Modares Mechanical Engineering

Modares Mechanical Engineering

Enhancing Defect Detection in Additively Manufactured PLA and ABS Polymer Parts Using PCA and PPT Image Processing in Active Thermography

Document Type : Original Article

Authors
School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, Iran
10.48311/mme.2025.117176.82871
Abstract
This study investigates the performance of active infrared thermography for detecting surface and subsurface defects in two commonly used polymers, PLA and ABS. To enhance detection accuracy and image contrast, two advanced image-processing techniques—Principal Component Analysis (PCA) and Pulsed Phase Thermography (PPT)—were applied individually and in combination to the thermal image sequences. Results show that PCA efficiently reduces noise and emphasizes dominant thermal patterns, providing superior identification of shallow defects. In contrast, PPT, through frequency-domain analysis, exhibits lower sensitivity to non-uniform heating and emissivity variations, enabling more reliable detection of deeper defects. Comparative thermal behavior analysis revealed that PLA, due to its higher thermal conductivity, identifies surface defects more rapidly and with greater contrast, whereas ABS, with its higher specific heat capacity, offers improved stability and precision in subsurface defect detection. Moreover, the hybrid application of PCA and PPT proved sequence-dependent: in PLA, the PCA→PPT approach yielded a balanced visualization of both surface and subsurface anomalies, while in ABS, the PPT→PCA sequence significantly enhanced subsurface defect contrast. These findings demonstrate that combining complementary thermographic processing methods can overcome the limitations of single techniques and, when tailored to material-specific thermal properties, provide a robust framework for non-destructive evaluation of additively manufactured polymer components
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[1] S. Bagavathiappan, B. B. Lahiri, T. Saravanan, J. Philip, and T. Jayakumar, "Infrared thermography for condition monitoring – A review," Infrared Physics & Technology, vol. 60, pp. 35-55, 2013/09/01/ 2013, doi:10.1016/j.infrared.2013.03.006.
[2] P. Meshkizadeh, "Assigning the heating mechanism for characterizing corrosion defects using thermography," master Faculty of Mechanical Engineering, University of Tehran, 2020.
[3] B. K. N. Rao, "Condition monitoring and the integrity of industrial systems," in Handbook of Condition Monitoring: Techniques and Methodology, A. Davies Ed. Dordrecht: Springer Netherlands, 1998, pp. 3-34, doi: 10.1007/978-94-011-4924-2_1.
[4] A. I. Moskovchenko, M. Švantner, V. P. Vavilov, and A. O. Chulkov, "Characterizing Depth of Defects with Low Size/Depth Aspect Ratio and Low Thermal Reflection by Using Pulsed IR Thermography," (in eng), Materials (Basel), vol. 14, no. 8, Apr 10 2021, doi:10.3390/ma14081886.
[5] K. Nategh, "Improving the nondestructive thermography inspection results for detection of circular defects in coated metals using principal component analysis," NDT Technology, vol. 2, no. 9, pp. 33-40, 2022,  doi:10.30494/jndt.2022.339719.1092.
[6] A. Ardebili and M. Farahani, "Delamination Defect Evaluation in CFRP Composite Patches by the Use of Active Thermography," Journal of Nondestructive Evaluation, vol. 41, no. 3, p. 61, 2022/09/05 2022, doi: doi:10.1007/s10921-022-00892-z.
[7] Y. Chung, S. Lee, and W. Kim, "Latest Advances in Common Signal Processing of Pulsed Thermography for Enhanced Detectability: A Review," Applied Sciences, vol. 11, no. 24, p. 12168, 2021. [Online]. Available: https://www.mdpi.com/2076-3417/11/24/12168.
[8] J. Andrés, J. M. López-Higuera, and F. J. Madruga, "Quantification by Signal to Noise Ratio of Active Infrared Thermography Data Processing Techniques," Optics and Photonics Journal, vol. 03, pp. 20-26, 01/01 2013, doi:10.4236/opj.2013.34A004.
[9] R. Khoshkbary, M. Farahani, M. Safarabadi, and S. Asghari, "Using of Modulated Thermography for Nondestructive Testing of Polymer Plates," NDT Technology, vol. 2, no. 4, pp. 38-45, 2019, doi:10.30494/jndt.2019.95383.
[10] M. Rodríguez-Martín et al., "Predictive Models for the Characterization of Internal Defects in Additive Materials from Active Thermography Sequences Supported by Machine Learning Methods," Sensors, vol. 20, no. 14, doi:10.3390/s20143982.
[11] M. Rodríguez-Martin, J. Pisonero, D. González-Aguilera, and F. J. Madruga, "Flash thermography to detect and evaluate impacts in polycarbonate parts produced by additive manufacturing," NDT & E International, vol. 146, p. 103163, 2024, doi:10.1016/j.ndteint.2024.103163.
[12] J. L. Bartlett, F. M. Heim, Y. V. Murty, and X. Li, "In situ defect detection in selective laser melting via full-field infrared thermography," Additive Manufacturing, vol. 24, pp. 595-605, 2018/12/01/ 2018, do:10.1016/j.addma.2018.10.045.
[13] R. Yang and Y. He, "Optically and non-optically excited thermography for composites: A review," Infrared Physics & Technology, vol. 75, pp. 26-50, 2016/03/01/ 2016, doi:10.1016/j.infrared.2015.12.026.
[14] K. H. H. Goh, Q. F. Lim, and P. K. Pallathadka, "Asynchronous Lock In Thermography of 3D Printed PLA and ABS samples," p. arXiv:1805.01343, doi:10.48550/arXiv.1805.01343