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Monitoring melted state of reinforced particle in metal matrix composite fabricated by laser melt injection using optical camera

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Abstract

Laser melt injection (LMI) is a promising technique for the fabrication of particle reinforced metal matrix composites (MMCs), in which process monitoring is highly demanded to ensure reliability. The objective of this work is to study the feasibility of using observed spatter and molten pool features for predicting the “invisible” reinforced particle melted state to explore the potential for in situ optical monitoring during LMI. To accomplish this, an in situ optical monitoring system was established and data-driven models were developed based on the analysis of the physical process and image signal formation mechanism in LMI. The image features had distinct behavioral characteristics at different reinforced particle melted states. Meanwhile, the different particle melted states determine the forming quality of the MMCs. The extracted particle spatter and droplet spatter features were proved to be significantly correlated with the particle melted state based on the correlation assessment; thus, the highly correlated spatter feature vectors were used as the input for the classification model. The test results showed that the overall classification accuracy of the prediction model has a high level from 85 to 95%, which illustrated the good generalization ability and robustness of the prediction model. The potential of inferring forming quality of MMCs based on image features is validated through the optical in situ monitoring system. This work contributed to the in-depth understanding of the LMI process and the further applications in process monitoring.

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References

  1. Hu Y, Cong W (2018) A review on laser deposition-additive manufacturing of ceramics and ceramic reinforced metal matrix composites. Ceram Int 44:20599–20612. https://doi.org/10.1016/j.ceramint.2018.08.083

    Article  Google Scholar 

  2. Xu B, Jiang P, Wang Y, Zhao J, Geng S (2022) Multi-physics simulation of wobbling laser melting injection of aluminum alloy with SiC particles: SiC particles gradient distribution in fusion zone. Int J Heat Mass Transfer 182:121960. https://doi.org/10.1016/j.ijheatmasstransfer.2021.121960

    Article  Google Scholar 

  3. Xu B, Jiang P, Geng S, Wang Y, Zhao J, Mi G (2021) In-situ reactions and mechanical properties of 6061 aluminum alloy weld joint with SiCp by laser melting injection. Mater Des 203:109538. https://doi.org/10.1016/j.matdes.2021.109538

    Article  Google Scholar 

  4. Li L, Wang D, Song W, Gong J, Hu Q, Zeng X (2020) Microstructures and mechanical properties of WCP/Ti-6Al-4V composite coatings by laser melt injection and laser-induction hybrid melt injection. Surf Coat Technol 385:125371. https://doi.org/10.1016/j.surfcoat.2020.125371

    Article  Google Scholar 

  5. Wang L, Yao J, Hu Y, Zhang Q, Sun Z, Liu R (2017) Influence of electric-magnetic compound field on the WC particles distribution in laser melt injection. Surf Coat Technol 315:32–43. https://doi.org/10.1016/j.surfcoat.2017.01.116

    Article  Google Scholar 

  6. Mirzade FK, Niziev VG, VYA P, Khomenko MD, Grishaev RV, Pityana S, Rooyen C (2013) Kinetic approach in numerical modeling of melting and crystallization at laser cladding with powder injection. Physica B 423:69–76. https://doi.org/10.1016/j.physb.2013.04.053

    Article  Google Scholar 

  7. Lu QY, Nguyen NV, Hum AJW, Tran T, Wong CH (2019) Optical in-situ monitoring and correlation of density and mechanical properties of stainless steel parts produced by selective laser melting process based on varied energy density. J Mater Process Technol 271:520–531. https://doi.org/10.1016/j.jmatprotec.2019.04.026

    Article  Google Scholar 

  8. Donadello S, Motta M, Demir AG, Previtali B (2019) Monitoring of laser metal deposition height by means of coaxial laser triangulation. Opt Laser Eng 112:136–144. https://doi.org/10.1016/j.optlaseng.2018.09.012

    Article  Google Scholar 

  9. Huang Y, Gao X, Ma B, Liu G, Zhang N, Zhang Y, You D (2021) Optimization of weld strength for laser welding of steel to PMMA using Taguchi design method. Opt Laser Technol 136:106726. https://doi.org/10.1016/j.optlastec.2020.106726

    Article  Google Scholar 

  10. Zhou S, Zeng X (2010) Growth characteristics and mechanism of carbides precipitated in WC–Fe composite coatings by laser induction hybrid rapid cladding. J Alloys Compd 505:685–691. https://doi.org/10.1016/j.jallcom.2010.06.115

