基于视觉及电弧传感技术的机器人GTAW三维焊缝实时跟踪控制技术研究
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摘要
机器人焊接自动化是焊接技术发展的一个趋势，目前，国内外大部分实际焊接生产使用的机器人总的来说还是属于第一代或者准二代的“示教-再现”型机器人。这种类型的机器人对于焊接环境的一致性要求异常严格，其焊接路径和相关工艺参数都是需要预先设置的。但是在实际的焊接中常常因为存在变形、变散热、变间隙、变错边、工件加工误差和装配误差等因素造成焊缝位置和尺寸的变化，导致焊缝和示教轨迹有偏差，由于“示教-再现”型机器人对示教轨迹偏差没有适应性，不具备焊缝实时跟踪控制功能，从而最终影响焊缝成形的质量，难以满足企业对焊接制造高质量、高效率的要求，因此限制了它在很多领域的应用。为了克服焊接过程中这些不确定性因素对精密焊接件焊缝质量的影响，迫切需要对焊缝进行实时跟踪来调整机器人的运动轨迹，提高现行焊接机器人的适应性和智能化水平。
在实际的焊接过程中，大部分的焊接工件为空间三维焊缝。在已有的基于被动视觉的焊缝跟踪研究中，视觉系统大多只能准确地获取图像的二维信息，三维重建的方法可以计算出图像中的高度信息，但其计算的精确性和可靠性难以满足实时焊缝跟踪的要求，仅仅依靠视觉技术很难满足机器人在实际生产中对焊接高度方向上的自动跟踪控制要求。在利用视觉传感技术对焊缝进行实时在线跟踪时必须利用其他方法对焊接高度进行实时跟踪控制。本文根据铝合金脉冲GTAW的焊接特点，利用基于视觉及电弧传感的复合传感技术对焊缝进行左右和高度进行纠偏，实现机器人GTAW过程的三维焊缝实时跟踪控制，这对将传统的“示教-再现”型机器人开发成具有一定自主功能的焊接机器人系统，不断扩大机器人焊接自动化技术在国防、航空、化工及电子等部门的应用范围具有重要的理论意义和工程实用价值。
利用视觉和电弧传感技术来对机器人GTAW过程三维焊缝进行实时跟踪控制要解决三个主要问题，一个是准确地获取焊缝的三维信息，这是进行实时焊缝跟踪的前提。另外一个问题是必须找到合适的三维信息处理算法，提取出三维焊缝信息的特征值。最后必须设计合理的焊缝跟踪控制器，使其能够满足机器人GTAW过程对焊缝实时跟踪控制要求。
本文首先研究开发了一套基于视觉及电弧传感技术的机器人三维焊缝跟踪系统，具体包括焊接平台的搭建、视觉及电弧传感器的设计加工、焊接系统的标定、系统控制软件的设计以及焊接工装夹具的设计等。
要对焊缝进行准确的实时跟踪，首先需要获得描述焊缝焊接过程状态中的准确信息。通过对铝合金GTAW焊接实际电弧光谱的分析，自主研制了一套多功能被动视觉传感器。通过分析减光滤光片、电流基值以及采像时刻等参数对获取焊接图像的影响，在仅依靠焊接过程电弧光照明的情况下，实现了铝合金脉冲GTAW过程实时焊接图像清晰地获取。针对已有焊接图像边缘检测方法的不足，提出了一种改进的Canny边缘检测算法，有效改善了不同焊接图像边缘的提取效果，提高了边缘检测的准确性和自适应性。在分析焊接图像特点的基础上，开发了一套完整的图像处理算法。通过焊接实验验证，其焊接图像处理精度可以控制在±0.169mm以内，其精度能很好地满足了机器人GTAW过程实时图像处理的需求。
根据铝合金脉冲GTAW的焊接特点，利用电弧传感器对电弧电压信号进行了有效地采集，并对弧压信号特点进行了仔细分析，提出了一种基于小波包的防脉冲干扰滑动均值去噪处理方法，能有效地去除电弧电压信号中含有的大量脉冲干扰和随机非平稳噪声。在此基础上，准确地提取出了弧压信号的特征值，其处理精度能达到0.273mm。建立了电弧电压和弧长的关系模型U=3.108h+21.472，并对模型精度进行了实验验证。实验表明，根据弧压与弧长关系模型计算出的弧长与实际焊接弧长有很好的匹配，其最小误差约为0.218mm，其精度完全能够满足后续的机器人焊接高度实时跟踪控制的要求。
通过分析“示教－再现”型焊接机器人的纠偏原理和实时焊缝跟踪控制的特点，设计了基于模糊切换的Fuzzy-PID双模复合控制器来对三维焊缝进行跟踪控制。针对不同的焊缝偏差，利用模糊逻辑规则，实现了Fuzzy控制器和PID控制器的无扰切换，最大限度地保证了焊接过程焊缝跟踪的实时性，稳定性和抗干扰性。通过仿真实验表明，基于模糊切换的Fuzzy-PID双模复合控制器具有可靠性好，抗干扰能力强，跟踪能力好的特点，能很好地满足机器人实时焊缝跟踪的要求。
最后，利用本文开发的三维焊缝跟踪焊接系统对多种不同三维曲线焊缝进行了跟踪控制实验，实验结果表明，其左右最大跟踪偏差可以控制在±0.3mm范围之内，高度跟踪误差可以控制在±0.4mm范围内，基本能够满足机器人实际焊接生产的要求。
Nowadays, robot welding is a trend of welding automation technicaldevelopment; more and more welding robots have been applied in theautomatic manufacturing process at home and abroad. However, most ofthem are primary teaching-playback robots, the welding path and processparameters of which are set in advance, and the requirement of conformanceto the welding operation conditions is very strict. That means if thework-pieces of weld are changed, they must be taught and programmed again.Especially, the seam position is often disturbed by distortion, ways ofspreading heat, variability of gap, stagger edge, etc. which will affect thequality of welding forming. In the practical welding application, this type ofwelding robot cannot meet the enterprises’ requirements on superior qualityand top efficiency because of the lackness of adaptability in teaching trajectory offset and no function of real-time tracking control, which limits itsapplication in many fields. In order to overcome the uncertainty which affectsthe quality of welding, there is an urgent need to track the seam in real timefor “teaching-playback” welding robot, which will make it more flexible andintelligent.
