本文關(guān)鍵詞：機(jī)器視覺(jué)激光焊接缺陷檢測(cè)算法研究　出處：《深圳大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 激光焊接 機(jī)器視覺(jué) CHT 缺陷檢測(cè) 改進(jìn)RHT

【摘要】：機(jī)器視覺(jué)激光焊接具有焊接質(zhì)量高、精度高、速度快等優(yōu)點(diǎn),實(shí)現(xiàn)了機(jī)械自動(dòng)化,現(xiàn)已經(jīng)被廣泛應(yīng)用到各行各業(yè)。如汽車行業(yè)對(duì)零部件采用激光焊接降低了車身的重量和生產(chǎn)成本、制船行業(yè)對(duì)船板采用激光焊接在焊后基本沒(méi)有變形等。隨著機(jī)器視覺(jué)激光焊接的發(fā)展,通過(guò)機(jī)器視覺(jué)實(shí)現(xiàn)對(duì)焊后焊件表面的自動(dòng)化缺陷檢測(cè)也變得尤為重要。機(jī)器視覺(jué)缺陷檢測(cè)系統(tǒng)一般都具有快速性和實(shí)時(shí)性,但是在不犧牲速度的前提下提高準(zhǔn)確性一直是攻克的難點(diǎn)。這里通過(guò)引入Hough變換檢測(cè)圓(CHT,Circular Hough Transform)做缺陷檢測(cè),其主要是定位缺陷所在位置,通過(guò)引入Hough變換使得產(chǎn)品缺陷檢測(cè)的準(zhǔn)確性和快速性得到了很大的提高。本課題來(lái)源于某公司“基于機(jī)器視覺(jué)的激光自動(dòng)焊接設(shè)備”項(xiàng)目。本文主要做了如下工作:1)將CHT應(yīng)用到基于機(jī)器視覺(jué)的激光焊接焊后焊件表面缺陷檢測(cè)領(lǐng)域中。對(duì)工業(yè)相機(jī)(CCD,Charge-coupled Device)采集到的圖像先用Canny算子進(jìn)行邊緣檢測(cè),然后用CHT做焊接位置定位,最后累計(jì)焊接位置處壞的像素點(diǎn)的個(gè)數(shù),并與設(shè)定的缺陷閾值進(jìn)行比較由此判斷產(chǎn)品焊接質(zhì)量的好壞。本算法與用模版匹配做缺陷檢測(cè)的算法進(jìn)行對(duì)比分析,誤判率和漏判率分別降低了5%和3%左右。2)將改進(jìn)隨機(jī)Hough變換(RHT,Random Hough Transform)應(yīng)用到基于機(jī)器視覺(jué)的激光焊接焊后焊件表面缺陷檢測(cè)領(lǐng)域中。RHT檢測(cè)圓與CHT相比速度得到了提高,但是由此會(huì)引入大量的無(wú)效累積,因此對(duì)RHT進(jìn)行如下改進(jìn):判斷隨機(jī)采樣的三點(diǎn)是否共線并對(duì)其之間的距離進(jìn)行限定,這樣避免了之后大量的無(wú)效計(jì)算;當(dāng)判斷候選圓是否為真實(shí)圓時(shí),先判斷邊緣點(diǎn)是否在候選圓的內(nèi)外切正方形之間然后再計(jì)算邊緣點(diǎn)是否在候選圓上,避免了大量計(jì)算;采用求弦的中垂線對(duì)圓參數(shù)求解,提高了運(yùn)行速度。該算法先在matlab上仿真運(yùn)行然后被應(yīng)用到機(jī)器設(shè)備上,驗(yàn)證了其準(zhǔn)確性與有效性。改進(jìn)RHT算法的準(zhǔn)確性與RHT、CHT的準(zhǔn)確性基本相同,改進(jìn)RHT相比RHT算法速度提高了100ms左右,改進(jìn)RHT算法相比CHT速度提高了600ms左右。
[Abstract]:Machine vision laser welding has many advantages, such as high quality, high precision, fast speed and so on. It has realized mechanical automation and has been widely used in all walks of life. Such as the automotive industry parts by laser welding reduces the body weight and production cost of the ship to ship industry, using laser welding after welding without deformation. With the development of machine vision laser welding, it is also very important to realize automatic defect detection on the surface of welding parts by machine vision. The machine vision defect detection system generally has fast and real time, but it is difficult to improve the accuracy without sacrificing speed. Here we introduce the Hough transformation to detect the circle (CHT, Circular Hough Transform) to do defect detection. It mainly locate the location of the defect. By introducing the Hough transform, the accuracy and rapidity of product defect detection have been greatly improved. This project comes from a company "laser automatic welding equipment based on machine vision". The main work of this paper is as follows: 1) the application of CHT to the surface defect detection field of laser welded parts of laser welding based on machine vision. The industrial camera (CCD, Charge-coupled Device) to the first image edge detection using Canny operator, and then use CHT to do the welding position, welding end cumulative number of pixels at the position of the bad, and compared the judgment of product welding quality and defect threshold setting. The algorithm is compared with the template matching algorithm for defect detection, and the error rate and the missed rate are reduced by 5% and 3% respectively. 2) the improved random Hough transform (RHT, Random Hough Transform) is applied to the surface defect detection field of laser welded parts of laser welding based on machine vision. RHT circle detection compared with CHT speed has been improved, but this will introduce invalid accumulated, thus improving the RHT as follows: three to determine the point of random sampling are collinear and the distance between the limit, so as to avoid the invalid after a lot of calculation; when judging the candidate circle for true circle. First determine whether the candidate edge points in the circle tangent square between inside and outside and then calculate the edge point in the candidate circle, to avoid a lot of calculation; using the string perpendicular to solve circle parameters, improves the running speed. The algorithm is first simulated on the MATLAB and then applied to the machine equipment to verify its accuracy and effectiveness. The accuracy of the improved RHT algorithm is basically the same as that of RHT and CHT. Compared with the RHT algorithm, the speed of the improved RHT algorithm is increased by about 100ms. Compared with the improved RHT algorithm, CHT speed has increased 600ms.
【學(xué)位授予單位】：深圳大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TG441.7;TP391.41

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