非球面子孔径拼接干涉测量的几何方法研究
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摘要
非球面光学零件具有矫正像差、改善像质、扩大视场和增大作用距离的优点,同时还能够减轻系统重量,减小占用空间,因此在现代光学系统中得到了越来越广泛的应用。随着装备性能要求的不断增长,高能激光武器、激光核聚变和空间望远镜等武器装备光学系统对大型光学零件的需求激增,其技术要求上较传统光学零件也有很大提升,突出体现在对大口径、大相对口径光学零件的中高频误差提出了严格要求。全口径、全波段(有效口径内波前的各种空间频率成分)面形误差的检测成为大型光学零件检测的主要目标。这个问题目前并没有得到有效解决,子孔径测试技术是最有希望的解决方案。本论文研究工作的主要任务就是要有效解决非球面子孔径拼接测量的关键问题。与传统的子孔径拼接算法不同,论文从几何学观点出发,结合工件定位、公差评定以及图像多视拼合理论中的一些方法,充分利用计算机软件处理技术,对这些关键问题展开研究。论文的研究工作包括以下几个部分:
     1.系统地研究了对称特征和多特征的位形空间理论,为形位公差和子孔径拼接问题提供了一个比较严格的数学背景。在此基础上按照美国标准ASME Y14.5.1M-1994的形式给出了形位公差的数学模型和评定算法,并且提出了改进算法性能的几个措施。与其他常用算法的性能比较和数值仿真验证了算法的有效性和优越性。
     2.从几何学观点出发,对子孔径拼接问题进行数学建模,将问题分解为重叠计算子问题和测试几何参数优化子问题,它实际上可以看作是广义的工件定位或图像多视拼合问题。提出基于交替优化和序列线性化的迭代优化算法,结合处理海量数据的稀疏矩阵技术、顺序QR分解方法以及代码向量化等编程技巧,可以快速有效地求解非球面子孔径拼接问题。由于算法利用了被测曲面的设计模型简化重叠计算子问题,随之全口径也要相对于名义表面最佳定位,因此算法是子孔径拼接与工件定位的结合。算法的主要优点是对相当大的测试几何参数(包括位形参数)的不确定性不敏感,因此就不再需要精确已知调零与对准运动量,以及参考球面半径等几何参数。通过大口径抛物面镜的子孔径拼接仿真,验证了算法的有效性。进一步提出利用标记点作为辅助手段,进行对称自由度的位形参数优化,从而实现全部6个自由度的运动不确定性补偿。采用平面干涉仪进行测量的子孔径拼接问题,由于测量数据以参考平面为基准,因此比采用球面干涉仪的子孔径拼接问题更简单,或者可以看作是后者的一个特例。
     3.子孔径划分是指确定子孔径的布局。由于曲率连续变化,非球面特别是离轴非球面的子孔径划分是一件精细而又复杂的工作。以凹抛物面为例,讨论了确定子孔径布局和计算子孔径最佳拟合球的方法,通过最小化用曲面积分表示的均方非球面偏差,确定最佳拟合球。随后给出了数值实例对提出的方法进行阐明和有效性验证。根据自由度分析确定了子孔径拼接干涉仪原型样机的设计方案,根据子孔径拼接算法对运动不确定性的鲁棒性,以及子孔径干涉图对运动误差的灵敏性分析,确定了对准与调零运动的分辨率、精度和行程等指标。
     4.分析了子孔径拼接测量的主要误差因素,结合子孔径拼接算法原理,讨论了测量不确定度的传递关系。在一定的假设下,得到了单点相位测量误差不确定度到单点绝对相位法向误差的不确定度传递的解析式。
     5.以平面镜和抛物面镜为例,划分子孔径后进行子孔径拼接干涉测量实验,并应用子孔径拼接算法获得全口径面形,与全口径测试得到的面形进行比较,对子孔径拼接测量的有效性进行实验验证。
Aspheric optics are being used more and more widely in modern optical systems,due to their ability of correcting aberrations, enhancing the image quality, enlarging thefield of view and extending the range of e?ect, while reducing the weight and volume ofthe system. With the ever-increasing demands on system performances, large optics areadopted in high-energy laser weapons, laser fusion systems and space telescopes. Thetechnical requirements are more than traditional. More rigorous control of high-middlefrequency error is now demanded within the full aperture of the large-relative apertureoptics. Thereby surface quality within the full aperture and full band of frequency (allspatial frequency components of the wavefront in the e?ective aperture) becomes themain content of inspection of large optics. Whereas this problem has never been solved.The subaperture testing method seems to provide the answer. This thesis is dedicatedto solve the key problems in subaperture testing of aspheric surfaces. Unlike traditionalsubaperture stitching algorithms, the problems are formulated from the geometrical pointof view, combined with methods for workpiece localization, tolerance assessment and multi-view registration. The major research e?orts include the following points.
     1. A systematic introduction is first given to the theory of configuration space of sym-metric features and multi-features, which provides a mathematical background for theproblem of tolerance assessment and subaperture stitching. Then the mathematicalmodels and algorithms for tolerance assessment problem are proposed, in the form ofthe American standard ASME Y14.5.1M-1994. Several techniques are discussed toimprove the algorithm performances. Comparisons with other published algorithmsprove the validity and advantages of the proposed method.
