Detectability of Subsurface Defects in Polypropylene/Glass Fiber Composites Using Multiple Lock-In Frequency Modulated Algorithms

Recently, thermographic testing has been applied as a non-destructive evaluation technology for composite materials due to its remarkable advantages, such as its non-contact, non-destructive, and high-speed properties, it is harmless to the human body and easy to use, as well as having both qualitative and quantitative inspection performance. In this paper, multiple lock-in frequency modulated thermography is applied to investigate defects on the subsurface of polypropylene/glass fiber composites, and experimental investigations were conducted on various defect conditions for qualitative and quantitative estimation. A thin rectangle-shaped PP-GF plate of dimension 100 × 180 mm and a depth of 3 mm with various 24 defects conditions was considered as a test sample. The sample was stimulated at multiple modulation frequencies, viz., 1 Hz, 0.2 Hz, 0.1 Hz, 0.05 Hz, 0.03 Hz, and 0.01 Hz. For qualitative and quantitative evaluation, two representatives, multiple lock-in frequency modulated algorithms of lock-in thermography, HA and FFT, were applied to the raw data. Moreover, their detectability performance was compared in terms of phase contrast and signal-to-noise ratio

A Social Network Analysis of Tourist Movement Patterns in Blogs: Korean Backpackers in Europe

Given recent developments in information and communication technology, the number of individual tourists enjoying free travel without the advice of travel agencies is increasing. Therefore, such tourists can visit more tourist destinations and create more complex movement patterns than mass tourists. These tourist movement patterns are a key factor in understanding tourist behavior and they contain various information that is important for tourism marketers. In this vein, this study aims to investigate tourist movement patterns in Europe. We acquired 122 data points from posts on the NAVER blog, which is the most famous social media platform in Korea. These data were transformed into matrix data for social network analysis and analyzed for centrality. The results suggest that Korean backpackers in Europe tend to enter Europe through London and Paris. Venezia and Firenze are also key cities

Latest Advances in Common Signal Processing of Pulsed Thermography for Enhanced Detectability: A Review

Non-destructive testing (NDT) is a broad group of testing and analysis techniques used in science and industry to evaluate the properties of a material, structure, or system for characteristic defects and discontinuities without causing damage. Recently, infrared thermography is one of the most promising technologies as it can inspect a large area quickly using a non-contact and non-destructive method. Moreover, thermography testing has proved to be a valuable approach for non-destructive testing and evaluation of structural stability of materials. Pulsed thermography is one of the active thermography technologies that utilizes external energy heating. However, due to the non-uniform heating, lateral heat diffusion, environmental noise, and limited parameters of the thermal imaging system, there are some difficulties in detecting and characterizing defects. In order to improve this limitation, various signal processing techniques have been developed through many previous studies. This review presents the latest advances and exhaustive summary of representative signal processing techniques used in pulsed thermography according to physical principles and thermal excitation sources. First, the basic concept of infrared thermography non-destructive testing is introduced. Next, the principle of conventional pulsed thermography and signal processing technologies for non-destructive testing are reviewed. Then, we review advances and recent advances in each signal processing. Finally, the latest research trends are reviewed

Defect Recognition and Morphology Operation in Binary Images Using Line-Scanning-Based Induction Thermography

Active infrared thermography is an attractive and highly reliable technique used for the non-destructive evaluation of test objects. In this paper, defect detection on the subsurface of the STS304 metal specimen was performed by applying the line-scanning method to induction thermography. In general, the infrared camera and the specimen are fixed in induction thermography, but the line-scanning method can excite a uniform heat source because relative movement occurs. After that, the local heating area due to Joule’s heating effect was removed, and filtering was applied for the 1st de-noising. Threshold-value-based binarization processing using the Otsu algorithm was performed for clear defect object recognition. After performing the 2nd de-noising, automatic defect recognition was performed using a boundary tracking algorithm. As a result, the conditions due to the parameters of the scanning line for the thermal image were determined

Latest Advances in Common Signal Processing of Pulsed Thermography for Enhanced Detectability: A Review

