scholarly journals Real-Time Weld Quality Prediction Using a Laser Vision Sensor in a Lap Fillet Joint during Gas Metal Arc Welding

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1625
Author(s):  
Kidong Lee ◽  
Insung Hwang ◽  
Young-Min Kim ◽  
Huijun Lee ◽  
Munjin Kang ◽  
...  
Keyword(s):  
Real Time ◽  
Prediction Models ◽  
Gma Welding ◽  
Gas Metal Arc Welding ◽  
Welding Process ◽  
Quality Prediction ◽  
Vision Sensor ◽  
Image Processing Algorithm ◽  
Laser Vision Sensor ◽  
Laser Vision

Nondestructive test (NDT) technology is required in the gas metal arc (GMA) welding process to secure weld robustness and to monitor the welding quality in real-time. In this study, a laser vision sensor (LVS) is designed and fabricated, and an image processing algorithm is developed and implemented to extract precise laser lines on tested welds. A camera calibration method based on a gyro sensor is used to cope with the complex motion of the welding robot. Data are obtained based on GMA welding experiments at various welding conditions for the estimation of quality prediction models. Deep neural network (DNN) models are developed based on external bead shapes and welding conditions to predict the internal bead shapes and the tensile strengths of welded joints.

Application of laser profilo metry in problems of welding equipment geometric adaptation

2021 ◽  
Author(s):  
Keyword(s):  
Neural Network ◽  
Welded Joint ◽  
Piecewise Linear ◽  
Welding Process ◽  
Piecewise Linear Approximation ◽  
Vision Sensor ◽  
Welding Equipment ◽  
The Neural Network ◽  
Laser Vision Sensor ◽  
Laser Vision

Adaptive adjustment of the relationship between the welding process parameters and the butt geometry permits to reduce the likelihood of welding defects appearance and improve the quality of the welded joint in automatic welding of large-diameter pipes. To obtain data on the configuration of the welded joint, the RF627 laser vision sensor is used. To reduce the influence of restrictions arising during the welding process, a median algorithm for filtering impulse noise is proposed. To calculate the geometric parameters of the welded joint, a model based on pixel data obtained from a laser sensor is proposed. The restoration of the welded butt parameters is carried out according to the algorithm of piecewise-linear approximation, which involves the determination of six characteristic points of the butt. The adaptive adjuster uses an inverse neural network model for adjustment the parameters of the welding process: welding current, voltage, wire feed speed. To train the neural network, the characteristic parameters of the welded butt are used: gap, skewing (warping of the edges) and bluntness (for the root weld), the current width of the butt groove in each layer (for other types of welds). The weights of the neural network layers are restored online using a gradient descent algorithm. The important role of the laser vision sensor in solving the problem of adaptation of welding equipment and the effectiveness of the proposed algorithms are confirmed experimentally. Keywords laser vision sensor; robotic welding; multilayer/multi-pass welding; piecewise linear approximation; adaptive control with a reverse neural network model

Development of an auto-welding system for CRD nozzle repair welds using a 3D laser vision sensor

2007 ◽  
Vol 21 (10) ◽  
pp. 1720-1725 ◽  
Author(s):  
K. Park ◽  
Y. Kim ◽  
J. Byeon ◽  
K. Sung ◽  
C. Yeom ◽  
...  
Keyword(s):  
Vision Sensor ◽  
Laser Vision Sensor ◽  
Laser Vision ◽  
Welding System

A study on the welding seam tracking by using Laser Vision Sensor

ICCAS 2010 ◽  
2010 ◽  
Author(s):  
Taewook Kim ◽  
Seungbeom Lee ◽  
Seunghwan Baek ◽  
Kwangsuck Boo
Keyword(s):  
Seam Tracking ◽  
Vision Sensor ◽  
Welding Seam ◽  
Laser Vision Sensor ◽  
Laser Vision

Welding seam recognition and tracking for a novel mobile welding robot based on multi-layer sensing strategy

2021 ◽  
Author(s):  
Chao Liu ◽  
Hui Wang ◽  
Yu Huang ◽  
Youmin Rong ◽  
Jie Meng ◽  
...  
Keyword(s):  
Seam Tracking ◽  
Sensor System ◽  
Vision Sensor ◽  
Welding Robot ◽  
Welding Seam ◽  
Localization And Mapping ◽  
Laser Vision Sensor ◽  
Tracking Ability ◽  
Mobile Welding Robot ◽  
Laser Vision

