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Thermography Sensing in Non-destructive Testing and Monitoring
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Thermography Sensing in Non-destructive Testing and Monitoring

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (30 November 2020) | Viewed by 25575

Special Issue Editor

Dr. Carosena Meola

E-Mail Website
Guest Editor
Department of Industrial Engineering, University of Naples Federico II Via Claudio 21, 80125 Napoli, Italy
Interests: infrared thermography; non-destructive testing; composite materials; personnel qualification and certification; safety at work regulation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Infrared thermography (IRT) allows mapping the surface temperature of an object without contact in a remote way by sensing the thermal energy that is radiated from objects in the infrared band.

Infrared thermography can be used in a broad number of application fields and for many different purposes since any process, which is temperature-dependent, may benefit from the use of an infrared imaging device. Amongst others IRT can be advantageously used for non destructive evaluation of materials and structures and for monitoring of their degradation with time. IRT allows also for monitoring of specimens under mechanical tests for materials characterization. In addition, an infrared imaging device can be exploited to finding heat losses for energy saving purposes.

The scope of this Special Issue is to collect experiences by researches involved with the use of infrared thermography in non-destructive inspection and condition monitoring and in materials characterization.

Topics include but are not limited to:

  • Aerospace and industrial applications
  • Applications to the cultural heritage
  • Civil engineering and buildings
  • Thermo-fluid-dynamics
  • Thermoelastic stress analysis
  • Monitoring of mechanical tests
  • Condition monitoring
  • Novel methods of processing and analysis of thermal images

Dr. Carosena Meola
Guest Editor

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Infrared thermography
  • Non contact sensor
  • Non destructive
  • Monitoring
  • Mechanical tests
  • Metals
  • Composite materials
  • Composite structures
  • Buildings
  • Cultural Heritage
  • Condition monitoring
  • Heat losses
  • Fluid infiltration
  • TSA
  • Pulse thermography
  • Lock-in thermography

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Published Papers (6 papers)

