簡易檢索 / 詳目顯示

研究生: 康大為
Kan, Ta-Wei
論文名稱: 柳杉心材、過渡材與邊材管胞效應之探討
Investigation of Tracheid Effect of Heartwood, Transitionwood and Sapwood of Japanese Cedar
指導教授: 王偉中
Wang, Wei-Chung
口試委員: 楊德新
Yang, Te-Hsin
李昌駿
Lee, Chang-Chun
學位類別: 碩士
Master
系所名稱: 工學院 - 動力機械工程學系
Department of Power Mechanical Engineering
論文出版年: 2021
畢業學年度: 109
語文別: 中文
論文頁數: 196
中文關鍵詞: 繞射光學元件管胞效應木材纖維掃描平臺邊材心材過渡材柳杉四點抗彎實驗
外文關鍵詞: DOE, Tracheid Effect, Fiber Orientation Scanning System, Sapwood, ransitionwood, Heartwood, Japanese Cedar, Four Point Bending Test
相關次數: 點閱:4下載:0
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 柳杉為臺灣及日本高經濟價值樹種,在臺灣木造建築中常使用柳杉為建材,在安全考量上,柳杉之強度與特性極其重要。以往大多使用接觸式方法進行柳杉木材分等,本研究使用非接觸檢測之方式對柳杉進行光學掃描。本研究發現掃描結果會因邊材、過渡材及心材特性不同而有所不同,又柳杉不同於歐洲與美洲之經濟樹種,柳杉於樹齡小時即有心材化現象,故本研究應用管胞效應於柳杉之邊材、過渡材及心材以探討光學掃描結果用於預測彈性模數(Modulus of Elasticity, MOE)之影響。
      本研究改良既有之木材纖維掃描平臺光路系統,於光路系統加上光學繞射元件(Diffractive Optical Element, DOE),由原本單點雷射點掃描改良成單排11點掃描,大幅提升掃描速率。在木材掃描檢測方面,本研究以橢圓擬合管胞效應於木材表面所形成之雷射散斑圖形(Speckle Pattern),於柳杉邊材、過渡材及心材可得不同的橢圓短長軸比(Shape Factor, SF),並以全域色階圖、單一平均法、區域平均法及曲線擬合法對SF值分析,觀察柳杉中邊材、過渡材及心材SF值之變化趨勢。本研究另將木材試片切片進行顯微影像觀察,確認本研究所挑選板材試片之管胞纖維角度並非影響SF值之因素,而邊材、過渡材與心材之SF值不同為管胞腔體大小不同所造成。本研究以木材纖維掃描平臺量測所得之SF值進而預測MOE並與四點抗彎實驗所得之MOE比較。


    Japanese Cedar is a tree species with high economic value in both Taiwan and Japan. Japan Cedar has been often used as the building material in Taiwan's wooden structures, therefore, its strength and material characteristics are very important. Non-contact inspection technique was used in this research to scan the Japanese Cedar. It was found that the scan results vary with the material characteristics of sapwood, transitional wood and heartwood. Moreover, different from other economic tree species in Europe and America, the formation of heartwood inside Japanese Cedar occurs at rather earlier wood age. To understand the effect on the prediction of modulus of elasticity(MOE), in this research, the tracheid effect was employed on investigation of the scanned results of sapwood, transitional wood and heartwood of Japanese Cedar, respectively.
    In this research, the optical system of an existing fiber orientation scanning system (FOSS) was improved. A diffractive optical element (DOE) was added in the existing FOSS. The scanning rate has been significantly improved from the original single-point laser spot scanning to a single-row 11-point scanning. An ellipse was adopted to fit the laser speckle pattern formed by the tracheid effect on the wood surface. Different shape factors (SFs) of the ellipse were obtained for sapwood, transitional wood and heartwood, respectively. The obtained SF values were analyzed by global chromaticity diagram, single average method, area average method and curve fitting method, respectively. Furthermore, tracheid orientation was also investigated by using the microscope. Based on the observation from the microscope, it was confirmed that the fiber angle of the wood specimens selected in this research will not affect the SF values. The difference of SF values of sapwood, transitional wood and heartwood is caused by the different cavity sizes of the tracheid. The predicted MOEs were calculated by using the SF values measured by the FOSS and were compared with the MOEs obtained from the four-point bending test.

