scholarly journals Characterization of Defects in Curved Composite Structures Using Active Infrared Thermography

2016 ◽  
Vol 157 ◽  
pp. 325-332 ◽  
Author(s):  
Przemysław Daniel Pastuszak
Keyword(s):  
Infrared Thermography ◽  
Composite Structures ◽  
Active Infrared Thermography

scholarly journals Evaluation and Selection of Video Stabilization Techniques for UAV-Based Active Infrared Thermography Application

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1604
Author(s):  
Shashank Pant ◽  
Parham Nooralishahi ◽  
Nicolas P. Avdelidis ◽  
Clemente Ibarra-Castanedo ◽  
Marc Genest ◽  
...  
Keyword(s):  
Infrared Thermography ◽  
Human Error ◽  
Inspection Time ◽  
Video Stabilization ◽  
Inspection System ◽  
Simple Method ◽  
Active Infrared Thermography ◽  
Thermal Profiling ◽  
Digital Video Stabilization

Unmanned Aerial Vehicles (UAVs) that can fly around an aircraft carrying several sensors, e.g., thermal and optical cameras, to inspect the parts of interest without removing them can have significant impact in reducing inspection time and cost. One of the main challenges in the UAV based active InfraRed Thermography (IRT) inspection is the UAV’s unexpected motions. Since active thermography is mainly concerned with the analysis of thermal sequences, unexpected motions can disturb the thermal profiling and cause data misinterpretation especially for providing an automated process pipeline of such inspections. Additionally, in the scenarios where post-analysis is intended to be applied by an inspector, the UAV’s unexpected motions can increase the risk of human error, data misinterpretation, and incorrect characterization of possible defects. Therefore, post-processing is required to minimize/eliminate such undesired motions using digital video stabilization techniques. There are number of video stabilization algorithms that are readily available; however, selecting the best suited one is also challenging. Therefore, this paper evaluates video stabilization algorithms to minimize/mitigate undesired UAV motion and proposes a simple method to find the best suited stabilization algorithm as a fundamental first step towards a fully operational UAV-IRT inspection system.

Comparative study of steel corrosion characterization by visible and THz imaging techniques

2020 ◽  
Author(s):  
Jean Dumoulin ◽  
Ilaria Catapano ◽  
Jean-Marc Moliard ◽  
Giovanni Ludeno ◽  
Thibaud Toullier ◽  
...  
Keyword(s):  
Comparative Study ◽  
Data Processing ◽  
Infrared Thermography ◽  
Composite Structures ◽  
High Speed ◽  
Imaging Techniques ◽  
Terahertz Imaging ◽  
Data Matrix ◽  
Processing Chain

<p>Transport infrastructures play a significant role in the economy of countries. However, in European countries, transport infrastructures aging (>40 years) and traffic increase require to develop in-situ efficient inspection and maintenance solutions. Monitoring of steel and composite structures are important issues for sustainability of existing and new infrastructure. Classical approach relies on large human activities eventually performed in unsafe conditions. To overcome the problem on site contactless global automated measurement methods are to be favoured.</p><p>For apparent corrosion, visible imaging coupled with image processing allows to detect and characterize the extension of the defective area. Anyway, characterization of corrosion thickness and nature require complementary measurements. Among imaging techniques, knowing that corrosion acts as a insulating layer, active infrared thermography is a possible approach [1-2]. But here we will focus on the complementary approach based on THz-TDS imaging as investigated and tested for corrosion detection under painting with preliminary corrosion type classification [2].</p><p>In the present study, we first performed a measurement campaign on several steel samples at different corrosion stages. Typically, three stages were investigated: from non-corroded with paint coating, to pitting corrosion up to fully corroded sample surface.</p><p>Data were gathered by means of the Z-Omega Fiber-Coupled Terahertz Time Domain (FICO) system working in a high-speed reflection mode and were processed by using a properly designed data processing chain recently proposed in [3] and involving a noise filtering procedure based on the Singular Value Decomposition (SVD) of the data matrix. Complementary post-processing approach for quick detection and characterization were added to these filtered data.</p><p>The obtained results, which will be presented in detail at the conference, allowed us to state the imaging capabilities offered by the adopted instrumentation and obtain valuable information on the surveyed specimens, such as the corrosion thickness connection with apparent pseudo-intensity images. Finally, perspectives on coupling techniques will be introduced.</p><p><strong>Acknowledgments:</strong></p><p>Authors wish to thank Research Fund for Coal and Steel for funding part of this work under grant agreement No 800687 in the framework of DESDEMONA project.</p><p> </p><p><strong>References</strong></p><p>[1] A. Crinière, J. Dumoulin, C. Ibarra-Castanedo and X. Maldague ,” Inverse model for defect characterization of externally glued CFRP on reinforced concrete structures: Comparative study of square pulsed and pulsed thermography “, Quantitative InfraRed Thermography Journal, Taylor & Francis Editor, vol 11, pp 84-114, 2014. DOI: 10.1080/17686733.2014.897512.</p><p>[2] T. Sakagami, D. Shiozawa, Y. Tamaki, H. Ito A. Moriguchi, T. Iwama, K. Sekine and T. Shiomi, “Nondestructive detection of corrosion damage under corrosion protection coating using infrared thermography and terahertz imaging, in. Proc AITA 2015 conference, pp. 229-233, 2015.</p><p>[3] I. Catapano, F. Soldovieri, “A Data Processing Chain for Terahertz Imaging and Its Use in Artwork Diagnostics".J Infrared Milli Terahz Waves, pp.13, Nov. 2016.</p>

