ENC-2024-0671-DETECTION OS DEFECTS IN ADDITIVE MANUFACTURING USING ACTIVE INFRARED THERMOGRAPHY

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<p>20th Brazilian Congress of Thermal Sciences and Engineering</p><p>November 10th-14th, 2024, Foz do Iguaçu – PR - Brazil</p><p>ENC-2024-0671</p><p>DETECTION OF DEFECTS IN ADDITIVE MANUFACTURING USING</p><p>ACTIVE INFRARED THERMOGRAPHY.</p><p>Alisson Augusto Azevedo Figueiredo</p><p>Willian de Vasconcelos Silva</p><p>State University of Maranhao – UEMA, Av. Lourenço Vieira da Silva, Nº 1000, Jardim São Cristóvão - São Luís/MA.</p><p>Federal Institute of Maranhao – IFMA, Av. Getúlio Vargas, N°04, CEP: 65030-005, Monte Castelo - São Luis/MA.</p><p>alissonfigueiredo@professor.uema.br</p><p>williansilva2@aluno.uema.br</p><p>Mateus Felipe Benicio Moraes</p><p>Sóstenes Pinheiro Campos</p><p>Federal Institute of Maranhao – IFMA, Av. Getúlio Vargas, N°04, CEP: 65030-005, Monte Castelo - São Luis/MA.</p><p>mfelipebmoraes@gmail.com</p><p>p.sostenes@acad.ifma.edu.br</p><p>Abstract. The main objective of this work is to investigate the effectiveness of the pulsed active infrared thermography</p><p>technique as a non-destructive testing tool for identifying internal defects in materials produced from additive</p><p>manufacturing. For the present study, two PLA samples were produced, with measurements of width, length and height</p><p>equal to 80 x 80 x 4.4 mm, with the same printing parameters, except the filling percentage, with sample 1 being 25%.</p><p>and sample 2 with 50%. The internal defects were created varying their diameters between 2 and 10 mm, equidistant</p><p>from each other, with a depth equal to 1.95 mm. The samples were positioned 0.50 m from a FLIR A700 infrared camera</p><p>and heated using two 500 W halogen lamps varying the pulse time between 5 and 25 seconds and were positioned 0.10</p><p>m from the sample. The thermal images obtained were processed using MATLAB® software. The results show that pulsed</p><p>active thermography using the reflection method was capable of identifying temperature variations in the region of</p><p>interest associated with defects, presenting a significant thermal contrast between the defective and healthy areas.</p><p>Keywords: Thermography, Additive manufacturing, 3d printer, Infrared camera, Defects.</p><p>1. INTRODUCTION</p><p>Broad design freedom, mass customization, waste minimization and the ability to manufacture complex structures as</p><p>well as rapid prototyping are the main benefits of additive manufacturing (AM) in particular the material extrusion</p><p>technique or Fused Deposition Modeling (FDM). For three-dimensional (3D) printing, there is a wide range of varieties</p><p>of materials, among which include polylactic acid (PLA), which is considered the main polymer used (Ngo et al., 2018),</p><p>(Gonçalves, 2022) and (Silva, 2021).</p><p>Defects such as porosity, cracks, delamination and lack of fusion can compromise the structural integrity and</p><p>functionality of components manufactured by additive manufacturing. The detection and characterization of these defects</p><p>are essential to guarantee the quality and safety of final products. However, conventional inspection methods prove to be</p><p>inadequate and invasive to detect defects in complex parts or geometries (Ngo et al., 2018), (Saeed et al., 2019), (Mandal,</p><p>2020), (Ciampa et al., 2018) and (Pierce and Crane, 2017).</p><p>Methods for detecting these defects is a relevant issue, since 3D printing has emerged as a technology capable of</p><p>producing complex parts with unique geometries in a variety of materials, in addition to increasing efficiency in material</p><p>use. In order to guarantee the functionality and safety of these parts in their various applications, ensuring their structural</p><p>integrity is vital (Manohar and Lanza di Scalea, 2013), (Wallace, Crane and Jones, 2022) and (Wang et al. 2022).