3D particle tracking velocimetry for the determination of temporally resolved particle trajectories within laser powder bed fusion of metals - Eschner, Eric; Staudt, Tobias; Schmidt, Michael (International Journal of Extreme Manufacturing, 2019)

Acoustic differentiation of dental soft and hard tissues using remote speckle-analysis during Er:YAG ablation - Lengenfelder, Benjamin; Schwarzkopf, Karen; Oetter, Nicolai; Mehari, Fanuel; Eschner, Eric; Klämpfl, Florian; Stelzle, Florian; Kesting, Marco Rainer; Zalevsky, Zeev; Schmidt, Michael (Opto-Acoustic Methods and Applications in Biophotonics IV; 110771L (2019), 2019)
The Er:YAG laser has gained significant interest in the field of oral surgery due to its high water absorptivity, precision and patient acceptance. However, its application is limited by the lack of a contact-free feedback system which would enable safe laser guidance. In this work, a potential new, robust feedback modality based on speckle-analysis is presented which detects the acoustic signals produced during laser surgery. Oral soft- and hard tissue samples are investigated ex-vivo for its differentiation capability using the speckle modality. This technique might help to broaden the clinical application of Er:YAG laser
Keywords: Laser surgery; Er:YAG laser; tissue differentiation

Arrangement for the benchmarking of in-situ process monitoring of topographical process signatures within the Laser Powder Bed Fusion process - Schwarzkopf, Karen; Eschner, Eric; Schmidt, Michael (Proceedings of the Lasers in Manufacturing (LiM), 2021)

Camera-based closed-loop control for beam positioning during deep penetration welding by means of keyhole front morphology - Dilger, Pablo; Eschner, Eric; Schmidt, Michael (Procedia CIRP, 2020)
Within this paper, we present a closed-loop control system for beam positioning during laser deep penetration welding of sheet metals. The system is comprised of a high-speed camera arranged coaxially to the laser beam on a welding head and linear stages for positioning of the specimen. It is shown that the keyhole front morphology correlates with the position of the seam in butt joint configuration. Within our closed-loop control prototype, this correlation is extracted by an image processing algorithm in a real-time environment. First experiments show that our system is able to adaptively correct the beam position with sufficient accurac
Keywords: laser-based material processing; deep penetration welding; process control; image processing

Correlation of Spatter Behavior and Process Zone Formation in Powder Bed Fusion of Metals - Eschner, Eric; Staudt, Tobias; Schmidt, Michael (CIRP Annals - Manufacturing Technology, 2020)
In powder bed fusion of metals by a laser beam (PBF-LB/M) spatters evolve due to evaporation phenomena within the interaction zone of the laser-beam and material. The evaporation is of high importance for the evolution of a melt depression in the process zone. We use high-speed stereoscopic imaging to measure the three-dimensional (3D) time-resolved spatter trajectories. The statistical spatter behavior is correlated with the transition from heat conduction mode into evaporation dominated mode in the interaction zone and its geometry. The results indicate a high potential to use statistical measures of the 3D spatter trajectories for quality assurance in PBF-LB/M.
CRIS-Team Scopus Importer:2020-05-29
Keywords: Additive manufacturing; Quality assurance; Stereoscopic imaging

Correlation of Spatter Quantity and Speed to Process Conditions in Laser Powder Bed Fusion of Metals - Eschner, Eric; Schwarzkopf, Karen; Staudt, Tobias; Schmidt, Michael (Production at the leading edge of technology, 2020)

Derivation of Three-dimensional Information of Particles in Laser Materials Processing by Means of Stereoscopic High-speed Imaging - Eschner, Eric; Staudt, Tobias; Schmidt, Michael (International Conference on Advanced Optical Technologies, 2019)