Abstract Mobile welding robot with adaptive seam tracking ability can greatly improve the welding efficiency and quality, which has been extensively studied. To further improve the automation in multiple station welding, a novel intelligent mobile welding robot consists of a four-wheeled mobile platform and a collaborative manipulator is developed. Under the support of simultaneous localization and mapping (SLAM) technology, the robot is capable of automatically navigating to different stations to perform welding operation. To automatically detect the welding seam, a composite sensor system including an RGB-D camera and a laser vision sensor is creatively applied. Based on the sensor system, the multi-layer sensing strategy is performed to ensure the welding seam can be detected and tracked with high precision. By applying hybrid filter to the RGB-D camera measurement, the initial welding seam could be effectively extracted. Then a novel welding start point detection method is proposed. Meanwhile, to guarantee the tracking quality, a robust welding seam tracking algorithm based on laser vision sensor is presented to eliminate the tracking discrepancy caused by the platform parking error, through which the tracking trajectory can be corrected in real-time. The experimental results show that the robot can autonomously detect and track the welding seam effectively in different station. Also, the multiple station welding efficiency can be improved and quality can also be guaranteed.

Improving the tracking quality of the weld seam butt with V-form grooving by using Kalman filter and neural network

2021 ◽  
Author(s):  
Keyword(s):  
Neural Network ◽  
Kalman Filter ◽  
Colored Noise ◽  
Weld Seam ◽  
Vision Sensor ◽  
Laser Vision Sensor ◽  
Characteristic Points ◽  
Laser Vision ◽  
Weld Seams

An algorithm for tracking of the welded seams grooving by using a Kalman filter based on six characteristic points of the profile obtained using the RF627 laser vision sensor is proposed. In order to reduce the error in weld seams control, a multilayer neural network with a backpropagation algorithm is created to compensate for errors caused by colored noise when using the Kalman filter. Experimental results show that when the algorithm is applied, the error in tracking the trajectory of weld seams is reduced. Keywords tracking of weld seams; multilayer/multi-pass welding; Kalman filter; multilayer perceptron

Measurement of Weld Bead Defect for Shock Absorber Using Laser Vision Sensor

2004 ◽  
Vol 270-273 ◽  
pp. 2332-2337 ◽  
Author(s):  
H. Lee ◽  
K. Sung ◽  
H. Park ◽  
Se Hun Rhee
Keyword(s):  
Shock Absorber ◽  
Weld Bead ◽  
Vision Sensor ◽  
Laser Vision Sensor ◽  
Laser Vision

Validation of evaporation-determined model of arc-cathode coupling in the peak current phase in pulsed GMA welding

2021 ◽  
Author(s):  
Marek Sebastian Simon ◽  
Oleg Mokrov ◽  
Rahul Sharma ◽  
Uwe Reisgen ◽  
Guokai Zhang ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Weld Pool ◽  
Cathode Surface ◽  
Gma Welding ◽  
Gas Metal Arc Welding ◽  
Welding Process ◽  
Qualitative Reasoning ◽  
Current Phase ◽  
Temperature Plasma ◽  
Peak Current

Abstract A first experimental validation of the EDACC (evaporation-determined arc-cathode coupling) model is performend by comparing the experimental and simulated current in the peak current phase of a pulsed GMAW (gas metal arc welding) process. For this, the EDACC model was extended to limit the cathode surface temperature to a realistic value of <2400K. The information on the plasma for the EDACC model was gathered from literature and extrapolated and extended according to qualitative reasoning. The information on the cathode surface of the EDACC model was derived from a steady-state simulation of the weld pool, using an averaging approach over time for the energy and current. The weld pool surface temperature was compared to pyrometric measurements, that were performed for this work, and the agreement was found to be fair. The observed agreement between the modelled and experimentally determined current was within 10%. As strong assumptions were made for the comparison, the validation cannot be considered as final, but the assumptions are thoroughly analyzed and discussed. However the critical link between surface temperature, plasma temperature and total current transmitted could be reconstructed.

Laser Vision Sensor for Disaster-Prevention Robot

1989 ◽  
Vol 1 (4) ◽  
pp. 274-277
Author(s):  
Minoru Kimura ◽  
◽  
Osamu Yamada ◽  
Hidemi Takahashi ◽  
Hiroshi Naitoh
Keyword(s):  
Disaster Prevention ◽  
Vision Sensor ◽  
Laser Vision Sensor ◽  
Laser Vision
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