    摘要 ii 英文摘要 iv 目錄 vi 表目錄 x 圖目錄 xi 一、簡介 1 1.1 研究動機 1 1.2 研究目的 2 1.3 研究流程 2 二、文獻回顧 4 2.1 木材簡介 4 2.2 木材品質判定方法 6 2.3 管胞效應 8 2.4 邊材與心材 10 三、實驗原理 16 3.1 橢圓方程式 16 3.2 木材之MOE 19 3.2.1 平面內及潛入角度與木材MOE之關係 19 3.2.2 木材纖維角度與木材剛性之關係 27 3.3 光學繞射元件 27 3.3.1 光的繞射原理 27 3.3.2 DOE設計原理 30 3.4 抗彎機械應力分等 32 四、實驗裝置 34 4.1 實驗樹種與試片 34 4.2 實驗裝置與架設 36 4.2.1 光源選擇 36 4.2.2 光學架設 36 4.2.3 三軸位移平臺 37 4.2.4 數位影像分析 38 4.2.5 顯微影像觀察 38 4.2.6 四點抗彎木材MOE測定 38 4.3 實驗設備 39 五、實驗流程 43 5.1 掃描平臺量測程序 43 5.1.1 龍門架設運作穩定度測試步驟 43 5.1.2 木材纖維角度檢測程序 44 5.1.3 掃描平臺再現性實驗測試程序 45 5.1.4 板材試片掃描 46 5.2 SF值分析方法 46 5.3 以光學顯微鏡觀察木材纖維角度 49 5.4 四點抗彎木材MOE之測定 50 六、結果與討論 52 6.1 龍門架設運作穩定度測試 52 6.2 DOE測試 52 6.3 木材纖維對雷射散斑圖形之影響 53 6.3.1 掃描平臺之重複性量測 53 6.3.2 橫跨板材掃描之結果 53 6.3.2.1 板材試片A 54 6.3.2.2 板材試片B 58 6.3.2.3 板材試片C 61 6.4 木材切片光學顯微鏡觀察 67 6.5 四點抗彎實驗 68 6.5.1 四點抗彎實驗結果分析 68 6.5.2 試片斷裂方式之探討 71 七、結論與未來展望 73 7.1 結論 73 7.2 未來展望 76   表目錄 表2.1 木材屬性與實際木材強度之決定係數R2 [5] 86 表4.1 板材A四點抗彎試片尺寸、密度及E4PB 87 表4.2 板材B四點抗彎試片尺寸、密度及E4PB 88 表4.3 板材C四點抗彎試片尺寸、密度及E4PB 89 表6.1 重複性量測之SFavg與SFtotal,avg差異值 90 表6.2 四種SF值分析方法優缺點 91 表6.3 各板材試片之R2 92 表6.4 針葉樹產生心材之年齡[21] 93 表6.5 顯微觀察試片角度 94   圖目錄 圖1.1 DOE光路系統效果 95 圖2.1 樹木結構圖 95 圖2.2 樹幹橫剖面示意圖[4] 96 圖2.3 含節點柳杉徑切面影像 97 圖2.4 樹枝生長示意圖[5] 98 圖2.5 樹木座標系統[2] 98 圖2.6 四分切法與平切法[6] 99 圖2.7 木材之應力-應變關係曲線[16] 99 圖2.8 管胞效應形成示意圖與實際影像[2] 100 圖2.9 針葉樹管胞與闊葉樹導管比較圖[19] 100 圖2.10 邊材、過渡材及心材內部之早材及晚材水分分佈圖[25] 101 圖2.11 柳杉過渡材 102 圖2.12 大山櫻橫向剖面圖[27] 102 圖3.1 橢圓示意圖[2] 103 圖3.2 座標系統轉換示意圖[29] 103 圖3.3 局部座標系統轉換至全域座標系統之示意圖[2] 104 圖3.4 座標軸轉換示意圖[2] 104 圖3.5 切向表面木材纖維方向與 之關係圖[31] 105 圖3.6 Huygens理論示意圖[32] 105 圖3.7 繞射座標關係圖[32] 106 圖3.8 四階相位DOE製程示意圖[34] 106 圖3.9 不同相位階數繞射元件外觀與繞射效率之比較[67] 107 圖3.10 抗彎實驗架設圖[36] 107 圖3.11 四點抗彎實驗示意圖[41] 108 圖4.1 板材試片 109 圖4.2 平切法製成板材 112 圖4.3 板材區域劃分 113 圖4.4 切片用刀片 114 圖4.6 波長808 nm近紅外光二極管雷射 118 圖4.7 光譜儀測試結果 119 圖4.8 光纖準直器 119 圖4.9 掃描平臺實景 120 圖4.10 掃描平臺之光路系統示意圖 121 圖4.11 孔徑0.8-1.2 mm可調式光圈 122 圖4.12 雷射經DOE形成11點有效光點 122 圖4.13 NIR相機 123 圖4.14 ZEISS Demonesion 2/35-高精度鏡頭 123 圖4.15 緊急開關實景圖 124 圖4.16 纖維掃描人機介面 125 圖4.17 