     2. A geometrical approach is introduced to formulate the subaperture stitching problemmathematically. The problem is decomposed into a series of overlapping calculationsubproblems and geometrical parameter optimization subproblems. Actually it canbe viewed as generalized workpiece localization or multi-view registration problem.By virtue of the alternating optimization technique and the successive linearizationmethod, the problem is solved e?ciently, combined with sparse techniques, sequentialQR decomposition method and code vectorization skills. The model of the surface un-der test is utilized to simplify the overlapping calculation subproblem. Consequentlythe full aperture should be best localized with regard to the nominal surface. There-fore the algorithm is a combination of subaperture stitching algorithm and workpiecelocalization algorithm. As a major advantage, the algorithm is immune from fairlybig parameter (including the motion parameter) uncertainties. Thanks to it, preciseprior knowledge of the nulling and alignment motion is no longer required, nor arethe radii of best fit spheres. Simulations of subaperture stitching test of a large-scaleparaboloid surface verify the validity of the proposed algorithms. Stitching algorithm with the aid of fiducial marks is also developed to further compensate uncertaintyof the symmetric degrees of freedom. Subaperture stitching problem using a pla-nar interferometer is simpler than using a spherical interferometer, since the phase ismeasured with a plane datum. It can be considered as special case of the latter.
     3. Lattice is used here to mean the collection and arrangement of subapertures. Becauseof the varying curvature, lattice design is subtle and complicate for aspheric surfaces,especially for o?-axis subapertures. Methods are described for lattice design and cal-culation of the best fit sphere for each subaperture. The best fit sphere is determinedby minimizing the mean-squares aspheric deviations in the form of surface integral. Anumerical example is given to illustrate the procedure, and also verify the validity ofthe proposed methods. A prototype design of the subaperture stitching interferome-ter is presented based on the analysis of the degree-of-freedom. Requirements on theresolution, accuracy and stroke of the nulling and alignment motion are determinedby the robustness of the stitching algorithm against motion uncertainties, as well asthe sensitivity of sub-interferograms to motion errors.
     4. Major error sources in subaperture stitching interferometry are recognized. The prop-agation of uncertainty is discussed with the subaperture stitching algorithms. Undercertain assumptions, it can be explicitly formulated.
     5. Finally lattice design and subaperture stitching test are performed with a planar mir-ror and a paraboloid mirror respectively. The stitched full-aperture is then comparedwith the measured full-aperture, which verifies the validity of the subaperture testingexperimentally.
引文
[1] 苏毅,万敏. 高能激光系统. 北京:国防工业出版社,2004
    [2] Lawson J. K., Auerbach J. M., English R. E. et al. NIF optical specifications - theimportance of the RMS gradient. LLNL Report UCRL-JC-130032, 1998:7~12
    [3] 郝云彩. 空间详查相机光学系统研究:博士学位论文. 上海:中国科学院上海药物研究所,2000
    [4] 杨力. 先进光学制造技术. 北京:科学出版社,2001
    [5] Harvey J. E., Lewotsky K. L., and Kotha A. E?ects of surface scatter onthe optical performance of x-ray synchrotron beam-line mirrors. Applied Optics,1995,34(16):3024~3032
    [6] Tricard M., and Murphy P. E. Subaperture stitching for large aspheric surfaces. Talkfor NASA Tech Day 2004
    [7] 潘君骅. 光学非球面的设计、加工与检验. 北京:科学出版社,1994
    [8] Hanson R. J. and Norris M. J. Analysis of measurements based on the singular valuedecomposition. SIAM J. Sci. Stat. Comput. 1981,2(3):363~373
    [9] Faugeras O. D. and Hebert M. The representation, recognition, and locating of 3-Dobjects. International Journal of Robotics Ressearch. 1986,5(3):27~52
    [10] Arun K. S., Huang T. S., and Blostein S. D. Least-squares fitting of two 3-D pointsets. IEEE Trans Pattern Anal Mach Intell, 1987,9(5):698~700
    [11] Horn B. K. P. Closed-form solution of absolute orientation using unit quaternions.J. Opt. Soc. Am. A, 1987,4(4):629~942
    [12] Horn B. K. P., Hilden H. M., and Negahdaripourt S. Closed-form solution of absoluteorientation using orthonormal matrices. J. Opt. Soc. Am. A, 1988,5(7):1127~1135
    [13] Walker M. W., Shao L., and Volz R. A. Estimating 3-D location parameters us-ing dual number quaternions. Computer Vision and Graph Image Process: ImageUnderstanding, 1991,54(3):358~367
    [14] Park F. and Martin B. Robot sensor calibration: Solving AX = XB on the Euclideangroup. IEEE Trans. on Robotics and Automation, 1994,10(5):717~721
    [15] Eggert D. W., Lorusso A., and Fisher R. B. Estimating 3-D rigid body transfor-mations: a comparison of four major algorithms. Machine Vision and Applications,1997,9:272~290
    [16] Chen Y., and Medioni G. Object modeling by registration of multiple range images.In: Proc. IEEE Conf. on Robotics and Automation, Sacramento, 1991,2729~2742
    [17] Besl P. J., and McKay H. D. A method for registration of 3-D shapes. IEEE Trans-actions on Pattern Analysis and Machine Intelligence, 1992,14(2):239~256