In the practical welding process, most of the welding seams arethree-dimensional, which are difficult for the only vision technology to trackand control in real-time. However, among what have been studied in weldtracking, the passive vision technology can accurately get the2Dseam-tracking information, but the height information should be acquiredonly through3D reconstruction method. It is a pity that most of thealgorithms are too complex to be used in real-time control, which causes thatthe vision technology can hardly meet the requirements of real-time heighttrack and control during actual robotic welding process. Thus, anothertechnology must be used in height tracking while the visual sensortechnology is used in real-time3D seam tracking. The composite sensorsbased on visual sensor and arc sensor can be used in the weld of3D seam,which provides a possibility to realize the function of real-time tracking of3D welding seam during robotic GTAW process, and will develop theteaching-playback robot into an intelligent welding robot. No doubt that theseresearches supply important theoretical significance and practical value forexpanding the applied range of robot welding automation technology in manydifferent fields, such as national defense, aviation, shipbuilding, machinery,automobile, electronics and electrics.
There are three problems which should be resolved in real-time trackingof3D welding seam during robotic GTAW process based on visual sensor and arc sensor. The first one is accurately retrieving the3D welding seam.The second one is that the right signal processing method must be found,which should be accurate enough to meet the requirements of real-timetracking of3D welding seam during robotic GTAW, and the characteristics of3D welding seam should be extracted. The third one is that the design ofreasonable controller for the seam tracking must meet the requirement ofreal-time welding seam tracking for welding robot GTAW process.
Firstly，this paper designed a set of tracking and control system forthree-dimension welding seam during welding robot GTAW process based onvision sensor and Arc sensor, including the setup of experimental platform,the design and processing of sensors, the calibration of welding equipment,the design of system control software and welding fixture, etc. Theexperiment platform can make better effect of real-time control onthree-dimension welding seam during welding robot GTAW process.
