Visual weld inspection enters the new millennium

Sensor Review ◽  
2001 ◽  
Vol 21 (4) ◽  
pp. 278-282 ◽  
Author(s):  
Jeffrey Noruk
Keyword(s):  
Automotive Industry ◽  
Visual Inspection ◽  
Three Dimensional ◽  
Sensor Technology ◽  
Production Lines ◽  
Inspection Systems ◽  
Weld Inspection ◽  
Welding Consumables ◽  
Handheld Scanner ◽  
Welding Processes

New weld inspection methods superceding visual inspection are presented. Laser‐based sensor technology contained in a handheld scanner for pre‐ and post‐weld inspection enables measurement of joint preparations or finished welds and validation of their geometry against pre‐set limits, as well as the analysis of three‐dimensional images of weld beads. The range of laser‐based sensor equipment available extends to full robotic weld inspection systems, which are applied in arc and laser welding processes on production lines, such as in the automotive industry. The benefits of these systems include higher repeatability, a permanent record for generating trending information, and the production of data helpful in reducing welding consumables used, resulting in significant savings to manufacturers.

Synchronous Position Control of Robotics System for Infrastructure Inspection Moving on Rope Tether

2019 ◽  
Vol 31 (2) ◽  
pp. 317-328 ◽  
Author(s):  
Makpal Sarieva ◽  
◽  
Lei Yao ◽  
Kei Sugawara ◽  
Tadashi Egami
Keyword(s):  
Control System ◽  
Wireless Communication ◽  
Disturbance Observer ◽  
Visual Inspection ◽  
Mobile Robotics ◽  
Position Control ◽  
Three Dimensional ◽  
Inspection Systems ◽  
Infrastructure Inspection ◽  
Cable Robots

Most bridges, tunnels, dams, and other infrastructure facilities were constructed in the 1950s to 1960s. At present, aging in these facilities is a social problem. Most of the maintenance check-ups of these infrastructure facilities are manually conducted by close visual inspection, which has limitations. As a result, there have been many proposals on inspection systems for unmanned infrastructure facilities, such as drones and cable robots. However, there are also problems with the use of cable robots and drones, such as restrictions in places that they can be used and effects from the environment. Thus, this study proposes a robotics system for infrastructure inspection that solves such problems. Two robots move on parallel ropes stretching in an H shape, and one robot with a three-dimensional gimbal and camera moves on a rope stretching between those robots. At this time, the three robots are capable of efficient, highly accurate wide-ranging observation by carrying out synchronous position control using wireless communication. The control system has optimum synchronous position capabilities and uses a disturbance observer. Regarding this infrastructure inspection robotics system, this study discusses the development of three mobile robotics systems and the synchronous position control of two robots.

scholarly journals A Vision-Based Self-Calibration Method for Robotic Visual Inspection Systems

Sensors ◽  
2013 ◽  
Vol 13 (12) ◽  
pp. 16565-16582 ◽  
Author(s):  
Shibin Yin ◽  
Yongjie Ren ◽  
Jigui Zhu ◽  
Shourui Yang ◽  
Shenghua Ye
Keyword(s):  
Visual Inspection ◽  
Calibration Method ◽  
Self Calibration ◽  
Inspection Systems

Artificial intelligence-based automatic visual inspection system for built heritage

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lukman E. Mansuri ◽  
D.A. Patel
Keyword(s):  
Artificial Intelligence ◽  
Visual Inspection ◽  
Image Data ◽  
Inspection System ◽  
Data Set ◽  
Web Based ◽  
Content Type ◽  
Built Heritage ◽  
Automatic Visual Inspection ◽  
Inspection Systems

PurposeHeritage is the latent part of a sustainable built environment. Conservation and preservation of heritage is one of the United Nations' (UN) sustainable development goals. Many social and natural factors seriously threaten heritage structures by deteriorating and damaging the original. Therefore, regular visual inspection of heritage structures is necessary for their conservation and preservation. Conventional inspection practice relies on manual inspection, which takes more time and human resources. The inspection system seeks an innovative approach that should be cheaper, faster, safer and less prone to human error than manual inspection. Therefore, this study aims to develop an automatic system of visual inspection for the built heritage.Design/methodology/approachThe artificial intelligence-based automatic defect detection system is developed using the faster R-CNN (faster region-based convolutional neural network) model of object detection to build an automatic visual inspection system. From the English and Dutch cemeteries of Surat (India), images of heritage structures were captured by digital camera to prepare the image data set. This image data set was used for training, validation and testing to develop the automatic defect detection model. While validating this model, its optimum detection accuracy is recorded as 91.58% to detect three types of defects: “spalling,” “exposed bricks” and “cracks.”FindingsThis study develops the model of automatic web-based visual inspection systems for the heritage structures using the faster R-CNN. Then it demonstrates detection of defects of spalling, exposed bricks and cracks existing in the heritage structures. Comparison of conventional (manual) and developed automatic inspection systems reveals that the developed automatic system requires less time and staff. Therefore, the routine inspection can be faster, cheaper, safer and more accurate than the conventional inspection method.Practical implicationsThe study presented here can improve inspecting the built heritages by reducing inspection time and cost, eliminating chances of human errors and accidents and having accurate and consistent information. This study attempts to ensure the sustainability of the built heritage.Originality/valueFor ensuring the sustainability of built heritage, this study presents the artificial intelligence-based methodology for the development of an automatic visual inspection system. The automatic web-based visual inspection system for the built heritage has not been reported in previous studies so far.