    [18] Menq C. H., Yau H. T., and Lai G. Y. Automated precision measurement of surfaceprofile in CAD-directed inspection. IEEE Transactions on Robotics and Automation,1992,8(2):268~278
    [19] Ristic M., and Brujic D. E?cient registration of NURBS geometry. Image and VisionComputing, 1997,15:925~935
    [20] Ristic M., and Brujic D. A framework for non-contact measurement and analysis ofNURBS surfaces. Int. J. Manuf. Technol., 1997,14:210~219
    [21] Ainsworth I., Ristic M., and Brujic D. CAD-based measurement path planning forfree-form shapes using contact probes. The International Journal of Advanced Man-ufacturing Technology,2000,16(1):23~31
    [22] Li Q.D., and Gri?ths J. Iterative closest geometric objects registration. Computersand Mathematics with Applications, 2000,40:1171~1188
    [23] Bentley J. L. Multidimensional binary search trees used for associative searching.Communications of the ACM, 1975,18(9):509~517
    [24] Kapoutsis C. A., Vavoulidis C. P., and Pitas I. Morphological iterative closest pointalgorithm. IEEE Transactions on Image Processing, 1999,8(11):1644~1646
    [25] Greenspan M., and Godin G. A nearest neighbor method for e?cient ICP. In:Proceedings Third International Conference on 3-D Digital Imaging and Modeling,2001,:161~168
    [26] Jost T., and Hu¨gli H. A multi-resolution scheme ICP algorithm for fast shape regis-tration. In: Proceedings of the First International Symposium on 3D Data ProcessingVisualization and Transmission (3DPVT 02), Padova, 2002:540~543
    [27] Turk G., and Levoy M. Zippered polygon meshes from range images. In: Proceedingsof the SIGGRAPH, 1994:311~318
    [28] Masuda T., and Yokoya N. A robust method for registration and segmen-tation of multiple range images. Computer Vision and Image Understanding,1995,10(3):295~307
    [29] Blais G., and Levine M. Registering multiview range data to create 3D com-puter objects. IEEE Trans. On Pattern and Machine Intelligence (PAMI),1995,17(8):820~824
    [30] Simon D. A. Fast and Accurate Shape-Based Registration: PhD Thesis. CarnegieMellon University, December 12, 1996
    [31] Chen C. S., Hung Y. P., and Cheng J. B. RANSAC-Based DARCES: A new ap-proach to fast automatic registration of partially overlapping range images. IEEETransactions on Pattern Analysis and Machine Intelligence, 1999,21(11):1229~1234
    [32] Pulli K. Multiview registration for large data sets. In: Proceedings of the 3DIM,1999:160~168
    [33] Neugebauer P. J. Geometric cloning of 3D objects via simultaneous registration ofmultiple range images. In: Proceedings of the International Conference on ShapeModelling and Applications, 1997:130~139
    [34] Rousseeuw P., and Leroy A. Robust regression and outlier detection. Wiley Seriesin Probability and Mathematical Statistics, 1987
    [35] Trucco E., Fusiello A., and Roberto V. Robust motion and correspondence of noisy3-D point sets with missing data. Pattern Recognition Letters, 1999,20:889~898
    [36] Rousseeuw P., and van Zomeren B. Unmasking multivariate outliers and leveragepoints. J. of the American Statistical Association, 1990,85:635~651
    [37] Masuda T., Sakaue K., and Yokoya N. Registration and integration of multiplerange images for 3-D model construction. In: Proceedings of the 13th InternationalConference on Pattern Recognition, 1996: 879~883
    [38] Pulli K. Surface Reconstruction and Display from Range and Color Data: PhDDissertation. Univ. of Washington, 1997
    [39] Chetverikov D., Svirko D., Stepanov D., and Krsek P. The trimmed iterative closestpoint algorithm. In: Proceedings 16th International Conference on Pattern Recog-nition, 2002,3:545~548
    [40] Nishino K., and Ikeuchi K. Robust simultaneous registration of multiple range im-ages. In: The 5th Asian Conference on Computer Vision, Melbourne, Australia,2002:454~461
    [41] Stewart C. V. Covariance-based registration, RPI-CS-TR 02-8 June 24, 2002
    [42] Dorai C., Wang G., Jain A.K., and Mercer C. From images to models: automaticmodel construction from multiple views. In: Proceedings of the ICPR, 1996:770~774
    [43] Dorai C., Wang G., Jain A.K., and Mercer C. Registration and integration of multi-ple object views for 3D model construction. IEEE Transactions on Pattern Analysisand Machine Intelligence, 1998,20(1):83~89
    [44] Feldmar J., Ayache N., and Betting F. 3D-2D projective registration of free-formcurves and surfaces. In: Proceedings Fifth International Conference on ComputerVision, 1995:549~556
    [45] Yamany S. M., Farag A. A. Free-form surface registration using surface signatures.In: Proceedings of the ICCV, 1999:1098~1104
    [46] Sharp G. C., Lee S. W., and Wehe D. K. ICP registration using invariant features.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002,24(1):90~102
    [47] Patrikalakis N. M., and Maekawa T. Shape Interrogation for Computer Aided Designand Manufacturing. Heidelberg: Springer, 2002
    [48] Ko K. H., Maekawa T., and Patrikalakis N. M. An algorithm for optimal free-formobject matching. Computer-Aided Design, 2003,35:913~923
    [49] Ko K. H., Maekawa T., and Patrikalakis N. M. Algorithms for optimal partial match-ing of free-form objects with scaling e?ects. Graphical Models, 2005,67:120~148
    [50] Johnson A., and Kang S. B. Registration and integration of textured 3D data. Tech-nical Report, CRL 96/4 DEC, Cambridge Research Laboratory, 1996