反射式光學顯微鏡 126 圖4.18 高感光生物相機 127 圖4.19 倍率10倍物鏡 127 圖4.20 以特徵點拼接顯微影像 128 圖4.21 材料試驗機 129 圖4.22 位移計 130 圖4.23 四點抗彎實驗架設 131 圖4.24 NIR相機與黑白相機在各波長之光子接收率 132 圖5.1 試片掃描與四點抗彎實驗流程圖 133 圖5.2 以光學顯微鏡觀察纖維角度之流程圖 134 圖5.3 3D-DIC架設示意圖 135 圖5.4 隨機斑點圖 135 圖5.5 影像校正用校正板 136 圖5.6 VIC-3D使用介面 137 圖5.7 龍門移動示意圖 138 圖5.8 再現性實驗掃描區域 139 圖5.9 重複性實驗之每次取得平均SF值(SFavg)方法示意圖 140 圖5.10 板材無節點區域 141 圖5.11 雷射點間距 141 圖5.12 掃描區域移動示意圖 142 圖5.13 以橢圓擬合之雷射散斑圖形之SF值誤差[41] 143 圖5.14 單一平均法掃描區域 144 圖5.15 區域平均法掃描區域 145 圖5.16 三點抗彎與四點抗彎實驗於各跨距剪力所造成之影響[58] 146 圖6.1 龍門架設移動穩定度結果分析 147 圖6.2 DOE測試結果 152 圖6.3 圖像11點且雜訊比1:230之DOE 154 圖6.4 龍門架設移動重複性結果 155 圖6.5 板材試片掃描之流程 156 圖6.7 試片A7 全域SF值全域色階圖 157 圖6.8 板材試片A7三種折線圖SF值結果 158 圖6.9 板材A7多項式曲線擬合與Optimization擬合結果比較 159 圖6.11 試片A8 全域SF值全域色階圖 160 圖6.12 板材試片A8三種折線圖SF值結果 161 圖6.13 板材A8多項式曲線擬合與Optimization擬合結果比較 162 圖6.14 板材試片A8三種折線圖SF值結果 163 圖6.15 試片A9掃描範圍 164 圖6.16 試片A9全域SF值全域色階圖 164 圖6.17 板材試片A9三種折線圖SF值結果 165 圖6.18 板材A9多項式曲線擬合與Optimization擬合結果比較 166 圖6.19 試片B8掃描範圍 167 圖6.20 試片B8全域SF值全域色階圖 167 圖6.22 板材B8多項式曲線擬合與Optimization擬合結果比較 169 圖6.23 試片B9掃描範圍 170 圖6.24 試片B9全域SF值全域色階圖 170 圖6.25 板材試片B9三種折線圖SF值結果 171 圖6.26 板材B9多項式曲線擬合與Optimization擬合結果比較 172 圖6.27 試片B10掃描區域 173 圖6.28 試片B10全域SF值全域色階圖 173 圖6.29 板材試片B10三種折線圖SF值結果 174 圖6.30 板材B10多項式曲線擬合與Optimization擬合結果比較 175 圖6.31 試片C8掃描區域 176 圖6.32 試片C8全域SF值全域色階圖 176 圖6.33 板材試片C8三種折線圖SF值結果 177 圖6.34 板材C8多項式曲線擬合與Optimization擬合結果比較 178 圖6.35 試片C9掃描區域 179 圖6.36 試片C9全域SF值全域色階圖 179 圖6.37 板材試片C9三種折線圖SF值結果 180 圖6.38 板材C9多項式曲線擬合與Optimization擬合結果比較 181 圖6.42 板材C10多項式曲線擬合與Optimization擬合結果比較 184 圖6.43 木材顯微影像 185 圖6.44 邊材、過渡材、及心材顯微影像 186 圖6.45 以板材試片A8為背景之E4PB、Ex與SF值之比較 189 圖6.46 以板材試片B9為背景之E4PB、Ex與SF值之比較 190 圖6.47 以板材試片C9為背景之E4PB、Ex與SF值之比較 191 圖6.48 MFA與年輪至髓心距離之關係[59] 192 圖6.49 MOE與MFA之關係[60] 192 圖6.50 板材試片A8 193 圖6.51 板材試片B9 193 圖6.52 板材試片C9 194 圖6.53 因正向應力斷裂之四點抗彎試片 195 圖6.54 由早材與晚材交界處斷裂之四點抗彎試片 195 圖6.55 四點抗彎實驗架設之剪力及彎矩圖 196

    [1] 智慧綠建築資訊網, "Website:http's://Sartre/art?no=41&Sub=%E 7%B 0%A 1%E 8%A 6%81%E 4%BB%8 B%E 7%B 4%B 9.," 2020/08.
