Defect Detection Capabilities of Pulse Compression Based Infrared Non-Destructive Testing and Evaluation

Dua, Geetika; Arora, Vanita; Mulaveesala, Ravibabu

doi:10.1109/jsen.2020.3046320

Cited by 31 publications

(10 citation statements)

References 29 publications

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“…Initially during the period of stage 1, a thermal profile as a reference point is carefully chosen as of the exact location of the region that is nondefective. Later, with the help of reference point the interrelationship for the two points said to be the crosscorrelation is conducted, which results a correlation coefficient sequence between 0 to 1 using Equation (12). These obtained normalized correlation coefficients are rearranged into their corresponding pixel locations to form correlation images for that delayed instant.…”

Section: Pulse Compressionmentioning

confidence: 99%

“…This coefficient contrast obtained can be utilized for subsurface feature extraction [21]. (12) Figure 2 shows the block diagram representation of various signal processing methods [21]. Figures 2a and 2b show the processing approaches steps for obtaining the frequency domain-based results whereas Figure 2c shows the processing steps to obtain time-domain phase results.…”

Section: Pulse Compressionmentioning

confidence: 99%

“…Moreover, the requirement of high power is the major drawback of pulse phased thermography [11]. However, to examine an object in single experimentation for a small duration of time, nonstationary thermal wave imaging is used [12]. Linear frequency modulated thermography uses frequency modulated chirp stimulus of low power through lower frequency band towards the test of entire sample during a particular investigation.…”

Section: Introductionmentioning

confidence: 99%

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Coded Thermal Wave Imaging based Defect Detection in Composites using Neural Networks

Shanmugam

Sangeetha

et al. 2022

IJE

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Industry 4.0 focuses on the deployment of artificial intelligence in various fields for automation of variety of industrial applications like aerospace, defence, material manufacturing, etc. Application of these principles to active thermography, facilitates automatic defect detection without human intervention and helps in automation in assessing the integrity and product quality. This paper employs artificial neural network (ANN) based classification post-processing modality for exploring subsurface anomalies with improved resolution and enhanced detectability. A modified bi-phase seven-bit barker coded thermal wave imaging is used to simulate the specimens. Experimentation has been carried over carbon fiber reinforced plastic (CFRP) and glass fiber reinforced plastic (GFRP) specimens using artificially made flat bottom holes of various sizes and depths. A phase based theoretical model also developed for quantitative assessment of depth of the anomaly and experimentally cross verified with a maximum depth error of 3%. Additionally, subsurface anomalies are compared based on probability of detection (POD) and signal to noise ratio (SNR). ANN provides better visualization of defects with 96% probability of detection even for small aspect ratio in contrast to conventional post processing modalities.

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Section: Pulse Compressionmentioning

confidence: 99%

Section: Pulse Compressionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Coded Thermal Wave Imaging based Defect Detection in Composites using Neural Networks

Shanmugam

Sangeetha

et al. 2022

IJE

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“…In fact, the cross-correlation process compresses the energy of the signal under a main lobe whose peak value determines the strength of the reflected echo, while the associated delay time (or lag value) indicates the depth of the reflector. Analogue frequency modulated (sweep) and discrete phase modulated (Barker coded) excitations are the two widely researched types of modulated waveforms in TWR [ 25 , 27 , 28 , 29 , 30 , 31 , 32 , 33 ]. Recently, the current authors introduced a discrete frequency-phase modulated waveform which was the outcome of an optimization study.…”

Section: Introductionmentioning

confidence: 99%

Vibro-Thermal Wave Radar: Application of Barker Coded Amplitude Modulation for Enhanced Low-Power Vibrothermographic Inspection of Composites

et al. 2021

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This paper proposes an efficient non-destructive testing technique for composite materials. The proposed vibro-thermal wave radar (VTWR) technique couples the thermal wave radar imaging approach to low-power vibrothermography. The VTWR is implemented by means of a binary phase modulation of the vibrational excitation, using a 5 bit Barker coded waveform, followed by matched filtering of the thermal response. A 1D analytical formulation framework demonstrates the high depth resolvability and increased sensitivity of the VTWR. The obtained results reveal that the proposed VTWR technique outperforms the widely used classical lock-in vibrothermography. Furthermore, the VTWR technique is experimentally demonstrated on a 5.5 mm thick carbon fiber reinforced polymer coupon with barely visible impact damage. A local defect resonance frequency of a backside delamination is selected as the vibrational carrier frequency. This allows for implementing VTWR in the low-power regime (input power < 1 W). It is experimentally shown that the Barker coded amplitude modulation and the resultant pulse compression efficiency lead to an increased probing depth, and can fully resolve the deep backside delamination.

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“…It has the advantages of fast, large observation area, intuitive, accurate, noncontact, and other conventional detection technologies. It is suitable for field applications, online in-service testing, and so on [13][14][15]. Ultrasonic infrared thermal wave nondestructive detection technology uses the characteristics of ultrasound to transfer energy in the form of waves and inject it into the sample.…”

Section: Introductionmentioning

confidence: 99%

A Defect Detection Method for the Surface of Metal Materials Based on an Adaptive Ultrasound Pulse Excitation Device and Infrared Thermal Imaging Technology

Zhang

Cao

et al. 2021

Complexity

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Ultrasonic excitation has been widely used in the detection of microcracks on metal surfaces, but there are problems such as poor excitation effect of ultrasonic pulse, long time to reach the best excitation, and difficult to find microcracks. In this paper, an adaptive ultrasonic pulse excitation device and infrared thermal imaging technology have been combined, as well as their control method, to solve the problem. The adaptive ultrasonic pulse excitation device adds intelligent modules to realize automatic adjustment of detection parameters, which can quickly obtain reliable excitation; the multidegree-of-freedom base realizes the three-dimensional direction change of the ultrasonic gun to adapt to different excitation occasions. When the appropriate ultrasonic excitation makes microcracks in the resonance state, the microcracks can be frictionated, which produce heat rise with the temperature. Then, the microcrack defect can be detected by the infrared thermal instrument through the different surface temperatures with imaging recognition method. Our detection experiments of the titanium alloy plates and the aluminum alloy profiles of marine engineering show that the method can get reliable detection parameters in a short time and measure the crack length effectively. It can be used in many aspects such as crack detection in mechanical structures or complex equipment operating conditions and industrial production processes.

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Defect Detection Capabilities of Pulse Compression Based Infrared Non-Destructive Testing and Evaluation

Cited by 31 publications

References 29 publications

Coded Thermal Wave Imaging based Defect Detection in Composites using Neural Networks

Coded Thermal Wave Imaging based Defect Detection in Composites using Neural Networks

Vibro-Thermal Wave Radar: Application of Barker Coded Amplitude Modulation for Enhanced Low-Power Vibrothermographic Inspection of Composites

A Defect Detection Method for the Surface of Metal Materials Based on an Adaptive Ultrasound Pulse Excitation Device and Infrared Thermal Imaging Technology

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