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Volume 48 Issue 9
Sep.  2022
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Journal of Beijing University of Aeronautics and Astronautics  > 2022  >  48(9): 1721-1733.
DING Xilun, LUO Weiheng, LIU Fei, et al. Review on automated fiber placement induced defects and their online monitoring technology[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(9): 1721-1733. doi: 10.13700/j.bh.1001-5965.2022.0307(in Chinese)
Citation: DING Xilun, LUO Weiheng, LIU Fei, et al. Review on automated fiber placement induced defects and their online monitoring technology[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(9): 1721-1733. doi: 10.13700/j.bh.1001-5965.2022.0307(in Chinese)
shu

Review on automated fiber placement induced defects and their online monitoring technology

doi: 10.13700/j.bh.1001-5965.2022.0307
  • 1.

    School of Mechanical Engineering and Automation, Beihang Unviersity, Beijing 100083, China

  • 2.

    Ningbo Innovation Research Institute of Beihang University, Ningbo 315800, China

  • 3.

    Beijing Satellite Manufacturing Factory Co., Ltd., Beijing 100190, China

Funds:

Zhejiang Provincial Natural Science Foundation of China LD22E050011

Ningbo Key Projects of Science and Technology Innovation 2025 Plan 2022Z070

More Information
  • Corresponding author: ZHANG Wuxiang, E-mail: zhangwuxiang@buaa.edu.cn
  • Received Date: 30 Apr 2022
  • Accepted Date: 18 May 2022
  • Publish Date: 16 Jun 2022
    Abstract

  • The automated fiber placement (AFP) process has become a promising solution to the fabrication of composite structures, due to its efficiency and stability. However, the instability of the lay-up process parameters and the performance of the equipment can easily cause such defects as gaps, overlaps, and waviness, which severely affect the overall performance and service life of composite structures. Therefore, automatic identification and evaluation of the defects on the surface or inside the laminates during the AFP process through in-situ monitoring systems are of particular importance. In this paper, the causes and appearance of common defects on the ply during the AFP process and their effects on the overall performance of products are first concluded. Then, the advantages, development, and applications of online monitoring systems based on different detection techniques are systematically reviewed, mainly including laser technology, image recognition technology, thermal imaging technology, and fiber Bragg grating technology. Finally, the limitations in the current online monitoring systems are summarized, and outlooks for their future trends are given.

     

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    • References(103)
  • [1]
    陈祥宝. 先进复合材料技术导论[M]. 北京: 航空工业出版社, 2017.

    CHEN X B. Introduction of advanced composite technology[M]. Beijing: Aviation Industry Press, 2017(in Chinese).
    [2]
    邢丽英, 包建文, 礼嵩明, 等. 先进树脂基复合材料发展现状和面临的挑战[J]. 复合材料学报, 2016, 33(7): 1327-1338. doi: 10.13801/j.cnki.fhclxb.20160323.003

    XING L Y, BAO J W, LI S M, et al. Development status and facing challenge of advanced polymer matrix composites[J]. Acta Materiae Compositae Sinica, 2016, 33(7): 1327-1338(in Chinese). doi: 10.13801/j.cnki.fhclxb.20160323.003
    [3]
    单忠德, 战丽, 缪云良, 等. 复合材料构件数字化精确成形技术与装备[J]. 科技导报, 2020, 38(14): 63-67. doi: 10.3981/j.issn.1000-7857.2020.14.006