Deriving spectral information upon the laser welding process employing a hyperspectral imaging technique - Staudt, Tobias; Eschner, Eric; Tenner, Felix; Schmidt, Michael (Procedia CIRP, 2018)
In this paper we present results from process observations of deep penetration laser welding using a hyperspectral imaging (HSI) technique. For monitoring different types of laser-based material processing, we developed an appropriate high-speed camera-based HSI system. This system enables us to derive spectra of the deep penetration welding process with high time resolution. These spectra can be used for temperature determination or to extract spectral characteristics, both of which can help to further investigate process dynamics and properties of the vapor. The presented results contain particularly HSI-derived spectral information of the evolving vapor plume that is related to corresponding high-speed images and spectra acquired with a conventional VIS-spectromete
Keywords: laser-based material processing; deep penetration laser welding; process monitoring; hyperspectral imaging

Determination of the beam position in laser deep penetration welding using coaxially acquired images of the keyhole front and machine learning - Dilger, Pablo; Forster, Carola; Klein, Elias; Burger, Silvana; Eschner, Eric; Schmidt, Michael (Proceedings of the Lasers in Manufacturing (LiM) 2021, 2021)
The joining technology of laser beam welding offers high flexibility and productivity. However, the small laser beam focus demands dependable quality assurance to ensure a sufficient connection of the parts. In keyhole welding of metal sheets in butt joint configuration, a gap is visible at the keyhole front, which correlates with the leading joint position. This process feature can be used for quality control by arranging a high-speed camera coaxially to the laser beam to monitor the keyhole. Here, we present a machine learning approach for a robust determination of the beam position relative to the joint based on the keyhole front morphology. For this purpose, we conducted a series of experiments to produce a set of labeled images, which are used to train a convolutional neural network. After training on the data, the network can predict the position of the keyhole front gap, setting the foundation for a quality control syste
Keywords: laser deep penetration welding; machine learning; image processing; quality assurance

Development of a joining gap control system for laser welding of zinc-coated steel sheets driven by process observation - Tenner, Felix; Eschner, Eric; Lutz, Benjamin; Schmidt, Michael (Journal of Laser Applications, 2018)

Employing Hyperspectral Imaging for Temperature Determination in Laser Materials Processing - Staudt, Tobias; Eschner, Eric; Schmidt, Michael (International Conference on Advanced Optical Technologies, 2019)
Laser materials processing techniques have gained a lot of interest particularly in R&D over the past years. Admittedly, the process understanding of many of those techniques is still very limited. In order to broaden the process understanding, correct temperature information becomes very valuable. The reason being that correct temperature information can be used to describe numerous of the occurring physical phenomena in laser materials processing, such as heat conduction/convection, formation of stress/distortion, solidification behavior, etc. Furthermore, it also helps to improve current process simulation approaches as well as to compare experiment and simulations. For this reason, we propose a novel approach for temperature determination based upon hyperspectral imaging (HSI). HSI allows to simultaneously acquiring spectral as well as spatial information upon the investigated target which makes it an already very popular and well-established tool in biomedical imaging, agriculture, food quality control, surveillance, astronomy and remote sensing. The acquired three-dimensional dataset includes two spatial and one spectral dimension – most commonly in the range from ultraviolet to near-infrared. This information can be used for instance to reveal the chemical composition of specimens, for pathogen detection or for early detection of diseases. However, most appealingly for monitoring purposes in laser materials processing is the possibility to retrieve temperature information as well. Our developed HSI system comprises a high-speed camera and a self-designed HSI-lens and is inspired by the work of Habel [1]. The high-speed camera features a full frame, one megapixel CMOS sensor spectrally sensitive from 350 nm to 1100 nm. The developed HSI-lens system comprises standard photography lenses and a dispersive element that separates the incident process emissions into its constituent wavelengths. This spectrum is then detected by the high-speed camera’s sensor. Interpreting the resulting spectrum as a gray-body spectrum, correct temperature information upon the investigated process can be retrieved without a priori knowledge of the emissivity. The HSI-system is capable of capturing up to 240,000 fps falling far below typical time resolutions of current state-of-the-art technologies, e.g. pyrometers. In this work, we show a proof of concept of high-speed temperature determination based upon HSI-derived spectra and present initial process observation result