To achieve accurate real-time seam tracking during welding, theaccurate information which is used to describe welding process should beobtained first. Thus, this paper designed a set of system of passive visionsensor for the robot to track the plane welding seam in real-time. The qualityof image acquisition is associated not only with dimmer-filter system, butalso with the value of base current and the time of capturing image. Througha large number of experiments, the parameters of Al alloy pulsed GTAW areascertained, such as the composite dimmer-filter system, the base current,the time of capturing images, etc. By using the passive vision sensor system,we can get some clear images during the robot weld automation process.Aiming at the deficiencies of existing edge detection algorithm, a newimproved Canny algorithm has been proposed to detect the edges of seam and pool, which effectively enhances the precision, accuracy and selfadaptability. By analyzing the features of welding images, a set of completealgorithm of image processing is proposed to extract the characteristicparameters of welding images. Finally, the algorithm of the image processingwas validated through the experiment. The precision can be controlled aboutwithin±0.169mm, which can completely meet the requirement of real-timewelding seam tracking for welding robot GTAW process.
By analyzing the characteristics of pulsed GTAW for Al alloy, the arcvoltage signals are successfully gathered by the arc sensor, and A newde-noising method of anti-impulse interference moving average based onwavelet packet is studied in this paper. The characteristics of arc voltage areextracted, which can be accurate to0.273mm. The relational model betweenarc voltage and arc length, which is U3.108h21.472, has been worked outand then confirmed by tests in the paper. The experiments have suggestedthat the characteristics of arc voltage, the arc-length calculated by therelational model and the real arc-length can be well matched, for the minimalerror is about0.218mm. Therefore, in accordance with the above points, wecan conclude that the accuracy of the relational model between arc voltageand arc length can completely meet the requirements of real-time trackingand control in height during robot GTAW process
By analyzing the deviation rectification of welding robot and thecharacteristics of3D welding seam, a compound Fuzzy-PID double modecontroller based on fuzzy rules switching has been designed for the system of3D seam tracking control during robotic GTAW process. By using fuzzylogic rules, it can shift from Fuzzy controller to PID controller according todifferent seam deviations, which ensures the maximum real time, anti-interference performance, and good stability of seam tracking in weldingprocess. It has been proved by the simulation-system test that the compoundFuzzy-PID double mode controller enjoys the advantages of excellentrobustness, strong anti-interference and tracking abilities, which cancompletely meet the requirements of real-time tracking and control duringrobot GTAW process