    SHAN Z D, ZHAN L, MIAO Y L, et al. Digital precision forming technology and equipment for composite materials[J]. Science and Technology Review, 2020, 38(14): 63-67(in Chinese). doi: 10.3981/j.issn.1000-7857.2020.14.006
    [4]
    BRASINGTON A, SACCO C, HALBRITTER J, et al. Automated fiber placement: A review of history, current technologies, and future paths forward[J]. Composites Part C: Open Access, 2021, 6: 100182. doi: 10.1016/j.jcomc.2021.100182
    [5]
    BARILE M, LECCE L, ESPOSITO M, et al. Advanced AFP applications on multifunctional composites[C]//The Second International Symposium on Automated Composites Manufacturing, 2015: 23-24.
    [6]
    QURESHI Z, SWAIT T, SCAIFE R, et al. In situ consolidation of thermoplastic prepreg tape using automated tape placement technology: Potential and possibilities[J]. Composites Part B: Engineering, 2014, 66: 255-267. doi: 10.1016/j.compositesb.2014.05.025
    [7]
    HARIK R, SAIDY C, WILLIAMS S J, et al. Automated fiber placement defect identity cards: Cause, anticipation, existence, significance, and progression[C]//SAMPE 2018, 2018.
    [8]
    LOPES C S, CAMANHO P P, GVRDAL Z, et al. Progressive failure analysis of tow-placed, variable-stiffness composite panels[J]. International Journal of Solids and Structures, 2007, 44(25-26): 8493-8516. doi: 10.1016/j.ijsolstr.2007.06.029
    [9]
    SHUART M J. Failure of compression-loaded multidirectional composite laminates[J]. AIAA Journal, 1989, 27(9): 1274-1279. doi: 10.2514/3.10255
    [10]
    NOEVERE A T, COLLIER C S. Design for manufacturing tool for automated fiber placement structures-verification and validation: AIAA 2020-1477[R]. Reston: AIAA, 2020.
    [11]
    SAWICKI A J, MINGUET P J. The effect of intraply overlaps and gaps upon the compression strength of composite laminates: AIAA-98-1786[R]. Reston: AIAA, 1998.
    [12]
    CROFT K, LESSARD L, PASINI D, et al. Experimental study of the effect of automated fiber placement induced defects on performance of composite laminates[J]. Composites Part A: Applied Science and Manufacturing, 2011, 42(5): 484-491. doi: 10.1016/j.compositesa.2011.01.007
    [13]
    LAN M, CARTIÉ D, DAVIES P, et al. Influence of embedded gap and overlap fiber placement defects on the microstructure and shear and compression properties of carbon-epoxy laminates[J]. Composites Part A: Applied Science and Manufacturing, 2016, 82: 198-207. doi: 10.1016/j.compositesa.2015.12.007
    [14]
    LAN M, CARTIÉ D, DAVIES P, et al. Microstructure and tensile properties of carbon-epoxy laminates produced by automated fibre placement: Influence of a caul plate on the effects of gap and overlap embedded defects[J]. Composites Part A: Applied Science and Manufacturing, 2015, 78: 124-134. doi: 10.1016/j.compositesa.2015.07.023
    [15]
    NGUYEN M H, VIJAYACHANDRAN A A, DAVIDSON P, et al. Effect of automated fiber placement (AFP) manufacturing signature on mechanical performance of composite structures[J]. Composite Structures, 2019, 228: 111335. doi: 10.1016/j.compstruct.2019.111335
    [16]
    MAROUENE A, LEGAY P, BOUKHILI R. Experimental and numerical investigation on the open-hole compressive strength of AFP composites containing gaps and overlaps[J]. Journal of Composite Materials, 2017, 51(26): 3631-3646. doi: 10.1177/0021998317690917
    [17]
    MUKHOPADHYAY S, JONES M I, HALLETT S R. Tensile failure of laminates containing an embedded wrinkle: Numerical and experimental study[J]. Composites Part A: Applied Science and Manufacturing, 2015, 77: 219-228. doi: 10.1016/j.compositesa.2015.07.007
    [18]
    MUKHOPADHYAY S, JONES M I, HALLETT S R. Compressive failure of laminates containing an embedded wrinkle: Experimental and numerical study[J]. Composites Part A: Applied Science and Manufacturing, 2015, 73: 132-142. doi: 10.1016/j.compositesa.2015.03.012
    [19]
