Development of three-dimensional welding deformation measurement based on stereo imaging technique

Shibahara, Masakazu; Kawamura, Eri; Ikushima, Kazuki; Itoh, Shinsuke; Mochizuki, Masahito; Masaoka, Koji

doi:10.1080/09507116.2012.715877

Cited by 3 publications

(2 citation statements)

References 10 publications

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“…The digital image correlation (DIC) technique has already been used to measure strain during the welding process. A digital camera was employed by Shibahara et al [10][11][12] to measure in-situ full-field deformation distribution during welding.…”

Section: Introductionmentioning

confidence: 99%

Investigation of solidification cracking susceptibility during laser beam welding using an in-situ observation technique

Bakir

Gumenyuk

Rethmeier

2018

Science and Technology of Welding and Joining

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In recent years, laser beam welding has found wide applications in many industrial fields. Solidification cracks are one of the most frequently encountered welding defects that hinder obtaining a safe weld joint. Decades of research have shown that one of the main causes of such cracks are the strain and the strain rate. Obtaining meaningful measurements of these strains has always been a major challenge for scientists, because of the specific environment of the measurement range and the many obstacles, as well as the high temperature and the plasma plume. In this study, a special experimental setup with a high-speed camera was employed to measure the strain during the welding process. The hot cracking susceptibility was investigated for 1.4301 stainless steel, and the critical strain required for solidification crack formation was locally and globally determined.

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Section: Introductionmentioning

confidence: 99%

Investigation of solidification cracking susceptibility during laser beam welding using an in-situ observation technique

Bakir

Gumenyuk

Rethmeier

2018

Science and Technology of Welding and Joining

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“…Displacement measurements can be made by generating speckle patterns that do not disappear at high temperatures. Stereo imaging technique (Shibahara, et al, 2013) can be used to measure the displacements of the three directional components, even when relatively large out-of-plane deformations occur.…”

Section: Basic Formulationmentioning

confidence: 99%

Non-destructive estimation of three-dimensional creep strain based on non-linear inverse analysis using displacement

FUJII,

OGAWA

2024

Mechanical Engineering Journal

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In mechanical structures exposed to high temperatures, such as turbine blades for power generation, cracks are detected during in-service inspections. However, there is a risk of fracture owing to the relatively rapid rate of crack propagation, even when a large safety factor is in force. Therefore, a technique is required to estimate the creep-strain distribution before crack initiation and to predict the remaining service life. An inverse analysis method, based on the eigenstrain methodology, has been proposed to estimate the three-dimensional creep-strain distribution using non-destructively measured surface displacements. Three-dimensional creep-strain distributions can be estimated even when the relationship between the creep strain and displacement is non-linear. Through iterative calculations, this method converges to a solution with relatively high estimation accuracy, however, a method for estimating actual complex creep-strain distributions is needed. In this study, a method was proposed to improve the convergence of the iterative calculations. Its effectiveness was demonstrated by numerical analysis using a torsional geometry model that could be used to describe an actual turbine blade. Many unknown values were assumed so that relatively complex creep-strain distributions could be estimated. Convergence calculations were performed to improve the estimation accuracy through iterative calculations, even when displacement measurement errors were considered. The estimation accuracy was improved by using more actual measurements in the inverse analysis.

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Strain Prediction Using Deep Learning during Solidification Crack Initiation and Growth in Laser Beam Welding of Thin Metal Sheets

et al. 2023

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The strain field can reflect the initiation time of solidification cracks during the welding process. The traditional strain measurement is to first obtain the displacement field through digital image correlation (DIC) or optical flow and then calculate the strain field. The main disadvantage is that the calculation takes a long time, limiting its suitability to real-time applications. Recently, convolutional neural networks (CNNs) have made impressive achievements in computer vision. To build a good prediction model, the network structure and dataset are two key factors. In this paper, we first create the training and test sets containing welding cracks using the controlled tensile weldability (CTW) test and obtain the real strain fields through the Lucas–Kanade algorithm. Then, two new networks using ResNet and DenseNet as encoders are developed for strain prediction, called StrainNetR and StrainNetD. The results show that the average endpoint error (AEE) of the two networks on our test set is about 0.04, close to the real strain value. The computation time could be reduced to the millisecond level, which would greatly improve efficiency.

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Development of three-dimensional welding deformation measurement based on stereo imaging technique

Cited by 3 publications

References 10 publications

Investigation of solidification cracking susceptibility during laser beam welding using an in-situ observation technique

Investigation of solidification cracking susceptibility during laser beam welding using an in-situ observation technique

Non-destructive estimation of three-dimensional creep strain based on non-linear inverse analysis using displacement

Strain Prediction Using Deep Learning during Solidification Crack Initiation and Growth in Laser Beam Welding of Thin Metal Sheets

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