</p><p>Motivated by the growing need for non-destructive testing methods to inspect parts manufactured by additive</p><p>manufacturing, which is gaining more and more attention in society, infrared thermography is a promising technique for</p><p>detecting defects, since it is possible to identify variations in the temperature of the surface of the parts by thermally</p><p>exciting it and thus identifying possible irregularities. (Manohar, Tippmann and Lanza di Scalea, 2012), (Pierce, 2018),</p><p>(Silva et al. 2023) and (Zhang, 2018).</p><p>For Almond (et al. 2017), Ciampa (et al., 2018), infrared thermography is a fast and accurate non-destructive</p><p>evaluation technique that is widely used for the inspection of large aerospace components, such as primary and secondary</p><p>aircraft structures. and helicopters, aeronautical engine parts, spacecraft components and their subsystems. It is generally</p><p>applied to different materials, including aluminum, composites and fiber hybrid metal laminates.</p><p>A. A. A. Figueiredo, W. V. Silva, M. F. B. Moraes, S. P. Campo.</p><p>Detection of Defects in Additive Manufacturing Using Active Thermography Infrared.</p><p>According to Vilardo (2018), Wallace (2022), there are two ways of positioning the thermal exciter in relation to the</p><p>inspected specimen: reflection and transmission. In reflection mode, the exciter and camera are positioned on the same</p><p>side, this mode being the most suitable for detecting discontinuities close to the surface to be thermally excited. In</p><p>transmission mode, the exciter is on the opposite side of the camera, which favors the detection of discontinuities that are</p><p>located close to the surface opposite to the thermal excitation surface.</p><p>The main objective of this work is to investigate the effectiveness of the pulsed active infrared thermography technique</p><p>as a non-destructive testing (NDT) tool for identifying defects in materials produced from additive manufacturing using</p><p>the FDM technique for the use of primary structures. or secondary sectors in various sectors of the automotive, aerospace,</p><p>architectural industries, among others. Experiments were carried out to detect internal defects in a PLA sample by varying</p><p>the filling percentage. The active approach was applied by heating the sample through halogen lamps installed for</p><p>reflection mode. During the experiment, a thermal camera recorded images of the sample's surface temperature field.</p><p>This article presents in Section 2 the materials and methodology used, including the sample manufacturing process</p><p>and experimental procedures. The results will be presented and discussed in Section 3, where the experimental analyzes</p><p>are presented. In Section 4, a conclusion of the main results is presented.</p><p>2. METHODS AND MATERIALS</p><p>Figure 1 shows the characteristics of the sample that will be used for the experiment, where the part has a width, height</p><p>and thickness equal to 80, 80 and 4.4 mm, respectively. Figure 1a presents the dimensions of the defects and their</p><p>locations, Fig. 1b presents the nomenclature of the defects, where in Table 1 shows the geometry of the defects and Fig.</p><p>1c presents the depth of the defect, which in turn has a thickness of 0.5mm.</p><p>Figure 1. Description of the samples: (a) measurements of the defect locations, (b) defect nomenclature and (c)</p><p>Depth of the defect in mm. Available from: Authors, 2024</p><p>Table 1. Defect geometry. Available from: Authors, 2024.</p><p>Defect</p><p>nomenclature</p><p>d10 d9 d8 d7 d6 d5 d4 d3 d2</p><p>Diameter (mm) 10 9 8 7 6 5 4 3 2</p><p>Depth (mm) 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5</p><p>Table 2 presents some printing characteristics of the samples, such as printing layer height, filling pattern and filling</p><p>density. To slice the sample, the Prusaslice2.8.0® software was used. The printing table temperature used was 210°C,</p><p>within the range required to facilitate material adhesion, and the nozzle temperature used was 180°C, within the permitted</p><p>range (Silva, 2021), (Gonçalves, 2022) and (Wallace, 2021).