    NARTEY M, ZHANG T, GONG B, et al. Understanding the impact of fibre wrinkle architectures on composite laminates through tailored gaps and overlaps[J]. Composites Part B: Engineering, 2020, 196: 108097. doi: 10.1016/j.compositesb.2020.108097
    [20]
    MAUNG P, PRUSTY B G, WHITE J M, et al. Structural performance of a shape-adaptive composite hydrofoil using automated fibre placement[J]. Engineering Structures, 2019, 183: 351-365. doi: 10.1016/j.engstruct.2019.01.014
    [21]
    MAUNG P T, PRUSTY B G, PHILLIPS A W, et al. Curved fibre path optimisation for improved shape adaptive composite propeller blade design[J]. Composite Structures, 2021, 255: 112961. doi: 10.1016/j.compstruct.2020.112961
    [22]
    ROBERT C, PECUR T, MAGUIRE J M, et al. A novel powder-epoxy towpregging line for wind and tidal turbine blades[J]. Composites Part B: Engineering, 2020, 203: 108443. doi: 10.1016/j.compositesb.2020.108443
    [23]
    RHEAD A T, DODWELL T J, BUTLER R. The effect of tow gaps on compression after impact strength of robotically laminated structures[J]. Computers, Materials and Continua, 2013, 35(1): 1-16.
    [24]
    ELSHERBINI Y M, HOA S V. Experimental and numerical investigation of the effect of gaps on fatigue behavior of unidirectional carbon/epoxy automated fiber placement laminates[J]. Journal of Composite Materials, 2017, 51(6): 759-772. doi: 10.1177/0021998316655393
    [25]
    ELSHERBINI Y M, HOA S V. Fatigue threshold-stress determination in AFP laminates containing gaps using IR thermography[J]. Composites Science and Technology, 2017, 146: 49-58. doi: 10.1016/j.compscitech.2017.04.006
    [26]
    CARTIÉ D, LAN M, DAVIES P, et al. Influence of embedded gap and overlap fiber placement defects on interlaminar properties of high performance composites[J]. Materials, 2021, 14(18): 5332. doi: 10.3390/ma14185332
    [27]
    QIAN S, LIU X, YE Y, et al. Effect of gap and overlap fiber placement defects on the delamination behavior of L-shaped composite laminates[J]. Composite Structures, 2021, 268: 113963. doi: 10.1016/j.compstruct.2021.113963
    [28]
    DAVIDSON P, WAAS A M. The effects of defects on the compressive response of thick carbon composites: An experimental and computational study[J]. Composite Structures, 2017, 176: 582-596. doi: 10.1016/j.compstruct.2017.05.046
    [29]
    MUKHOPADHYAY S, NIXON-PEARSON O J, HALLETT S R. An experimental and numerical study on fatigue damage development in laminates containing embedded wrinkle defects[J]. International Journal of Fatigue, 2018, 107: 1-12. doi: 10.1016/j.ijfatigue.2017.10.008
    [30]
    XU X, JONES M I, ALI H, et al. Effect of out-of-plane wrinkles in curved multi-directional carbon/epoxy laminates[J]. Composites Science and Technology, 2020, 197: 108282. doi: 10.1016/j.compscitech.2020.108282
    [31]
    LUKASZEWICZ D H J A, POTTER K D, EALES J. A concept for the in situ consolidation of thermoset matrix prepreg during automated lay-up[J]. Composites Part B: Engineering, 2013, 45(1): 538-543. doi: 10.1016/j.compositesb.2012.09.008
    [32]
    OROMIEHIE E, PRUSTY B G, COMPSTON P, et al. Automated fibre placement based composite structures: Review on the defects, impacts and inspections techniques[J]. Composite Structures, 2019, 224: 110987. doi: 10.1016/j.compstruct.2019.110987
    [33]
    CAI J, QIU L, YUAN S, et al. Structural health monitoring for composite materials[M/OL]//HU N. Composites and their applications. (2012-08-22)[2022-04-01]. https://www.intechopen.com/chapters/38395.
    [34]
    GUIN W E, JACKSON J R, BOSLEY C M. Effects of tow-to-tow gaps in composite laminates fabricated via automated fiber placement[J]. Composites Part A: Applied Science and Manufacturing, 2018, 115: 66-75. doi: 10.1016/j.compositesa.2018.09.014
    [35]
    HALBRITTER A, HARPER R. Big parts demand big changes to the fiber placement status quo[R]. [S. l. ]: SME Composites Manufacturing, 2012.
    [36]
    马少博, 文立伟, 王若舟, 等. 复合材料自动铺放表面缺陷检测技术研究进展[J]. 复合材料科学与工程, 2020(12): 121-128. doi: 10.3969/j.issn.1003-0999.2020.12.020

