Litcius/Paper detail

Acoustic process monitoring in laser beam welding

Leander Schmidt, Florian Römer, David Böttger, Frank Leinenbach, Benjamin Straß, Bernd Wolter, Klaus Schricker, Marc Seibold, Jean Pierre Bergmann, Giovanni Del Galdo

2020Procedia CIRP41 citationsDOIOpen Access PDF

Abstract

Structure-borne acoustic emission (AE) measurement shows major advantages regarding quality assurance and process control in industrial applications. In this paper, laser beam welding of steel and aluminum was carried out under varying process parameters (welding speed, focal position) in order to provide data by means of structure-borne AE and simultaneously high-speed video recordings. The analysis is based on conventionally (e.g. filtering, autocorrelation, spectrograms) as well as machine learning methods (convolutional neural nets) and showed promising results with respect to the use of structure-borne AE for process monitoring using the example of spatter formation.

Topics & Concepts

WeldingSpectrogramLaser beam weldingProcess (computing)Acoustic emissionConvolutional neural networkAcousticsBeam (structure)Materials scienceLaserMechanical engineeringPosition (finance)AutocorrelationComputer scienceOpticsEngineeringArtificial intelligenceStructural engineeringPhysicsEconomicsStatisticsMathematicsOperating systemFinanceLaser and Thermal Forming TechniquesWelding Techniques and Residual StressesAdvanced machining processes and optimization