High-Frequency Real-Time Bead Geometry Measurement in Wire Arc Additive Manufacturing Based on Welding Signals

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Publicado en:IEEE Transactions on Industrial Informatics vol. 21, no. 3 (2025), p. 2630
Autor principal: Mu, Haochen
Otros Autores: He, Fengyang, Yuan, Lei, Commins, Philip, Xu, Jing, Pan, Zengxi
Publicado:
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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001 3174175474
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022 |a 1551-3203 
022 |a 1941-0050 
024 7 |a 10.1109/TII.2024.3514121  |2 doi 
035 |a 3174175474 
045 2 |b d20250101  |b d20251231 
084 |a 121667  |2 nlm 
100 1 |a Mu, Haochen  |u School of Mechanical and Power Engineering, Nanjing Tech University, Nanjing, China 
245 1 |a High-Frequency Real-Time Bead Geometry Measurement in Wire Arc Additive Manufacturing Based on Welding Signals 
260 |b The Institute of Electrical and Electronics Engineers, Inc. (IEEE)  |c 2025 
513 |a Journal Article 
520 3 |a To support the increasing demand for smart manufacturing in wire arc additive manufacturing, such as digital twins, high-frequency real-time bead measurement is a long-standing challenge due to the protracted processing time of laser scans and vision-based approaches. This article introduces a pioneering approach for high-frequency, real-time bead geometry measurements. Utilizing high-frequency electric signal sensors, welding current, and voltage are captured. Time and frequency features are subsequently extracted and channeled into multilayer perceptron regressors to predict bead height and width. The model is trained using ground truth data derived from a laser profilometer. Furthermore, a feature dimension reduction algorithm coupled with an incremental learning framework is incorporated to optimize time efficiency and adaptability. Comprehensive practical experiments and a comparative analysis have been conducted. The results demonstrate that the proposed measurement system offers faster measuring speeds than vision-based methods while maintaining accuracy comparable to laser scanning techniques. 
653 |a Wire 
653 |a Algorithms 
653 |a Welding current 
653 |a Laser beam welding 
653 |a Manufacturing 
653 |a Real time 
653 |a Laser applications 
653 |a Multilayer perceptrons 
653 |a Ground truth 
653 |a Time measurement 
653 |a Digital twins 
653 |a Welding 
653 |a Signal processing 
700 1 |a He, Fengyang  |u Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, NSW, Australia 
700 1 |a Yuan, Lei  |u School of Mechanical and Power Engineering, Nanjing Tech University, Nanjing, China 
700 1 |a Commins, Philip  |u Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, NSW, Australia 
700 1 |a Xu, Jing  |u Department of Mechanical Engineering, Tsinghua University, Beijing, China 
700 1 |a Pan, Zengxi  |u Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, NSW, Australia 
773 0 |t IEEE Transactions on Industrial Informatics  |g vol. 21, no. 3 (2025), p. 2630 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3174175474/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch