Improvement on strip flatness of cold temper mills by modifying roll contour shape

A study on roll gap profile (strip profile) control was accomplished in a1700 mm single-stand temper mill. Some critical problems such as the deviation of work roll contourcaused by grinding and wear, the effectiveness of work roll bending were discussed. Using a finiteelement model, the effects of roll contours (ground and wear) on strip profile were investigated.The roll bending effect on strip thickness was also analyzed. It is pointed out that there are somespecial features of flatness control in the temper mill: during temper rolling, roll deformation isslight due to small rolling load, and the loaded roll gap profile mainly depends on work rollcontour, while the backup roll has a little effect on gap crown; the effect of bending force ongauge can not be ignored due to the coupling between flatness control and gauge control. A new rollcontour arrangement adaptable to the mill was presented and has been put into practical production.The application of the new set of rolls showed some good results: larger crown control range of workroll bender, higher rolling stability, better strip profile and flatness quality.

New shape clustering method based on contour DFT descriptor and modified SOFM neural network

A contour shape descriptor based on discrete Fourier transform （DFT） and a K-means al- gorithm modified self-organizing feature map （SOFM） neural network are established for shape clus- tering. The given shape is first sampled uniformly in the polar coordinate. Then the discrete series is transformed to frequency domain and constructed to a shape characteristics vector. Firstly, sample set is roughly clustered using SOFM neural network to reduce the scale of samples. K-means algo- rithm is then applied to improve the performance of SOFM neural network and process the accurate clustering. K-means algorithm also increases the controllability of the clustering. The K-means algo- rithm modified SOFM neural network is used to cluster the shape characteristics vectors which is previously constructed. With leaf shapes as an example, the simulation results show that this method is effective to cluster the contour shapes.

Using shapes correlation for active contour segmentation of uterine fibroid ultrasound images in computer-aided therapy

Segmenting the lesion regions from the ultrasound （US） images is an important step in the intra-operative planning of some computer-aided therapies. High-Intensity Focused Ultrasound （HIFU）, as a popular computer-aided therapy, has been widely used in the treatment of uterine fibroids. However, such segmentation in HIFU remains challenge for two reasons： （1） the blurry or missing boundaries of lesion regions in the HIFU images and （2） the deformation of uterine fibroids caused by the patient＇s breathing or an external force during the US imaging process, which can lead to complex shapes of lesion regions. These factors have prevented classical active contour-based segmentation methods from yielding desired results for uterine fibroids in US images. In this paper, a novel active contour-based segmentation method is proposed, which utilizes the correlation information of target shapes among a sequence of images as prior knowledge to aid the existing active contour method. This prior knowledge can be interpreted as a unsupervised clustering of shapes prior modeling. Meanwhile, it is also proved that the shapes correlation has the low-rank property in a linear space, and the theory of matrix recovery is used as an effective tool to impose the proposed prior on an existing active contour model. Finally, an accurate method is developed to solve the proposed model by using the Augmented Lagrange Multiplier （ALM）. Experimental results from both synthetic and clinical uterine fibroids US image sequences demonstrate that the proposed method can consistently improve the performance of active contour models and increase the robustness against missing or misleading boundaries, and can greatly improve the efficiency of HIFU therapy.

宽厚板全液压滚切剪机组智能化定尺系统研究与应用

高规格中厚板是众多领域重型装备制造的重要原料,成品板的精准分段和分段后板形测量是剪切智能化系统的重要部分。研究液压滚切剪智能剪切全过程的定尺技术、板头板尾不规则形状识别技术,以及剪切完成后的板形检测技术,构建剪切定尺和中厚板不规则形状检测的融合模型,借助视觉测量中的三维传感手段,定量监测剪切钢板的平直度、长度和宽度等参数,达到剪切过程的全域自动化应用,为高智能化的中厚板剪切工艺控制提供理论支撑和技术保证,实现热轧生产线上的智能升级优化。

