An On-line Visual Seam Tracking Sensor System During Laser Beam Welding

Zhang, Lei; Wu, Chuanyu; Zou, Yuanyuan

doi:10.1109/itcs.2009.211

Cited by 7 publications

(3 citation statements)

References 12 publications

(5 reference statements)

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“…In order to determine the region of interest, Radon transform is applied to the captured image, and median filtering and thresholding are then also used for denoising [17,18]. Zhang et al [19] used the similar method to extract WSP in laser beam welding. Gu et al [20] proposed a image preprocessing method to eliminate the impact of arc light, light reflection and splashes on the captured image, which includes adaptive threshold segmentation and smoothing.…”

Section: Introductionmentioning

confidence: 99%

Discerning Weld Seam Profiles from Strong Arc Background for the Robotic Automated Welding Process via Visual Attention Features

Zhang

et al. 2020

Chin. J. Mech. Eng.

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In the robotic welding process with thick steel plates, laser vision sensors are widely used to profile the weld seam to implement automatic seam tracking. The weld seam profile extraction (WSPE) result is a crucial step for identifying the feature points of the extracted profile to guide the welding torch in real time. The visual information processing system may collapse when interference data points in the image survive during the phase of feature point identification, which results in low tracking accuracy and poor welding quality. This paper presents a visual attention featurebased method to extract the weld seam profile (WSP) from the strong arc background using clustering results. First, a binary image is obtained through the preprocessing stage. Second, all data points with a gray value 255 are clustered with the nearest neighborhood clustering algorithm. Third, a strategy is developed to discern one cluster belonging to the WSP from the appointed candidate clusters in each loop, and a scheme is proposed to extract the entire WSP using visual continuity. Compared with the previous methods the proposed method in this paper can extract more useful details of the WSP and has better stability in terms of removing the interference data. Considerable WSPE tests with butt joints and T-joints show the anti-interference ability of the proposed method, which contributes to smoothing the welding process and shows its practical value in robotic automated welding with thick steel plates.

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Section: Introductionmentioning

confidence: 99%

Discerning Weld Seam Profiles from Strong Arc Background for the Robotic Automated Welding Process via Visual Attention Features

Zhang

et al. 2020

Chin. J. Mech. Eng.

View full text Add to dashboard Cite

show abstract

“…In recent decades, the laser stripe sensor has been widely used and is becoming promising in many industrial applications, such as a seam tracking system [ 1 ], a weld quality inspecting system [ 2 ] and an inspection system of automobile assembly [ 3 ], because of its fast acquisition speed, very simple mechanical structure, low cost, and robustness. The main working principle of the laser stripe sensor is that a laser line projector projects a single laser stripe plane onto the object’s surface, forming a light stripe.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Calibration of a Novel One-Mirror Galvanometric Laser Scanner

Chen

2017

Sensors

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A laser stripe sensor has limited application when a point cloud of geometric samples on the surface of the object needs to be collected, so a galvanometric laser scanner is designed by using a one-mirror galvanometer element as its mechanical device to drive the laser stripe to sweep along the object. A novel mathematical model is derived for the proposed galvanometer laser scanner without any position assumptions and then a model-driven calibration procedure is proposed. Compared with available model-driven approaches, the influence of machining and assembly errors is considered in the proposed model. Meanwhile, a plane-constraint-based approach is proposed to extract a large number of calibration points effectively and accurately to calibrate the galvanometric laser scanner. Repeatability and accuracy of the galvanometric laser scanner are evaluated on the automobile production line to verify the efficiency and accuracy of the proposed calibration method. Experimental results show that the proposed calibration approach yields similar measurement performance compared with a look-up table calibration method.

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“…This technology has been well studied. Significant research has been conducted on vision system computing techniques for a variety of tasks such as guiding of position (Chen et al , 2006; Chen and Chen, 2010), seam tracking (Zhang et al , 2009), pose detection (Park et al , 2009), and trajectory reconstruction (Chen et al , 2005; Cojanu and Marra, 2009). However, most studies have not addressed accuracy analysis and effect‐factors for the use of stereo vision technology robotic arc welding.…”

Section: Introductionmentioning

confidence: 99%

Model analysis and experimental technique on computing accuracy of seam spatial position information based on stereo vision for welding robot

Chen

Huang

Chen

2012

Industrial Robot: An International Journal

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PurposeStereo vision technique simulates the function of the human eyes to observe the world, which can be used to compute the spatial information of weld seam in the robot welding field. It is a typical kind of application to fix two cameras on the end effector of robot when stereo vision is used in intelligent robot welding. In order to analyse the effect of vision system configuration on vision computing, an accuracy analysis model of vision computing is constructed, which is a good guide for the construction and application of stereo vision system in welding robot field.Design/methodology/approachA typical stereo vision system fixed on welding robot is designed and constructed to compute the position information of spatial seam. A simplified error analysis model of the two arbitrary putting cameras is built to analyze the effect of sensors' structural parameter on vision computing accuracy. The methodology of model analysis and experimental verification are used in the research. And experiments related with image extraction, robot movement accuracy is also designed to analyze the effect of equipment accuracy and related processed procedure in vision technology.FindingsEffect of repeatability positioning accuracy and TCP calibration error of welding robot for visual computing are also analyzed and tested. The results show that effect of the repeatability on computing accuracy is not bigger than 0.3 mm. However, TCP affected the computing accuracy greatly, when the calibrated error of TCP is bigger than 0.5, the re‐calibration is very necessary. The accuracy analysis and experimental technique in this paper can guide the research of three‐dimensional information computing by stereo vision and improve the computed accuracy.Originality/valueThe accuracy of seam position information is affected by many interactional factors, the systematic experiments and a simplified error analysis model are designed and established, the main factors such as the sensor's configurable parameters, the accuracy of arc welding robot and the accuracy of image recognition, are included in the model and experiments. The model and experimental method are significant for design of visual sensor and improvement of computing accuracy.

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An On-line Visual Seam Tracking Sensor System During Laser Beam Welding

Cited by 7 publications

References 12 publications

Discerning Weld Seam Profiles from Strong Arc Background for the Robotic Automated Welding Process via Visual Attention Features

Discerning Weld Seam Profiles from Strong Arc Background for the Robotic Automated Welding Process via Visual Attention Features

Modeling and Calibration of a Novel One-Mirror Galvanometric Laser Scanner

Model analysis and experimental technique on computing accuracy of seam spatial position information based on stereo vision for welding robot

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