【摘要】：通過振動臺實驗,我們可以研究結(jié)構(gòu)試件的振動位移等信息。通過分析位移信息得到其抗震性能。檢測結(jié)構(gòu)試件的特征點作為物體測試的特定點,其位移、速度、加速度、撓度等運動參數(shù)是實驗所要得到的數(shù)據(jù)。而本文的重點在于檢測特征點的位移變化,通過對位移變化曲線的分析,來判斷結(jié)構(gòu)試件是否發(fā)生了變形。本文主要研究了視覺技術(shù)應用于結(jié)構(gòu)位移檢測的現(xiàn)狀以及發(fā)展趨勢。了解了振動臺試驗的位移檢測的基本理論,主要包括數(shù)字圖像的成像原理及其表現(xiàn)形式與特征、圖像用于測量工作時所涉及的坐標系、圖像預處理的相關(guān)算法、目標點的定位以及相機標定算法。提出了基于雙目立體視覺技術(shù)的振動臺試驗的結(jié)構(gòu)試件位移測量的算法,并對該算法的關(guān)鍵技術(shù)做了具體的研究。其核心內(nèi)容包括,1)本文采用基于圓形陣列組成的標定板與張氏標定算法對系統(tǒng)進行標定。2)通過基于彩色空間轉(zhuǎn)換與Hough變換檢測直線,降低了直線漏檢率。再根據(jù)Harris角點檢測算法得到圖像的特征點,通過控制閾值來控制角點的數(shù)目和質(zhì)量。3)本文研究了特征點匹配的約束條件以及sift特征描述子,采用基于極線約束的雙向匹配算法進行實驗匹配,得到較好的結(jié)果。研究了雙目視覺測量位移的原理。并將其應用于結(jié)構(gòu)試件位移檢測中。本文重點研究了雙目視覺系統(tǒng)的標定、特征點的檢測及匹配。通過設(shè)計靜態(tài)試驗驗證了本文算法的可行性,再將此算法應用到振動臺的動態(tài)試驗中,得到結(jié)構(gòu)試件的動態(tài)位移曲線。針對本文提出的測量方法,設(shè)計了相應的動、靜態(tài)兩種實驗方案,并在我校的振動臺實驗室中進行了實驗。首先通過靜態(tài)試驗來驗證本文算法測量的可行性以及測量精度。然后進行了正弦波激勵實驗,并通過本文算法計算結(jié)構(gòu)試件特征點的位移,得到的位移曲線基本與正弦激勵信號變化趨勢是一致的。
[Abstract]:Through the shaking table experiment, we can study the vibration displacement and other information of the structural specimen. The seismic performance is obtained by analyzing the displacement information. The movement parameters such as displacement, velocity, acceleration, deflection and so on are the data to be obtained by testing the characteristic points of the structural specimens as the special points of the object test. The emphasis of this paper is to detect the displacement change of the characteristic points and to judge the deformation of the structural specimen by analyzing the curve of the displacement change. This paper mainly studies the present situation and development trend of the application of visual technology in structural displacement detection. In this paper, the basic theory of displacement detection in shaking table test is understood, including the imaging principle of digital image, the form and characteristics of digital image, the coordinate system involved in the measurement work of the image, and the related algorithm of image pre-processing. Target location and camera calibration algorithm. An algorithm based on binocular stereo vision for measuring the displacement of structural specimen in shaking table test is presented and the key technology of the algorithm is studied in detail. The core contents of this paper are as follows: 1) the calibration algorithm based on circular array is used to calibrate the system. 2) through color space conversion and Hough transform to detect straight line, the detection rate of straight line is reduced. 2) the calibration board based on circular array and Zhang's calibration algorithm are used to calibrate the system. Then the feature points of the image are obtained according to the Harris corner detection algorithm, and the number and quality of the corners are controlled by the control threshold. 3) in this paper, the constraint conditions of feature point matching and the sift feature descriptor are studied. Two-way matching algorithm based on polar constraint is used for experimental matching, and good results are obtained. The principle of measuring displacement with binocular vision is studied. It is applied to the displacement detection of structural specimens. This paper focuses on the calibration of binocular vision system, the detection and matching of feature points. The feasibility of the proposed algorithm is verified by the static test. Then the dynamic displacement curve of the structural specimen is obtained by applying the algorithm to the dynamic test of the vibration table. In view of the measurement method proposed in this paper, the corresponding dynamic and static experimental schemes are designed, and the experiments are carried out in the shaking table laboratory of our school. First of all, the feasibility and accuracy of this algorithm are verified by static test. Then the sinusoidal excitation experiment is carried out and the displacement of the characteristic points of the structural specimen is calculated by this algorithm. The displacement curve obtained is basically consistent with the changing trend of the sinusoidal excitation signal.
【學位授予單位】：蘭州理工大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP391.41;TB534.2

【參考文獻】

相關(guān)期刊論文 前10條

1 金兆楠;;Zernike矩的圓陣列靶標特征點精確提取方法[J];山西電子技術(shù);2015年04期

2 于合龍;劉浩洋;蘇恒強;;基于光流追蹤技術(shù)的變形位移測量方法[J];吉林大學學報(理學版);2014年02期

3 季云峰;;結(jié)構(gòu)動位移測試的計算機視覺方法實現(xiàn)[J];同濟大學學報(自然科學版);2013年11期

4 趙薇;陸余恬;;基于自適應算法的去噪濾波仿真比較[J];中國傳媒大學學報(自然科學版);2013年04期

5 王民;劉偉光;;基于改進SIFT特征的雙目圖像匹配算法[J];計算機工程與應用;2013年02期

6 蘇恒強;馮雪;于合龍;賈晶敏;汪巖;;基于Harris角點檢測的位移測量算法[J];實驗力學;2012年01期

7 田國偉;韓曉健;徐秀麗;劉偉慶;;基于視頻圖像處理技術(shù)的振動臺試驗動態(tài)位移測量方法[J];世界地震工程;2011年03期

8 張子淼;王鵬;孫長庫;;單目視覺位姿測量方法及數(shù)字仿真[J];天津大學學報;2011年05期

9 方莉;張萍;;經(jīng)典圖像去噪算法研究綜述[J];工業(yè)控制計算機;2010年11期

10 孔軍;湯心溢;蔣敏;;多尺度特征提取的雙目視覺匹配[J];計算機工程與應用;2010年33期

相關(guān)碩士學位論文 前4條

1 陳運貴;利用數(shù)字圖像處理技術(shù)監(jiān)測隧道變形的探索研究[D];廣東工業(yè)大學;2014年

2 肖鋒;基于數(shù)字圖像處理技術(shù)的建筑裂縫監(jiān)測研究[D];重慶大學;2013年

3 康晶;基于立體視覺攝像機標定方法的三維重建技術(shù)研究[D];湖南大學;2006年

4 董輝;馬桑溪長江大橋變形動態(tài)監(jiān)測系統(tǒng)研究[D];重慶大學;2004年

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