    Article  Google Scholar 

  11. Xu H, Huang H (2022) Microstructure evolution and mechanical properties of thermally sprayed coating modified by laser remelting and injection with tungsten carbide. Ceramics Int 48:22854–22868. https://doi.org/10.1016/j.ceramint.2022.04.189

    Article  Google Scholar 

  12. Ortiz A, García A, Cadenas M, Fernández MR, Cuetos JM (2017) WC particles distribution model in the cross-section of laser cladded NiCrBSi + WC coatings, for different wt% WC. Surf Coat Technol 324:298–306. https://doi.org/10.1016/j.surfcoat.2017.05.086

    Article  Google Scholar 

  13. Liu W-W, Tang Z-J, Liu X-Y, Wang H-J, Zhang H-C (2017) A review on in-situ monitoring and adaptive control technology for laser cladding remanufacturing. Procedia CIRP 61:235–240. https://doi.org/10.1016/j.procir.2016.11.217

    Article  Google Scholar 

  14. Everton SK, Hirsch M, Stravroulakis P, Leach RK, Clare AT (2016) Review of in-situ process monitoring and in-situ metrology for metal additive manufacturing. Mater Des 95:431–445. https://doi.org/10.1016/j.matdes.2016.01.099

    Article  Google Scholar 

  15. Tang Z, Liu W, Wang Y, Saleheen KM, Liu Z, Peng S, Zhang Z, Zhang H (2020) A review on in situ monitoring technology for directed energy deposition of metals. Int J Adv Manuf Technol 108:3437–3463. https://doi.org/10.1007/s00170-020-05569-3

    Article  Google Scholar 

  16. Xing W, Chu X, Lyu T, Lee C, Zou Y, Rong Y (2022) Using convolutional neural networks to classify melt pools in a pulsed selective laser melting process. J Manuf Process 74:486–499. https://doi.org/10.1016/j.jmapro.2021.12.030

    Article  Google Scholar 

  17. Le T-N, Lee M-H, Lin Z-H, Tran H-C, Lo Y-L (2021) Vision-based in-situ monitoring system for melt-pool detection in laser powder bed fusion process. J Manuf Process 68:1735–1745. https://doi.org/10.1016/j.jmapro.2021.07.007

    Article  Google Scholar 

  18. Song L, Bagavath-Singh V, Dutta B, Mazumder J (2012) Control of melt pool temperature and deposition height during direct metal deposition process. Int J Adv Manuf Technol 58:247–256. https://doi.org/10.1007/s00170-011-3395-2

    Article  Google Scholar 

  19. Esfahani MN, Bappy MM, Bian L, Tian W (2022) In-situ layer-wise certification for direct laser deposition processes based on thermal image series analysis. J Manuf Process 75:895–902. https://doi.org/10.1016/j.jmapro.2021.12.041

    Article  Google Scholar 

  20. Muvvala G, Patra Karmakar D, Nath AK (2017) Online monitoring of thermo-cycles and its correlation with microstructure in laser cladding of nickel based super alloy. Opt Laser Eng 88:139–152. https://doi.org/10.1016/j.optlaseng.2016.08.005

    Article  Google Scholar 

  21. Farshidianfar MH, Khajepour A, Gerlich A (2016) Real-time control of microstructure in laser additive manufacturing. Int J Adv Manuf Technol 82:1173–1186. https://doi.org/10.1007/s00170-015-7423-5

    Article  Google Scholar 

  22. Farshidianfar MH, Khajepouhor A, Gerlich A (2017) Real-time monitoring and prediction of martensite formation and hardening depth during laser heat treatment. Surf Coat Technol 315:326–334. https://doi.org/10.1016/j.surfcoat.2017.02.055

    Article  Google Scholar 

  23. Santhanakrishnan S, Kovacevic R (2012) Hardness prediction in multi-pass direct diode laser heat treatment by on-line surface temperature monitoring. J Mater Process Technol 212:2261–2271. https://doi.org/10.1016/j.jmatprotec.2012.06.002

    Article  Google Scholar 

  24. Barua S, Liou F, Newkirk J, Sparks T (2014) Vision-based defect detection in laser metal deposition process. Rapid Prototyping J 20:77–85. https://doi.org/10.1108/RPJ-04-2012-0036

    Article  Google Scholar 

  25. Zhang B, Liu S, Shin YC (2019) In-process monitoring of porosity during laser additive manufacturing process. Addit Manuf 28:497–505. https://doi.org/10.1016/j.addma.2019.05.030

    Article  Google Scholar 

  26. Caggiano A, Zhang J, Alfieri V, Caiazzo F, Gao R, Teti R (2019) Machine learning-based image processing for on-line defect recognition in additive manufacturing. CIRP Ann 68:451–454. https://doi.org/10.1016/j.cirp.2019.03.021

