本研究目的為改良既有的可攜帶式非接觸式表面量測系統，前代系統之擴束裝置為利用兩塊平凸透鏡所組成，導致較邊緣的光線產生畸變，造成輪廓量測時產生較大之誤差；另一方面造成其擴束光源亮度均勻度不佳，也會造成進行粗糙度量測時的精確度受到影響。
本研究對前代系統之光源部分進行改善更換擴束裝置，選用Edmund Optics所生產的59-133擴束鏡，再於擴束鏡前端搭配光圈遮蔽雷射光束外圍較弱的光源，並設計新的遮罩與夾具與擴束裝置做搭配，測試九個點之亮度，九個點之亮度寬度，變異係數僅3.39%。
本量測系統的功能可分為粗糙度量測與輪廓量測兩部分。粗糙度量測部分，本研究設計九個點遮罩，並使用光能量統計法，分析反射光斑亮度資訊找出與實際之粗糙度值間之關係，藉此擬合趨勢方程式，用以預估物件表面粗糙度，本研究發現利用指數型式擬合趨勢方程式於門檻值40時，可靠度達0.99455，可針對0.05μm-0.17μm之試片進行量測。
關於輪廓量測部分，本研究在原本曲面輪廓預估之方程式中，發現入射光點與屏幕距離存在量測上的誤差，嘗試修正原本之關係方程式，並分別對圓柱體、標準鋼球及實驗室自製之鞍型面工件進行實際量測，並利用三次元量測儀之結果進行誤差比對，最大誤差僅0.043mm，可證實本系統相較於前代系統有明顯改善。

This study aims to improve the prototype of a portable non-contact surface roughness and surface profile measurement system. The beam expansion device of the previous system was composed of two plano-convex lenses, which caused the light at the edge to be distorted, bringing about the error generated during the surface profile measurement. Moreover, it degraded the expanded light uniformity of illuminance and influenced the degree of precision of the surface measurement.
In this study, the 59-133 beam expander produced by Edmund Optics has been used to replace the two previously plano-convex lenses, combined the iris diaphragm at the front of the beam expander to hide the weaker laser beam of the edge. A nine-point new mask has been designed to match the laser expander, and the coefficient of variation of the brightness width of the nine points was only 3.39%.
The function of the measurement system was divided into two parts: the surface roughness measurement and surface profile measurement. Regarding the surface roughness measurement, a nine-point mask has been designed to get nine light spots, and the reflected light intensity distribution method has been used to analyze the relationship between the surface roughness value and the reflected light intensity. According to the experimental results, when the threshold value of the measurement system was set as 40, the regression equation had a reliability of 0.99455. The test piece with the surface roughness of 0.05μm-0.17μm can be measured.
Regarding the surface profile measurement, in the relation equation of the original profile prediction, some errors in the distance between the laser light point of incidence and the screen have been modified. The profile of a cylinder, standard steel ball and the saddle surface workpiece have been measured, based on the modified equation. The experiment results showed that a good consistency was obtained between the improved measurement system and the coordinate measuring machine. The maximum error was about 0.043mm, which can be proved that the developed system has been significantly improved compared with the previous system.

[1] C. W. Tang, X.C. Liang, C. P. Zou, “Analysis on Modern Measuring Methods of Curved Surfaces,” SPIE, Vol. 2101, pp.122-124, 1993.
[2] W.C. Tai, M. Chang, “Noncontact Profilometric Measurement of Large-Form Parts,” Optical Engineering, Vol. 35, No. 9, pp.2730-2735, 1996.
[3] Y. Bickel, G. Hausler, M. Mual, “Triangulation with Expanded Range of Depth,” Opt. Eng., Vol. 24, pp.975-977, 1985.
[4] P. Beckmann, A. Spizzichino, “The Scattering of Eletromagnetic Waves from Rough Surfaces,” Pergamon Press Ltd., Chap.1-5,1987
[5] D. J. Whitehouse, “Comparison between Stylus and Optical Methods for Measuring Surfaces.” Annals of the C.I.R.P., Vol. 37, pp. 649-653, 1988.
[6] 修芳仲，「SMC試片表面特性量測法研究」，國立台灣大學機械工程研究所碩士論文，1990。
[7] K. C. Fan, F. J. Shiou, “An optical flatness measurement system for medium-sized surface plates,” Precision Engineering, Vol. 21, pp. 112-197, 1997.
[8] E. Kayahan, H. Oktemb, F. Hacizade, H. Nasibov, O. Gundogdu, “Measurement of surface roughness of metals using binary speckle image analysis,” Tribology International, Vol. 43, pp. 307-311, 2010.
[9] R. Guo, Z. Tao, “Experimental investigation of a modified Beckmann-Kirchhoff scattering theory for the in-process optical measurement of surface quality,” Optik: International Journal for Light and Electron Optics, Vol. 122, No. 21, 2011.
[10] M. Shimizu, H. Sawano, H. Yoshioka, H. Shinno, “Surface texture assessment of ultra-precision machined parts based on laser speckle pattern analysis,” Precision Engineering, Vol. 38, pp. 1-8, 2014.