    MA S B, WEN L W, WANG R Z, et al. A review of surface defect inspection technology of automated fiber placement manufacturing[J]. Science and Engineering of Composite Materials, 2020(12): 121-128(in Chinese). doi: 10.3969/j.issn.1003-0999.2020.12.020
    [37]
    RUDBERG T, NIELSON J, HENSCHEID M, et al. Improving AFP cell performance[J]. SAE International Journal of Aerospace, 2014, 7(2): 317-321. doi: 10.4271/2014-01-2272
    [38]
    RUDBERG T, CEMENSKA J. Incorporation of laser projectors in machine cell controller reduces ply boundary inspection time, on-part course identification and part probing[J]. SAE International Journal of Aerospace, 2012, 5(1): 74-78. doi: 10.4271/2012-01-1886
    [39]
    SHADMEHRI F, IOACHIM O, PAHUD O, et al. Laser-vision inspection system for automated fiber placement (AFP) process[C]//20th International Conference on Composite Materials, 2015.
    [40]
    SHADMEHRI F. Laser vision inspection system and method: US 20170248406A1[P]. 2017-08-31.
    [41]
    KITSON L E. Composite material laser flaw detection: US 05562788A[P]. 1996-10-08.
    [42]
    OLDANI T. Visual fiber placement inspection: US07835567B2[P]. 2010-11-16.
    [43]
    OLDANI T. Visual fiber placement inspection: US20110017381A1[P]. 2011-01-27.
    [44]
    ZAMBAL S, HEINDL C, EITZINGER C, et al. End-to-end defect detection in automated fiber placement based on artificially generated data[C]//14th International Conference on Quality Control by Artificial Vision, 2019: 11172.
    [45]
    MAASS D. Progress in automated ply inspection of AFP layups[J]. Reinforced Plastics, 2015, 59(5): 242-245. doi: 10.1016/j.repl.2015.05.002
    [46]
    CEMENSKA J, RUDBERG T, HENSCHEID M, et al. AFP automated inspection system performance and expectations[R]. [S. l. ]: SAE, 2017: 1-8.
    [47]
    CEMENSKA J, RUDBERG T, HENSCHEID M. Automated in-process inspection system for AFP machines[J]. SAE International Journal of Aerospace, 2015, 8(2): 303-309. doi: 10.4271/2015-01-2608
    [48]
    MEISTER S. Automated defect analysis using optical sensing and explainable artificial intelligence for fibre layup process in composite manufacturing[D]. Delft: Delft University of Technology, 2022.
    [49]
    MEISTER S, WERMES M, STVVE J, et al. Investigations on explainable artificial intelligence methods for the deep learning classification of fibre layup defect in the automated composite manufacturing[J]. Composites Part B: Engineering, 2021, 224: 109160. doi: 10.1016/j.compositesb.2021.109160
    [50]
    MEISTER S, MÖLLER N, STVVE J, et al. Synthetic image data augmentation for fibre layup inspection processes: Techniques to enhance the data set[J]. Journal of Intelligent Manufacturing, 2021, 32(6): 1767-1789. doi: 10.1007/s10845-021-01738-7
    [51]
    SACCO C, RADWAN A B, HARIK R, et al. Automated fiber placement defects: Automated inspection and characterization[C]//SAMPE 2018, 2018.
    [52]
    SACCO C. Machine learning methods for rapid inspection of automated fiber placement manufactured composite structures[D]. Columbia: University of South Carolina, 2019.
    [53]
    SACCO C, RADWAN A B, BEATTY T, et al. Machine learning based AFP inspection: A tool for characterization and integration[C]//SAMPE 2019, 2019.
    [54]
    SOUCY K A. In-process monitoring for quality assurance of automated composite fabrication[M]//THOMPSON D O, CHIMENTI D E. Review of progress in quantitative nondestructive evaluation. Berlin: Springer, 1996: 2225-2231.
    [55]
    ENGELBART R. System and method for identifying defects in a composite structure: US07171033B2[P]. 2007-01-30.
    [56]
    陈文, 曹力, 肖军, 等. 基于视觉的复合材料自动铺放表面纹理实时检测方法[J]. 科学技术与工程, 2011, 11(18): 4143-4149. doi: 10.3969/j.issn.1671-1815.2011.18.006

