SpringerLink
Log in

Experimental study of quality monitoring system integrated with a microphone array in laser microlap welding

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

In microlap welding, a real-time welding quality monitoring system is crucial to the identification of low strength joints caused by the unreliable contact between two layers of stainless metal sheets. In this study, a multispacing configured microphone array filter was designed and applied to a sound-based quality monitoring system for laser microlap welding, and the filter’s performance was evaluated to improve the reliability of the developed monitoring system when collected sound signals are contaminated by the noises generated around a welding site. In the experimental setup, joint strength was modulated by controlling the clam** conditions of the fixture and changing the welding location. The results indicated that noises contaminated the signals obtained from single microphones and reduced classification rates by up to 25% when time domain features were adopted. Through the application of the proposed microphone array in the developed monitoring system, the classification rate of weld quality can be improved to a level resembling that observed when artificial noise is not applied to the system.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

source installation

Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21

Similar content being viewed by others

Availability of data and material

The data will not be shared publicly.

References

  1. Okamoto Y, Nishi N, Nakashiba S, Sakagawa T, Okada A (2015) Smart laser micro-welding of difficult-to-weld materials for electronic industry. Proc Laser-based Micro Nanoprocess IX SPIE 9351:935102. https://doi.org/10.1117/12.2076232

  2. Mehlmann B, Olowinsky A, Thuilot M, Gillner A (2014) Spatially modulated laser beam micro welding of CuSn6 and nickel-plated DC04 steel for battery applications. J Laser Micro Nanoeng 9(3):276–281

    Article  Google Scholar 

  3. Shao J, Yan Y (2005) Review of techniques for on-line monitoring and inspection of laser welding. J Phys Conf Ser 15:101–107

    Article  Google Scholar 

  4. You DY, Gao XD, Katayama S (2014) Review of laser welding monitoring. Sci Technol Weld Join 19(3):181–201

    Article  Google Scholar 

  5. Stavridis J, Papacharalampopoulo A, Stavropoulos P (2018) Quality assessment in laser welding: a critical review. Int J Adv Manuf Technol 94:1825–1847

    Article  Google Scholar 

  6. Chauveau D (2018) Review of NDT and process monitoring techniques usable to produce high-quality parts by welding or addi-tive manufacturing. Weld World 62:1097–1118

    Article  Google Scholar 

  7. Cai W, Wang JZ, Jiang P, Cao LC, Mi GY, Zhou Q (2020) Application of sensing techniques and artificial intelli-gence-based methods to laser welding real-time monitoring: a critical review of recent literature. J Manuf Syst 57:1–18

    Article  Google Scholar 

  8. Yusof MFM, Ishak M, Ghazali MF (2021) Acoustic methods in real-time welding process monitoring: application and future potential adv ancement. J Mech Eng Sci (JMES) 15(4):8490–8507

    Article  Google Scholar 

  9. Sun AS (2000) Multiple sensor monitoring of laser welding. Ph.D. Dissertation, The University of Michigan

  10. Hamann C, Rosen HG, LaBiger B (1989) Acoustic emission and its application to laser spot welding. Proc SPIE 1132:275–281

    Article  Google Scholar 

  11. Habenicht G, Stark W, Deimann R (1991) Quality assurance of laser spot welds with acoustic emission analysis using the example of selected copper alloys. Schweissen und Schneiden/Welding and Cuttin 43(10):213–215

    Google Scholar 

  12. Lee S, Ahn S, Park C (2014) Analysis of acoustic emission signals during laser spot welding of S304 stainless steel. J Mater Eng Perform 23:700–707

    Article  Google Scholar 

  13. Schmidta L, Römer F, Böttger D, Leinenbach F, Stra B, Wolter B, Schricker K, Seibold M, Bergmann JP, Del Galdo G (2020) Acoustic process monitoring in laser beam welding. Procedia CIRP 94:763–768

    Article  Google Scholar 

  14. ** X, Li L, Zhang Y (2002) A study on fresnel absorption and reflections in the keyhole in deep penetration laser welding. J Phys D Appl Phys 35:2304–2310

    Article  Google Scholar 

  15. Shevchik SA, Le-Quang T, Farahani FV, Faivre N, Meylan A, Zanoli S, Wasmer AK (2019) Laser welding quality moni-toring via graph support vector machine with data adaptive kernel. IEEE Access 7:93108–93122

    Article  Google Scholar 

  16. Chien K (2012) Applications of acoustic emission and sound signal for welding defect monitoring in Nd:YAG laser thin plate butt welding, M.S. Thesis, National Chung Hsing University, Taichung, Taiwan

  17. Matteson A, Morris R, Tate R (1993) Real-time GMAW quality classification using an artificial neural network with airborne acoustic signals as inputs. Proceedings of the 12th International Conference on Offshore Mechanics and Arctic Engineering III-A 273–278

  18. Kuo B, Lu M (2020) Analysis of sound signal for quality monitoring in laser microlap welding. Appl Sci 10(1):1934. https://doi.org/10.3390/app10061934

    Article  Google Scholar 

  19. Smith ET (1999) Monitoring laser weld quality using acoustic signals. Ph.D. Dissertation, The University of Michigan

  20. Shimada W, Ohmine M, Hoshinouchi S, Kobayashi M (1982) Study on in-process assessment of joint efficiency in the laser welding process. Int Symp Jpn Weld Soc 1:175–180

    Google Scholar 

  21. Gu H, Duley W (1996) A statistical approach to acoustic monitoring of laser welding. J Phys D Appl Phys 29:556–560

    Article  Google Scholar 

  22. Grad L, Grum J, Polajnar I, Slabe JM (2004) Feasibility study of acoustic signals for on-line monitoring in short circuit gas metal arc welding. Int J Mach Tools Manuf 44:555–561

