本文選題：視覺測量 + 高速攝像　； 參考：《中國科學(xué)技術(shù)大學(xué)》2017年博士論文

【摘要】：測量技術(shù)作為現(xiàn)代工業(yè)技術(shù)的基礎(chǔ)技術(shù),其測量的精度和效率是衡量國家科學(xué)技術(shù)發(fā)展水平的重要因素,工業(yè)制造技術(shù)的進步與加工工藝的提高對測量方法的性能提出了更高的要求。隨著數(shù)字成像技術(shù)與圖像處理芯片的發(fā)展,圖像傳感器在成像精度和速度上均得到較大提升,以機器視覺和深度學(xué)習(xí)為代表的分析算法的進步使得圖像信息的提取更加多元化。基于視覺的測量技術(shù)作為一種新興的測量手段,以其非接觸、高精度、全場測量、無負載效應(yīng)和自動化程度高等諸多優(yōu)點,受到越來越多國內(nèi)外研究人員和學(xué)者的關(guān)注。視覺測量技術(shù)已經(jīng)在機械零件的形狀與尺寸檢測、目標識別與追蹤、結(jié)構(gòu)運動分析和生理信號采集等領(lǐng)域得到了廣泛應(yīng)用。隨著高速成像技術(shù)的發(fā)展,視覺測量中相機的采樣幀率不斷提升,使其能夠?qū)Ρ粶y物體瞬間發(fā)生的變化以及更高頻率的運動信息進行記錄與分析。本文以高速視覺測量系統(tǒng)作為研究對象,對高速視覺測量系統(tǒng)的硬件結(jié)構(gòu)設(shè)計和信息提取算法進行了深入研究,并且針對結(jié)構(gòu)不同的運動情況提出一系列行之有效的測量方案。本文首先闡述了視覺測量的研究意義與發(fā)展現(xiàn)狀,對高速視覺測量系統(tǒng)的硬件構(gòu)架進行了詳細介紹,分析了不同硬件的選型標準和工作特點。通過合理搭配硬件結(jié)構(gòu),視覺測量系統(tǒng)可以完成不同尺度和不同距離下的目標運動參數(shù)測量與分析。文章同時對視覺測量系統(tǒng)中相機的幾何成像原理進行了推導(dǎo)與分析,明確了在使用標靶的簡單相機標定中影響測量精度的主要誤差來源。常規(guī)的圖像處理算法往往具有人工參數(shù)調(diào)整、自動化程度低、魯棒性差等不足,文中針對結(jié)構(gòu)視覺測量中物體的平動、旋轉(zhuǎn)和微小振動等問題提出了一系列簡單有效的信息提取算法。首先通過將簡單梯度優(yōu)化和曲面擬合優(yōu)化與多種整像素精度的圖像匹配算法相結(jié)合,提升了原始振動提取算法的測量精度和運算效率。使用優(yōu)化后算法的視覺測量系統(tǒng)與傳統(tǒng)的光柵尺位移傳感器相比測量數(shù)據(jù)的誤差小于1%,算法幀間位移提取耗時降低至1ms以下,可以滿足實際拍攝幀率在1000fps左右的實時測量需求。其次,文章針對物體旋轉(zhuǎn)參數(shù)測量問題給出了徑向和軸向兩種情況下的解決方案,將Lucas-Kanade與ECC圖像對齊算法及其快速反向組合算法應(yīng)用于物體的旋轉(zhuǎn)參數(shù)測量中,提出了一種新的非線性扭曲函數(shù)描述圓柱結(jié)構(gòu)徑向旋轉(zhuǎn)測量中目標圖像與模板圖像的扭曲變化關(guān)系,優(yōu)化了參數(shù)在運算時的迭代方式,提升了算法的運行效率。最后,文章將視覺測量系統(tǒng)用于提取目標物體表面微小的亮度變化和振動信息中,通過對影像放大算法的剖析發(fā)現(xiàn),放大視頻中的微小變化量的前提在于有效提取該信息,針對影像放大算法執(zhí)行效率低的問題,文章提出一種基于SVD奇異值分解的快速微振動提取算法,能夠在去除冗余信息的同時有效提取圖像序列中像素信息的微小變化。所提出的相關(guān)測量算法被集成在搭建的高速視覺測量系統(tǒng)中,在實際工程測量中取得了良好的效果。文中分別使用該裝置對叉車方向盤系統(tǒng)和鐵路橋聲屏障結(jié)構(gòu)的振動,故障軸承驅(qū)動時的旋轉(zhuǎn)參數(shù)以及聲音激勵產(chǎn)生的微小振動進行了測量與分析,實驗結(jié)果表明所開發(fā)的高速視覺測量系統(tǒng)在實際測量時工作穩(wěn)定可靠,具有重要的應(yīng)用價值。
[Abstract]:As the basic technology of modern industrial technology, measurement technology is an important factor in measuring the level of national science and technology development. The progress of industrial manufacturing technology and the improvement of processing technology put forward higher requirements for the performance of measurement methods. With the development of digital image technology and image processing chip, image transmission is the key factor. The sensor has greatly improved the accuracy and speed of imaging. The progress of the analysis algorithm represented by machine vision and depth learning makes the extraction of image information more diversified. The vision based measurement technology is a new measuring method, with its non-contact, high precision, full field measurement, no load effect and high automation. Many advantages have attracted more and more attention from researchers and scholars at home and abroad. Visual measurement technology has been widely used in the fields of shape and size detection of mechanical parts, target recognition and tracking, structural motion analysis and physiological signal acquisition. With the development of high-speed imaging technology, the sampling frame of the camera in visual measurement In this paper, the high speed vision measurement system is taken as the research object, and the hardware structure design and information extraction algorithm of the high-speed visual measurement system are studied in this paper. In this paper, a series of effective measurement schemes are put forward. Firstly, the research significance and development status of visual measurement are expounded. The hardware framework of the high speed vision measurement system is introduced in detail, and the selection standards and work characteristics of different hardware are analyzed. The visual measurement system can complete the different scales through the rational matching of hardware structure. The principle of the geometric imaging of the camera in the visual measurement system is derived and analyzed, and the main source of error which affects the measurement accuracy in the calibration of the simple camera using the target target is clarified. The conventional image processing algorithms often have artificial parameters adjustment and automation. In this paper, a series of simple and effective information extraction algorithms are proposed for the translation, rotation and micro vibration of objects in structural vision measurement. First, the original vibration extraction is improved by combining simple gradient optimization and surface fitting optimization with a variety of pixel precision image matching algorithms. The measurement accuracy and efficiency of the algorithm. Compared with the traditional grating scale displacement sensor, the error of the visual measurement system using the optimized algorithm is less than 1%, and the time time of the inter frame displacement extraction is reduced to less than 1ms, which can meet the real time measurement requirement of the actual shooting frame rate of about 1000fps. Secondly, the article is aimed at the rotation of the object. The solution of two kinds of radial and axial conditions is given in the parameter measurement problem. The Lucas-Kanade and ECC image alignment algorithm and its fast reverse combination algorithm are applied to the measurement of the rotation parameters of the object. A new nonlinear distortion function is proposed to describe the distortion of the target image and the template image in the radial rotation measurement of the cylindrical structure. The iteration method of the parameter in operation is optimized and the efficiency of the algorithm is improved. Finally, the visual measurement system is used to extract the small brightness change and vibration information of the object surface. By analyzing the image magnification algorithm, it is found that the premise of enlarging the small change in the visual frequency is to extract it effectively. Information, in view of the low efficiency of image amplification algorithm, a fast micro vibration extraction algorithm based on SVD singular value decomposition (SVD) is proposed, which can effectively extract the small change of pixel information in the image sequence while removing redundant information. The proposed correlation measurement algorithm is integrated in the built high speed vision measurement system. Good results have been achieved in practical engineering measurement. The device is used to measure and analyze the vibration of the sound barrier structure of the steering wheel system and the railway bridge, the rotation parameters and the small vibration caused by the sound excitation. The experimental results show that the developed high-speed visual measurement system is real. The measurement work is stable and reliable, and has important application value.
【學(xué)位授予單位】：中國科學(xué)技術(shù)大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2017
【分類號】：TP391.41