    CHEN W, CAO L, XIAO J, et al. A vision-based real-time detection method of texture in automatic composite fiber placement[J]. Science Technology and Engineering, 2011, 11(18): 4143-4149(in Chinese). doi: 10.3969/j.issn.1671-1815.2011.18.006
    [57]
    倪金辉, 肖军, 文立伟. 一种基于直线拟合的预浸料边缘直线在线视觉检测方法[J]. 计算机科学, 2015, 42(Z6): 16-19. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJA2015S1005.htm

    NI J H, XIAO J, WEN L W. Real-time visual inspection method to detect prepreg edge straight based on line fitting[J]. Computer Science, 2015, 42(Z6): 16-19(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JSJA2015S1005.htm
    [58]
    刘辉. 基于机器视觉的纤维铺放角度及间距检测系统研究[D]. 武汉: 武汉理工大学, 2008.

    LIU H. The research of image detection system of fiber tape laying based on machine vision[D]. Wuhan: Wuhan University of Technology, 2008(in Chinese).
    [59]
    TAO Y, JIA S, DUAN Y, et al. An online detection method for composite fibre tow placement accuracy[J]. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2016, 230(9): 1614-1621. doi: 10.1177/0954405416640189
    [60]
    ENGELBART R W. Verification of tow cut for automatic fiber placement: EP2072224B1[P]. 2012-02-08.
    [61]
    ENGELBART R W. Mapping tow splices in composite structures: US20120216957A1[P]. 2012-08-30.
    [62]
    RITTER J A. Real-time infrared thermography inspection and control for automated composite marterial layup: US 07513964B2[P]. 2009-04-07.
    [63]
    ENGELBART R W. Systems and methods enabling automated return to and/or repair of defects with a material placement machine: US07039485B2[P]. 2006-05-02.
    [64]
    ENGELBART R W. Systems and methods for using light to indicate defect locations on a composite structure: EP05735387A[P]. 2005-04-11.
    [65]
    ENGELBART R W. Systems and method for identifying foreign objects and debris (FOD) and defects during fabrication of a composite structure: US20050025350A1[P]. 2005-02-03.
    [66]
    ENGELBART R W. In-process vision detection of flaws and FOD by back field illumination: US07678214B2[P]. 2010-03-16.
    [67]
    CHEN M, JIANG M, LIU X, et al. Intelligent inspection system based on infrared vision for automated fiber placement[C]//Proceedings of 2018 IEEE International Conference on Mechatronics and Automation. Piscataway: IEEE Press, 2018: 918-923.
    [68]
    DENKENA B, SCHMIDT C, WEBER P. Automated fiber placement head for manufacturing of innovative aerospace stiffening structures[J]. Procedia Manufacturing, 2016, 6: 96-104. doi: 10.1016/j.promfg.2016.11.013
    [69]
    DENKENA B, SCHMIDT C, VÖLTZER K, et al. Thermographic online monitoring system for automated fiber placement processes[J]. Composites Part B: Engineering, 2016, 97: 239-243. doi: 10.1016/j.compositesb.2016.04.076
    [70]
    SCHMIDT C, DENKENA B, VÖLTZER K, et al. Thermal image-based monitoring for the automated fiber placement process[J]. Procedia CIRP, 2017, 62: 27-32. doi: 10.1016/j.procir.2016.06.058
    [71]
    SCHMIDT C, DENKENA B, HOCKE T, et al. Influence of AFP process parameters on the temperature distribution used for thermal in-process monitoring[J]. Procedia CIRP, 2017, 66: 68-73. doi: 10.1016/j.procir.2017.03.220
    [72]
    SCHMIDT C, HOCKE T, DENKENA B. Deep learning-based classification of production defects in automated-fiber-placement processes[J]. Production Engineering, 2019, 13(3-4): 501-509. doi: 10.1007/s11740-019-00893-4
    [73]
    SCHMIDT C, HOCKE T, DENKENA B. Artificial intelligence for non-destructive testing of CFRP prepreg materials[J]. Production Engineering, 2019, 13(5): 617-626. doi: 10.1007/s11740-019-00913-3
