喷砂表面形貌的影响,在适宜评价尺度下建立粗糙度参数和工艺参数之间的线性回归模型。 结果 大部分三维粗糙度参数(Sku)的最优评价尺度均为 80 μm,在该评价尺度下,Sku与喷砂工作距离之间存在线性关系,且其线性相关系数最大;随着喷砂工作距离的增加,Sku随之增大,试样表面形貌的峰谷数量也随之增大。 结论本次喷砂工艺实验的最优评价尺度为 80 μm,最优表面形貌表征参数为 Sku,与普遍使用的 Sa 和 Sq 相比,Sku包含更多三维形貌信息,能更好地刻画喷砂工作距离对表面形貌的影响。 |
| 英文摘要: |
| Objective To analyze and characterize the complicated surface topography of sandblasted surface, so as to obtain the 3D roughness parameter which is optimal in describing the influence of sandblasting parameters on surface topography. Methods The multi-scale analysis was conducted on the sandblasted surfaces of AISI 304L steel specimens, which were sandblasted at different distances as the processing parameter. Each surface was characterized using 12 common 3D roughness parameters at 5 evaluation scales. The variation trend of each roughness parameter against the evaluation scale was analyzed, meanwhile, the influence of process parameter (distance) on surface topography was considered, the linear regression model between the roughness parameters and the process parameter was established at an appropriate evaluation scale. Results The optimal evaluation scale of most roughness parameters was 80 μm, and a linear relationship was found to be pertinent in modeling Sku as a function of the distance at this evaluation scale, besides, the coefficient of determination of Sku was the biggest among the 12 roughness parameters. The number of high peaks and low valleys of the surface topography increased and the value of Sku increased with the increasing of sandblasting distance. Conclusion For this sandblasting experiment, the optimal evaluation scale was 80 μm, the parameter Sku was more promising than the widely used Sa and Sq as it collected more spatial information which allowed to better describing the effect of distance on the sandblasted topography. |
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