    [2] 鄭宇倢, “木材彈性模數光學掃描方法量測之研究,” 動力機械工程學系碩士論文, 國立清華大學, 2019.
    [3] 王松永、丁昭義, 林產學, 臺灣商務印書館, 臺北市新店區復興路43號8樓.
    [4] Glos P. and Burger N., “Maschinelle Sortierung Von Frisch Eingeschnittenem Schnittholz (Machine Strength Grading of Green Sawn Timber),” Holz als Roh- und Werkstoff, Vol. 56, pp. 319-329, 1998.
    [5] Shigo A. L., A New Tree Biology - Facts, Photos, and Philosophies on Trees and Their Problems and Proper Care, Shigo and Trees, Associates, Durham, New Hampshire, USA, 1986.
    [6] Core77, https://www.core77.com/posts/24891/How-Logs-Are-Turned-Into-Boards-Part-2-Quartersawn, Accessed: Aug., 2020.
    [7] DIN EN 14081-1, “Timber Structures – Strength Graded Structural Timber with Rectangular Cross Section,” European Committee for Standardization, 2016.
    [8] Lukacevic M., Füssl J., and Eberhardsteiner J., “Discussion of Common and New Indicating Properties for the Strength Grading of Wooden Boards,” Wood Science and Technology, Vol. 49, pp. 551-576, 2015.
    [9] CNS451, “Wood - Determination of Density for Physical and Mechanical Tests.”
    [10] CNS454, “Wood - Determination of Static Bending Properties,” Chinese National Standards, Bureau of Standards.
    [11] CNS455, “Wood – Determination of Ultimate Shearing Stress Parallel to Grain,” Chinese National Standards, Bureau of Standards.
    [12] Lei Y. C., Zhang S. Y., and Jiang Z., “Models for Predicting Lumber Bending MOR and MOE Based on Tree and Stand Characteristics in Black Spruce,” Wood Science and Technology, Vol. 39, pp. 37-47, 2005.
    [13] Olsson A., Oscarsson J., Johansson M., and Källsner B., “Prediction of Timber Bending Strength on Basis of Bending Stiffness and Material Homogeneity Assessed from Dynamic Excitation,” Wood Science and Technology, Vol. 46, pp. 667-683, 2011.
    [14] Roblot G., Bléron L., Mériaudeau F., and Marchal R., “Automatic Computation of the Knot Area Ratio for Machine Strength Grading of Douglas-Fir and Spruce Timber,” European Journal of Environmental and Civil Engineering, Vol. 14, pp. 1317-1332, 2010.
    [15] Olsson A., Oscarsson J., Serrano E., Källsner B., Johansson M., and Enquist B., “Prediction of Timber Bending Strength and in-Member Cross-Sectional Stiffness Variation on the Basis of Local Wood Fibre Orientation,” European Journal of Wood and Wood Products, Vol. 71, pp. 319-333, 2013.
    [16] Elghazouli A. Y., Seismic Design of Buildings to Eurocode 8, 2nd ed., CRC Press, Boca Raton, FL, 2017.
    [17] Nyström J., “Automatic Measurement of Fiber Orientation in Softwoods by Using the Tracheid Effect,” Computers and Electronics in Agriculture, Vol. 41, pp. 91-99, 2003.
    [18] Zhou J. and Shen J., “Ellipse Detection and Phase Demodulation for Wood Grain Orientation Measurement Based on the Tracheid Effect,” Optics and Lasers in Engineering, Vol. 39, pp. 73-89, 2003.
    [19] Zimmermann M. H., "Conducting Units: Tracheids and Vessels," Xylem Structure and the Ascent of Sap, pp. 4-20, Springer Berlin Heidelberg, Berlin, Heidelberg, Germany, 1983.
