Optimization of the Inspection of Large Composite Materials Using Robotized Line Scan Thermography

NDT methods and applications

Many useful NDT methods were introduced in the literature to detect the defects and delamination which has been used according to defect size and type, material, and defect location [6]. Some of the most commonly used NDT methods are: Acoustic Emission Testing (AET), Electromagnetic Testing (ET), Laser Testing Methods (LM), Magnetic Flux Leakage (MFL), Magnetic Particle Testing (MT), Neutron Radiographic Testing (NRT), Radiographic Testing (RT), Thermal/Infrared Testing (IR), Ultrasonic Testing (UT), Vibrothermography (VT).

Among various NDT methods, infrared thermography is known as an effective technique, which is utilized on a wide range of materials. The infrared thermography has many advantages as a non-contact method, non-destructive and fast technique, does not emit any harmful radiation and etc. [8]. IR thermography is an interesting approach to analyze the thermal information obtained from a specimen. This technique detects energy emitted from the specimen under investigation and converts it to the temperature variation. The output is an image of temperature variation from the specimen. IR thermography refers to the radiations located between visible and microwave in electromagnetic bands [9-11]. Generally, IR bands are divided into four parts: short-wave-infrared (SWIR), mid-wave-infrared (MWIR), long-wave-infrared (LWIR), and Far-infrared (FIR), which are respectively from 0.75 to 3 μm, 3–5 μm, 8–12 μm, and 50–1000 μm [9]. IR radiation was unknown until more than 200 years ago when Herschel conducted the first experiment with a thermometer. He built a crude monochromator in which a thermometer was used to detect radiative energy under sunlight.

Line scan thermography

Non-destructive testing (NDT) with infrared thermography techniques have been broadly applied to defect detection in specimens. Therefore, there is the need of advanced inspection methods that can provide results in a fast, accurate and reliable manner. Line scan thermography (LST) provides an alternative for these challenging situations. In this method – conversely, to static active thermography – the component of interest is inspected in motion and the acquired data can be organized as a pseudo-static sequence, similar to static data.

LST is a dynamic active thermography technique and one of the emerging technologies aimed to solve key problems in the inspection of complex component (for instance, non-uniform heating due to the irregular shape of the surface under inspection). In LST, the inspection is performed by heating the component, line-by-line while acquiring a series of thermograms with an IR camera. The robotic arm—which carries an infrared camera and the heating source—moves along the surface while the specimen is motionless.

The robotized LST provides some advantages in comparison to the static approaches. Robotized LST provides heating uniformity and allows image processing which enhances the detection probability, allowing a large-scale component to be inspected without a loss of resolution. Using the LST approach, it is possible to inspect large areas at high scan speeds. Also, the inspection results are immediately available for analysis while the scanning process continues. The acquired data is then reorganized as a pseudo-static sequence (PSS) for further analysis and processing in a similar way as is done in the static configuration.

Figure 1.1 illustrates a picture of the robotized line scanning setup. The infrared camera and heat source are installed on the robot arm. These components move in tandem, while the specimen remains fixed.

Terahertz technology

Recent works in optical NDT technology have improved sensitivity, the accuracy of detection, signal multiplexing, in addition to finding solutions for eliminating electromagnetic interference. Among these advances, the term ‘terahertz’ (THz) has been used to refer to a part of the electromagnetic spectrum which is located between IR light and microwaves (frequency range: 300 GHz to 3 THz with corresponding wavelength range: 1 mm–100 μm). There are various THz systems which can be divided into two principal kinds: continuous wave (CW) and picosecond pulses. CW could be generated by two near IR lasers of adjacent wavelengths which are spatially overlapped. This technique has some advantages such as: high resolution, spectral selectivity, and superior signal-to-noise ratio (SNR) values.[65] Femtosecond lasers generate Pulsed terahertz radiation.

