在傳統的反覆載重實驗中，若油壓致動器需要夾治具轉接後方與試體連接時，常使用外部位移計做為致動器位移控制回饋訊號，以確保試體達到預期的變形。在實驗進行的過程中，若位移計與試體的連接脫落，無法將正確位移訊號傳回控制器，恐造成致動器失控而導致實驗失敗。此外，對於近十公尺高度或夾治具架設較複雜的實驗試體，常不容易準確且安全地架設外部位移計。有鑑於此，本研究應用影像量測技術，透過即時運算機器分析試體的位移反應，並將其回饋至致動器控制器進行位移控制，不僅可以避免因架設外部位移計鬆脫導致的實驗風險，也可以不受限架設外部位移計的工作空間，有效地進行非接觸式之量測。
本研究使用LabVIEW做為程式的開發軟體，LabVIEW為一種圖形化程式編譯平台，以使用者電腦當作PXI控制器與MTS致動器控制器溝通的媒介，撰寫LabVIEW的影像量測程式。實驗時將目標物標定於試體上，藉由高速相機拍攝並即時計算目標物的位移量，計算出的位移量透過光纖共享記憶體，以數位訊號的形式直接與致動器控制器進行數據的交換，以達到即時位移回饋控制。實驗驗證結果顯示，本研究所開發的技術可成功應用於靜態反覆載重實驗以及動態位移加載實驗。

Generally, an external displacement transducer is essential to measuring specimen deformation as displacement feedback for controlling the servo-hydraulic actuator on condition that fixtures are used to connect the actuator to the specimen for structural testing. This approach is called external displacement control which is frequently adopted in structural testing in order to ensure that the specimen deformation meets the predefined displacement profile accurately. However, if the connection between the displacement transducer and specimen is loosen, incorrect feedback displacement could result in out of control of the actuator and fail the structural testing.
In this study, image-based analysis technology has been applied to displacement feedback control of servo-hydraulic actuators for structural testing. A high-speed camera with frame rates in excess of 340 frames per second was setup to capture images of a marker installed on the specimen during the test. The captured images were sent to a NI PXI running LabVIEW to calculate the specimen displacement in real time. This displacement was then sent to the digital controller of the actuator through the Shared Common Random Access Memory Network (SCRAMNet) interface. The digital controller utilized the displacement as the feedback for displacement control of the actuator, forming a closed-loop control system. Experimental results demonstrate that the proposed image-based technology for feedback control of the actuator complete quasi-static cyclic loading tests and dynamic-loading tests successfully and stably with exceptional control performance.

考文獻
[1] Yuan-Sen Yang, Chiun-lin Wu, Chin-Hsiung Loh, Chung-Ming Yang, Wen-Hsiang Tu, Ming-Hsiang Shih, Shih-Heng Tung, Philippe Caperan (2008) “Preliminary Study on Image-based Measurement.”NCREE-08 ,13：1-47
[2] Yuan-Sen Yang, Chang-Wei Huang and Chiun-lin Wu (2012) “Image-based Surface Strain Field Measurement in an RC-Wall Cyclic Test.”, Earthquake Engng Struct. , 41:1-17
[3] Chamindalal Sujeewa Lewangamage, Masato Abe, Yozo Fujino, Junji Yoshida (2004) “Strain field measurements of rubber by image analysis and design criteria for laminated rubber bearings (LRB)” Earthquake Engng Struct. Dyn. , 33:445-464
[4] Chiun-lin Wu, Wu-Wei Kuo, Yuan-Sen Yang, Shyh-Jiann Hwang, Kenneth J. Elwood, Chin-Hsiung Loh, Jack P. Moehle (2009) “ Collapse of a nonductile concrete frame: Shaking table tests”, Earthquake Engng Struct. Dyn ,38:205-224
[5] 石康，葉宏，胡安燦，周雷，孫(2014) “ A New Method for Machine Vision Calibration and Rectification Based on LabVIEW” 中國激光雜誌, 51:1-10
[6] Yuan-Sen Yang (2019) “ Measurement of Dynamic Responses from Large Scale Shake Table Tests by Analyzing Non-Synchronized Videos”, MDPI, 19:1-28
[7] 莊權德 (2007) “ Design and Implementation of Real-Time Stereo Vision Target Tracking System”，南台科技大學電機工程研究所碩士學位論文：1-66
[8] Ming-Chih Lu, Pei-Chun Chang, Cheng-Pei Tsai (2006) “A Real-Time Object Tracking System Using the Image Recognition” 聖約翰科技大學電子工程系碩士學位論文：1-16
[9] 魏逢城 (2008) “Design And Development Of An Automatic Optical Inspection Machine For Scrolls” 國立交通大學機械工程學系碩士論文：1-84
[10] 白楚平(2017) “ Design And Development Of An Automatic Optical Inspection Machine For Scrolls” 國立臺灣海洋大學機電與機械工程學系碩士學位論文：1-56
[11] 林偉超(2012) “ Design And Development Of An Automatic Optical Inspection Machine For Scrolls” 國立勤益科技大學機械工程系在職碩士班碩士論文：1-117
[12] 邱俊智(2009) “A Study of Machine Vision Systems for Pattern Matching Inspection and Pattern Size Measurement” 國立勤益科技大學機械工程系碩士論文：1-92
[13] Rubén Posada-Gómez,Oscar Osvaldo Sandoval-González, Albino Martínez Sibaja, Otniel Portillo-Rodríguez, Giner Alor-Hernández(2011) “ Digital Image Processing Using LabVIEW”, Instituto Tecnológico de Orizaba, Departamento de Postgrado e Investigación：1-21
[14] Asoke K. Nandi,N. Sujatha R. Menaka, John Sahaya Rani Alex(2018) “Computational Signal Processing and Analysis” Lecture Notes in Electrical Engineering：407-411
[15] Rahul B. Diwate, Satish J. Alaspurkar(2013) “Study of Different Algorithms for Pattern Matching” International Journal of Advanced Research in Computer Science and Software Engineering,3：2-7
[16] Andreas Domingo,Rini Akmeliawati,Kuang Ye Chow (2007) “Pattern Matching for Automatic Sign Language Translation System using LabVIEW” International Conference on Intelligent and Advanced Systems：1-6
[17] Shuprajhaa, Subasree, Vaitheeshwar, Sivakumar(2016)“ A review on Image Processing techniques using Pattern matching in LabVIEW” International Journal of Advanced Engineering Research and Applications (IJAERA),1：1-5
[18] Khalid AA, Sture S. (1999) “Sand shear band thickness measurement by digital imaging techniques” Journal of Computing in Civil Engineering (ASCE),13:103-109.
[19] Murat G, Tuncer BE, Peter JB(1999) “Measurement of particle movement in granular soils using image analysis.” Journal of Computing in Civil Engineering (ASCE),13:116-122.
[20] Giachetti A. (2000) “Matching techniques to compute image motion.” Journal of Image and Vision Computing ,18:247-260.
[21] Bing Pan, Liping Yu, Dafang Wu (2013) “High-Accuracy 2D Digital Image Correlation Measurements with Bilateral Telecentric Lenses: Error Analysis and Experimental Verification”, Experimental Mechanics ,53:1719-1733
[22] National Instruments(2000)”IMAQ Vision Concepts Manual”, National Instruments Corporation :1-313