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Projects / Programmes source: ARIS

Analysisi and Characterisation of Influence of Modulation of Output Laser Beam Power on the Quality of CO_2 Laser Beam Welding Process

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Research activity

Code Science Field Subfield
2.10.06  Engineering sciences and technologies  Manufacturing technologies and systems  Welding 

Code Science Field
T121  Technological sciences  Signal processing 
T165  Technological sciences  Laser technology 
Keywords
laser welding, process characterisation, process optimisation, signal analysis, chaotic dynamics
Evaluation (rules)
source: COBISS
Evaluation of bibliographic research performance indicators according to ARIS methodology
Citations Citations for bibliographic records in COBIB.SI that are linked to records in citation databases
source: WoS source: Scopus source: COBISS
Researchers (1)
no. Code Name and surname Research area Role Period No. of publications
1.  08782  PhD Edvard Govekar  Manufacturing technologies and systems  Head  1998 - 2001  429 
Organisations (1)
no. Code Research organisation City Registration number No. of publications
1.  0782  University of Ljubljana, Faculty of Mechanical Engineering  Ljubljana  1627031  29,223 
Abstract
The aim of the project is to investigate the possibilities of in-process characterisation and optimisation of the dynamics and the quality of the laser beam welding process. The dynamics of the process will be empirically described by the time series of light intensity emitted by the plasma which is generated during the welding process.The quality of the process is characterised by the average penetration depth and the fluctuations of the penetration depth of the laser beam into processed material. As control parameters, the feed rate, laser beam output power and focus position of the laser beam will be considered. For time series analysis, beside conventional methods also methods of non-linear and chaotic analysis will be applied. To model the relation between features of time series, process parameters, and process quality, computer simulated neural networks will be used. It is expected from the results, that beside possibilities of in-process characterisation also directions for optimisation and control strategies of the laser beam welding process by the resonant stimulation technique will be given.
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