Classification of Spot-Welded Joints in Laser Thermography Data Using Convolutional Neural Networks

Linh Kastner,Peter Jung,Florian Jonietz,Jens Lambrecht,Giuseppe Caire,Samim Ahmadi,Mathias Ziegler

doi:10.1109/access.2021.3063672

Abstract

Spot welding is a crucial process step in various industries. However, classification of spot welding quality is still a tedious process due to the complexity and sensitivity of the test material, which drain conventional approaches to its limits. In this article, we propose an approach for quality inspection of spot weldings using images from laser thermography data. We propose data preparation approaches based on the underlying physics of spot-welded joints, heated with pulsed laser thermography by analyzing the intensity over time and derive dedicated data filters to generate training datasets. Subsequently, we utilize convolutional neural networks to classify weld quality and compare the performance of different models against each other. We achieve competitive results in terms of classifying the different welding quality classes compared to traditional approaches, reaching an accuracy of more than 95 percent. Finally, we explore the effect of different augmentation methods.

Highlights

Spot welding plays a major role in joining technologies, especially in the automotive industry
Traditional methods to assure the quality of spot-welded joints include random and periodic destructive tests like torsion testing or manual destructive testing, where the specimen has to be cut in half to be investigated
We explore ways to generate feasible datasets out of utilizing the underlying physics of the laser thermography process described in the previous chapter

Summary

Introduction

Spot welding plays a major role in joining technologies, especially in the automotive industry. Traditional methods to assure the quality of spot-welded joints include random and periodic destructive tests like torsion testing or manual destructive testing, where the specimen has to be cut in half to be investigated. These methods are tedious and destroy the sample. A. RELATED WORKS Among popular NDT methods for quality inspection of welded material are ultrasonic testing, X-Ray tomography [2], acoustic emission testing and laser thermography. A non-destructive testing approach based on laser thermography was proposed by Jonietz et al [1], where the researchers could detect important metrics of quality like the welding diameter by applying active thermography in transmission and reflection. The quality of the spot-welded joints could not be assessed in detail

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Results

Conclusion