A simple method for defect area detection using active thermography

2009 ◽  
Vol 17 (4) ◽  
Author(s):  
S. Dudzik
Keyword(s):  
Thermal Diffusivity ◽  
Infrared Thermography ◽  
Subsurface Layer ◽  
Quantitative Characterization ◽  
Simple Method ◽  
Active Thermography ◽  
Active Infrared Thermography ◽  
Defect Area

AbstractIn this paper a simple method for defect area detection in the subsurface layer of materials was presented. The method uses active infrared thermography. A statistical detectivity ratio was introduced for a quantitative characterization of areas containing defects. The described algorithm of defect area detection was tested for a material with a low thermal diffusivity. The results of experimental and simulation investigations are presented. It was stated that the statistical detectivity ratio can be used to detect regions of defect presence, even for the non-uniformly heated surfaces.

Hidden Text Detection by Infrared Thermography / Anwendung der aktiven Infrarotthermographie (IRT) zur Erfassung von verdeckten Texten / Utilisation de la thermographie infrarouge (IRT) pour détecter des textes cachés

2013 ◽  
Vol 34 (3) ◽  
Author(s):  
Fulvio Mercuri ◽  
Roberta Gnoli ◽  
Stefano Paoloni ◽  
Noemi Orazi ◽  
Cristina Cicero ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Infrared Thermography ◽  
Text Detection ◽  
Qualitative Description ◽  
Physical Mechanisms ◽  
Active Infrared Thermography ◽  
History Of

AbstractWe present an opto-thermal approach based on the use of active infrared thermography (IRT) for the study of texts hidden inside the bookbinding structure of ancient books. In particular we focus our investigation on the detection and characterization of texts on paper scraps, belonging to earlier handwritten or printed leaves, used for the making of bookbindings and lying between the end papers and the cover. A qualitative description of the physical mechanisms allowing the identification of texts is proposed and a comparative analysis of the results obtained by means of different IRT experimental configurations is presented. The results show that active IRT can be a very useful tool for the detection and the identification of underlying texts whose reading can provide useful information on the specific history of ancient books.

Characterization of Fouled Flat Sheet Membranes by Infrared Thermography

2014 ◽  
Author(s):  
Kennethrex O. Ndukaife ◽  
George Agbai Nnanna
Keyword(s):  
Surface Temperature ◽  
Infrared Thermography ◽  
Spectral Power ◽  
Membrane Surface ◽  
Infrared Camera ◽  
Feed Solution ◽  
Feed Concentration ◽  
Ir Camera ◽  
Measure Surface Temperature

An Infrared thermography (IRT) technique for characterization of fouling on membrane surface has been developed. The emitted spectral power from the fouled membrane is a function of emissivity and surface morphology. In this work, a FLIR A320 IR camera was used to measure surface temperature and emissivity. The surface temperature and the corresponding emissivity value of various areas on the fouled membrane surface is measured by the infrared camera and recorded alongside its thermogram. Different fouling experiments were performed using different concentrations of aluminum oxide nanoparticle mixed with deionized water as feed solution (333 ppm, 1833 ppm and 3333 ppm) so as to investigate the effect of feed concentration on the degree of fouling and thus its effect on the emissivity values measured on the membrane surfaces. Surface plots in 3D and Line plots are obtained for the measured emissivity values and thickness of the fouling deposit on the membrane surface respectively. The results indicate that the IRT technique is sensitive to changes that occur on the membrane surface due to deposition of contaminants on the membrane surface and that emissivity is a function of temperature, surface roughness and thickness of the specimen under investigation.

scholarly journals A Method of Defect Depth Recognition in Active Infrared Thermography Based on GRU Networks

2021 ◽  
Vol 11 (14) ◽  
pp. 6387
Author(s):  
Li Xu ◽  
Jianzhong Hu
Keyword(s):  
Infrared Thermography ◽  
Visual Information ◽  
Evaluation Method ◽  
Recognition Performance ◽  
Principal Component ◽  
Defect Depth ◽  
Model Learning ◽  
Flat Bottom ◽  
Bp Network ◽  
Active Infrared Thermography

Active infrared thermography (AIRT) is a significant defect detection and evaluation method in the field of non-destructive testing, on account of the fact that it promptly provides visual information and that the results could be used for quantitative research of defects. At present, the quantitative evaluation of defects is an urgent problem to be solved in this field. In this work, a defect depth recognition method based on gated recurrent unit (GRU) networks is proposed to solve the problem of insufficient accuracy in defect depth recognition. AIRT is applied to obtain the raw thermal sequences of the surface temperature field distribution of the defect specimen. Before training the GRU model, principal component analysis (PCA) is used to reduce the dimension and to eliminate the correlation of the raw datasets. Then, the GRU model is employed to automatically recognize the depth of the defect. The defect depth recognition performance of the proposed method is evaluated through an experiment on polymethyl methacrylate (PMMA) with flat bottom holes. The results indicate that the PCA-processed datasets outperform the raw temperature datasets in model learning when assessing defect depth characteristics. A comparison with the BP network shows that the proposed method has better performance in defect depth recognition.

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