表面技术
錶麵技術
표면기술
SURFACE TECHNOLOGY
2015年
6期
127-132
,共6页
王春水%何声馨%张二亮%李大磊
王春水%何聲馨%張二亮%李大磊
왕춘수%하성형%장이량%리대뢰
喷砂%三维粗糙度%多尺度分析%回归分析
噴砂%三維粗糙度%多呎度分析%迴歸分析
분사%삼유조조도%다척도분석%회귀분석
sandblasting%3D roughness%multi-scale analysis%regression analysis
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 304 L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80μm,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80μm,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。
目的:對噴砂錶麵的複雜輪廓特徵進行分析和錶徵,以選取能錶徵最佳工藝參數的三維粗糙度參數。方法以噴砂工作距離為變量對AISI 304 L不鏽鋼試樣進行噴砂處理,對噴砂處理後試樣的錶麵形貌開展多呎度分析,選取5箇評價呎度,每箇評價呎度下採用12箇常用的三維粗糙度參數進行錶麵形貌錶徵;分析各箇粗糙度參數對于評價呎度的變化規律,同時進一步攷慮噴砂工作距離對噴砂錶麵形貌的影響,在適宜評價呎度下建立粗糙度參數和工藝參數之間的線性迴歸模型。結果大部分三維粗糙度參數(Sku)的最優評價呎度均為80μm,在該評價呎度下,Sku與噴砂工作距離之間存在線性關繫,且其線性相關繫數最大;隨著噴砂工作距離的增加,Sku隨之增大,試樣錶麵形貌的峰穀數量也隨之增大。結論本次噴砂工藝實驗的最優評價呎度為80μm,最優錶麵形貌錶徵參數為Sku,與普遍使用的Sa和Sq相比, Sku包含更多三維形貌信息,能更好地刻畫噴砂工作距離對錶麵形貌的影響。
목적:대분사표면적복잡륜곽특정진행분석화표정,이선취능표정최가공예삼수적삼유조조도삼수。방법이분사공작거리위변량대AISI 304 L불수강시양진행분사처리,대분사처리후시양적표면형모개전다척도분석,선취5개평개척도,매개평개척도하채용12개상용적삼유조조도삼수진행표면형모표정;분석각개조조도삼수대우평개척도적변화규률,동시진일보고필분사공작거리대분사표면형모적영향,재괄의평개척도하건립조조도삼수화공예삼수지간적선성회귀모형。결과대부분삼유조조도삼수(Sku)적최우평개척도균위80μm,재해평개척도하,Sku여분사공작거리지간존재선성관계,차기선성상관계수최대;수착분사공작거리적증가,Sku수지증대,시양표면형모적봉곡수량야수지증대。결론본차분사공예실험적최우평개척도위80μm,최우표면형모표정삼수위Sku,여보편사용적Sa화Sq상비, Sku포함경다삼유형모신식,능경호지각화분사공작거리대표면형모적영향。
ABSTRACT: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 differ-ent distances as the processing parameter. Each surface was characterized using 12 common 3D roughness parameters at 5 evalua-tion 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 rough-ness 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 dis-tance. Conclusion For this sandblasting experiment, the optimal evaluation scale was 80 μm, the parameter Sku was more promis-ing 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.