    [51] Weik S. Registration of 3-D partial surface models using luminance and depth in-formation. In:Proceedings., International Conference on Recent Advances in 3-DDigital Imaging and Modeling, 1997:93~100
    [52] Schutz C., Jost T., and Hu¨gli H. Multi-feature matching algorithm for free-form 3Dsurface registration. In: Proceedings Fourteenth International Conference on PatternRecognition, 1998,2:982~984
    [53] Liu Y. H., and Rodrigues M. A. An iterative algorithm for the projective registrationof free form surfaces. In: Proceedings International Conference on Image Processing,2000,1:497~500
    [54] Liu Y. H., Rodrigues M. A., and Wei B.G. A novel method to cope with appear-ing and disappearing points for the projective registration of free-form surfaces. In:Proceedings International Conference on Image Processing, 2001,3:700~703
    [55] Rodrigues M. A., Liu Y. H., and Wei Q. Geometric alignment of two overlappingrange images. In: Proceedings IEEE International Conference on Acoustics, Speech,and Signal Processing, 2001,3:1689~1692
    [56] Rodrigues M. A., and Liu Y. H. Registering two overlapping range images using arelative registration error histogram. In: Proceedings 2002 International Conferenceon Image Processing, 2002,3:841~844
    [57] Liu Y. H., Rodrigues M. A., and Cooper D. Using geometric properties of corre-spondence vectors for the registration of free-form shapes. In: Proceedings 15thInternational Conference on Pattern Recognition, 2000,1:1011~1014
    [58] Liu Y. H., Rodrigues M. A., and Wang Y. Developing rigid motion constraintsfor the registration of free-form shapes. In: Proceedings IEEE/RSJ InternationalConference on Intelligent Robots and Systems, 2000,3:2280~2285
    [59] Liu Y. H., and Rodrigues M. A. Accurate registration of structured data usingtwo overlapping range images. In: Proceedings IEEE International Conference onRobotics and Automation, 2002,3:2519~2524
    [60] Liu Y. H., and Wei B.G. Developing structural constraints for accurate registrationof overlapping range images. Robotics and Autonomous Systems, 2004,47:11~30
    [61] Liu Y. H. Improving ICP with easy implementation for free form surface matching.Pattern Recognition, 37(3):211~226
    [62] Benjemaa R., and Schmitt F. A solution for the registration of multiple 3d pointsets using unit quaternions. In: Fifth European Conference on Computer Vision,Freiburg, Germany, 1998:34~50
    [63] Haralick V. B. Pose estimation from corresponding point data. In: Freeman H.(Ed.),Machine Vision for Inspection and Measurement, New York: Academic Press,1989:1~4
    [64] Li X. M., Yeung M., and Li Z. X. An algebraic algorithm for workpiece localization.In: IEEE Intl. Conf. on Robotics and Automation, 1996:152~158
    [65] Hong J., and Tan X. Method and apparatus for determining position and orientationof mechanical objects. U.S. Patent No. 5208763, 1990
    [66] Lorusso A., Eggert D., and Fisher R. B. A Comparison of Four Algorithms forEstimating 3-D Rigid Transformations. In: Proc. British Machine Vision Conference,Birmingham, 1995:237~246
    [67] Li .Z. X., Gou J. B., and Chu Y. X. Geometric algorithms for workpiece localization.IEEE Transactions on Robotics & Automation, 1998,14(6):864~78
    [68] Hu¨gli H., and Schutz C. Geometric matching of 3D objects: assessing the range ofsuccessful initial configurations. In: Proceedings, International Conference on RecentAdvances in 3-D Digital Imaging and Modeling, 1997:101~106
    [69] Brunnstrom K., and Stoddart A. J. Genetic algorithms for free-form surface match-ing. In: Proceedings of the 13th International Conference on Pattern Recognition,1996,4:689~693
    [70] Yang R. G., and Allen P. K. Registering, integrating, and building CAD modelsfrom range data. In: Proceedings 1998 IEEE International Conference on Roboticsand Automation, 1998,4:3115~3120
    [71] Wyngaerd J. V., Gool L. V., Koch B., and Proesmans M. Invariant-based registra-tion of surface patches. In: Proceedings of the ICCV, 1999:301~306
    [72] Zhang Z. Y., Iterative Point Matching for Registration of Free-Form Curves. Inter-national Journal of Computer Vision, 1994,13(2):119~152
    [73] Tucker T. M., and Kurfess T. R. Newton methods for parametric surface registration,Part II: Experimental validation. Computer-Aided Design, 2003,35(1):115~120
    [74] Boughorbel F., Koschan A., Abidi B., and Abidi M. Gaussian fields: a new criterionfor 3Drigid registration. Pattern Recognition, 2004,37(7):1567~1571
    [75] Luck J., Little C., and Ho? W. Registration of range data using a hybrid simulatedannealing and iterative closest point algorithm. In: Proceedings IEEE InternationalConference on Robotics and Automation, 2000,4:3739~3744
    [76] Chow C. K., Tsui H. T., and Lee T. Surface registration using a dynamic geneticalgorithm. Pattern Recognition, 2004,37:105~117
    [77] Langis C., Greenspan M., and Godin G. The parallel iterative closest point algo-rithm. In: Proceedings Third International Conference on 3-D Digital Imaging andModeling, 2001:195~202
    [78] Dorai C., Wang G., and Jain A. K. Optimal registration of object views us-ing range data. IEEE Transactions on Pattern Analysis and Machine Intelligence,1997,19(10):1131~1138