    Article  Google Scholar 

  23. Nava-Rüdiger E, Houlot M (1997) Integration of real time quality control systems in a welding process. J Laser Appl 9:95–102

    Article  Google Scholar 

  24. Yusof MFM, Ishak M, Ghazali MF (2020) Classification of weld penetration condition through synchro squeezed-wavelet analysis of sound signal acquired from pulse mode laser welding process. J Mater Process Tech 279:116559

    Article  Google Scholar 

  25. Yusof MFM, Ishak M, Ghazali MF (2021) Weld depth estimation during pulse mode laser welding process by the analysis of the acquired sound using feature extraction analysis and artificial neural network. J Manuf Process 63:163–178

    Article  Google Scholar 

  26. Luo H, Zeng H, Hu L, Hu X, Zhou Z (2005) Application of artificial neural network in laser welding defect diagnosis. J Mater Process Technol 170:403–411

    Article  Google Scholar 

  27. Lin RH, Fischer GW (1995) An on-line arc welding quality monitor and process control system. industrial automation and control: emerging technologies. International IEEE/IAS Conference on IEEE 22–29

  28. Farson D, Hillsley K, Sames J, Young R (1996) Frequency–time characteristics of air-borne signals from laser welds. J Laser Appl 8:33–42

    Article  Google Scholar 

  29. Huang W, Kovacevic R (2009) Noise reduction during acoustic monitoring of laser welding of high-strength steels. Proceedings of ASME 2009 International Manufacturing Science and Engineering Conference 763–770 (MSEC2009–84080)

  30. Fischer S, Simmer KU (1996) Beamforming microphone arrays for speech acquisition in noisy environments. Speech Commun 20(3–4):215–227

    Article  Google Scholar 

  31. Inoue M, Nakamura S, Yamada T, Shikano K (1997) Microphone array design measures for hands-free speech recognition. Proceedings of European Conference on Speech Communication and Technology (EUROSPEECH) 331–334

  32. Dedieu S, Moquin P (2005) Goubran R (2005) Sound measurement in noisy environment using optimized conformal microphone arrays. Instrum Meas Technol Conf IMTC 1:748–751

    Article  Google Scholar 

  33. Kobayashi K, Furuya K, Kataoka A (2006) A microphone array system with echo canceller. Electron Commun Jpn (Part III Fund Electr Sci) 89(10):23–32

    Article  Google Scholar 

  34. Dedieu S, Moquin P, Goubran R (2005) Sound measurement in noisy environment using optimized conformal microphone arrays. Proc Instrum Meas Technol Conf IMTC’05 1:748–751

    Article  Google Scholar 

  35. Lee H (2021) Multichannel 3D microphone arrays: a review. J Audio Eng Soc 69(1/2):5–26

    Article  Google Scholar 

  36. Wang P (2015) Application of mems microphone array for tool wear monitoring in precision turning. Thesis, National Chung Hsing University, Taichung, Taiwan, Master’s

    Google Scholar 

  37. Lv N, Fang G, Xu Y, Zhao H, Chen S, Zou J (2017) Real-time monitoring of welding path in pulse metal-inert gas robotic welding using a dual-microphone array. Int J Adv Manuf Technol 90:2955–2968

    Article  Google Scholar 

  38. Lv N, Chen S, Chen Q, Tao W, Zhao H, Chen S (2021) Dynamic welding process monitoring based on microphone array technology. J Manuf Process 64:481–492

    Article  Google Scholar 

  39. Luo Z, Liu W, Wang Z, Ao S (2016) Monitoring of laser welding using source localization and tracking processing by microphone array. Int J Adv Manuf Technol 86:21–28

    Article  Google Scholar 

  40. Hsieh WH, Lu MC, Chiou SJ (2011) Application of backpropagation neural network for spindle vibration-based tool wearmonitoring in micro-milling. Int J Adv Manuf Technol 61:53–61

    Article  Google Scholar 

  41. Wang CY (2018) The development of tool condition monitoring in the milling of Inconel 718 by recurrent HMMs. Master’s Thesis, National Chung Hsing University, Taichung, Taiwan

Download references

Acknowledgements

This study was supported by the Microware Precision Co. Ltd. for the implementation of experiments in production line.

Funding

This research received partially financial support from the Ministry of Science and Technology, Taiwan. Grant number: MOST 104–2221-E-005–019 and MOST 110–2218-E-002–038.

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, National Chung Hsing University, Taichung, 402, Taiwan

    Ming-Zong Chen, Ming-Chyuan Lu, Pei-Ning Wang & Shean-Juinn Chiou

Authors
  1. Ming-Zong Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ming-Chyuan Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Pei-Ning Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Shean-Juinn Chiou
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Ming-Chyuan Lu contributes to the conceptualization, methodology, signal analysis, and writing. Ming-Jong Chen contributes to the development, the conduction of experiments, and the data process and analysis.

Pei-Ning Wang contributes to the development, the conduction of experiments, and the data process and analysis

Shean-Juinn Chiou contributes to the resources acquisition and writing.

Corresponding author

Correspondence to Ming-Chyuan Lu.

Ethics declarations

Ethical approval

None.

Consent to participate

All authors gave consent to participate.

Consent for publication

All authors gave consent to publish.

Competing interests

The authors declare no competing interests.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, MZ., Lu, MC., Wang, PN. et al. Experimental study of quality monitoring system integrated with a microphone array in laser microlap welding. Int J Adv Manuf Technol 121, 2305–2316 (2022). https://doi.org/10.1007/s00170-022-09459-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-022-09459-8

Keywords

Search

Navigation