[11] J. Liu, E.H. Lu, H.A. Yi, P. Ao, “Grinding surface roughness measurement based on image quality assessment,” Journal of Electronic Measurement and Instrumentation, Vol. 30, No. 3, 2016.
[12] H. Kosler, U. Pavlovčič, M. Jezeršek, J. Možina, “Adaptive Robotic Deburring of Die-Cast Parts with Position and Orientation Measurements Using a 3D Laser-Triangulation Sensor,” Strojniski Vestnik/Journal of Mechanical Engineering, Vol. 62, No. 4, pp. 207-212, 2016.
[13] P.A.S. Guru, M.V. Matham, K.H.K. Chan, “Fiber Optic Probe for Surface Roughness Measurement of ALM Samples Based on Laser Speckle Intensity,” IEEE International Conference On Recent Trends In Electronics Information Communication Technology, May 20-21, 2016.
[14] M. Jezeršek, M. Kos, H. Kosler , J. Možina, “Automatic teaching of a robotic remote laser 3D processing system based on laser-triangulation profilometry,” Tehnicki Vjesnik, Vol. 24, No. 1, pp.89-95, 2017.
[15] I. Robles-Urquijo, M. Lomer, L. Rodriguez-Coboand, J. M. Lopez Higuera, “Non-contact vibration analysis using speckle-based techniques,” Proceedings of SPIE - The International Society for Optical Engineering, Vol. 10323, 2017.
[16] S. Shao, X. Tao, X. Wang, “On-machine surface shape measurement of reflective mirrors by ultra-precision turning based on fringe reflection,” Laser and Optoelectronics Progress, Vol. 55, No. 7, 2018.
[17] G. Sajjad, G.K. Saeideh, M. Mohsen, “Nondestructive, fast, and cost-effective image processing method for roughness measurement of randomly rough metallic surfaces,” Journal of the Optical Society of America A, Vol. 35, No. 6, pp 998-1013, 2018.
[18] D. Xu, Q. Yang, F. Dong, S. Krishnaswamy, “Evaluation of surface roughness of a machined metal surface based on laser speckle pattern”, The Institution of Engineering and Technology, Vol. 2018, No. 9, pp. 773-778, 2018.
[19] S. Bharathi, M.M. Ratnam, “Evaluation of 3D surface roughness of milled surfaces using laser speckle pattern,” IOP Conference Series: Materials Science and Engineering, Vol. 530, No. 1, 2019.
[20] T. Wada, S.Koyama, H. Ishizawa, “Simple construction of calibration curve and surface roughness detection in surface roughness detection by speckle contrast method,” Journal of the Illuminating Engineering Institute of Japan, Vol. 103, No. 6, pp. 195-200, 2019.
[21] E. Baradit, C. Gatica, M. Yáñez, J. C. Figueroa, R. Guzmán, C. Catalán,“Surface roughness estimation of wood boards using speckle interferometry,” Optics and Lasers in Engineering, Vol. 128, 2020.
[22] 陳信儒，「以可程式化單一條紋反射法或結構光條紋投射法開發物體表面輪廓量測系統」，機械工程研究所碩士論文，台灣科技大學，2008年。
[23] 詹啟孟，「可攜帶式船用複合材料表面特徵光學量測系統之研製」，機械工程研究所碩士論文，台灣科技大學，2009年。
[24] 賴耀梓，「輕量化可攜式複合材料螺紋印量測器之研製」，機械工程研究所碩士論文，台灣科技大學，2010年。
[25] 羅楚雲，「可攜式表面粗糙度及輪廓之光學量測系統開發」，機械工程研究所碩士論文，台灣科技大學，2012年。
[26] 陳映喬，「可攜式非接觸式表面粗糙度與輪廓量測系統」，機械工程研究所碩士論文，台灣科技大學，2019年。
[27] T.R. Thomas, Rough Surfaces, Imperial College Press, London, pp.3-5, 1999.
[28] ASME B46.1. Surface texture (surface roughness, waviness, and lay), 1995.
[29] 范光照、張郭益，精密量具及機件檢驗，高立圖書有限公司，1998
[30] 林凡異，「光電實驗講義」，國立清華大學，電機工程學系/光電工程研究所，2000
[31] 鍾國亮，「影像處理與電腦視覺」，東華書局股份有限公司，2015
[32] N. Otsu, “A threshold selection method from gray level histogram,” IEEE Trans. on Systems, Man, and Cybernetics, SMC-9, pp. 62-66, 1979.
[33] Z-Laser Corporation Germany, “ZM18-DM Laser,” https://z-laser.com/en/product/laser-modules/zm-laser-family/zm18/
[34] 銓州光電，「線上目錄 -光圈」，https://www.onset-eo.com/product/iris-diaphragm/
[35] The Imaging Source,「DMK33UX25工業相機」 https://reurl.cc/NelZ9
[36] MORITEX 產品，http://cn.moritex.com/model/1-1-2-4-3-03.html
[37] ASSAB瑞典優質鋼材，台灣盛百股份有限公司，2003