为解决轮胎硫化工序中制造成型花纹与设计花纹存在偏差的问题，提出一种从胎面扫描数据中提取花纹边界特征并进行加工特征重构的新方法。该方法依据花纹节距排布和挤压压延成型工艺确定空间分割方案，利用轮廓设计理论和主成分统计分析方法获取胎顶轮廓曲线，从而实现三维点云向二维灰度图像（带有深度值）的转化，根据花纹的增长规律并借鉴区域增长法的思想对花纹边界特征进行识别和提取。结合三次样条插值法将花纹边界离散化处理为一簇等间距坐标点的形式，最终根据最佳一致逼近的定义实现自适应相切连续圆弧直线的花纹曲线逼近。实验结果表明，该方法可在90 s左右的时间内完成各种半钢子午线轮胎花纹的重构，特征提取误差不大于0.15 mm，重构误差绝对值均值不超过0.25 mm，最大值不超过0.4 mm。该方法不仅能快速有效提取胎面花纹边界特征并重构，并且解决了传统逆向工程技术在花纹重构中失真性的问题，为花纹开发效率的提高和综合性能的改善提供了指导方向。
董玉德
,
张荣团
,
宋忠辉
,
房玉强
,
白苏诚
,
张方亮
. 胎面花纹边界特征提取及重构方法研究[J]. 机械工程学报, 2018
, 54(3)
: 137
-147
.
DOI: 10.3901/JME.2018.03.137
In order to solve the deviation problem between tread pattern and design pattern in the process of tire vulcanization, a new method is proposed to extract and reconstruct tread pattern feature from tire tread scan data. Firstly, A new space segmentation method is determined according to the pattern pitch arrangement and the extrusion and calendering process, secondly, obtained the Contour of the tire crest by contour design theory and principal component analysis method, and finally successfully transformed the dimensional point cloud to the two-dimensional gray image (with depth value). According to the growth rhythm of the pattern and the idea of regional growth law, the pattern border characteristics can be identified and extracted accurately. The cubic boundary spline interpolation method is used to discretize the pattern boundary into a series of equidistant coordinate points. And finally, the approximation of tread curve of Self-adaptive Tangent Continuous Circle and Line is realized according to the definition of optimal uniform approximation. The experimental results show that the method can be used to reconstruct the tire tread pattern of various semi-steel radial tire in about 90s, the feature extraction error is less than 0.15mm, the mean value of reconstruction error absolute value is less than 0.25mm, the maximum value is less than 0.4mm. This method can extract and reconstruct the tread pattern boundary feature effectively and deal the distortion problem in pattern reconstruction of traditional reverse engineering technology, as well as provides a direction for improvement of the efficiency of pattern development and the comprehensive performance of the tire.
[1] 钱锦锋,陈志杨,张三元,等. 点云数据压缩中的边界特征检测[J]. 中国图象图形学报, 2005(2):164-169. QIAN Jinfeng,CHEN Zhiyang,ZHANG Sanyuan,et al. The detection of boundary point of point cloud compression[J]. Journal of Image and Graphics,2005(2):164-169.
[2] 欧阳徕. 轮胎断面轮廓重构关键技术研究[D]. 广州:华南理工大学,2010. OUYANG Lai. Key technology research on contour reconstruction of tyres section[D]. Guangzhou:South China University of Technology,2010.
[3] YI An,ZHUO Hanli,CHENG Shao. Feature extraction from 3D point cloud data based on discrete curves[J]. Mathematical Problems in Engineering,2013,6:87-118.
[4] 孙殿柱,范志先,李延瑞. 散乱数据点云边界特征自动提取算法[J]. 华中科技大学学报,2008,36(8):82-84. SUN Dianzhu,FAN Zhixian,LI Yanrui. Automatic extraction of boundary characteristic from scatter data[J]. Journal of Huazhong University of Science and Technology,2008,36(8):82-84.