青年男性颈肩部轮廓量化分析与形态匹配

以190名青年男大学生为研究对象,通过照片测量法、三维人体扫描法获取人体正侧面照片及三维点云数据。基于三维点云数据,提取颈肩部轮廓曲线进行椭圆傅立叶拟合得到椭圆系数,经主成分分析和聚类分析,将青年男性颈肩部正侧面形态各分为3类。采用角度半径和欧几里得距离实现二维照片与三维点云数据之间的匹配,并验证匹配准确率。结果显示:颈肩部正面轮廓匹配验证准确率达92.5%,侧面轮廓匹配验证准确率达95.0%。该研究为基于人体照片的人体形态研究提供了理论依据。

修形斜齿轮成形磨削中齿廓精度补偿方法

建立了斜齿轮齿廓修形的坐标方程与成形磨削砂轮修整的几何算法,优化出齿廓修形后的砂轮截面廓形;通过数值模拟分析,得到了机床位置误差与齿廓偏差之间的耦合关系;编制了成形磨削齿廓精度调整软件,计算出斜齿轮修形与之对应的成形砂轮廓形和齿廓精度调整参数。通过修形斜齿轮的成形磨削试验,验证了砂轮廓形修整的正确性和齿廓精度调整的有效性。

不完备轮廓图像小天体三维重构算法

受光照角度的影响,探测器拍摄的小天体图像不完整,三维重构困难。针对此问题,提出了一种基于不完备轮廓的小天体三维重构算法。首先,利用Ostu算法对图像进行阈值分割,利用EDPF(edge drawing parameter free)算法提取不完备轮廓;其次,利用太阳的方位信息,结合不完备轮廓,考虑阴影的影响,保留被照亮区域和可能区域,计算出扩展轮廓;然后,利用一组扩展轮廓和投影矩阵,将三维包围盒的计算转化为线性不等式的求解;最后,划分体素实现小天体的三维重构。利用平均半径对重构结果与参考模型的豪斯多夫距离进行归一化,评价重构质量。仿真结果表明,重构误差小于4%的分布概率占95%以上,并对光照角度变化具有一定的鲁棒性。

肉毒毒素注射在面部轮廓及躯体塑型中的应用

肉毒毒素(botulinum toxin,BTX)源自肉毒梭状芽孢杆菌,通过抑制神经元末梢递质的释放,阻断信号传递,从而减少肌肉活动。肉毒毒素注射是目前全球使用最广泛的非手术美容治疗,并越来越多地被应用于轮廓塑型。关于肉毒毒素注射对肌肉和骨骼运动功能的长远影响,已有数据证实了其潜在的不良影响,但也存在相反观点,本文将对此进行概括和总结。总体上,BTX应用于肌肉塑型的安全性被认可,但应谨慎排除禁忌证,避免过量及频繁注射。

利用Alpha Shapes算法提取离散点轮廓线

本文介绍了Alpha Shapes算法的原理和具体的实现方法,并将其应用到LiDAR离散点云数据的轮廓线提取,取得良好效果。

涡轮盘榫槽电火花线切割加工质量研究

为了提高涡轮叶盘榫槽电火花加工的材料去除率、几何形状精度,文中采用3种相同直径、不同材质的电极丝,进行电火花线切割GH4169枞树形榫槽的对比实验。采用不同工艺规准下的3道线切割工艺:第一次切割使用较大脉冲能量,加工出外形轮廓;第二次切割消除工件在上次加工中产生的变形,提高工件尺寸精度;第三次切割对工件表面进行精修整,减小工件表面变质层。对加工后榫槽进行材料去除率的计算、几何形状精度和轮廓偏差的测量,分析电火花线切割加工对榫槽加工质量的影响。试验结果表明:在高速线加工下榫槽的材料去除率最高;不同电极丝加工后的榫槽几何形状精度均在要求的0.075 mm之内;线切割加工的榫槽轮廓偏差都在0.030 mm左右,同时采用黄铜丝加工的榫槽轮廓偏差最小。采用电火花线切割工艺加工出的榫槽几何形状精度和加工质量均满足加工要求,显示出该工艺巨大的技术潜力。

