基于機(jī)器視覺的焊縫自動(dòng)跟蹤系統(tǒng)研究
發(fā)布時(shí)間：2018-11-17 13:17
【摘要】：當(dāng)前,焊接結(jié)構(gòu)件在各行各業(yè)均有著廣泛的應(yīng)用。但是,由于人工焊接勞動(dòng)強(qiáng)度大、工作環(huán)境惡劣、效率低下、焊接熱變形所引起的焊縫位置不可控以及操作者人為因素等問題,焊接加工質(zhì)量往往難以保證。近年來,隨著人工智能技術(shù)的發(fā)展,實(shí)時(shí)、自適應(yīng)焊接智能化生產(chǎn)成為了可能。而焊縫跟蹤技術(shù)作為焊接路徑控制中最有效的解決方案之一,是國內(nèi)外焊接界矚目的研究熱點(diǎn)。然而要實(shí)現(xiàn)焊縫自動(dòng)跟蹤,首先應(yīng)解決焊縫自動(dòng)跟蹤的傳感方式和焊縫特征提取問題,而這正是本文的主要研究?jī)?nèi)容。本文研究獲得了蘇州市產(chǎn)業(yè)前瞻性應(yīng)用研究(工業(yè))指導(dǎo)性計(jì)劃項(xiàng)目“基于視覺的弧焊機(jī)器人智能焊接關(guān)鍵技術(shù)研究”項(xiàng)目的資助。在基于機(jī)器視覺的焊縫跟蹤系統(tǒng)中,視覺傳感系統(tǒng)是整個(gè)系統(tǒng)的核心部分。本文對(duì)視覺傳感系統(tǒng)硬件,即光源、視覺傳感器、光路系統(tǒng)等進(jìn)行了綜合分析研究,針對(duì)焊接工作狀態(tài)下電弧光的特征、結(jié)構(gòu)光的光譜特征與工業(yè)相機(jī)的成像特點(diǎn),確定了工業(yè)相機(jī)、光源和工件在光路系統(tǒng)中相對(duì)位置,在保證視覺傳感器能夠清楚采集到焊縫位置并盡可能減少電弧光對(duì)圖像采集干擾的前提下,設(shè)計(jì)了基于以太網(wǎng)的數(shù)字型CMOS工業(yè)相機(jī)和結(jié)構(gòu)光法進(jìn)行圖像采集分析的視覺傳感硬件系統(tǒng)方案。結(jié)合系統(tǒng)特點(diǎn),整合了視覺系統(tǒng)標(biāo)定與機(jī)器人—攝像頭系統(tǒng)標(biāo)定技術(shù),得到了焊縫實(shí)際坐標(biāo)、焊縫圖像坐標(biāo)和機(jī)器人坐標(biāo)三者關(guān)系關(guān)聯(lián)矩陣;分析圖像特征,采用中值濾波平滑去噪、灰度拉伸增強(qiáng)對(duì)圖像進(jìn)行預(yù)處理;然后采用Canny算子提取圖像邊緣,骨骼化方法獲得圖像單像素骨骼線,最小二乘法對(duì)骨骼線上的點(diǎn)進(jìn)行擬合,并通過直線求交點(diǎn)的方法得到表征實(shí)際焊縫特點(diǎn)的5個(gè)特征點(diǎn)。構(gòu)建基于機(jī)器視覺的機(jī)器人焊縫自動(dòng)跟蹤系統(tǒng)試驗(yàn)平臺(tái)。視覺傳感器、工控機(jī)、焊接機(jī)器人三大硬件通過以太網(wǎng)進(jìn)行連接,采用TCP/IP協(xié)議通訊;在集成了攝像頭、機(jī)器人通訊軟件二次開發(fā)包基礎(chǔ)之上,設(shè)計(jì)了焊縫圖像處理、焊縫PID糾偏控制以及機(jī)器人通訊檢測(cè)等功能模塊;最后,分別在短路過渡、射滴過渡和射流過渡工藝條件下,根據(jù)偏差“由小到大”,示教點(diǎn)“先疏后密”對(duì)該系統(tǒng)進(jìn)行測(cè)試。試驗(yàn)結(jié)果表明,該系統(tǒng)能夠克服常規(guī)焊接工藝過程中不同強(qiáng)度電弧光的干擾,并能對(duì)0.5mm-3mm之間的偏差進(jìn)行糾偏處理。
[Abstract]:At present, welded structural parts are widely used in various industries. However, the welding quality is often difficult to guarantee because of the large labor intensity of manual welding, poor working environment, low efficiency, uncontrollable welding seam position caused by welding heat deformation and human factors of operator. In recent years, with the development of artificial intelligence technology, real-time intelligent production of adaptive welding has become possible. As one of the most effective solutions in welding path control, welding seam tracking technology is a hot research topic in welding field at home and abroad. However, in order to realize automatic seam tracking, it is necessary to solve the problem of sensing mode and feature extraction of weld seam automatic tracking, which is the main research content of this paper. In this paper, the project of "Vision based intelligent welding key technology research for arc welding robot" is supported by Suzhou industry prospective application research (industrial) guidance project. In the weld seam tracking system based on machine vision, the vision sensing system is the core of the whole system. In this paper, the hardware of the vision sensing system, namely light source, vision sensor, optical circuit system and so on, are comprehensively analyzed and studied. Aiming at the characteristics of arc light, the spectral characteristics of structure light and the imaging characteristics of industrial camera, the characteristics of arc light, structure light and industrial camera are analyzed and studied in this paper. The relative position of the industrial camera, the light source and the workpiece in the optical path system is determined. On the premise of ensuring that the visual sensor can clearly capture the weld seam position and minimize the interference of arc light to the image acquisition, This paper designs a hardware system of visual sensor based on Ethernet digital CMOS industrial camera and structured light method for image acquisition and analysis. Combined with the characteristics of the system, the visual system calibration and the robot-camera system calibration technology are integrated, and the actual welding seam coordinates, weld image coordinates and robot coordinates are obtained. The image feature is analyzed and the image is preprocessed by median filter smoothing denoising and gray-scale extension enhancement. Then Canny operator is used to extract the edge of the image and the skeleton method is used to obtain the single pixel skeleton line of the image. The points on the bone line are fitted by the least square method and five feature points representing the characteristics of the actual weld are obtained by the method of straight line intersection. A robot welding seam automatic tracking system test platform based on machine vision is constructed. Vision sensor, industrial