    [79] Blostein S. D., and Huang T. S. Error analysis in stereo determination of 3D pointposition. IEEE Trans. Pattern Analysis and Machine Intelligence, 1987,9(6):752~765
    [80] Yau H. T., and Menq C. H. A unified least-squares approach to the evalua-tion of geometric errors using discrete measurement data. Intl. J. Mach. ToolsManufact.,1996,36:1269~1290
    [81] Stoddart A. J., Lemke S., Hilton A., and Renn T. Estimating pose uncertainty forsurface registration. Image and Vision Computing, 1998,16(2):111~120
    [82] Lee B. U., Kim C. M., and Park R. H. An orientation reliability matrix for the iter-ative closest point algorithm. IEEE Transactions on Pattern Analysis and MachineIntelligence, 2000,22(10):1205~1208
    [83] Pennec X., and Thirion J-P. A framework for uncertainty and validation of 3Dregistration methods based on points and frames. International Journal of ComputerVision, 1997,25(3),203~229
    [84] Ramos J. A., and Verriest E. I. Total least squares fitting of two point sets inm-D. In: Proceedings of the 36th IEEE Conference on Decision and Control,1997,5:5048~5053
    [85] Williams J., and Bennamoun M. A multiple view 3D registration algorithm withstatistical error modeling. IEICE TRANS. INF. & SYST., 2000,E83-D(8):1662-1670
    [86] Chu Y. X., Gou J. B., and Li Z. X. Localization algorithms: Performance evaluationand reliability analysis. Journal of Manufacturing Systems, 1999,18(2):113~126
    [87] Xiong Z. H., Wang M. Y., and Li Z. X. A computer-aided probing strategy forworkpiece localization. In: Proceedings of the 2003 IEEE International Conferenceon Robotics & Automation, Taipei, Taiwan, 2003:3941~3946
    [88] 周凯. 无夹具制造中工件寻位的一种新方法. 仪器仪表学报,1999,20(1):32~36
    [89] 周凯,林喜荣. 自由曲面轮廓零件的寻位加工方法. 清华大学学报(自然科学版),2000,40(5):40~43
    [90] 周凯, 毛德柱, 张伯鹏. 自寻位数控机床的研究. 机械工程学报,2001,37(5):48~51
    [91] Zhou K., Zhao J.S., and Mao D.Z. Research on an intelligent manufacturing systembased on an information-localizing machining mode. Journal of Materials ProcessingTechnology, 2002,129:597~602
    [92] 胡东明,段广洪,张伯鹏. 非定位、欠定位加工中的三维自由曲面定位算法研究. 中国机械工程,1997,8(1):77~79
    [93] 李剑. 第六章:自由曲面零件寻位自适应检测方法研究. 基于激光测量的自由曲面数字制造基础技术研究:博士学位论文. 杭州:浙江大学,2001
    [94] Yan S. J., Zhou .Y. F. et al. Research on the localisation of the workpieces withlarge sculptured surfaces in NC machining. The International Journal of AdvancedManufacturing Technology, 2004,23(5-6):429~435
    [95] Zhu L. M., Xiong Z. H., Ding H., and Xiong Y. L. A distance function based approachfor localization and profile error evaluation of complex surface. Transactions of theASME. 2004,16:542~554
    [96] 刘阳. 计算制造中的定位与检测理论、方法研究:博士学位论文. 长沙:国防科技大学,2001
    [97] Feng S. C., and Hopp T. H. A review of current geometric tolerancing theories andinspection data analysis algorithms. Technical Report NISTIR 4509, 1991
    [98] Walker R. GIDEP Alert No. X1-A-88-01. Government-Industry Data Exchange Pro-gram, August 22, 1988
    [99] Nasson M. A. Mathematical definition of demensioning and tolerancing principles.In: Dimensioning and Tolerancing Handbook, New York: McGraw-Hill, 1999:7-1~7-15
    [100] Dimensioning and tolerancing, ASME Standard Y14.5M- 1994. New York: TheAmerican Society of Mechanical Engineers, 1994
    [101] Mathematical definition of dimensioning and tolerancing principles, ASME StandardY14.5.1M-1994. New York: The American Society of Mechanical Engineers, 1994
    [102] Yau H. T. Evaluation and uncertainty analysis of vectorial tolerances. PrecisionEngineering, 1997,20:123~137
    [103] 熊有伦. 精密测量中的数学方法. 北京:中国计量出版社,1989
    [104] Murthy T. S. R., and Abdin S. Z. Minimum zone evaluation of surfaces. Int. J. MachTool Des. Res., 1980,20:123~136
    [105] Shunmugam M. S. New approach for evaluating form errors of engineering surfaces.Comp. Aided Design, 1987,19:368~374
    [106] Wang Y. Minimum zone evaluation of form tolerances. Manufacturing Review,1992,5:213~220
    [107] Carr K., and Ferreira P. Verification of form tolerance, Part I: Basic issues, ?atness,and straightness. Precision Engineering, 1995,17:131~143
    [108] Carr K., and Ferreira P. Verification of form tolerances, Part II: Cylindricity andstraightness of a median line. Precision Engineering, 1995,17:144~156
    [109] Choi W., and Kurfess T. R. Dimensional measurement data analysis, Part 1:A zone fitting algorithm. Journal of Manufacturing Science and Engineering,1999,121:238~245
    [110] Choi W., and Kurfess T. R. Dimensional measurement data analysis, Part 2:Minimum zone evaluation. Journal of Manufacturing Science and Engineering,1999,121:246~250
    [111] Weber T., Motavalli S., Fallahi B., and Cheraghi S. H. A unified approach to formerror evaluation. Precision Engineering, 2002,26:269~278
    [112] Traband T. M., Joshi S., Wysk R. A., and Cavalier T. M. Evaluation of straight-ness and ?atness tolerances using the minimum zone. Manufacturing Review,1989,2:189~195
    [113] Yap C. Exact computational geometry and tolerancing metrology. In: Snapshots ofComputational and Discrete Geometry, Tech. Rep. No. SOCS-94.50, 1994
    [114] Novaski O., and Barczak A. L. C. Utilization of Voronoi diagrams for circularityalgorithms. Precision Engineering, 1997,20:188~195
    [115] Huang J. An exact minimum zone solution for three-dimensional straightness eval-uation problems. Precision Engineering, 1999,23:204~208
