Observing molten pool surface oscillations during keyhole processing in laser powder bed fusion as a novel method to estimate the penetration depth

Caprio, Leonardo; Demir, Ali Gökhan; Previtali, Barbara

doi:10.1016/j.addma.2020.101470

Cited by 25 publications

(22 citation statements)

References 72 publications

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“…The intrinsic oscillation occurs for both stable and unstable keyholes (Fig. 2, A The type of keyhole oscillation is consistent with those observed in the previous studies (13,(20)(21)(22)(23).…”

Section: Intrinsic Keyhole Oscillationsupporting

confidence: 90%

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Machine learning–aided real-time detection of keyhole pore generation in laser powder bed fusion

Ren

Gao

Clark

et al. 2023

Science

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Porosity defects are currently a major factor that hinders the widespread adoption of laser-based metal additive manufacturing technologies. One common porosity occurs when an unstable vapor depression zone (keyhole) forms because of excess laser energy input. With simultaneous high-speed synchrotron x-ray imaging and thermal imaging, coupled with multiphysics simulations, we discovered two types of keyhole oscillation in laser powder bed fusion of Ti-6Al-4V. Amplifying this understanding with machine learning, we developed an approach for detecting the stochastic keyhole porosity generation events with submillisecond temporal resolution and near-perfect prediction rate. The highly accurate data labeling enabled by operando x-ray imaging allowed us to demonstrate a facile and practical way to adopt our approach in commercial systems.

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Section: Intrinsic Keyhole Oscillationsupporting

confidence: 90%

“…The Marangoni force starts to drive the liquid flow again, initiating a new cycle of intrinsic oscillation [( 19 ), section 2.4]. The type of keyhole oscillation is consistent with those observed in the previous studies ( 13 , 20 – 23 ).…”

Section: Intrinsic Keyhole Oscillationsupporting

confidence: 83%

Machine learning–aided real-time detection of keyhole pore generation in laser powder bed fusion

Ren

Gao

Clark

et al. 2023

Science

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“…The high-speed video acquisitions could be employed to measure the melt pool oscillation frequency according to the methodology developed by Caprio et al [26,32]. The frames acquired were analysed by identifying a region of interest (ROI) just behind the laser-material interaction position and quantifying the specular reflections of the secondary illumination light in such a region.…”

Section: High-speed Imaging Equipmentmentioning

confidence: 99%

“…The emission profiles were measured with a fast photodiode prior to the experimental study. Linear paths 20 mm in length, associated with the different experimental conditions, were scanned over a 50 µm thick powder bed with localised Ar gas inertisation (as done in previous investigations by Caprio et al) [32]. Details of the experimental campaign are reported in table 4.…”

Section: Experimental Planmentioning

confidence: 99%

Understanding the effects of temporal waveform modulation of laser emission power in laser powder bed fusion: Part II - Experimental investigation

Caprio¹,

Demir²,

Previtali³

2022

J. Phys. D: Appl. Phys.

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The Laser Powder Bed Fusion (LPBF) process has been historically operating with high brilliance fiber laser sources with Continuous Wave (CW) emission. Nonetheless, temporal waveform modulation of the laser emission power at high frequency levels can provide a means to enhance the deposition process by modifying the melt dynamics and solidification mechanisms. In order to disclose the effect of different waveform shapes and their parameters, an experimental study using an open LPBF system was conducted. This work configures as the second part of an investigation on this topic with the aim of validating the analytical model proposed in the first part of this work. The LPBF system developed enabled to program the power emission profiles during single track depositions. Four different waveform shapes were tested (namely Square Wave, Ramp Up, Ramp Down and Triangle Wave) at different levels of waveform amplitude (ΔP=200-400 W) and different frequencies (fw= 2 – 4 – 6 – 8 kHz) during the single track deposition of AISI316L. High speed imaging acquisitions allowed to disclose the melt dynamics and identify the melt oscillation frequency. Larger waveform amplitudes and waveforms with sudden variations of the emission power generated melt ejections and process instabilities. Stable conditions could be identified when employing Ramp Up and Triangle waveforms with ΔP=200. Melt surface oscillation frequency corresponded to the values imposed via the modulation of the laser emission power thus validating the analytical model of Part I which correlated the melt surface temperature to the recoil pressure induced over the molten pool. Optical microscopy images and metallographic cross-sections confirmed the high speed video observations. 3D reconstructions of the depositions via focus variation microscopy allowed to determine the build rates and roughness of the single tracks. Build rates obtained in stable deposition conditions with waveform modulation are analogous to values obtainable with CW emission and beneficial effects over the roughness were reported.

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“…Caprio [3] utilized the oscillation of the welding pool to estimate its penetration during the Laser Powder Bed Fusion process. Thomas [4] reconstructed the thermal images of cold metal transfer process to monitor the porosity defects and improper weld beads.…”

Section: Introductionmentioning

confidence: 99%

Three-Dimensional Reconstruction of Welding Pool Surface by Binocular Vision

Chen

2021

Chin. J. Mech. Eng.

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Current research of binocular vision systems mainly need to resolve the camera’s intrinsic parameters before the reconstruction of three-dimensional (3D) objects. The classical Zhang’ calibration is hardly to calculate all errors caused by perspective distortion and lens distortion. Also, the image-matching algorithm of the binocular vision system still needs to be improved to accelerate the reconstruction speed of welding pool surfaces. In this paper, a preset coordinate system was utilized for camera calibration instead of Zhang’ calibration. The binocular vision system was modified to capture images of welding pool surfaces by suppressing the strong arc interference during gas metal arc welding. Combining and improving the algorithms of speeded up robust features, binary robust invariant scalable keypoints, and KAZE, the feature information of points (i.e., RGB values, pixel coordinates) was extracted as the feature vector of the welding pool surface. Based on the characteristics of the welding images, a mismatch-elimination algorithm was developed to increase the accuracy of image-matching algorithms. The world coordinates of matching feature points were calculated to reconstruct the 3D shape of the welding pool surface. The effectiveness and accuracy of the reconstruction of welding pool surfaces were verified by experimental results. This research proposes the development of binocular vision algorithms that can reconstruct the surface of welding pools accurately to realize intelligent welding control systems in the future.

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Observing molten pool surface oscillations during keyhole processing in laser powder bed fusion as a novel method to estimate the penetration depth

Cited by 25 publications

References 72 publications

Machine learning–aided real-time detection of keyhole pore generation in laser powder bed fusion

Machine learning–aided real-time detection of keyhole pore generation in laser powder bed fusion

Understanding the effects of temporal waveform modulation of laser emission power in laser powder bed fusion: Part II - Experimental investigation

Three-Dimensional Reconstruction of Welding Pool Surface by Binocular Vision

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