Features for image processing of OCT images for seam tracking applications in laser welding - Will, Thomas; Eschner, Eric; Schmidt, Michael (Journal of Laser Applications, 2022)
The coaxial integration of optical coherence tomography (OCT) enables the determination of surface topography and measurement of object features along the optical path within laser machining. The measurement of surface information from the processed workpiece allows for the identification of features from the joint configuration and the subsequent control of the welding process by seam tracking. State-of-the-art seam tracking approaches are based on monochromatic cameras or laser triangulation. Typically, these approaches apply line segmentations for the identification of the joint position. The interferometric measurement method of OCT gives rise to the identification of new features for image processing in seam tracking. In this work, we identify specific noise components and features based on the theoretical background of OCT for image processing in seam tracking applications. Two different features are derived for the detection of arbitrary joint configurations with corresponding systematic image processing approaches. In the first step, we show the applicability of line detection methods for feature detection of arbitrary joint configurations. The necessary evaluation algorithm for case sensitivity and limitations (e.g., chamfer) in detecting different joint geometries are discussed. In the second step, we show an approach in feature extraction with feature detectors (e.g., ORB, SURF) for a new image feature. Here, significant image space from (multiple) reflections at the joint position is used for joint detection. The detectability is discussed depending on the joint configuration. The results show good suitability of both features for seam tracking applications.
CRIS-Team Scopus Importer:2022-06-24

Influence of vapor on hyperspectral imaging for monitoring laser-based material processing - Staudt, Tobias; Tenner, Felix; Eschner, Eric; Klämpfl, Florian; Schmidt, Michael (Proceedings of the 36th International Congress on Applications of Lasers & Electro-Optics - ICALEO, 2017)

Quantification of Melt Dynamics from High-Speed Observations Within the Remote Fusion Cutting Regime by Means of Image Processing - Burger, Silvana; Dilger, Pablo; Eschner, Eric; Schmidt, Michael (2021)
Keywords: Laser cutting; Remote fusion cutting; Image processing

Sensing approach for the in-situ determination of spatter motion within PBF-LB/M - Eschner, Eric; Staudt, Tobias; Schmidt, Michael (CIRP Annals - Manufacturing Technology, 2022)
Within powder bed fusion of metals by a laser-beam (PBF-LB/M) spatter particles evolve due to the entrainment of powder particles and their ejection along the vapor plume. Motion properties of the evolving spatter particles are directly linked to the process zone topography, qualifying them as an interesting process signature for in-situ sensing. This work shows an industrially applicable sensing approach which allows the determination of three-dimensional spatter positions in real-time. A camera setup is derived reducing ambiguity within the reconstruction at high framerates. The presented parallel image processing and reconstruction algorithm allows for the determination of three-dimensional spatter coordinates in real-time.
CRIS-Team Scopus Importer:2022-04-22
Keywords: Algorithm; Selective laser melting (SLM); Sensor

Temperature determination in laser welding based upon a hyperspectral imaging technique - Staudt, Tobias; Eschner, Eric; Schmidt, Michael (CIRP Annals - Manufacturing Technology, 2019)
Hyperspectral imaging (HSI)is a very promising technique for temperature determination in laser welding without the need for a priori knowledge of the emissivity. HSI is commonly considered a technique that allows to simultaneously acquire spatial as well as spectral information – that is essentially containing the temperature information – upon the investigated object. For that purpose, we developed a suitable HSI-system comprising a self-designed HSI-lens system and a high-speed CMOS-camera. In the present paper we address influences upon the HSI-based temperature determination and present as well as discuss temperature determination results in laser welding of metal sheets.
CRIS-Team Scopus Importer:2019-05-17
Keywords: Hyperspectral imaging; Laser welding; Temperature