    [116] Huang J. An exact solution for the roundness evaluation problems. Precision Engi-neering, 1999,23:2~8
    [117] Huang J. An exact minimum zone solution for sphericity evaluation. Computer-Aided Design, 1999,31:845~853
    [118] Samuel G. L., Shunmugam M. S. Evaluation of straightness and ?atness error usingcomputational geometric techniques. Computer-Aided Design, 1999,31:829~843
    [119] Samuel G. L., Shunmugam M. S. Evaluation of circularity from coordinateand form data using computational geometric techniques. Precision Engineering,2000,24:251~263
    [120] Samuel G. L., Shunmugam M. S. Evaluation of sphericity error from form datausing computational geometric techniques. International Journal of Machine Tools& Manufacture, 2002,42:405~416
    [121] Huang J. An e?cient approach for solving the straightness and the ?atness problemsat large number of data points. Computer-Aided Design, 2003,35:15~25
    [122] Devillers O. Computational geometry and discrete computations. Rapport derecherche n? 3533, 1998
    [123] Lai H. Y., Jywe W. Y., Chen C. K., and Liu C. H. Precision modeling of formerrors for cylindricity evaluation using genetic algorithms. Precision Engineering,2000,24:310~319
    [124] Sharma R., Rajagopal K., and Anand S. A genetic algorithm based approachfor robust evaluation of form tolerances. Journal of Manufacturing Systems,2000,19:46~57
    [125] Wen X. L., and Song A. G. An improved genetic algorithm for planar and spatialstraightness error evaluation. International Journal of Machine Tools & Manufacture,2003,43:1157~1162
    [126] Wen X. L., and Song A. G. An immune evolutionary algorithm for spheric-ity error evaluation. International Journal of Machine Tools and Manufacture.2004,44(10):1077~1084
    [127] Chou S. Y., and Sun C. W. Assessing cylindricity for oblique cylindrical features.International Journal of Machine Tools & Manufacture, 2000,40:327~341
    [128] Malysche? A. M., Trafalis T. B., and Raman S. From support vector machine learn-ing to the determination of the minimum enclosing zone. Computer & IndustrialEngineering, 2002,42:59~74
    [129] Prakasvudhisarn C., Trafalis T. B., and Raman S. Support Vector Regression for De-termination of Minimum Zone. Journal of Manufacturing Science and Engineering,2003,125:736~739
    [130] Endrias D. H., and Feng H. Y. Minimum-zone form tolerance evaluation using rigid-body coordinate transformation. Journal of Computing and Information Science inEngineering, 2003,3:31~38
    [131] Zhu L. M., and Ding H. Application of kinematic geometry to computational metrol-ogy. International Journal of Machine Tools & Manufacture, 2003,43:203~215
    [132] Zhu L. M., Ding H., and Xiong Y. L. A steepest descent algorithm for circularityevaluation. Computer-Aided Design, 2003,35:255~265
    [133] Lao Y. Z., Leon H. W., Preparata F. P., and Singh G. Accurate cylindricity evalu-ation with axis-estimation preprocessing. Precision Engineering, 2003,27:429~437
    [134] Orady E., Li S. N., and Chen Y. B. Evaluation of minimum zone straightness by anonlinear optimization method. Journal of Manufacturing Science and Engineering,2000,122:795~797
    [135] Trabend M. T. A Statistical Approach to Tolerance Evaluation Using CoordinateMeasuring Machine Data: PhD thesis. The Pennsylvania State Univ., Dec. 1994
    [136] Yang T. H., Jackman J. Form error estimation using spatial statistics. Journal ofManufacturing Science and Engineering, 2000,122:262~272
    [137] B′arcenas C. C., Gri?n P. M. Parametric-based determination of cylindrical varia-tions in geometric tolerancing. Journal of Manufacturing Science and Engineering,2000,122:549~555
    [138] Sourlier D., and Bucher A. Surface-independent, theoretically exact best fit forarbitrary sculptured, complex, or standard geometries. Precision Engineering,1995,17:101~213
    [139] Yau H. T. A model-based approach to form tolerance evaluation using non-uniform rational B-splines. Robotics and Computer-Integrated Manufacturing,1999,15:283~295
    [140] Bhat V., De Meter E.C. An analysis of the e?ect of datum-establishment methodson the geometric errors of machined features. International Journal of Machine Tools& Manufacture, 2000,40:1951~1975
    [141] Kaiser M. J. The containment model for composite positional tolerance evaluation.Precision Engineering, 2000,24:291~301
    [142] Kaiser M. J., Cheraghi S. H., and Li S. H. The structure of positional tolerance eval-uation, I: Constructive geometric approach. Comput. Methods Appl. Mech. Engrg.,2000,190:1021~1048
    [143] Jiang G. H., and Cheraghi S. H. Evaluation of 3-D feature relating positional error.Precision Engineering, 2001,25:284~292
    [144] Huang J. Evaluation of angular error between two lines. Precision Engineering,2003,27:304~310
    [145] Hopp T. H. Representation of axes for geometric fitting. NISTIR 5897, Septem-ber,1996
    [146] Gou J. B., Chu Y. X., and Li Z. X. A geometric theory of form, profile, and orien-tation tolerances. Precision Engineering, 1999,23:79~93
    [147] Gou J. B., Chu Y. X., Xiong Z. H., and Li Z. X. A geometric method for compu-tation of datum reference frames. IEEE Transactions on Robotics & Automation,2000,16:797~806