    [20] Simonaho S. P. and Silvennoinen R., “Sensing of Wood Density by Laser Light Scattering Pattern and Diffractive Optical Element Based Sensor,” Journal of Optical Technology, Vol. 73, pp. 170-174, 2006.
    [21] Luo B, He R, and Y Y., “A Review of Physiological Function of Sapwood and Formation Mechanism of Heartwood,” Journal of Beijing Forestry University, pp. 40:120-129, 2018.
    [22] Baas P., “A New Multilingual Glossary of Terms Used in Wood Anatomy,” IAWA Bulletin, New Series, Vol. 6, pp. 83, 1983.
    [23] Rais A., Ursella E., Vicario E., and Giudiceandrea F., “The Use of the First Industrial X-Ray CT Scanner Increases the Lumber Recovery Value: Case Study on Visually Strength-Graded Douglas-Fir timber,” Annals of Forest Science, Vol. 74, pp. 28-1-9, 2017.
    [24] Nobuchi T and H H., “Physiological Features of the" White Zone" of Sugi (Cryptomeria Japonica D. Don)-Cytological Structure and Moisture Content,” Mokuzai Gakkaishi, Vol. 29, pp. 824-832, 1983.
    [25] Kuroda K., Yamashita K., and Fujiwara T., “Cellular Level Observation of Water Loss and the Refilling of Tracheids in the Xylem of Cryptomeria Japonica During Heartwood Formation,” Trees, Vol. 23, pp. 1163, 2009.
    [26] Nagai S. and Utsumi Y., “The Function of Intercellular Spaces Along the Ray Parenchyma in Sapwood, Intermediate Wood, and Heartwood of Cryptomeria Japonica (Cupressaceae),” American Journal of Botany, Vol. 99, pp. 1553-1561, 2012.
    [27] Higuchi T., Biochemistry and Molecular Biology of Wood, Springer Science & Business Media, Berlin, Heidelberg, Germany, 2012.
    [28] 林鳳美, 千古圓錐曲線探源, 三民書局, 臺北市復興北路386號, 2018.
    [29] Hu M., “Local Variation in Bending Stiffness in Structural Timber of Norway Spruce: for the Purpose of Strength Grading,” Master Thesis, Department of Building Technology, Linnaeus University Press, Växjö, Sweden, 2014.
    [30] Johansson C. J., Brundin J., and Gruber R., Stress Grading of Swedish and German Timber - A Comparison of Machine Stress Grading and Three Visual Grading Systems, SP Report: 1992:23, Swedish National Testing and Research Institute, 1992.
    [31] Hu M., “Studies of the Fibre Direction and Local Bending Stiffness of Norway Spruce: Timber for Application on Machine Strength Grading,” Ph. D. Dissertation, Department of Building Technology, Linnaeus University Press, Växjö, Sweden, 2018.
    [32] Goodman J., Introduction to Fourier Optics, 2nd ed., McGraw Hill, New York, U.S.A, 1968.
    [33] Herzig H. P., Micro-Optics: Elements, Systems and Applications, CRC Press, Switzerland, 1997.
    [34] 張勝雄、楊慶忠和陳信川, “多光束分光繞射光學元件(DOE)之設計,” 遠東學報第十九期, 2001.
    [35] 金國潘、嚴瑛白和鄔敏賢, 二元光學, 國防工業出版社, 北京市海碇區紫竹院南路, 1998.
    [36] Johansson C. J., "Chapter 3: Grading of timber with respect to mechanical properties," Timber Engineering, S. Thelandersson and H. J. Larsen, eds., Wiley, New York, 2003.
    [37] Xia P., Liu S., Zhou L., and Xu B., “A Measurement Method of Wood Growth Ring Density Based on X-Ray Combined Image Processing,” Scientia Silvae Sinicae, Vol. 43, pp. 61-66, 2007.
    [38] 李佳如、楊德新, “應用非破壞檢測技術評估杉木集成元之抗彎性質,” 林業研究季刊, Vol. 32, pp. 45-60, 2010.
    [39] CNS14633, “Softwood Sawn Lumber and Finger Jointed Lumber Used in Platform Construction by Machine Stress Rating,” Chinese National Standards, Bureau of Standards, 2019.
    [40] Borgström E. and Karlsson R., Structural Aspects of Timber Construction, Swedish Forest Industries Federation, Stockholm, Sweden, 2016.