    Article  Google Scholar 

  27. Ye D, Zhu K, Fuh JYH, Zhang Y, Soon HG (2019) The investigation of plume and spatter signatures on melted states in selective laser melting. Opt Laser Technol 111:395–406. https://doi.org/10.1016/j.optlastec.2018.10.019

    Article  Google Scholar 

  28. Bartlett JL, Heim FM, Murty YV, Li X (2018) In situ defect detection in selective laser melting via full-field infrared thermography. Addit Manuf 24:595–605. https://doi.org/10.1016/j.addma.2018.10.045

    Article  Google Scholar 

  29. Wang C, Tan XP, Tor SB, Lim CS (2020) Machine learning in additive manufacturing: state-of-the-art and perspectives. Addit Manuf 36:101538. https://doi.org/10.1016/j.addma.2020.101538

    Article  Google Scholar 

  30. Xu H, Huang H (2023) In situ monitoring in laser melt injection based on fusion of infrared thermal and high-speed camera images. J Manuf Process 92:466–478. https://doi.org/10.1016/j.jmapro.2023.02.059

    Article  Google Scholar 

  31. Liu Y, Yang Y, Mai S, Wang D, Song C (2015) Investigation into spatter behavior during selective laser melting of AISI 316L stainless steel powder. Mater Des 87:797–806. https://doi.org/10.1016/j.matdes.2015.08.086

    Article  Google Scholar 

  32. Repossini G, Laguzza V, Grasso M, Colosimo BM (2017) On the use of spatter signature for in-situ monitoring of laser powder bed fusion. Addit Manuf 16:35–48. https://doi.org/10.1016/j.addma.2017.05.004

    Article  Google Scholar 

  33. Zhang Y, Hong GS, Ye D, Zhu K, Fuh JYH (2018) Extraction and evaluation of melt pool, plume and spatter information for powder-bed fusion AM process monitoring. Mater Des 156:458–469. https://doi.org/10.1016/j.matdes.2018.07.002

    Article  Google Scholar 

  34. Xu H, Huang H, Liu Z (2021) Influence of plasma transferred arc remelting on microstructure and properties of PTAW-deposited Ni-based overlay coating. J Therm Spray Technol 30:946–958. https://doi.org/10.1007/s11666-021-01183-1

    Article  Google Scholar 

  35. Kaptay G (1996) Interfacial phenomena during melt processing of ceramic particle-reinforced metal matrix composites. Mater Sci Forum 215:467–474. https://doi.org/10.4028/www.scientific.net/MSF.215-216.467

    Article  Google Scholar 

  36. Liu A, Guo M, Hu HL (2010) Distribution and dissolution of WC particles in surface metal matrix composites produced by plasma melt injection. Surf Eng 26:623–628. https://doi.org/10.1179/174329409X389317

    Article  Google Scholar 

  37. Karlsson J, Norman P, Kaplan AFH, Rubin P, Lamas J, Yañez A (2011) Observation of the mechanisms causing two kinds of undercut during laser hybrid arc welding. Appl Surf Sci 257:7501–7506. https://doi.org/10.1016/j.apsusc.2011.03.068

    Article  Google Scholar 

  38. Siva Prasad H, Brueckner F, Kaplan AFH (2020) Powder incorporation and spatter formation in high deposition rate blown powder directed energy deposition. Addit Manuf 35:101413. https://doi.org/10.1016/j.addma.2020.101413

    Article  Google Scholar 

  39. Sutton AT, Kriewall CS, Leu MC, Newkirk JW, Brown B (2020) Characterization of laser spatter and condensate generated during the selective laser melting of 304L stainless steel powder. Addit Manuf 31:100904. https://doi.org/10.1016/j.addma.2019.100904

    Article  Google Scholar 

  40. Zhang J, Yu M, Li Z, Liu Y, Zhang Q, Jiang R, Sun S (2021) The effect of laser energy density on the microstructure, residual stress and phase composition of H13 steel treated by laser surface melting. J Alloys Compd 856:158168. https://doi.org/10.1016/j.jallcom.2020.158168

    Article  Google Scholar 

  41. Cui C, Wu M, Miao X, Gong Y, Zhao Z (2021) The effect of laser energy density on the geometric characteristics, microstructure and corrosion resistance of Co-based coatings by laser cladding. J Mater Res Technol 15:2405–2418. https://doi.org/10.1016/j.jmrt.2021.09.073