    [148] Kim C., and Wyant J. Subaperture test of a large ?at on a fast aspheric surface. J.Opt. Soc. Am., 1981,71:1587
    [149] Thunen J. G., and Kwon O. Y. Full aperture testing with subaperture test optics.In: Wavefront Sensing, Proc. SPIE, 1982,351:19~27
    [150] Hainaut C. R. D., and Erteza A. Numerical processing of dynamic subaperturetesting measurements. Applied Optics, 1986,25(4):503~509
    [151] Chow W. W., and Lawrence G. N. Method for subaperture testing interferogramreduction. Opt. Lett., 1983,8:468~470
    [152] Jensen S. C., Chow W. W., and Lawrence G. N. Subaperture testing approaches: acomparison. Appl. Opt., 1984,23:740~745
    [153] Stuhlinger T. W., Subaperture optical testing: experimental verification, In Con-temporary Optical Instrument Design, Fabrication, and Testing, Proc. SPIE1986,656:118~127
    [154] Chen M. Y., Cheng W. M., and Wang C. W. Multiaperture overlap-scanning tech-nique for large-aperture test. In: Laser Interferometry IV: Computer-Aided Inter-ferometry, Proc. SPIE 1991,1553:626~635
    [155] Cheng W. M., and Chen M. Y. Transformation and connection of subapertures in themultiaperture overlap-sacnning technique for large optics tests. Optical Engineering,1993,32:1947~1950
    [156] Cheng W. M., Lin Y. L., and Chen M. Y. Accuracy analysis of multiaperture overlap-scanning technique (MAOST). In: Interferometry: Techniques and Analysis II, Proc.SPIE, 1993,2003:283~288
    [157] Otsubo M., Okada K., and Tsujiuchi J. Measurement of large plane surface shapewith interferometric aperture synthesis. In: Intl. Symp. on Optical Fabrication, Test-ing, and Surface Evaluation, Proc. SPIE, 1992,1720:444~447
    [158] Chen J. B., Song D. Z., and Zhu R.H. et. al. Large-aperture high-accuracyphase-shifting digital ?at interferometer. In: Proc. SPIE (Interferometry VI),1993,2003:367~375
    [159] Wang Q., Chen J. B., and Zhu R.H. et. al. A New technique for testing large optical?at. In: Proc. SPIE (Interferometry VI), 1993,2003:389~397
    [160] Otsubo M., Okada K., and Tsujiuchi J. Measurement of large plane surface shapesby connecting small-aperture interferograms. Optical Engineering, 1994,33:608~613
    [161] Chen M. Y., and Wu D. Z. Multiaperture overlap-scanning technique formoire metrology. In: Laser Interferometry VIII: Applications, Proc. SPIE,1996,2861:107~112
    [162] Bray M. Stitching interferometer for large plano optics using a standard interferom-eter. In: Optical Manufacturing and Testing II, Proc. SPIE, 1997,3134:39~50
    [163] Tang S. H. Stitching: high-spatial-resolution microsurface measurements over largeareas. In: Laser Interferometry IX: Applications, Proc. SPIE, 1998,3479:43~49
    [164] Wyant J. C., and Schmit J. Large Field of View, High Spatial Resolution, SurfaceMeasurements. Intl. J. of Machine Tools and Manufacture, 1998,38:691~698
    [165] Schmucker M. A., and Schmit J. Selection process for sequentially combining multi-ple sets of overlapping surface profile interferometric data to produce a continuouscomposite map. US Patent #5,991,461; Veeco Corporation, Nov. 23,1999
    [166] Bray M. Stitching interferometer for large optics: recent developments of a system.In: Third International Conference on Solid State Lasers for Application to InertialConfinement Fusion, Proc. SPIE, 1999,3492:946~955
    [167] 郭红卫. 多孔径拼接技术实现360?面形测量:博士学位论文. 上海:上海大学,2001
    [168] Bray M. Stitching Interferometry and Absolute Surface Shape Metrology: Similari-ties. In: Optical Manufacturing and Testing IV, Proc. SPIE, 2001,4501:375~383
    [169] Sj¨oedahl M., and Oreb B. F. Stitching interferometric measurement data for inspec-tion of large optical components. Optical Engineering, 2002,41:403~408
    [170] Assoufid L., Bray M., Qian J., and Shu D. M. 3-D surface profile measurements oflarge x-ray synchrotron radiation mirrors using stitching interferometry. In: X-RayMirrors, Crystals, and Multilayers II, Proc. SPIE, 2002,4782:21~28
    [171] Yu Y. J., and Chen M. Y. Correlative stitching interferometer and its key techniques.In: Interferometry XI: Techniques and Analysis, Proc. SPIE,2002,4777:382~393
    [172] Chen M. Y., Guo H. W., Yu Y. J., and He H. T. Recent developments of multi-aperture overlap-scanning technique. In: Optical Manufacturing and Testing V,Proc. SPIE, 2003,5180:393~401
    [173] 何海涛,郭红卫,于嬴洁,陈明仪. 基于虚拟圆柱的曲面拼接方法. 光学学报,2004,24(7):978~982
    [174] Bray M. Stitching Interferometry: Recent results and Absolute calibration. In: Op-tical Fabrication, Testing, and Metrology, Proc. SPIE, 2004,5252:305~313
    [175] Murphy P.E., Forbes G., Fleig J., Dumas P., and Tricard M. Stitching inter-ferometry: A ?exible solution for surface metrology. Optics & Photonics News,2003,14:38~43
    [176] Fleig J., Dumas P., Murphy P. E., and Forbes G. W. An automated subaperturestitching interferometer workstation for spherical and aspherical surfaces. In: Ad-vanced Characterization Techniques for Optics, Semiconductors, and Nanotechnolo-gies, Proc. SPIE, 2003,5188:296~307
    [177] Dumas P. R., Fleig J., and Forbes G. W., et al. Flexible polishing and metrologysolutions for free-form optics. In: Proc. ASPE Winter Meeting on Free-Form Optics:Design, Fabrication, Metrology, Assembly, 2004:39~44
    [178] Tricard M., Dumas P., and Forbes G. Sub-aperture approaches for asphere polishingand metrology. In: Optical Design and Testing II, Proc. SPIE, 2005,5638:284~299
