研究目的
Investigating the influence of focal position on the surface topography during ultra-short pulse laser ablation and assessing the focal position in-process based on acoustic emissions.
研究成果
A strong correlation between focal position and the sum of the calculated intensity values from AE signals was detected. The intensity values exhibit large variances, thus mean values have to be calculated to reach a maximum deviation of 0.2 mm enabling in-process focal position detection. Further improvements are needed in robust signal intensity extraction for reliable focal position detection.
研究不足
The large uncertainties in signal intensity extraction need to be reduced for reliable focal position detection by acoustic emissions without calculation of mean values. The dependence of the AE signals on the location of the piezoelectric sensor in relation to the AE source needs to be investigated.
1：Experimental Design and Method Selection:
Microstructures were ablated using an ultra-short pulse laser system to investigate the influence of focal position on the surface topography. Acoustic emissions were measured by a piezoelectric sensor and analyzed.
2：Sample Selection and Data Sources:
AISI 4140 (EN steel 1.7225) in a quenched and tempered state was used as workpiece material.
3：7225) in a quenched and tempered state was used as workpiece material.
List of Experimental Equipment and Materials:
3. List of Experimental Equipment and Materials: Ultra-short pulse laser system TruMicro 5050 (Trumpf GmbH), piezoelectric sensor O-WT 232 from QASS GmbH, AE analyzing device Optimizer4D (QASS GmbH), confocal light microscopy μSurf and the μsoft analysis software of the company Nanofocus AG.
4：Experimental Procedures and Operational Workflow:
Microgrooves were ablated with varied z-axis positions and analyzed in terms of structure depths and widths. AE signals during laser processing were recorded and analyzed.
5：Data Analysis Methods:
STFT analysis was used to determine frequency ranges sensitive to variations of the z-axis position. Significant signal components were processed to enable an inference about the focal position.
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