Initialisation of Autonomous Aircraft Visual Inspection Systems via CNN-Based Camera Pose Estimation

2021 ◽  
Author(s):  
Xueyan Oh ◽  
Leonard Loh ◽  
Shaohui Foong ◽  
Zhong Bao Andy Koh ◽  
Kow Leong Ng ◽  
...  
Keyword(s):  
Pose Estimation ◽  
Visual Inspection ◽  
Camera Pose Estimation ◽  
Camera Pose ◽  
Inspection Systems ◽  
Autonomous Aircraft

High Strength Consumables for High Dilution Submerged Arc Welding

2006 ◽  
Author(s):  
Matthew James ◽  
Teresa Melfi ◽  
Rajeev Katiyar
Keyword(s):  
High Strength ◽  
Alloy System ◽  
High Heat ◽  
High Dilution ◽  
Base Materials ◽  
Welding Consumables ◽  
Future Work ◽  
Welding Processes ◽  
Submerged Arc ◽  
Very High

Current requirements for high strength pipelines are placing extreme demands on welding consumables. These applications include strain based pipelines using X80 as well as traditionally designed pipelines using X100 and even X120 base materials. Traditional procedures used in the pipemills for both the seam weld and the jointer weld utilize a SAW process with very high dilution and high heat inputs. Existing consumables are not able to meet the minimum strength requirements under these conditions. A project was undertaken to develop an alloy system that could meet these requirements while still allowing the use of traditional welding processes. Testing results with this new consumable are presented and future work is described. This alloy system may also prove useful in other high dilution applications where high strength is required.

scholarly journals An Implementation of Yolo-family Algorithms in Classifying the Product Quality for the ABS Metallization

2021 ◽  
Author(s):  
YUH-WEN CHEN ◽  
Jing Mau Shiu
Keyword(s):  
Visual Inspection ◽  
Acrylonitrile Butadiene Styrene ◽  
Labor Cost ◽  
Classification Performance ◽  
Video Data ◽  
Production Lines ◽  
Learning Framework ◽  
Optical Inspection ◽  
The Neural Network ◽  
Product Surface

Abstract In the traditional electroplating industry of Acrylonitrile Butadiene Styrene (ABS), quality control inspection of the product surface is usually performed with the naked eye. However, these defects on the surface of electroplated products are minor and easily ignored under reflective conditions. If the number of defectiveness and samples is too large, manual inspection will be challenging and time-consuming. We innovatively applied Additive Manufacturing (AM) to design and assemble an automatic optical inspection (AOI) system. The system can identify defects on the reflective surface of the plated product. Based on the deep learning framework from YOLO, we successfully started the neural network model on GPU using the family of YOLO algorithms: from v2 to v5. Finally, our efforts showed an accuracy rate over an average of 70 percentage for detecting real-time video data in production lines. We also compare the classification performance among various YOLO algorithms. Our efforts of visual inspection significantly reduce the labor cost of visual inspection in the electroplating industry.

scholarly journals Prediction of Residual Stresses in a Multipass Pipe Weld by a Novel 3D Finite Element Approach

2018 ◽  
Author(s):  
Hui Huang ◽  
Jian Chen ◽  
Blair Carlson ◽  
Hui-Ping Wang ◽  
Paul Crooker ◽  
...  
Keyword(s):  
Finite Element ◽  
Residual Stresses ◽  
High Performance ◽  
Large Scale ◽  
Graphics Processing Unit ◽  
Computational Cost ◽  
Three Dimensional ◽  
Processing Unit ◽  
Girth Welds ◽  
Welding Processes

Due to enormous computation cost, current residual stress simulation of multipass girth welds are mostly performed using two-dimensional (2D) axisymmetric models. The 2D model can only provide limited estimation on the residual stresses by assuming its axisymmetric distribution. In this study, a highly efficient thermal-mechanical finite element code for three dimensional (3D) model has been developed based on high performance Graphics Processing Unit (GPU) computers. Our code is further accelerated by considering the unique physics associated with welding processes that are characterized by steep temperature gradient and a moving arc heat source. It is capable of modeling large-scale welding problems that cannot be easily handled by the existing commercial simulation tools. To demonstrate the accuracy and efficiency, our code was compared with a commercial software by simulating a 3D multi-pass girth weld model with over 1 million elements. Our code achieved comparable solution accuracy with respect to the commercial one but with over 100 times saving on computational cost. Moreover, the three-dimensional analysis demonstrated more realistic stress distribution that is not axisymmetric in hoop direction.

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