    [179] Murphy P. E., Fleig J., Forbes G., and Tricard M. High precision metrology of domesand aspheric optics. In: Window and Dome Technologies and Materials IX, Proc.SPIE, 2005,5786,112~121
    [180] Day R. D., Beery T. A., and Lawrence G. N. Sphericity measurements of full spheresusing subaperture optical testing techniques. In: Optical Testing and Metrology,Proc. SPIE, 1986,661:334~341
    [181] Lawrence G. N., and Day R. D. Interferometric characterization of full spheres: datareduction techniques. Applied Optics, 1987,26:4875~4882
    [182] Griesmann U., Soons J., and Wang Q. Measuring form and redius of spheres withinterferometry. CIRP Annals, 2004:451~454
    [183] Liu Y. M., Lawrence G. N., and Koliopoulo C. L. Subaperture testing of asphereswith annular zones. Applied Optics,1988,27(21):4504~4513
    [184] Tronolone M. J., Fleig J. F., Huang C. S., and Bruning J. H. Method of testingaspherical optical surfaces with an interferometer. U.S. Patent #5,416,586, TropelCorporation, 1995
    [185] 白剑, 程上彝. 子孔径检测及拼接的矩阵分析. 上海交通大学学报,1997,31:77~80
    [186] 张蓉竹,杨春林,石琦凯,许乔,蔡邦维. 子孔径拼接干涉检测及其精度分析.光学学报,2003,23:1241~1244
    [187] 张蓉竹. ICF系统光学元件高精度波前检测技术研究:博士学位论文. 成都:四川大学,2003
    [188] 侯溪, 伍凡等. 环形子孔径拼接算法的精度影响因素分析. 光电工程,2005,32(3):20~24
    [189] Boothby W. M. An Introduction to Di?erentiable Manifolds and Riemannian Ge-ometry. California: Academic Press, Revised Second Edition, 2003
    [190] Onishchik A. O., Encyclopaedia of Mathematical Science, Volume 20: Lie Groupsand Lie Algebras I, Berlin: Springer-Verlag, 1998
    [191] Murray R. M., Li Z. X., and Sastry S. S. A Mathematical Introduction to RoboticManipulation. Boca Raton: CRC Press, 1993
    [192] 陈维桓. 微分流形初步. 北京:高等教育出版社,1998
    [193] 黄宣国. 李群基础. 上海:复旦大学出版社,1995
    [194] 林金坤. 拓扑学基础. 北京:科学出版社,2004
    [195] Selig J. M. Geometrical Methods in Robotics. New York: Springer-Verlag, 1996
    [196] O’Connor M. Z., Srinivasan V.,and Jones A. Connected Lie and symmetry sub-groups of the rigid motions: Foundations and classification. IBM Research ReportRC 20512(7/26/96)
    [197] 袁亚湘,孙文瑜. 最优化理论与算法. 北京:科学出版社,1997
    [198] Horst R., Pardalos P. M., and Thoai N. V. Introduction to Global Optimization.Kluwer Academic Publishers, 2nd ed., 2000
    [199] Hu Y. K., and Hathaway R. J. On e?ciency of optimization in fuzzy c-means. Neural,Parallel & Scientific Computations, 2002,10:141~156
    [200] Kolday .T. G., Lewisz R. M., and Torczon V. Optimization by direct search:New perspectives on some classical and modern methods. SIAM REVIEW,2003,45(3):385~482
    [201] Fletcher R. Practical Methods of Optimization, Volume 1:Unconstrained Optimiza-tion. 2nd Ed., New York:John Wiley & Sons, 1980
    [202] Bezdek J. C., and Hathaway R. J. Some notes on alternating optimization. In:Proceedings of the 2002 AFSS International Conference on Fuzzy Systems: Advancesin Soft Computing, Calcutta, India, 2002:288~300
    [203] Pike R. W. Optimization for Engineering Systems. http://www.mpri.lsu.edu
    [204] Reklaitis G. V., Ravindran A., and Ragsdell K., M. Engineering Optimization: Meth-ods and Applications. New York: John Wiley & Sons, 1983
    [205] Hopp T. H. The mathematics of datums. ASPE Newsletter, 1990:4~9
    [206] Hopp T. H. Preprint of “The Language of Tolerances”. In: Quality Through Engi-neering Design. New York: Elsevier, 1993
    [207] Gloub G. H., and Van Loan C. F., 袁亚湘等译. 矩阵计算. 北京:科学出版社,2001,674
    [208] Samuel G. L., Shunmugam M. S. Evaluation of circularity from coordinateand form data using computational geometric techniques. Precision Engineering,2000,24:251~263
    [209] Samuel G. L., Shunmugam M. S. Evaluation of circularity and sphericity from coordi-nate measurement data. Journal of Materials Processing Technology, 2003,139:90~95
    [210] Huang J. A new strategy for circularity problems. Precision Engineering,2001,25:301~308
    [211] Wilson R. H., Brost R. C., and Strip D.R., et al. Considerations for tolerancingaspheric optical components. Applied Optics, 2004,43:57~66
    [212] 刘万勋等编. 大型稀疏线性方程组的解法. 北京:国防工业出版社,1981
    [213] Gander W., and Gautschi W. Adaptive Quadrature - Revisited. BIT,2000,40:84~101
    [214] Hayes J. Dynamic interferometry handles vibration. Laser Focus World, 2002
    [215] Millerd J. E., and Wyant J. C. Simultaneous phase-shifting Fizeau interferometer.US Patent #20050046864, 2005
    [216] Besl P. J. The free-form surface matching problem. In: Machine Vision for ThreeDimensional Scenes, New York: 1990
    [217] Li Q. S. et al., Computer controlled fabrication of free-form glass lens. In: SPIEConference on Optical Manufacturing and Testing III, 1999:203~212
    [218] Timinger A., Muschaweck J., and Riesa H. Designing tailored free-form surfacesfor general illumination. In: Proc. SPIE Design of E?cient Illumination Systems,2003,5186:128~132
    [219] Morgan D. J., and Cook L. Conformal window design with static and dynamicaberration correction. US Patent #6018424, 2000
    [220] Ian. P., and Emmanuelle G. Absolute figure measurements with a liquid-?at refer-ence. Applied Optics, 1998,37(13):2579~2588
    [221] Elssner K-E., Burow R., Grzanna J., and Spolaczyk R. Absolute sphericity measure-ment. Applied Optics, 1989,28(21):4649~4661

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