</p><p>(a) (b)</p><p>(c)</p><p>19th Brazilian Congress of Thermal Sciences and Engineering</p><p>November 16-20, 2024, Bento Gonçalves, RS, Brazil</p><p>Table 2. Sample printing characteristics. Available from: Authors, 2024.</p><p>Print</p><p>Configuration</p><p>Layer height</p><p>(mm)</p><p>Fill Pattern Top fill pattern Base fill pattern Fill density (%)</p><p>Sample</p><p>1 0.3 Rectilíneo Monotônico Monotônico 25</p><p>Sample 2 0.3 Rectilíneo Monotônico Monotônico 50</p><p>Figure 2 shows the materials used to manufacture the samples, Fig. 2a shows the Longer 3D printer used for the</p><p>production process, Fig. 2b shows the PLA filament used to produce the samples, in which the black color due to its high</p><p>emissivity value due to the tendency to absorb more radiation resulting in a greater increase in surface temperature when</p><p>compared to other colors. Table 4 presents some thermal properties.</p><p>Figure 2. Sample manufacturing process: (a) Longer 3D Printer, (b) Premium Black PLA Filament and (c) Final test</p><p>specimen. Available from: Authors, 2024</p><p>Table 4. Thermal properties. Available from: (Wallace, 2021), (Saeed et al., 2019) e (Çengel and Ghajar, 2012)</p><p>Thermal Condutivity</p><p>(k) (W/m K)</p><p>Specific Heat</p><p>Capacity (c) (J/kg K)</p><p>Density (ρ)</p><p>(kg/m³)</p><p>Thermal Diffusivity</p><p>(α) (m²/s)</p><p>PLA 0.130 1800 1300 5.556 * 10−8</p><p>Air 0.026 1005 1.225 2.141 * 10−5</p><p>Figure 3 shows the configuration for carrying out the experiments. Figure 3a shows a schematic setup of the</p><p>experiment. Figure 3b shows an overview of the experiment, where it is possible to highlight the heating sources, a FLIR</p><p>A700 thermal camera (resolution of 640 x 480 pixels) with a measurement range of -20 °C to 2000 °C, used to record</p><p>thermal images of the front surface of the sample and Fig. 3c shows the heat source formed by two reflectors composed</p><p>of two 500W halogen lamps.</p><p>Figure 3. Experimental setup: (a) schematic setup, (b) experiment overview, and (c) heating source. Available from:</p><p>Authors, 2024</p><p>(b) (a) (c)</p><p>Sample</p><p>Halogen lamp Halogen lamp</p><p>Thermal</p><p>camera</p><p>Halogen lamp</p><p>A. A. A. Figueiredo, W. V. Silva, M. F. B. Moraes, S. P. Campo.</p><p>Detection of Defects in Additive Manufacturing Using Active Thermography Infrared.</p><p>To carry out the thermographic test, the sample was positioned 0.10 m from the lamps on a support with clamps, and</p><p>a wooden support was positioned behind the sample where matte black paint was applied with the aim of reducing</p><p>reflection. from the light and 0.50 m from the camera. A timer relay and an Arduino UNO were responsible for controlling</p><p>the heating using two 500W halogen lamps each, with varying pulses. Using this configuration, active pulsed</p><p>thermography was performed and thermal images were obtained using FLIR Research Studio® software. For each</p><p>sample, a total of 5 tests were carried out, according to Table 3, which presents some frame acquisition characteristics,</p><p>such as the total acquisition time of the experiment, the frame rate and the total number of frames for each test.</p><p>Table 3. Characteristics of acquisition of experiments. Available from: Authors, 2024</p><p>Acquisition rate</p><p>(Hz)</p><p>Heating time</p><p>(s)</p><p>Acquisition time</p><p>(s)</p><p>Total frames</p><p>Test 1 10 5 65 650</p><p>Test 2 10 10 70 700</p><p>Test 3 10 15 75 750</p><p>Test 4 10 20 80 800</p><p>Test 5 10 25 85 850</p><p>The temperature curves can be extracted from the defective areas and subtracted from the healthy area curves, to</p><p>obtain the thermal contrast as described in Eq. (1). Absolute thermal contrast (Ca(t)) is best a great feature to consider as</p><p>it highlights the temperature difference between the defective and healthy areas, for each of the different defects across</p><p>the entire sample (Saeed et al. 2019). The normalized thermal contrast (Cn(t)) is described in Eq. (2) (Dattoma et al.</p><p>2017).</p><p>𝐶𝑎(𝑡) = 𝑇𝑑(𝑡) − 𝑇𝑠(𝑡) Eq. (1)</p><p>𝐶𝑛(𝑡) = (𝑇𝑑(𝑡)/ 𝑇𝑑(𝑡0 − 1)) − (𝑇𝑠(𝑡)/𝑇𝑠(𝑡0 − 1)) Eq. (2)</p><p>where 𝑇𝑑(𝑡) is the average temperature in the defective zones and 𝑇𝑠(𝑡) is the average temperature in the healthy zones</p><p>during the cooling phase.