Stereo vision based measuring system for online welding path inspection

Bračun, Drago; Sluga, Alojzij

doi:10.1016/j.jmatprotec.2015.04.023

Cited by 22 publications

(9 citation statements)

References 10 publications

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“…They detected the defects in the process, seams in the process of steel rolling, and flares in solar activities. Bračun and Sluga [8] used a stereo monitor for the welding track sensing system. They measured the position of the arc in the 3D space and in the time sequence.…”

Section: Literature Reviewmentioning

confidence: 99%

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A Statistical Method for Sequential Images–based Process Monitoring

Fattahzadeh

Saghaei

2020

IJE

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Today, with the growth of technology, monitoring processes by the use of video and satellite sensors have been more expanded, due to their rich and valuable information. Recently, some researchers have used sequential images for defect detection because a single image is not sufficient for process monitoring. In this paper, by adding the time dimension to the image-based process monitoring problem, we detect process changes (such as the changes in the size, location, speed, color, etc.). The temporal correlation between the images and the high dimensionality of the data make this a complex problem. To address this, using the sequential images, a statistical approach with RIDGE regression and a Q control chart is proposed to monitor the process. This method can be applied to color and gray images. To validate the proposed method, it was applied to a real case study and was compared to the best methods in literature. The obtained results showed that it was more effective in finding the changes.

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Section: Literature Reviewmentioning

confidence: 99%

“…In this problem, the objective is to detect process changes that occur, for example, in the position, speed, shape, and color by using at least two images. Sequential images can be used in many contexts, e.g., in Welding (Figure 1a (Figure 1d) [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

A Statistical Method for Sequential Images–based Process Monitoring

Fattahzadeh

Saghaei

2020

IJE

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“…Having been extensively applied to robotic welding due to its high accuracy and non-contact, vision sensing is considered one of the most promising welding seam trajectory recognition technologies [ 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 ]. Great attention has been paid to welding seam detection methods based on structured light vision sensing [ 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 ].…”

Section: Introductionmentioning

confidence: 99%

“…Mitchell et al [ 42 ] installed two color cameras on the welding gun of an industrial robot, and they used the adaptive linear growth algorithm to identify the robustness of fillet welding seams. Drago et al [ 43 ] applied a 3D vision detection system for the online detection of the 3D welding paths of arcs to automatically identify arc welding abnormalities. Yang et al [ 44 ] designed a 3D structured light sensor using a DLP projector and two cameras to obtain 3D information of welding seams.…”

Section: Introductionmentioning

confidence: 99%

Welding Seam Trajectory Recognition for Automated Skip Welding Guidance of a Spatially Intermittent Welding Seam Based on Laser Vision Sensor

Hong

Gao

et al. 2020

Sensors

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To solve the problems of low teaching programming efficiency and poor flexibility in robot welding of complex box girder structures, a method of seam trajectory recognition based on laser scanning displacement sensing was proposed for automated guidance of a welding torch in the skip welding of a spatially intermittent welding seam. Firstly, a laser scanning displacement sensing system for measuring angles adaptively is developed to detect corner features of complex structures. Secondly, a weld trajectory recognition algorithm based on Euclidean distance discrimination is proposed. The algorithm extracts the shape features by constructing the characteristic triangle of the weld trajectory, and then processes the set of shape features by discrete Fourier analysis to solve the feature vector used to describe the shape. Finally, based on the Euclidean distance between the feature vector of the test sample and the class matching library, the class to which the sample belongs is identified to distinguish the weld trajectory. The experimental results show that the classification accuracy rate of four typical spatial discontinuous welds in complex box girder structure is 100%. The overall processing time for weld trajectory detection and classification does not exceed 65 ms. Based on this method, the field test was completed in the folding special container production line. The results show that the system proposed in this paper can accurately identify discontinuous welds during high-speed metal active gas arc welding (MAG) welding with a welding speed of 1.2 m/min, and guide the welding torch to automatically complete the skip welding, which greatly improves the welding manufacturing efficiency and quality stability in the processing of complex box girder components. This method does not require a time-consuming pre-welding teaching programming and visual inspection system calibration, and provides a new technical approach for highly efficient and flexible welding manufacturing of discontinuous welding seams of complex structures, which is expected to be applied to the welding manufacturing of core components in heavy and large industries such as port cranes, large logistics transportation equipment, and rail transit.

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“…3D vision sensors are widely applied in 3D measurement due to their characteristics of non-contact and abundant information. The common 3D vision sensors include stereo vision [3]- [7] and structured light vision [8]- [10]. The stereo vision systems require neither moving parts nor active illumination and provide high spatial resolution at low power consumption [11].…”

Section: Introductionmentioning

confidence: 99%

Articulated Laser Sensor for Three-Dimensional Precision Measurement

Kang

Xue

2019

IEEE Access

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Breaking through the orthogonal shafting architecture of traditional measurement instruments, a novel articulated laser sensor for three-dimensional (3D) precision measurement is proposed. The novel sensor consists of two articulated laser sensing modules, and each module is mainly made up of two one-dimensional rotary tables and one collimated laser to achieve a flexible angle intersection. Moreover, a high-resolution digital camera is mounted on the right sensing module to achieve vision guidance. The three axes of each sensing module represent a non-orthogonal shafting architecture. The requirements of structural design, material selection, processing technology, assembling, calibration and maintain are greatly lowered. The costs are greatly reduced, including time and money. The system architecture, parameter calibration and measurement principle are elaborated. An accurate intersection model of two laser beams is proposed to calculate the accurate rotation angles of rotary tables by discrete point interpolation method. The experimental results showed that a maximum error less than 0.05 mm was detected from 100 mm to 500 mm. It is proved that 3D precision measurement is feasible with this proposed articulated laser sensor.INDEX TERMS Articulated laser sensor, non-orthogonal shafting architecture, 3D precision measurement, accurate intersection model.

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Stereo vision based measuring system for online welding path inspection

Cited by 22 publications

References 10 publications

A Statistical Method for Sequential Images–based Process Monitoring

A Statistical Method for Sequential Images–based Process Monitoring

Welding Seam Trajectory Recognition for Automated Skip Welding Guidance of a Spatially Intermittent Welding Seam Based on Laser Vision Sensor

Articulated Laser Sensor for Three-Dimensional Precision Measurement

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