Characterization of acoustic signals during a direct metal laser sintering process

Ye, Dongsen; Zhang, Yingjie; Zhu, Kun Yan; Hong, G.Y.; Ying, Jerry

doi:10.1201/9781315116174-89

Cited by 11 publications

(3 citation statements)

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“…The system can pinpoint the location and timing of defects by analysing the amplitude difference and time domain of AE signals, achieving spatial positioning accuracy within a few millimetres. Other researchers used a microphone sensor to collect the AE signals in metal AM and established a map between the AE signals and the process parameters [239,242]. Similarly, Whiting et al [243] devised an AE sensing monitoring system to monitor the powder flow rate in the DED process, attaching ultrasonic transducers directly to the nozzles to identify any clogs or flow inconsistencies.…”

Section: Acoustic Signalsmentioning

confidence: 99%

Section: Acoustic Signalsmentioning

confidence: 99%

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Advancements in 3D Printing: Directed Energy Deposition Techniques, Defect Analysis, and Quality Monitoring

Imran,

Che Idris,

De Silva

et al. 2024

Technologies

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This paper provides a comprehensive analysis of recent advancements in additive manufacturing, a transformative approach to industrial production that allows for the layer-by-layer construction of complex parts directly from digital models. Focusing specifically on Directed Energy Deposition, it begins by clarifying the fundamental principles of metal additive manufacturing as defined by International Organization of Standardization and American Society for Testing and Materials standards, with an emphasis on laser- and powder-based methods that are pivotal to Directed Energy Deposition. It explores the critical process mechanisms that can lead to defect formation in the manufactured parts, offering in-depth insights into the factors that influence these outcomes. Additionally, the unique mechanisms of defect formation inherent to Directed Energy Deposition are examined in detail. The review also covers the current landscape of process evaluation and non-destructive testing methods essential for quality assurance, including both traditional and contemporary in situ monitoring techniques, with a particular focus given to advanced machine-vision-based methods for geometric analysis. Furthermore, the integration of process monitoring, multiphysics simulation models, and data analytics is discussed, charting a forward-looking roadmap for the development of Digital Twins in Laser–Powder-based Directed Energy Deposition. Finally, this review highlights critical research gaps and proposes directions for future research to enhance the accuracy and efficiency of Directed Energy Deposition systems.

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Section: Acoustic Signalsmentioning

confidence: 99%

Section: Acoustic Signalsmentioning

confidence: 99%

Advancements in 3D Printing: Directed Energy Deposition Techniques, Defect Analysis, and Quality Monitoring

Imran,

Che Idris,

De Silva

et al. 2024

Technologies

View full text Add to dashboard Cite

show abstract

“…Acoustic emission holds promise as a simple, low-cost process monitoring tool, however, AE in-situ monitoring devices are not yet commercially available. In a L-PBF process, a simple microphone was used to monitor the process signature in Ye et al (2017) and machine learning methods were employed to find process signals correlating to irregular track formation and porosity formation due to balling and overheating, showing great promise for the method (Ye et al, 2018). Under less severe conditions with smaller porosities, a similar approach was recently found to be successful, though using a more specialized microphone (fiber Bragg grating) (Shevchik et al, 2018;Wasmer et al, 2018;Wasmer et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Monitoring of Laser Powder Bed Fusion by Acoustic Emission: Investigation of Single Tracks and Layers

et al. 2021

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Quality concerns in laser powder bed fusion (L-PBF) include porosity, residual stresses and deformations during processing. Single tracks are the fundamental building blocks in L-PBF and their shape and geometry influence subsequent porosity in 3D L-PBF parts. The morphology of single tracks depends primarily on process parameters. The purpose of this paper is to demonstrate an approach to acoustic emission (AE) online monitoring of the L-PBF process for indirect defect analysis. This is demonstrated through the monitoring of single tracks without powder, with powder and in layers. Gas-borne AE signals in the frequency range of 2–20 kHz were sampled using a microphone placed inside the build chamber of a L-PBF machine. The single track geometry and shape at different powder thickness values and laser powers were studied together with the corresponding acoustic signals. Analysis of the acoustic signals allowed for the identification of characteristic amplitudes and frequencies, with promising results that support its use as a complementary method for in-situ monitoring and real-time defect detection in L-PBF. This work proves the capability to directly detect the balling effect that strongly affects the formation of porosity in L-PBF parts by AE monitoring.

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Technology of Quality Detection and Feedback in Laser Powder Bed Fusion Process

Wang,

Yang,

Liu

et al. 2023

Additive Manufacturing Technology

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Characterization of acoustic signals during a direct metal laser sintering process

Cited by 11 publications

References 1 publication

Advancements in 3D Printing: Directed Energy Deposition Techniques, Defect Analysis, and Quality Monitoring

Advancements in 3D Printing: Directed Energy Deposition Techniques, Defect Analysis, and Quality Monitoring

Monitoring of Laser Powder Bed Fusion by Acoustic Emission: Investigation of Single Tracks and Layers

Technology of Quality Detection and Feedback in Laser Powder Bed Fusion Process

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