    Article  Google Scholar 

  42. Ye D, Hsi Fuh JY, Zhang Y, Hong GS, Zhu K (2018) In situ monitoring of selective laser melting using plume and spatter signatures by deep belief networks. ISA T 81:96–104. https://doi.org/10.1016/j.isatra.2018.07.021

    Article  Google Scholar 

  43. Farrahi Moghaddam R, Cheriet M (2012) AdOtsu: An adaptive and parameterless generalization of Otsu’s method for document image binarization. Pattern Recognit 45:2419–2431. https://doi.org/10.1016/j.patcog.2011.12.013

    Article  Google Scholar 

  44. Freiße H, Bohlen A, Seefeld T (2019) Determination of the particle content in laser melt injected tracks. J Mater Process Technol 267:177–185. https://doi.org/10.1016/j.jmatprotec.2018.12.018

    Article  Google Scholar 

  45. Xu H, Huang H (2022) Plasma remelting and injection method for fabricating metal matrix composite coatings reinforced with tungsten carbide. Ceram Int 48:2645–2659. https://doi.org/10.1016/j.ceramint.2021.10.048

    Article  Google Scholar 

  46. Wang Y, Huang Y, Yang L, Sun T (2021) Microstructure and property of tungsten carbide particulate reinforced wear resistant coating by TIG cladding. Int J Refract Met Hard Mater 100:105598. https://doi.org/10.1016/j.ijrmhm.2021.105598

    Article  Google Scholar 

  47. Zhao S, Xu S, Yang L, Huang Y (2022) WC-Fe metal-matrix composite coatings fabricated by laser wire cladding. J Mater Process Technol 301:117438. https://doi.org/10.1016/j.jmatprotec.2021.117438

    Article  Google Scholar 

  48. Xiao Q, Sun W, Yang K, Xing X, Chen Z, Zhou H, Lu J (2021) Wear mechanisms and micro-evaluation on WC particles investigation of WC-Fe composite coatings fabricated by laser cladding. Surf Coat Technol 420:127341. https://doi.org/10.1016/j.surfcoat.2021.127341

    Article  Google Scholar 

  49. Peng Y, Zhang W, Li T, Zhang M, Liu B, Liu Y, Wang L, Hu S (2020) Effect of WC content on microstructures and mechanical properties of FeCoCrNi high-entropy alloy/WC composite coatings by plasma cladding. Surf Coat Technol 385:125326. https://doi.org/10.1016/j.surfcoat.2019.125326

    Article  Google Scholar 

  50. Muvvala G, Mullick S, Nath AK (2020) Development of process maps based on molten pool thermal history during laser cladding of Inconel 718/TiC metal matrix composite coatings. Surf Coat Technol 399:126100. https://doi.org/10.1016/j.surfcoat.2020.126100

    Article  Google Scholar 

  51. Li L, Huang H, Zhao F, Zou X, Lu Q, Wang Y, Liu Z, Sutherland JW (2019) Variations of energy demand with process parameters in cylindrical drawing of stainless steel. J Manuf Sci E-T ASME 141:091002. https://doi.org/10.1115/1.4043982

    Article  Google Scholar 

  52. Kumar P, Sharma S (2021) Influence of FSW process parameters on formability and mechanical properties of tailor welded blanks AA6082-T6 and AA5083-O using RSM with GRA-PCA approach. Trans Indian Inst Met 74:1943–1968. https://doi.org/10.1007/s12666-021-02255-0

    Article  Google Scholar 

  53. Cortes C, Vapnik V (1995) Support-vector networks. Mach Learn 20:273–297. https://doi.org/10.1007/BF00994018

    Article  MATH  Google Scholar 

  54. Fan X, Gao X, Zhang N, Ye G, Liu G, Zhang Y (2022) Monitoring of 304 austenitic stainless-steel laser-MIG hybrid welding process based on EMD-SVM. J Manuf Process 73:736–747. https://doi.org/10.1016/j.jmapro.2021.11.031

    Article  Google Scholar 

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Funding

This work is financially supported by the National Natural Science Foundation of China (Grant Nos. U20A20295 and 51722502).

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Hongmeng Xu: investigation, conceptualization, methodology, acquisition of data, writing — original draft; Haihong Huang: conceptualization, resources, supervision, project administration, funding acquisition, writing — review and editing.

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Correspondence to Haihong Huang.

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Xu, H., Huang, H. Monitoring melted state of reinforced particle in metal matrix composite fabricated by laser melt injection using optical camera. Int J Adv Manuf Technol 128, 1781–1800 (2023). https://doi.org/10.1007/s00170-023-11977-y

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