control computer and welding robot are connected by Ethernet, and TCP/IP protocol is used to communicate. Based on the integration of the camera and the secondary development kit of robot communication software, the function modules of weld image processing, weld PID correction control and robot communication detection are designed. Finally, under the conditions of short-circuit transfer, droplet transfer and jet transfer, the system is tested according to the deviation "from small to large". The experimental results show that the system can overcome the interference of arc light with different intensity in conventional welding process and can correct the deviation between 0.5mm-3mm.
【學(xué)位授予單位】：中國礦業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP391.41;TG409
本文編號(hào)：2337929
[Abstract]:At present, welded structural parts are widely used in various industries. However, the welding quality is often difficult to guarantee because of the large labor intensity of manual welding, poor working environment, low efficiency, uncontrollable welding seam position caused by welding heat deformation and human factors of operator. In recent years, with the development of artificial intelligence technology, real-time intelligent production of adaptive welding has become possible. As one of the most effective solutions in welding path control, welding seam tracking technology is a hot research topic in welding field at home and abroad. However, in order to realize automatic seam tracking, it is necessary to solve the problem of sensing mode and feature extraction of weld seam automatic tracking, which is the main research content of this paper. In this paper, the project of "Vision based intelligent welding key technology research for arc welding robot" is supported by Suzhou industry prospective application research (industrial) guidance project. In the weld seam tracking system based on machine vision, the vision sensing system is the core of the whole system. In this paper, the hardware of the vision sensing system, namely light source, vision sensor, optical circuit system and so on, are comprehensively analyzed and studied. Aiming at the characteristics of arc light, the spectral characteristics of structure light and the imaging characteristics of industrial camera, the characteristics of arc light, structure light and industrial camera are analyzed and studied in this paper. The relative position of the industrial camera, the light source and the workpiece in the optical path system is determined. On the premise of ensuring that the visual sensor can clearly capture the weld seam position and minimize the interference of arc light to the image acquisition, This paper designs a hardware system of visual sensor based on Ethernet digital CMOS industrial camera and structured light method for image acquisition and analysis. Combined with the characteristics of the system, the visual system calibration and the robot-camera system calibration technology are integrated, and the actual welding seam coordinates, weld image coordinates and robot coordinates are obtained. The image feature is analyzed and the image is preprocessed by median filter smoothing denoising and gray-scale extension enhancement. Then Canny operator is used to extract the edge of the image and the skeleton method is used to obtain the single pixel skeleton line of the image. The points on the bone line are fitted by the least square method and five feature points representing the characteristics of the actual weld are obtained by the method of straight line intersection. A robot welding seam automatic tracking system test platform based on machine vision is constructed. Vision sensor, industrial control computer and welding robot are connected by Ethernet, and TCP/IP protocol is used to communicate. Based on the integration of the camera and the secondary development kit of robot communication software, the function modules of weld image processing, weld PID correction control and robot communication detection are designed. Finally, under the conditions of short-circuit transfer, droplet transfer and jet transfer, the system is tested according to the deviation "from small to large". The experimental results show that the system can overcome the interference of arc light with different intensity in conventional welding process and can correct the deviation between 0.5mm-3mm.
【學(xué)位授予單位】：中國礦業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP391.41;TG409
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