[5] HUANG S,WANG C. Genetic algorithms for approximation of digital curves with line segments and circular arcs[J]. Journal of the Chinese Institute of Engineers,2009,32(4):437-444.
[6] KAEWSAIHA P,DEJDUMRONG N. Modeling of Bézier curves using a combination of linear and circular arc approximations[C]// Proceedings of the 9th International Conference on Computer Graphics,Imaging and Visualization (CGIV),July 25-27, 2012,Hsinchu, Taiwan. 2012:27-30.
[7] SARKAR B,SINGH L K,SARKAR D. Approximation of digital curves with line segments and circular arcs using genetic algorithms[J]. Pattern Recognition Letters,2003, 24(15):2585-2595.
[8] SHU S H,LIN Z Z,DING Y. B-Spline curve approximation with nearly arc-length parameterization[J]. Applied Mechanics and Materials,2014,513-517:3372-3376.
[9] ZHANG Z Q,YAN Q S,ZHENG Z D. Error estimate of approximate double circular arc interpolated method for curve smoothing[J]. Materials Science Forum,2004,471:92-95.
[10] SABITOV I K,SLOVESNOV A V. Approximation of plane curves by circular arcs[J]. Computational Mathematics and Mathematical Physics,2010,50(8):1279-1288.
[11] YUE Y. Bi-arc approximation algorithm for NURBS curve in the numerical control machining[C]// Control Conference (CCC),Beijing,July 29-31,2010.
[12] MAIER G,JANDA F,SCHINDLER A. Minimum description length arc spline approximation of digital curves[C]// Image Processing (ICIP),2012 19th IEEE International Conference,September 30-October 3,2012, Florida. 2012:1869-1872.
[13] 卢维欣,万幼川,何培培,等. 大场景内建筑物点云提取及平面分割算法[J]. 中国激光,2015(9):344-350. LU Weixin, WAN Youchuan,HE Peipei,et al. Extracting and plane segmenting buildings from large scene point cloud[J]. Chinese Journal of Lasers,2015(9):344-350.
[14] ZHU H,LI C,ZHANG L L,et al. River channel extraction from SAR images by combining gray and morphological features[J]. Circuits,Systems,and Signal Processing,2015,34(7):2271-2286.
[15] 庞世燕,刘亚文,左志奇,等. 结合区域增长法和TIN边缘分割的建筑物立面几何特征提取[J]. 武汉大学学报,2015(1):102-106. PANG Shiyan,LIU Yawen,ZUO Zhiqi,et al. Combination of region growing and TIN edge segmentation for extraction of geometric features on building facades[J]. Journal of Wuhan University,2015(1):102-106.
[16] 丁尤蓉,王敬东,邱玉娇,等. 基于自适应阈值的FAST特征点提取算法[J]. 指挥控制与仿真,2013(2):47-53. DING Yourong,WANG Jingdong,QIU Yujiao,et al. FAST feature detection algorithm based on self-adaptive threshold selection[J]. Command Control & Simulation,2013(2):47-53.
[17] 陈义仁,王一宾,彭张节,等. 一种改进的散乱点云边界特征点提取算法[J]. 计算机工程与应用,2012(23):177-180. CHEN Yiren,WANG Yibin,PENG Zhangjie,et al. Improved algorithm for extraction of boundary character-istic point from scattered point cloud[J]. Computer Engineering and Applications,2012(23):177-181.
[18] 邰能建,吴德伟,戚君宜. 基于改进SIFT的高鲁棒性特征点提取方法[J]. 航空学报,2012(12):2313-2321. TAI Nengjian,WU Dewei,QI Junyi. A method to extract high robust keypoints based on improved SIFT[J]. Acta Aeronautica et Astronautica Sinica,2012(12):2313-2321.
[19] 程效军,方芳. 基于形态学的散乱点云轮廓特征线提取[J]. 同济大学学报,2014(11):1738-1743. CHENG Xiaojun,FANG Fang. Morphology-based scattered point cloud contour extraction[J]. Journal of Tongji University,2014(11):1738-1743.
