Informational properties of surface acoustic waves generated by laser-material interactions during laser precision machining

Laser precision machining is primarily a computer numerical control based technology; therefore, the need for on-line process monitoring and control system is very high, mainly because, under usual circumstances, the operator has to make a host of complex decisions, based on a trial-and-error method...

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Veröffentlicht in:Measurement science & technology 2002-06, Vol.13 (6), p.836-845, Article 303
Hauptverfasser: Bordatchev, Evgueni V, Nikumb, Suwas K
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Sprache:eng
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Zusammenfassung:Laser precision machining is primarily a computer numerical control based technology; therefore, the need for on-line process monitoring and control system is very high, mainly because, under usual circumstances, the operator has to make a host of complex decisions, based on a trial-and-error method, to set the process control parameters related to the laser, optics, workpiece material and motion system. However, the crucial element of any control system is information about the process and system dynamics. The problem of choosing reliable and, at the same time, physically observed information on process parameters becomes more complicated in the case of laser precision machining where the laser-material interactions generate a number of emissions with a different physical nature. To capture the informational properties from the measured signals and parameters for the purpose of monitoring and controlling the process, a thorough understanding of the entire laser-machining system performance and the laser-material interactions is required. This paper describes a method for the analysis of informational properties of surface acoustic waves to generate the knowledge as an informational basis for future development of on-line monitoring and process control systems. The study involves measurement of the acoustic emission signal from the laser-material interaction zone, the statistical and spectral signatures and the pattern recognition analysis to select informational parameters, which could reliably correlate with variations within the incident laser pulse energy.
ISSN:0957-0233
1361-6501
DOI:10.1088/0957-0233/13/6/303