    [41] Kuo T.-Y., “ Multiscale Investgation of Mechanical Behavior of Wood by Using Characteristics of Japanese Cedar,” Ph. D. Dissertation, Department of Power Mechanicals Engineering, National Tsing Hua University, Taiwan, Republic of China, 2020.
    [42] CNS450, “Wood-Sampling Methods and General Requirements for Physical and Mechanical Tests,” Chinese National Standards, Bureau of Standards.
    [43] CNS442-O1001, “Classification of Timber,” Chinese National Standards, Bureau of Standards.
    [44] Changchun New Industries Optoelectronics Technology, https://optics.org/buyers/company/C000015007, Accessed: Dec., 2020.
    [45] Thorlabs, https://www.thorlabs.com/, Accessed: Dec., 2020.
    [46] 迪歐伊工作坊, http://www.doeopticalworkshop.com.tw/, Accessed: Dec., 2020.
    [47] iDS, https://en.ids-imaging.com/, Accessed: Dec., 2020.
    [48] ZEISS, https://www.zeiss.com/corporate/int/home.html, Accessed: Dec., 2020.
    [49] 晶基科技有限公司, https://data.bznk.com, Accessed: Dec., 2020.
    [50] National Instruments, https://www.ni.com/, Accessed: Dec., 2020.
    [51] OLYMPUS, https://www.olympus.com.tw/, Accessed: Dec., 2020.
    [52] 智盛生物科技有限公司, http://www.pentagontek.com/index.php, Accessed: Dec., 2020.
    [53] 臺灣弘達儀器公司, http://www.twredstar.com/, Accessed: Dec., 2020.
    [54] Mitutoyo, https://www.mitutoyo.com.tw/, Accessed: Dec., 2020.
    [55] MathWorks - Makers of MATLAB and Simulink, https://www.mathworks.com/, Accessed: Jan., 2019.
    [56] Correlated Solutions, Inc., South Carolina, USA, www.correlatedsolutions.com/vic-3d/, Accessed: Feb., 2019.
    [57] 龍格現象, https://en.wikipedia.org/wiki/Runge%27s_phenomenon, Accessed: Jan., 2021.
    [58] Jozsef B. and Jayne B. A., Mechanics of Wood and Wood Composites, Van Nostrand Reinhold, New York, USA, 1982.
    [59] Matsumura Y., Murata K., Ikami Y., Ohmori M., and Matsumura J., “Application of the Wood Properties of Large-Diameter Sugi (Cryptomeria Japonica) Logs to Sorting Logs and Sawing Patterns,” Journal of Wood Science, Vol. 59, pp. 271-281, 2013.
    [60] Ando K., Mizutani M., Toba K., and Yamamoto H., “Dependence of Poisson’s Ratio and Young’s Modulus on Microfibril Angle (MFA) in Wood,” Holzforschung, Vol. 72, pp. 321-327, 2018.
    [61] Johansson C.-J., Brundin J., and Gruber R., Stress Grading of Swedish and German Timber. A Comparison of Machine Stress Grading and Three Visual Grading Systems, 1992.
    [62] Larsson D., Ohlsson S., Perstorper M., and Brundin J., “Mechanical Properties of Sawn Timber from Norway Spruce,” Holz Als Roh-Und Werkstoff, Vol. 56, pp. 331-338, 1998.
    [63] Steiger R. and Arnold M., “Strength Grading of Norway Spruce Structural Timber: Revisiting Property Relationships Used in EN 338 Classification System,” Wood Science and Technology, Vol. 43, pp. 259-278, 2009.
    [64] Castéra P., Faye C., and Ouadrani A. E., “Prevision of the Bending Strength of Timber with a Multivariate Statistical Approach,” Annales of Forest Science, Vol. 53, pp. 885-896, 1996.
    [65] Ranta-Maunus A., Denzler J., and Stapel P., Strength of European Timber, Part 2 - Properties of Spruce and Pine tested in Gradewood Project, VTT Working Papers 179, VTT Technical Research Centre of Finland, Espoo, Finland, 2011.
    [66] Divos F. and Kiss S., “Strength Grading of Structural Lumber by Portable Lumber Grading - Effect of Knots,” The Future of Quality Control for Wood & Wood Products - the Final Conference of COST Action E53, Edinburgh, 2010.
    [67] 林政穎, “多功能彩色共焦干涉系統之研發,” 動力機械工程學系碩士論文, 國立清華大學, 2019.

    QR CODE