    [74]
    JUAREZ P D, GREGORY E D. In situ thermal inspection of automated fiber placement for manufacturing induced defects[J]. Composites Part B: Engineering, 2021, 220: 109002. doi: 10.1016/j.compositesb.2021.109002
    [75]
    JUAREZ P D, GREGORY E D. In situ thermal inspection of automated fiber placement manufacturing[C]//AIP Conference, 2019: 120005.
    [76]
    JUAREZ P D, CRAMER K E, SEEBO J P. Advances in in-situ inspection of automated fiber placement systems[C]//Thermosense: Thermal Infrared Applications, 2016: 986109.
    [77]
    GREGORY E D, JUAREZ P D. In-situ thermography of automated fiber placement parts[C]//AIP Conference Proceedings, 2018: 060005.
    [78]
    GREGORY E D, JUAREZ P D. In situ thermal nondestructive evaluation for assessing part quality during composite automated fiber placement[J]. Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems, 2018, 1(4): 1-6.
    [79]
    SHOKRIEH M M, MOHAMMADI A R G. Non-destructive testing (NDT) techniques in the measurement of residual stresses in composite materials: An overview[M]//SHOKRIEH M M. Residual stresses in composite materials. Amsterdam: Elsevier, 2014: 58-75.
    [80]
    PARLEVLIET P P, BERSEE H E N, BEUKERS A. Residual stresses in thermoplastic composites-A study of the literature. Part Ⅰ: Formation of residual stresses[J]. Composites Part A: Applied Science and Manufacturing, 2006, 37(11): 1847-1857. doi: 10.1016/j.compositesa.2005.12.025
    [81]
    BAEJEWSKI W, GSIOR P, KALET J. Application of optical fibre sensors to measuring the mechanical properties of composite materials and structures[M/OL]//ATTAF B. Advances in composite materials-Ecodesign and analysis. (2011-03-16)[2022-04-01]. https://www.intechopen.com/chapters/14299.
    [82]
    GROS X E. Current and future trends in non-destructive testing of composite materials[J]. Annales De Chimie Science Des Matériaux, 2000, 25(7): 539-544. doi: 10.1016/S0151-9107(01)80007-6
    [83]
    MAJUMDER M, GANGOPADHYAY T K, CHAKRABORTY A K, et al. Fibre Bragg gratings in structural health monitoring-Present status and applications[J]. Sensors and Actuators, A: Physical, 2008, 147(1): 150-164. doi: 10.1016/j.sna.2008.04.008
    [84]
    MURUKESHAN V M, CHAN P Y, ONG L S, et al. Cure monitoring of smart composites using fiber Bragg grating based embedded sensors[J]. Sensors and Actuators, A: Physical, 2000, 79(2): 153-161. doi: 10.1016/S0924-4247(99)00266-6
    [85]
    LENG J, ASUNDI A. Structural health monitoring of smart composite materials by using EFPI and FBG sensors[J]. Sensors and Actuators, A: Physical, 2003, 103(3): 330-340. doi: 10.1016/S0924-4247(02)00429-6
    [86]
    RUZEK R, KUDRNA P, KADLEC M, et al. Strain and damage monitoring in CFRP fuselage panels using fiber Bragg grating sensors. Part Ⅱ: Mechanical testing and validation[J]. Composite Structures, 2014, 107: 737-744. doi: 10.1016/j.compstruct.2013.09.056
    [87]
    OROMIEHIE E, RAJAN G, PRUSTY G B. Thermal sensitivity and relaxation of carbon fibre-foam sandwich composites with fibre optic sensors[J]. Journal of Sandwich Structures and Materials, 2016, 18(5): 652-664. doi: 10.1177/1099636216647929
    [88]
    OROMIEHIE E, PRUSTY G B, COMPSTON P, et al. Structural health monitoring and processing of composites using photonic sensing technology[C]//Proceedings of the 20th International Conference on Composite Materials, 2015: 19-24.
    [89]