【參考文獻】

相關(guān)期刊論文 前10條

1 喻其炳;尹愛軍;薛磊;張泉;;基于單目離面視覺的結(jié)構(gòu)振動檢測[J];中國機械工程;2016年17期

2 余應(yīng)淮;謝仕義;梅其祥;;基于核回歸修正的上采樣相位相關(guān)精確運動估計算法[J];計算機應(yīng)用;2016年08期

3 徐超;王大軼;黃翔宇;;采用雙目視覺測量的行星著陸相對導(dǎo)航方法[J];宇航學(xué)報;2016年07期

4 劉昶;韋飛云;孫維廣;;基于雙平行平面相機模型的鋼板尺寸視覺測量[J];光學(xué)精密工程;2016年04期

5 楊景豪;劉巍;劉陽;王福吉;賈振元;;雙目立體視覺測量系統(tǒng)的標定[J];光學(xué)精密工程;2016年02期

6 王耀東;朱力強;史紅梅;郭保青;;高速機械系統(tǒng)運動特性的實時視覺檢測技術(shù)研究[J];機械工程學(xué)報;2016年02期

7 占棟;于龍;肖建;陳唐龍;;鋼軌輪廓全斷面高精度動態(tài)視覺測量方法研究[J];鐵道學(xué)報;2015年09期

8 單寶華;張博一;嚴雨;;高速沖擊荷載作用后泡沫鋁夾層板表觀變形立體視覺測量[J];振動與沖擊;2015年16期

9 喬玉晶;王浩然;趙燕江;;大尺寸曲面零件的雙目視覺測量網(wǎng)絡(luò)規(guī)劃研究[J];儀器儀表學(xué)報;2015年04期

10 郭寶云;;工業(yè)零件形狀與尺寸高精度視覺測量方法研究[J];測繪學(xué)報;2015年04期

，

本文編號：2073978