Finally, aiming at the complex three-dimension curve seam, someexperiments have been done to verify the precision of3D seam trackingbased on visual sensor and arc sensor technology. The results demonstratethat the precision range of planar seam tracking and arc length tracking canbe controlled within±0.3mm and0.4mm, respectively, which is accurateenough to meet the practical welding requirements of the real-time trackingand controlling during the welding robot GTAW process.
在实际的焊接过程中，大部分的焊接工件为空间三维焊缝。在已有的基于被动视觉的焊缝跟踪研究中，视觉系统大多只能准确地获取图像的二维信息，三维重建的方法可以计算出图像中的高度信息，但其计算的精确性和可靠性难以满足实时焊缝跟踪的要求，仅仅依靠视觉技术很难满足机器人在实际生产中对焊接高度方向上的自动跟踪控制要求。在利用视觉传感技术对焊缝进行实时在线跟踪时必须利用其他方法对焊接高度进行实时跟踪控制。本文根据铝合金脉冲GTAW的焊接特点，利用基于视觉及电弧传感的复合传感技术对焊缝进行左右和高度进行纠偏，实现机器人GTAW过程的三维焊缝实时跟踪控制，这对将传统的“示教-再现”型机器人开发成具有一定自主功能的焊接机器人系统，不断扩大机器人焊接自动化技术在国防、航空、化工及电子等部门的应用范围具有重要的理论意义和工程实用价值。
利用视觉和电弧传感技术来对机器人GTAW过程三维焊缝进行实时跟踪控制要解决三个主要问题，一个是准确地获取焊缝的三维信息，这是进行实时焊缝跟踪的前提。另外一个问题是必须找到合适的三维信息处理算法，提取出三维焊缝信息的特征值。最后必须设计合理的焊缝跟踪控制器，使其能够满足机器人GTAW过程对焊缝实时跟踪控制要求。
本文首先研究开发了一套基于视觉及电弧传感技术的机器人三维焊缝跟踪系统，具体包括焊接平台的搭建、视觉及电弧传感器的设计加工、焊接系统的标定、系统控制软件的设计以及焊接工装夹具的设计等。
要对焊缝进行准确的实时跟踪，首先需要获得描述焊缝焊接过程状态中的准确信息。通过对铝合金GTAW焊接实际电弧光谱的分析，自主研制了一套多功能被动视觉传感器。通过分析减光滤光片、电流基值以及采像时刻等参数对获取焊接图像的影响，在仅依靠焊接过程电弧光照明的情况下，实现了铝合金脉冲GTAW过程实时焊接图像清晰地获取。针对已有焊接图像边缘检测方法的不足，提出了一种改进的Canny边缘检测算法，有效改善了不同焊接图像边缘的提取效果，提高了边缘检测的准确性和自适应性。在分析焊接图像特点的基础上，开发了一套完整的图像处理算法。通过焊接实验验证，其焊接图像处理精度可以控制在±0.169mm以内，其精度能很好地满足了机器人GTAW过程实时图像处理的需求。
根据铝合金脉冲GTAW的焊接特点，利用电弧传感器对电弧电压信号进行了有效地采集，并对弧压信号特点进行了仔细分析，提出了一种基于小波包的防脉冲干扰滑动均值去噪处理方法，能有效地去除电弧电压信号中含有的大量脉冲干扰和随机非平稳噪声。在此基础上，准确地提取出了弧压信号的特征值，其处理精度能达到0.273mm。建立了电弧电压和弧长的关系模型U=3.108h+21.472，并对模型精度进行了实验验证。实验表明，根据弧压与弧长关系模型计算出的弧长与实际焊接弧长有很好的匹配，其最小误差约为0.218mm，其精度完全能够满足后续的机器人焊接高度实时跟踪控制的要求。
通过分析“示教－再现”型焊接机器人的纠偏原理和实时焊缝跟踪控制的特点，设计了基于模糊切换的Fuzzy-PID双模复合控制器来对三维焊缝进行跟踪控制。针对不同的焊缝偏差，利用模糊逻辑规则，实现了Fuzzy控制器和PID控制器的无扰切换，最大限度地保证了焊接过程焊缝跟踪的实时性，稳定性和抗干扰性。通过仿真实验表明，基于模糊切换的Fuzzy-PID双模复合控制器具有可靠性好，抗干扰能力强，跟踪能力好的特点，能很好地满足机器人实时焊缝跟踪的要求。
最后，利用本文开发的三维焊缝跟踪焊接系统对多种不同三维曲线焊缝进行了跟踪控制实验，实验结果表明，其左右最大跟踪偏差可以控制在±0.3mm范围之内，高度跟踪误差可以控制在±0.4mm范围内，基本能够满足机器人实际焊接生产的要求。
Nowadays, robot welding is a trend of welding automation technicaldevelopment; more and more welding robots have been applied in theautomatic manufacturing process at home and abroad. However, most ofthem are primary teaching-playback robots, the welding path and processparameters of which are set in advance, and the requirement of conformanceto the welding operation conditions is very strict. That means if thework-pieces of weld are changed, they must be taught and programmed again.Especially, the seam position is often disturbed by distortion, ways ofspreading heat, variability of gap, stagger edge, etc. which will affect thequality of welding forming. In the practical welding application, this type ofwelding robot cannot meet the enterprises’ requirements on superior qualityand top efficiency because of the lackness of adaptability in teaching trajectory offset and no function of real-time tracking control, which limits itsapplication in many fields. In order to overcome the uncertainty which affectsthe quality of welding, there is an urgent need to track the seam in real timefor “teaching-playback” welding robot, which will make it more flexible andintelligent.