</p><p>3. RESULTS AND DISCUSSIONS</p><p>The initial analyzes of the results were carried out in the MATLAB R2024a software and with the aim of reducing</p><p>noise, the region of interest (ROI) was selected for this study, and the ROI in the thermal image can be seen in Fig. 4a</p><p>and in Fig. 4b presents the ROI with dimensions of 280 x 280 pixels.</p><p>Figure 4. Selection of the ROI in the thermal image: (a) ROI in the thermal image and (b) Region of interest.</p><p>Available from: Authors, 2024</p><p>Thermographic images obtained with the highest thermal contrasts of sample 1 for each pulse time are shown in Fig.</p><p>5. Figures 5a, 5b, 5c, 5d and 5e present the maximum thermal contrasts for pulses 5, 10, 15, 20 and 25 seconds</p><p>respectively. As sample 1 was filled with only 25% PLA, the other 75% being air, the temperature accumulation was</p><p>lower in the regions with the defects due to the significant presence of air in the regions without defects. As air has lower</p><p>thermal conductivity than PLA, the heat applied to the piece had greater resistance to be transferred to healthy regions,</p><p>promoting greater thermal contrasts.</p><p>It can also be seen that as the time of the heat pulse increases, the characterization of defects based on thermal contrast</p><p>becomes more evident, especially for those with smaller diameters.</p><p>19th Brazilian Congress of Thermal Sciences and Engineering</p><p>November 16-20, 2024, Bento Gonçalves, RS, Brazil</p><p>(a) 5 s (b) 10 s</p><p>(c) 15 s (d) 20 s (e) 25 s</p><p>Figure 5. Higher contrast thermal images for sample 1: (a) 5 s pulse, (b) 10 s pulse, (c) 15 s pulse, (d) 20 s pulse, and</p><p>(e) 25 s pulse. Available from: Authors, 2024</p><p>Figure 6 presents the thermal contrast curves on the surface of sample 1 obtained from lines 1, 2 and 3 traced on the</p><p>sample for each pulse time.</p><p>(a) 5 s (b) 10 s</p><p>(c) 15 s (d) 20 s (e) 25 s</p><p>Figure 6. Graphs of the thermal contrast curves of sample 1: (a) 5 s pulse, (b) 10 s pulse, (c) 15 s pulse, (d) 20 s</p><p>pulse and (e) 25 s pulse. Available from: Authors, 2024</p><p>Figure 7 shows the normalized thermal contrast curves on the surface of sample 1 obtained from lines 1, 2 and 3 traced</p><p>on the sample for each pulse time.</p><p>Line 1</p><p>Line 2</p><p>Line 3</p><p>Line 1</p><p>Line 2</p><p>Line 3</p><p>Line 1</p><p>Line 2</p><p>Line 3</p><p>Line 1</p><p>Line 2</p><p>Line 3</p><p>Line 1</p><p>Line 2</p><p>Line 3</p><p>A. A. A. Figueiredo, W. V. Silva, M. F. B. Moraes, S. P. Campo.</p><p>Detection of Defects in Additive Manufacturing Using Active Thermography Infrared.</p><p>(a) 5 s (b) 10 s</p><p>(c) 15 s (d) 20 s (e) 25 s</p><p>Figure 7. Graphs of the normalized thermal contrast curves of sample 1: (a) 5 s pulse, (b) 10 s pulse, (c) 15 s pulse,</p><p>(d) 20 s pulse and (e) 25 s pulse. Available from: Authors, 2024</p><p>Thermographic images obtained from the highest thermal contrasts of sample 2 for each pulse time are presented in</p><p>Fig. 5. Figures 5a, 5b, 5c, 5d and 5e present the maximum thermal contrasts for the 5, 10, 15, 20 and 25 second pulses</p><p>respectively. As sample 2 was filled with 50% PLA, the other 50% being air, the temperature accumulation was lower in</p><p>the regions with defects due to a significant presence of air in the regions without defects.</p><p>(a) 5 s (b) 10 s</p><p>(c) 15 s (d) 20 s (e) 25 s</p><p>Figure 8. Higher contrast thermal images for sample 2: (a) 5 s pulse, (b) 10 s pulse, (c) 15 s pulse, (d) 20 s pulse, and</p><p>(e) 25 s pulse. Available from: Authors, 2024</p><p>Figure 9 presents the thermal contrast curves on the surface of sample 2 obtained from lines 1, 2 and 3 traced on the</p><p>sample for each pulse time.