颧骨颧弓区射频溶脂辅助吸脂联合局部脂肪填充行面部轮廓重塑

目的:探讨在面部审美设计基础上采用颧骨、颧弓区域射频溶脂联合吸脂在面部轮廓塑形中的重要作用。方法:2021年1月-2022年1月,笔者对76例颧骨及颧弓区域明显凸起的女性就医者,首先进行面部审美设计,用“先吸脂后填充”的方式,即先用射频设备对颧骨及颧弓区域皮下脂肪进行溶脂操作,随后进行脂肪抽吸,最后对额部、中面部、颞区、颊区凹陷进行多部位的脂肪填充。结果:本组76例就医者,颧骨及颧弓区域吸脂量(5.5±2.4)ml,其中71例行一次填充术,5例行二次填充术,就医者满意率达90.7%,所有患者均未发生严重并发症。结论:在面部审美设计的基础上,颧骨及颧弓区域明显凸起者,可利用面部“加减法”技术联合局部射频溶脂处理,进行面部轮廓塑形,满意率高,并发症发生率低,临床上可借鉴。

弧焊机器人针对V形坡口的焊接路径规划设计与仿真分析

为解决弧焊机器人面向中厚板V形坡口的焊接变形难题,通过分析传统逐层逐道堆积焊接容易引起热量聚集而导致焊接变形的特性,采用V形截面投影轨迹、空间平行往复轨迹及空间轮廓偏置轨迹相结合的方法建立V形焊层,实现焊接过程热量的快速散发。同时,在建立各轨迹方程解析式的基础上,应用Simufact Welding和MATLAB仿真软件对比分析了空间平行往复轨迹和空间轮廓偏置轨迹与传统逐层逐道焊的优缺点。为了进一步验证可行性,采用FANUC工业机器人进行试验。仿真和试验结果表明:以零件y、z轴方向的变形量为依据,空间平行往复轨迹和空间轮廓偏置轨迹都优于传统的逐层逐道焊接方法,且后者更优于前者。但空间平行往复轨迹在轨道变换过程中机器人末端执行器的空间位姿调整相对简单、引入误差少、控制精度高,更适合于坡口较窄、长度较短的情况;而空间轮廓偏置轨迹更适用于坡口较宽,长度较长的情况。

基于国产T300级碳纤维复合材料C型肋结构成型工艺

以C型肋结构为研究对象,采用国产T300级碳纤维单向带预浸料,针对C型肋结构成型过程中存在的R角厚度减薄以及外形轮廓控制等问题,开展了一系列的工艺路线设计优化,通过优化零件封装方式和成型工装固化摆放方式,R角厚度实测值合格率由4.17%提高到100%;设计工装回弹角值,制造均衡铺层和对称铺层的试验件外形轮廓均能满足工程要求。通过一系列低成本高效的优化方式,本方法成功解决了成型过程中R角厚度减薄以及外形轮廓控制等问题,为国产复合材料改进研究提供借鉴,缩短了国产复合材料应用研究周期。

复杂异型建筑立面测绘轮廓提取方法设计

为解决点云数据密度异常时复杂异型建筑立面测绘轮廓提取精度变差的问题,提出基于局部点云密度的复杂异型建筑立面测绘轮廓提取方法。引入基于平面投影和双边滤波的测绘点云数据平滑方法,对测绘数据进行去噪和平滑处理,并通过点云分割方法提取目标点云区域。通过基于改进Alpha Shapes算法的立面测绘轮廓提取方法,以边界网格筛选的方式,去除目标点云区域冗余点云数据后,使用滚动圆半径自适应调节方法提取轮廓数据。试验结果表明,所提取轮廓匹配度高达95.08%,具有良好的精度和可行性。该方法可在有效平滑点云数据、分割获取目标点云区域的同时,高精度提取复杂异型建筑立面测绘轮廓。

Backup roll contour of a SmartCrown tandem cold rolling mill

SmartCrown was a new system developed by VAI for improving the strip profile and flatness control first applied in 1700 mm tandem cold rolling mills at Wuhan Iron ＆ Steel （Group） Corporation （WISCO）. After tracing and testing, the application of the conventional crown backup roll matching the SmartCrown work roll of the production mill led to heavy and nonuniform wear, and the edge spalling of the backup roll often occurred. A 3-dimension finite element model of roll stacks was established, which was used to analyze the above-mentioned problems, and it was found that the main reason was the highly nonuniform contact pressure distribution between the work roll and the backup roll. A new FSR （flexible shape backup roll） was developed and applied in 1700 mm tandem cold rolling mills. A lot of good actual effects of FSR, such as evident improvement in profile and flatness of strips, non-occurring edge spalling, wear uniform, and remarkable decrease in roll consumption were validated by long-term industrial applications.

