Publications

Photonics May 2026

Laser Turning with Advanced Process Monitoring by Optical Microphone

Authors:

J. Zettl, C. Lutz, R. Hellmann

Contents:

• XARION’s Eta450 Optical Microphone enabled real-time monitoring of ultrashort-pulse laser turning by detecting the ultrasonic emissions generated by individual femtosecond laser ablation events.
• Thanks to its unique ultrasound bandwidth of 50 kHz to 2 MHz, the system reliably operated in an industrial machining environment despite process gas flow, exhaust systems, and ambient machine noise.
• Analysis of the acoustic signal provided direct information on material removal, workpiece diameter reduction, surface quality, laser fluence, and beam offset position, allowing multiple process parameters to be monitored with a single sensor.
• The results demonstrate that XARION’s membrane-free Optical Microphone can serve not only as a process monitoring tool but also as a foundation for automated closed-loop process control in ultrafast laser manufacturing.

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13th CIRP Conference on Photonic Technologies  08/2024

Acoustic process monitoring during the structuring of diffusion media for fuel cells with Ultrashort Laser Pulses

Authors:

Christian Geigera, Pawel Garkushaa, Christian Bernauera, Simon Mehrla, Pascal A. Schirmerb, Michael F. Zaeha

Contents:

•          Diffusion media in fuel cells can be optimized through laser structuring to improve their performance characteristics.
•          An optical microphone was used to monitor the process during laser structuring.
•          This paper demonstrated that acoustic data can be used to monitor the laser focus position as well as material transitions in the diffusion media during structuring.

13th CIRP Conference on Photonic Technologies

Wood Materal Science & Engineering  10/2024

Predicting wood moisture classes by sound frequency spectra and Explainable Machine Learning during milling

Authors:

Mehieddine Derbas, Timothy Mark Young, Stephan Frömel-Frybort, Hans- Christian Möhring & Martin Riegler

Contents:

•          The moisture content in wood has a strong impact on the optimal process parameters during milling.
•          In this work, wood milling was monitored by a novel optical microphone to distinguish between moisture classes (dried, conditioned, wet and frozen).
•          Machine learning was applied to the selected spectral data to determine both the moisture classes and milling speed. The best model achieved an accuracy of 97.2%. 

Wood Materal Science & Engineering

Journal of Laser Applications  03/2025

Layer detection in ultrashort pulsed multilayer laser ablation by analyzing ultrasonic process emission

Authors:

Christian Lutz, Cemal Esen, Ralf Hellmann

Contents:

• Laser ablation is used for processing electronic applications (e.g. PCB)
• This paper presents the detection of material transitions during laser ablation by analyzing acoustic data captured with an optical microphone.
• The focus of this work was on the material transition between polyimide and copper. Due to the higher removal rate in polyimide compared to copper, a    significant increase in acoustic energy was detected at the material transition.
•  In addition to detecting material transitions, a correlation between the emitted acoustic energy and layer thickness was observed.

Journal of Laser Applications

17th CIRP Conference on Intelligent Computation in Manufacturing Engineering (CIRP ICME ‘23)  08/2024

In-situ acoustic signals correlation of process parameters in laser powder bed fusion

Authors:

Levent Subasi, Soner Oren, Gokhan Dursun, Cagdas Sen, Akin Orhangul

Contents:

• Laser powder bed fusion (LPBF) is a metal additive manufacturing technique in which repeatability is a major concern in quality results.
•          An optical microphone was used to monitor the acoustic emission during the LPBF process.
•          The analysis showed a strong correlation between the acoustic signals and the process parameters.
•         This methodology allows for the evaluation of process flaws and overall quality.

17th CIRP Conference on Intelligent Computation in Manufacturing Engineering

Proceedings of LANE 2024 Fürth, Germany 09/2024

Toward in-line crack detection and localization during metal additive manufacturing using laser-based air-coupled ultrasound sensors

Authors:

Matthias Kettner, Ryan Sommerhuber et.al.

Contents:

• The study demonstrates that ultrasonic emissions generated during the L-DED process enable reliable, early in-line detection of cold cracks in metal additive manufacturing.
• Using XARION’s air-coupled Optical Microphone, both the occurrence and exact timing of crack formation were identified through their characteristic signatures and correlated with the robot’s motion profile.
• This allowed precise defect localization even on large components, while initial experiments with a sensor array highlight the potential of even more accurate triangulation methods for future real-time monitoring solutions.

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Applied Sciences 10/2024

Acoustic Emission and Digital Image Correlation-Based Study for Early Damage Identification in Sandwich Structures

Authors:

Aitor García de la Yedra, Igor Erro, et al.

Contents:

• Monitoring the quality of complex sandwich structures is difficult with common testing techniques for accessibility reasons
• A novel approach to solve this issue is enabled by acoustic monitoring in the ultrasound regime with the Optical Microphone
• The results from acoustic monitoring were compared to findings obtained with digital image correlation
• It could be shown that early identification of structural damage is possible with the Optical Microphone

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Additive Manufacturing 01/2024

Healing of keyhole porosity by means of defocused laser beam remelting: Operando observation by X-ray imaging and acoustic emission-based detection

Authors:

Charlotte de Formanoir, Milad Hamidi Nasab, et al.

Contents:

• In Laser Powder-Bed Fusion (LPBF) the unpredictable formation of defects such as pores can lead to compromised mechanical properties
• Using XARION’s optical microphone a strategy for monitoring in-situ healing of pores through laser remelting was implemented
• Acoustic signals acquired during laser remelting are temporally synchronized and analyzed with X-ray images to identify acoustic signatures of the pore healing event
• The approach presented in this paper enables precise monitoring of defect healing during the LPBF process without the use of elaborate machine learning algorithms

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