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Research

15 pages, 3227 KiB  
Article
Infrared Thermography Measurement for Vibration-Based Structural Health Monitoring in Low-Visibility Harsh Environments
by Jia-Hao He, Ding-Peng Liu, Cheng-Hsien Chung and Hsin-Haou Huang
Sensors 2020, 20(24), 7067; https://doi.org/10.3390/s20247067 - 10 Dec 2020
Cited by 26 | Viewed by 4381
Abstract
In this study, infrared thermography is used for vibration-based structural health monitoring (SHM). Heat sources are employed as sensors. An acrylic frame structure was experimentally investigated using the heat sources as structural marker points to record the vibration response. The effectiveness of the [...] Read more.
In this study, infrared thermography is used for vibration-based structural health monitoring (SHM). Heat sources are employed as sensors. An acrylic frame structure was experimentally investigated using the heat sources as structural marker points to record the vibration response. The effectiveness of the infrared thermography measurement system was verified by comparing the results obtained using an infrared thermal imager with those obtained using accelerometers. The average error in natural frequency was between only 0.64% and 3.84%. To guarantee the applicability of the system, this study employed the mode shape curvature method to locate damage on a structure under harsh environments, for instance, in dark, hindered, and hazy conditions. Moreover, we propose the mode shape recombination method (MSRM) to realize large-scale structural measurement. The partial mode shapes of the 3D frame structure are combined using the MSRM to obtain the entire mode shape with a satisfactory model assurance criterion. Experimental results confirmed the feasibility of using heat sources as sensors and indicated that the proposed methods are suitable for overcoming the numerous inherent limitations associated with SHM in harsh or remote environments as well as the limitations associated with the SHM of large-scale structures. Full article
(This article belongs to the Special Issue Thermography Sensing in Non-destructive Testing and Monitoring)
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20 pages, 8874 KiB  
Article
Evaluation of Dust Deposition on Parabolic Trough Collectors in the Visible and Infrared Spectrum
by Rubén Usamentiaga, Alberto Fernández and Juan Luis Carús
Sensors 2020, 20(21), 6249; https://doi.org/10.3390/s20216249 - 2 Nov 2020
Cited by 10 | Viewed by 3104
Abstract
Solar energy is mostly harnessed in arid areas where a high concentration of atmospheric dust represents a major environmental degradation factor. Gravitationally settled particles and other solid particles on the surface of the photovoltaic panels or thermal collectors greatly reduce the absorbed solar [...] Read more.
Solar energy is mostly harnessed in arid areas where a high concentration of atmospheric dust represents a major environmental degradation factor. Gravitationally settled particles and other solid particles on the surface of the photovoltaic panels or thermal collectors greatly reduce the absorbed solar energy. Therefore, frequent cleaning schedules are required, consuming high quantities of water in regions where water precipitation is rare. The efficiency of this cleaning maintenance is greatly improved when methods to estimate the degree of cleanness are introduced. This work focuses on the need for better detecting the degradation created by dust deposition, considering experimental data based on different air pollutants, and analyzing the resulting thermal and visible signatures under different operating environments. Experiments are performed using six different types of pollutants applied to the surface of parabolic trough collectors while varying the pollutant density. The resulting reflectivity in the visible and infrared spectrum is calculated and compared. Results indicate that the pollutants can be distinguished, although the reflectivity greatly depends on the combination of the particle size of the pollutant and the applied amount, with greater impact from pollutants with small particles. Full article
(This article belongs to the Special Issue Thermography Sensing in Non-destructive Testing and Monitoring)
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16 pages, 13666 KiB  
Article
Infrared Thermography for the Detection and Characterization of Photovoltaic Defects: Comparison between Illumination and Dark Conditions
by Sara Gallardo-Saavedra, Luis Hernández-Callejo, María del Carmen Alonso-García, Jesús Muñoz-Cruzado-Alba and Javier Ballestín-Fuertes
Sensors 2020, 20(16), 4395; https://doi.org/10.3390/s20164395 - 6 Aug 2020
Cited by 19 | Viewed by 3659
Abstract
Newly installed renewable power capacity has been increasing incredibly in recent years. For example, in 2018, 181 GW were installed worldwide. In this scenario, in which photovoltaic (PV) energy plays a leading role, it is essential for main players involved in PV plants [...] Read more.
Newly installed renewable power capacity has been increasing incredibly in recent years. For example, in 2018, 181 GW were installed worldwide. In this scenario, in which photovoltaic (PV) energy plays a leading role, it is essential for main players involved in PV plants to be able to identify the failure modes in PV modules in order to reduce investment risk, to focus their maintenance efforts on preventing those failures and to improve longevity and performance of PV plants. Among the different systems for defects detection, conventional infrared thermography (IRT) is the fastest and least expensive technique. It can be applied in illumination and in dark conditions, both indoor and outdoor. These two methods can provide complementary results for the same kind of defects, which is analyzed and characterized in this research. Novel investigation in PV systems propose the use of a power inverter with bidirectional power flow capability for PV plants maintenance, which extremely facilitates the electroluminescence (EL) inspections, as well as the outdoor IRT in the fourth quadrant. Full article
(This article belongs to the Special Issue Thermography Sensing in Non-destructive Testing and Monitoring)
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26 pages, 3362 KiB  
Article
Predictive Models for the Characterization of Internal Defects in Additive Materials from Active Thermography Sequences Supported by Machine Learning Methods
by Manuel Rodríguez-Martín, José G. Fueyo, Diego Gonzalez-Aguilera, Francisco J. Madruga, Roberto García-Martín, Ángel Luis Muñóz and Javier Pisonero