Finite element analysis of shape control for continuous hot rolling mills of super wide strip steel

The efficacy of shape control is the core of this technology and the main basis of automatic shape control system model designing. This passage constructs the three-dimensional elastic deformation model of CVCplus roll system in 2250 mm hot rolling mill. Comparing and analyzing different influence of working factors on control characteristic, the shape control characteristic of CVCplus roll system in its whole work time is studied, and the cause is analyzed and the difference of the roll gap curve and crown adjustable area in early and latter work time is compared. The outcome has crucial meaning in both theory and production.

Comprehensive contour prediction model of work rolls in hot wide strip mill

The predictive calculation of comprehensive contour of work rolls in the on-line strip shape control model during hot rolling consists of two important parts of wear contour calculation and thermal contour calculation, which have a direct influence on the ac- curacy of shape control. A statistical wear model and a finite difference thermal contour model of work rolls were described. The comprehensive contour is the equivalence treatment of the sum of grinding, wear, and thermal contours. This comprehensive contour calculation model has been applied successfully in the real on-line strip shape control model. Its high precision has been proved through the large amounts of actual roll profile measurements and theoretical analyses. The hit rates （percent of shape index satisfying re- quirement） of crown and head flatness of the strips rolled, by using the shape control model, which includes the comprehensive contour calculation model, have about 16% and 10% increase respectively, compared to those of strips rolled by using manual operation.

THREE DIMENSIONAL DIGITIZATION OF HUMAN HEAD BY FUSING STRUCTURED LIGHT AND CONTOURS

Three dimensional digitization of human head is desired in many applications. In this paper, an information fusion based scheme is presented to obtain 3-D information of human head. Structured light technology is employed to measure depth. For the special reflection areas,in which the structured light stripe can not be detected directly, the shape of the structured light stripe can be calculated from the corresponding contour. By fusing the information of structured light and the contours, the problem of reflectance influence is solved, and the whole shape of head,including hair area, can be obtained. Some good results are obtained.

基于Alpha Shapes算法的LIDAR数据建筑物轮廓线提取

机载LIDAR点云数据分布呈现离散化,扫描的目标点云没有明确的轮廓,而建筑物形状呈现复杂化和多样化,这给提取机载LIDAR数据中建筑物轮廓线带来了困难。Alpha Shapes算法的优点在于无需知道点云中各点处的法向量及其他先验知识就能进行处理,避免了插值算法带来的误差影响,对于少量点云缺失及数据冗余的情况,算法仍具有良好的稳定性和适应性。AlphaShapes方法可以得到较为精细的建筑物边缘,且该算法适用于各种多边形建筑物轮廓线的提取。

基于α-shape的三维激光点云计算树冠体积的研究

针对树冠形状各异、结构复杂、轮廓难以提取和体积难以精确计算等问题,文中基于三维激光扫描得到的树冠点云,提出一种综合树冠点云切片算法、α-shape点云轮廓提取算法和散乱轮廓点云排序算法的树冠体积计算方法。首先对树冠点云按照一定的间隔进行切片,将树冠点云分成多个类似台体和锥体部分,然后利用α-shape算法对每一层树冠点云进行轮廓点的提取,再使用点云排序算法对α-shape算法提取到的轮廓点集进行逆时针排序,利用多边形面积的行列式计算公式分别计算每层点云的面积;并使用台体和锥体的体积计算公式计算每部分的体积,最终累加各部分体积值得到树冠的最终体积。通过对利用TrimbleTX8地面三维激光扫描仪得到的九棵不同形状和品种的树木树冠点云进行计算与分析,并使用传统的体元法和凸包法对本文提出的算法进行了验证。结果表明本计算方法能很好地提取树冠的外包轮廓,进而得到准确的树冠体积值,在准确性和精度上优于两种传统方法,可应用于林业资源的调查与分析。