    OROMIEHIE E. In-situ process monitoring in automated fibre placement-based manufacturing of advanced composites[D]. Sydney: University of New South Wales, 2017.
    [90]
    OROMIEHIE E, PRUSTY B G, RAJAN G, et al. Optical fiber Bragg grating sensors for process monitoring in advanced composites[C]//2016 IEEE Sensors Applications Symposium (SAS). Piscataway: IEEE Press, 2016: 1-5.
    [91]
    OROMIEHIE E, PRUSTY B G, COMPSTON P, et al. In situ process monitoring for automated fibre placement using fibre Bragg grating sensors[J]. Structural Health Monitoring, 2016, 15(6): 706-714. doi: 10.1177/1475921716658616
    [92]
    OROMIEHIE E, PRUSTY B G, COMPSTON P, et al. Characterization of process-induced defects in automated fiber placement manufacturing of composites using fiber Bragg grating sensors[J]. Structural Health Monitoring, 2018, 17(1): 108-117. doi: 10.1177/1475921716685935
    [93]
    OROMIEHIE E, PRUSTY G B, COMPSTON P, et al. In-situ simultaneous measurement of strain and temperature in automated fiber placement (AFP) using optical fiber Bragg grating (FBG) sensors[J]. Advanced Manufacturing: Polymer and Composites Science, 2017, 3(2): 52-61. doi: 10.1080/20550340.2017.1317447
    [94]
    OROMIEHIE E, PRUSTY B G, RAJAN G, et al. Machine learning based process monitoring and characterisation of automated composites[C]//SAMPE 2017, 2017: 398-410.
    [95]
    OROMIEHIE E, DAS CHAKLADAR N, RAJAN G, et al. Online monitoring and prediction of thermo-mechanics of AFP based thermoplastic composites[J]. Sensors (Basel), 2019, 19(6): 1310. doi: 10.3390/s19061310
    [96]
    HAN Z, SUN S, LI W, et al. Experimental study of the effect of internal defects on stresswaves during automated fiber placement[J]. Polymers, 2018, 10(4): 1-14.
    [97]
    SCHMIDT C, SCHULTZ C, WEBER P, et al. Evaluation of eddy current testing for quality assurance and process monitoring of automated fiber placement[J]. Composites Part B: Engineering, 2014, 56: 109-116. doi: 10.1016/j.compositesb.2013.08.061
    [98]
    SHAMSUDDOHA M, DAVID M, OROMIEHIE E, et al. Distributed optical fibre sensor based monitoring of thermoplastic carbon composite cylinders under biaxial loading: Experimental and numerical investigations[J]. Composite Structures, 2021, 261: 113277. doi: 10.1016/j.compstruct.2020.113277
    [99]
    ELKINGTON M, ALMAS E, WARD-CHERRIER B, et al. Real time defect detection during composite layup via tactile shape sensing[J]. Science and Engineering of Composite Materials, 2021, 28(1): 1-10. doi: 10.1515/secm-2021-0001
    [100]
    ZHANG H, HUA J, GAO F, et al. Efficient Lamb-wave based damage imaging using multiple sparse Bayesian learning in composite laminates[J]. NDT and E International, 2020, 116: 102277. doi: 10.1016/j.ndteint.2020.102277
    [101]
    CAIRNS D S, NELSON J W, WOO K, et al. Progressive damage analysis and testing of composite laminates with fiber waves[J]. Composites Part A: Applied Science and Manufacturing, 2016, 90: 51-61. doi: 10.1016/j.compositesa.2016.03.005
    [102]
    SCHLEGEL K, FRIEDBERGER A, LOPEZ-BRAVO D. Fiber composite laying device and fiber composite laying method for producing a fiber composite scrim for forming a fiber composite component: US161033300[P]. 2019-01-17.
    [103]
    SCHLEGEL K, ALOIS F, DAVID L B. Fiber composite laying device and fiber composite laying method for producing a fiber composite scrim for forming a fiber composite component: US202210032561A1[P]. 2022-02-03.
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