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The ultrashort (ultrafast) laser pulses produce a fast current transient. This laser emits electromagnetic waves in the terahertz range.[66] In the last few years, terahertz detectors and sources have been developed considerably and used as one of the new NDT technologies. By analysing changes in the THz signal, the internal structure of the object can be determined and the defects can be identified.[67–69] In comparison to other NDT techniques, THz has the particular advantage of being able to detect internal defects in non-metallic materials. THz radiation penetrates clothing and many other opaque materials; it is also selectively absorbed by water and organic substances. These unique qualities make THz radiation interesting and informative. When a source with a fixed-frequency and a single detector is applied, the CW terahertz does not have the capability of providing any depth, frequency-domain or time-domain information.

CW imaging is less complex than a pulsed THz system, since the CW imaging does not require a pump probe system, and also it is a compact, simple system.[69] Terahertz is safe to use on living organisms (non ionising radiation) and has a shorter wavelength and higher spatial resolution than microwave radiation. It is increasingly been used in a large range of fields such as spectroscopy, medicine, NDT, chemistry, agriculture, food industry, materials science, biology and pharmacy.

Introduction
Chapter I
1.1 Infrared thermography
1.1.1 NDT methods and applications
1.1.2 Composite materials
1.1.3 Line scan thermography
1.2 Research objective
1.3 Thesis organization
1.4 Conclusion
Chapter II
-Infrared thermography and NDT: 2050 horizon
2.1. Résumé
2.2. Summary
-Infrared thermography and NDT: 2050 horizon
-ABSTRACT
1.Introduction
2.Background and history
2.1. Short history of IR thermographic technology
2.2. Thermography: a multifaceted technique for NDE
3.IR detectors
3.1. Current IR detectors
3.2. Future developments
4.Smart sensors
5.Multi-band detector
6.Terahertz technology
7.Data processing algorithms for IRT-NDT
8.IRT applications: NDT and more
9.Recent and new IR technologies
10.Conclusion
-References
Chapter III
Data processing algorithms in pulsed thermography
1. Introduction
2. Thermographic signal reconstruction (TSR)
3. Differential absolute contrast (DAC)
4. Pulsed phase thermography (PPT)
5. Principal component thermography (PCT)
6. Partial Least-Squares thermography (PLST)
3.6.1. Mathematical formulation of PLSR
3.6.2. Application of PLSR to pulsed thermography inspection
7. Tanimoto criterion
8. Signal to noise ratio (SNR)
9. Probability of detection (PoD)
10. Conclusion
Chapter IV
Three dimensional simulation of Line scan thermography using COMSOL Multiphysics
4.1. Introduction
4.2. COMSOL Multiphysics software
4.3. Definition of a new model in COMSOL
4.4. Numerical Simulation of LST
4.5. Mathematical model of the heat transfer
4.6. Conclusion
1. Résumé
2. Summary
-Abstract
1.Introduction
2.Thermography
2.1 Pulsed thermography
2.2 Lock-in thermography
2.3 Vibrothermography (VT
2.4 LED optical excitation
3.Test specimen and data analysis
4.Discussion
5.Conclusion
Chapter VI
Optimization of the Inspection of Large Composite Materials Using Robotized Line Scan Thermography
1. Résumé
2. Summary
-Abstract
1 Introduction
2 Robotized Line Scan Setup
3 Numerical Simulation of LST
4 Simulation Results
5 Experimental Setup
5.1 Validation of the Numerical Simulation
5.2 Data Reconstruction
6 Data Processing Algorithms
6.1 TSR
6.2 PCA
6.3 PPT
6.4 PLST
7 Evaluation of Signal Processing Techniques
8 Conclusion
-References
Chapter VII
Implementation of Advanced Signal Processing Techniques on Line-Scan Thermography Data
1. Résumé
2. Summary
INTRODUCTION
ROBOTIZED LINE SCAN SETUP
III. EXPERIMENTAL RESULTS
ADVANCED SIGNAL PROCESSING TECHNIQUES
SIGNAL TO NOISE RATIO
CONCLUSION
References
Chapter VIII
1. Résumé
2. Summary 1
1 Introduction
2 Robotized Line Scan Setup
3 Analytical model
4 Numerical Simulation of LST
4.1 Geometry and meshing
4.2 Governing Equations
5 Experimental Setup
6 Result Analysis and Optimization
7 Conclusion
References
Conclusion and future works
Conclusion
Future works
Acknowledgments
References

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