In the practical welding process, most of the welding seams arethree-dimensional, which are difficult for the only vision technology to trackand control in real-time. However, among what have been studied in weldtracking, the passive vision technology can accurately get the2Dseam-tracking information, but the height information should be acquiredonly through3D reconstruction method. It is a pity that most of thealgorithms are too complex to be used in real-time control, which causes thatthe vision technology can hardly meet the requirements of real-time heighttrack and control during actual robotic welding process. Thus, anothertechnology must be used in height tracking while the visual sensortechnology is used in real-time3D seam tracking. The composite sensorsbased on visual sensor and arc sensor can be used in the weld of3D seam,which provides a possibility to realize the function of real-time tracking of3D welding seam during robotic GTAW process, and will develop theteaching-playback robot into an intelligent welding robot. No doubt that theseresearches supply important theoretical significance and practical value forexpanding the applied range of robot welding automation technology in manydifferent fields, such as national defense, aviation, shipbuilding, machinery,automobile, electronics and electrics.
There are three problems which should be resolved in real-time trackingof3D welding seam during robotic GTAW process based on visual sensor and arc sensor. The first one is accurately retrieving the3D welding seam.The second one is that the right signal processing method must be found,which should be accurate enough to meet the requirements of real-timetracking of3D welding seam during robotic GTAW, and the characteristics of3D welding seam should be extracted. The third one is that the design ofreasonable controller for the seam tracking must meet the requirement ofreal-time welding seam tracking for welding robot GTAW process.
Firstly，this paper designed a set of tracking and control system forthree-dimension welding seam during welding robot GTAW process based onvision sensor and Arc sensor, including the setup of experimental platform,the design and processing of sensors, the calibration of welding equipment,the design of system control software and welding fixture, etc. Theexperiment platform can make better effect of real-time control onthree-dimension welding seam during welding robot GTAW process.
To achieve accurate real-time seam tracking during welding, theaccurate information which is used to describe welding process should beobtained first. Thus, this paper designed a set of system of passive visionsensor for the robot to track the plane welding seam in real-time. The qualityof image acquisition is associated not only with dimmer-filter system, butalso with the value of base current and the time of capturing image. Througha large number of experiments, the parameters of Al alloy pulsed GTAW areascertained, such as the composite dimmer-filter system, the base current,the time of capturing images, etc. By using the passive vision sensor system,we can get some clear images during the robot weld automation process.Aiming at the deficiencies of existing edge detection algorithm, a newimproved Canny algorithm has been proposed to detect the edges of seam and pool, which effectively enhances the precision, accuracy and selfadaptability. By analyzing the features of welding images, a set of completealgorithm of image processing is proposed to extract the characteristicparameters of welding images. Finally, the algorithm of the image processingwas validated through the experiment. The precision can be controlled aboutwithin±0.169mm, which can completely meet the requirement of real-timewelding seam tracking for welding robot GTAW process.
By analyzing the characteristics of pulsed GTAW for Al alloy, the arcvoltage signals are successfully gathered by the arc sensor, and A newde-noising method of anti-impulse interference moving average based onwavelet packet is studied in this paper. The characteristics of arc voltage areextracted, which can be accurate to0.273mm. The relational model betweenarc voltage and arc length, which is U3.108h21.472, has been worked outand then confirmed by tests in the paper. The experiments have suggestedthat the characteristics of arc voltage, the arc-length calculated by therelational model and the real arc-length can be well matched, for the minimalerror is about0.218mm. Therefore, in accordance with the above points, wecan conclude that the accuracy of the relational model between arc voltageand arc length can completely meet the requirements of real-time trackingand control in height during robot GTAW process
By analyzing the deviation rectification of welding robot and thecharacteristics of3D welding seam, a compound Fuzzy-PID double modecontroller based on fuzzy rules switching has been designed for the system of3D seam tracking control during robotic GTAW process. By using fuzzylogic rules, it can shift from Fuzzy controller to PID controller according todifferent seam deviations, which ensures the maximum real time, anti-interference performance, and good stability of seam tracking in weldingprocess. It has been proved by the simulation-system test that the compoundFuzzy-PID double mode controller enjoys the advantages of excellentrobustness, strong anti-interference and tracking abilities, which cancompletely meet the requirements of real-time tracking and control duringrobot GTAW process
Finally, aiming at the complex three-dimension curve seam, someexperiments have been done to verify the precision of3D seam trackingbased on visual sensor and arc sensor technology. The results demonstratethat the precision range of planar seam tracking and arc length tracking canbe controlled within±0.3mm and0.4mm, respectively, which is accurateenough to meet the practical welding requirements of the real-time trackingand controlling during the welding robot GTAW process.
引文
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