本文選題：線結構光 + RANSAC算法　； 參考：《廣東工業(yè)大學》2017年碩士論文

【摘要】：目前,對于焊縫的拋光打磨,工業(yè)現(xiàn)場主要依靠人工通過肉眼觀察焊縫外觀以及使用千葉片或者砂輪等來進行打磨作業(yè)。這種作業(yè)方式不僅效率低下,且其拋磨精度和穩(wěn)定性比較差。機器視覺技術的發(fā)展為解決焊縫拋磨提供了一種新的思路,尤其是線結構光視覺在焊縫檢測中的應用,能夠很好的解決上述問題。在焊縫拋磨中最重要的參數(shù)即余高以及熔寬,因此本文對焊縫檢測所涉及到的關鍵技術進行了初步研究。本文首先從系統(tǒng)層面介紹了整個線結構光視覺系統(tǒng)以及其原理。根據實際工況需求,對線結構光光路進行了設計并對CMOS相機進行選型;考慮到焊縫材料特征,選擇了650nm波長的激光發(fā)生器,采用了窄帶濾光片來濾除環(huán)境光干擾;通過以上視覺元件的結構,結合機器人末端尺寸,對視覺傳感器夾具進行了設計,并最終搭建了焊縫余高和熔寬檢測實驗系統(tǒng)。為了建立相機中像素坐標與三維空間的關系,對視覺系統(tǒng)進行了標定。首先建立了相機的數(shù)學模型,并利用張氏標定法對相機進行了標定,獲得了相機的內參;利用平面棋盤作為標定參照物;對線結構光進行了標定,并得到了線結構光平面方程;在上述內參模型的基礎上利用兩步法對機器人手眼關系進行了標定,并得到了手眼關系矩陣。應用隨機抽樣一致性(RANSAC)算法對焊縫圖像進行了處理,提取出焊縫余高以及熔寬信息。首先對采集到的焊縫圖像進行預處理,得到二值化圖像;通過邊緣提取得到激光條紋邊緣圖像,采用改進了的平均法得到單像素激光中心線;通過RANSAC算法可得到其數(shù)學模型,并動態(tài)設定感興趣區(qū)域(ROI);在此ROI中,再次進行預處理以及RANSAC算法處理,可得到只包含焊縫余高信息的單像素激光中心線,從而得到焊縫特征點及余高和熔寬信息;為實現(xiàn)機器人拋磨,定義了機器人拋磨位姿。為實現(xiàn)視覺信息與機器人的交互,基于MFC以及開源算法庫OpenCV開發(fā)了焊縫余高和熔寬檢測系統(tǒng)軟件。軟件系統(tǒng)采用模塊式開發(fā)的方法,分別對圖像采集、圖像處理、焊縫數(shù)據處理、視覺系統(tǒng)標定以及可視化等功能模塊進行了開發(fā);為驗證系統(tǒng)的可行性,最后進行了焊縫檢測實驗。
[Abstract]:At present, for the polishing and grinding of weld seam, the industrial field mainly relies on manual observation of weld appearance with naked eye and the use of thousands of blades or grinding wheels for grinding. This operation is not only inefficient, but also its grinding accuracy and stability is poor. The development of machine vision technology provides a new way to solve weld grinding, especially the application of line structured light vision in weld seam detection, which can solve the above problems well. The most important parameters in weld polishing are residual height and weld width. Therefore, the key technologies involved in weld inspection are studied in this paper. This paper first introduces the whole line structured light vision system and its principle from the system level. According to the actual working conditions, the optical path of the line structure is designed and the CMOS camera is selected, considering the characteristics of the weld material, the laser generator of 650nm wavelength is selected and the narrow band filter is used to filter the environmental light interference. According to the structure of the vision component and the size of the robot, the fixture of the vision sensor is designed, and the experiment system of weld residual height and weld width detection is built. In order to establish the relationship between pixel coordinates and 3D space, the vision system is calibrated. Firstly, the mathematical model of the camera is established, and the camera is calibrated by the method of Zhang's calibration, and the inner parameters of the camera are obtained, the plane chessboard is used as the calibration reference, the linear structured light is calibrated, and the plane equation of the linear structured light is obtained. Based on the above model, a two-step method is used to calibrate the hand-eye relationship of the robot, and the hand-eye relation matrix is obtained. The random sampling consistency algorithm (RANSAC) is used to process the weld image and extract the residual height and weld width information. Firstly, we preprocess the weld image to get binary image; get the edge image of laser stripe by edge extraction, get the laser center line of single pixel by the improved average method; get the mathematical model by RANSAC algorithm. In this ROI, pretreatment and RANSAC algorithm are used again to get the single pixel laser centerline which only contains the information of residual height of the weld, thus obtaining the characteristic point of the weld and the information of the residual height and the width of the weld. In order to realize robot grinding, the position of robot grinding is defined. In order to realize the interaction between visual information and robot, the software of weld residual height and weld width detection system is developed based on MFC and open source algorithm library OpenCV. In order to verify the feasibility of the system, the function modules of image acquisition, image processing, weld data processing, visual system calibration and visualization are developed. Finally, the weld test was carried out.
【學位授予單位】：廣東工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TG441.7;TP391.41

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