</p><p>Line 1</p><p>Line 2</p><p>Line 3</p><p>Line 1</p><p>Line 2</p><p>Line 3</p><p>Line 1</p><p>Line 2</p><p>Line 3</p><p>Line 1</p><p>Line 2</p><p>Line 3</p><p>Line 1</p><p>Line 2</p><p>Line 3</p><p>19th Brazilian Congress of Thermal Sciences and Engineering</p><p>November 16-20, 2024, Bento Gonçalves, RS, Brazil</p><p>(a) 5 s (b) 10 s</p><p>(c) 15 s (d) 20 s (e) 25 s</p><p>Figure 9. Graphs of the thermal contrast curves of sample 2: (a) 5 s pulse, (b) 10 s pulse, (c) 15 s pulse, (d) 20 s</p><p>pulse and (e) 25 s pulse. Available from: Authors, 2024</p><p>Figure 10 presents the normalized thermal contrast curves on the surface of sample 2 obtained from lines 1, 2 and 3</p><p>traced on the sample for each pulse time.</p><p>(a) 5 s (b) 10 s</p><p>(c) 15 s (d) 20 s (e) 25 s</p><p>Figure 10. Graphs of the normalized thermal contrast curves of sample 2: (a) 5 s pulse, (b) 10 s pulse, (c) 15 s pulse,</p><p>(d) 20 s pulse and (e) 25 s pulse. Available from: Authors, 2024</p><p>4. CONCLUSION</p><p>The study concludes that pulsed active infrared thermography using the reflection method is promising for detecting</p><p>defects in materials produced by AM, offering advantages over traditional inspection methods in terms of speed, accuracy</p><p>and large area for analysis. the analysis of the temperature curves in different regions of the sample confirms the</p><p>relationship between the size of the defects and the observed thermal contrast. This experiment showed that larger ceramic</p><p>defects contained greater heat accumulation during heating and heating, resulting in a thermal contrast when compared</p><p>to smaller defects.</p><p>A. A. A. Figueiredo, W. V. Silva, M. F. B. Moraes, S. P. Campo.</p><p>Detection of Defects in Additive Manufacturing Using Active Thermography Infrared.</p><p>5. ACKNOWLEDGEMENTS</p><p>The authors would like to thank the State University of Maranhão (UEMA), the Heat Experimentation and Simulation</p><p>Laboratory (LESC), the PPGMEC-IFMA Monte Castelo and the National Council for Scientific and Technological</p><p>Development (CNPq) for the fundamental help provided in the construction of the experimental setup.</p><p>6. REFERENCES</p><p>Almond, D. P., Angioni, S. L., Pickering, S. G., 2017. “Long pulse excitation thermographic non-destructive evaluation”.</p><p>Independent Nondestructive Testing and Evaluation, Vol. 87, pp 1-14.</p><p>Ciampa, F.; Mahmoodi, P.; Pinto, F.; Meo, M., 2018. “Recent Advances in Active Infrared Thermography for Non-</p><p>Destructive Testing of Aerospace Components”. Sensors. v. 18.</p><p>Çengel, Y. A. e Ghajar, A. J., 2012. 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A., 2019. “Experimentally validated defect depth estimation using</p><p>artificial neural network in pulsed thermography”. Infrared Physics & Technology, Vol. 98, pp. 192-200.</p><p>Silva, H. V., Martins, A. P., Machado, M. A., Santos, T. G., Carvalho, M. S., 2023. “Double active thermographic</p><p>inspection of additive manufacturing composites: numerical modelling and validation”. Journal of the International</p><p>Measurement Confederation, Vol. 218.</p><p>Silva, H. V., 2021. Simulação e validação experimental de termografia ativa para compósitos de matriz polimérica</p><p>reforçados com fibras contínuas produzidos por manufatura aditiva. Master’s thesis, Universidade NOVA de Lisboa,</p><p>Lisboa, Portugal.</p><p>Wallace, N. J., Crane, N. B., Jones, M. R., 2022. “Defect measurement limits using flash thermography with application</p><p>to additive manufacturing”. Independent Nondestructive Testing and Evaluation , Vol. 128.</p><p>Wallace, N. J., 2021. Active Thermography for addtive manufacturing processes. Master’s thesis, Brigham Young</p><p>University, Utah, United States American.</p><p>Wang, Z., Wan, L., Zhu, J. Ciampa, F., 2022. “Evaluation of defect depth in CFRP composites by long pulse</p><p>thermography”. Independent Nondestructive Testing and Evaluation, Vol. 129.</p><p>Zhang, B., Duemmler, M., Sripragash, L., Adewumi, O., Davies, A., Ziegert, J., Waters, C., Evans, C., 2018. “Detection</p><p>of subsurface defect for metal additive manufacturing using flash thermography”. Conference: 2018 ASPE and euspen</p><p>Summer Topical Meeting. Berkeley, CA, USA.</p><p>7. RESPONSIBILITY NOTICE</p><p>The authors are the only responsible for the printed material included in this paper.</p>