Sensors 2020, 20(14), 3982; https://doi.org/10.3390/s20143982 - 17 Jul 2020
Cited by 24 | Viewed by 3599
Abstract
The present article addresses a generation of predictive models that assesses the thickness and length of internal defects in additive manufacturing materials. These modes use data from the application of active transient thermography numerical simulation. In this manner, the raised procedure is an [...] Read more.
The present article addresses a generation of predictive models that assesses the thickness and length of internal defects in additive manufacturing materials. These modes use data from the application of active transient thermography numerical simulation. In this manner, the raised procedure is an ad-hoc hybrid method that integrates finite element simulation and machine learning models using different predictive feature sets and characteristics (i.e., regression, Gaussian regression, support vector machines, multilayer perceptron, and random forest). The performance results for each model were statistically analyzed, evaluated, and compared in terms of predictive performance, processing time, and outlier sensibility to facilitate the choice of a predictive method to obtain the thickness and length of an internal defect from thermographic monitoring. The best model to predictdefect thickness with six thermal features was interaction linear regression. To make predictive models for defect length and thickness, the best model was Gaussian process regression. However, models such as support vector machines also had significative advantages in terms of processing time and adequate performance for certain feature sets. In this way, the results showed that the predictive capability of some types of algorithms could allow for the detection and measurement of internal defects in materials produced by additive manufacturing using active thermography as a non-destructive test. Full article
(This article belongs to the Special Issue Thermography Sensing in Non-destructive Testing and Monitoring)
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21 pages, 10700 KiB  
Article
Principal Component Thermography for Defect Detection in Concrete
by Bojan Milovanović, Mergim Gaši and Sanjin Gumbarević
Sensors 2020, 20(14), 3891; https://doi.org/10.3390/s20143891 - 13 Jul 2020
Cited by 41 | Viewed by 5377
Abstract
The goal of the condition assessment of concrete structures is to gain an insight into current condition of concrete and the existence of defects, which decrease durability and usability of the structure. Defects are quite difficult to detect using infrared thermography when concrete [...] Read more.
The goal of the condition assessment of concrete structures is to gain an insight into current condition of concrete and the existence of defects, which decrease durability and usability of the structure. Defects are quite difficult to detect using infrared thermography when concrete elements cannot be thermally excited with the Sun, together with unfavorable thermophysical properties of concrete structures. In this paper, principal component thermography (PCT) is applied as a post-processing method to a sequence of thermograms in order to enhance defect detectability in concrete structures. Defects are detected by analyzing a set of empirical orthogonal functions (EOFs), which were acquired by applying principal component analysis to a sequence of thermograms. The research was performed using concrete samples containing known defects, which were tested using a step heating thermography setup. The results of presented research show that PCT is an effective post-processing method to improve defect detection in concrete structures. By effectively improving the defect detection, PCT has a potential to improve the non-destructive testing (NDT) accuracy of using infrared thermography (IRT) on concrete structures, especially in shaded areas of such structures. The research also shows the defect detectability depending on concrete type thermal excitation setup and defect geometry. Full article
(This article belongs to the Special Issue Thermography Sensing in Non-destructive Testing and Monitoring)
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19 pages, 5576 KiB  
Article
Thermography-Based Deterioration Detection in Concrete Bridge Girders Strengthened with Carbon Fiber-Reinforced Polymer
by Van Ha Mac, Jungwon Huh, Nhu Son Doan, Geunock Shin and Bang Yeon Lee
Sensors 2020, 20(11), 3263; https://doi.org/10.3390/s20113263 - 8 Jun 2020
Cited by 20 | Viewed by 4757
Abstract
In bridge structures worldwide, carbon fiber-reinforced polymer (CFRP) sheets are applied to strengthen weak components, especially concrete girders that are at a high risk of rapid degradation during the bridge’s operation owing to impacts from the superstructure’s weight and traffic loads. Regarding the [...] Read more.
In bridge structures worldwide, carbon fiber-reinforced polymer (CFRP) sheets are applied to strengthen weak components, especially concrete girders that are at a high risk of rapid degradation during the bridge’s operation owing to impacts from the superstructure’s weight and traffic loads. Regarding the thermography-based method (TM), although deteriorations in the concrete core are some of the main defects in concrete structures strengthened with CFRP, these do not receive as much attention as damage in the CFRP. Therefore, the interpretation of the structural health in terms of these defects using TM is still unclear. The problem presented in this work addresses the quantification of delamination inside the concrete part of a specimen with a CFRP sheet installed on the surface (assumed to be the girder surface strengthened with CFRP) via step heating thermography. Additionally, the empirical thermal diffusivity of concrete girders strengthened with a CFRP sheet (CSC girder), has not been provided previously, is proposed in the present study to predict delamination depths used for field investigations. Moreover, the effect of the CFRP sheet installed on the structure’s surface on the absolute contrast of delamination is clarified. Finally, advanced post-processing algorithms, i.e., thermal signal reconstruction and pulsed phase thermography, are applied to images obtained with step heating thermography to enhance the visibility of delamination in CSC girders. Full article
(This article belongs to the Special Issue Thermography Sensing in Non-destructive Testing and Monitoring)
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