Non-destructive testing (NDT) is a broad group of testing and analysis techniques used in science and industry to evaluate the properties of a material, structure, or system for characteristic defects and discontinuities without causing damage. Recently, infrared thermography is one of the most promising technologies as it can inspect a large area quickly using a non-contact and non-destructive method. Moreover, thermography testing has proved to be a valuable approach for non-destructive testing and evaluation of structural stability of materials. Pulsed thermography is one of the active thermography technologies that utilizes external energy heating. However, due to the non-uniform heating, lateral heat diffusion, environmental noise, and limited parameters of the thermal imaging system, there are some difficulties in detecting and characterizing defects. In order to improve this limitation, various signal processing techniques have been developed through many previous studies. This review presents the latest advances and exhaustive summary of representative signal processing techniques used in pulsed thermography according to physical principles and thermal excitation sources. First, the basic concept of infrared thermography non-destructive testing is introduced. Next, the principle of conventional pulsed thermography and signal processing technologies for non-destructive testing are reviewed. Then, we review advances and recent advances in each signal processing. Finally, the latest research trends are reviewed

Detectability of Subsurface Defects in Polypropylene/Glass Fiber Composites Using Multiple Lock-In Frequency Modulated Algorithms

Recently, thermographic testing has been applied as a non-destructive evaluation technology for composite materials due to its remarkable advantages, such as its non-contact, non-destructive, and high-speed properties, it is harmless to the human body and easy to use, as well as having both qualitative and quantitative inspection performance. In this paper, multiple lock-in frequency modulated thermography is applied to investigate defects on the subsurface of polypropylene/glass fiber composites, and experimental investigations were conducted on various defect conditions for qualitative and quantitative estimation. A thin rectangle-shaped PP-GF plate of dimension 100 × 180 mm and a depth of 3 mm with various 24 defects conditions was considered as a test sample. The sample was stimulated at multiple modulation frequencies, viz., 1 Hz, 0.2 Hz, 0.1 Hz, 0.05 Hz, 0.03 Hz, and 0.01 Hz. For qualitative and quantitative evaluation, two representatives, multiple lock-in frequency modulated algorithms of lock-in thermography, HA and FFT, were applied to the raw data. Moreover, their detectability performance was compared in terms of phase contrast and signal-to-noise ratio

Binarization Mechanism Evaluation for Water Ingress Detectability in Honeycomb Sandwich Structure Using Lock-In Thermography

The growing use of composite honeycomb structures in several industries including aircraft has demonstrated the need to develop effective and efficient non-destructive evaluation methods. In recent years, active thermography has attracted great interest as a reliable technology for non-destructive testing and evaluation of composite materials due to its advantages of non-contact, non-destructive, full-area coverage, high speed, qualitative, and quantitative testing. However, non-uniform heating, low spatial resolution, and ambient environmental noise make the detection and characterization of defects challenging. Therefore, in this study, lock-in thermography (LIT) was used to detect water ingress into an aircraft composite honeycomb sandwich structure, and the phase signals were binarized through the Otsu algorithm. A square composite honeycomb with dimensions of 210 mm × 210 mm along with 16 different defective areas of various sizes in groups filled with water by 25%, 50%, 75%, and 100% of the cell volume was considered. The sample was excited at multiple modulation frequencies (i.e., 1 Hz to 0.01 Hz). The results were compared in terms of phase contrast and CNR according to the modulation frequency. In addition, the detectability was analyzed by comparing the number of pixels of water ingress in the binarized image and the theoretical calculation

Automatic Thinning Detection through Image Segmentation Using Equivalent Array-Type Lamp-Based Lock-in Thermography

Among the non-destructive testing (NDT) techniques, infrared thermography (IRT) is an attractive and highly reliable technology that can measure the thermal response of a wide area in real-time. In this study, thinning defects in S275 specimens were detected using lock-in thermography (LIT). After acquiring phase and amplitude images using four-point signal processing, the optimal excitation frequency was calculated. After segmentation was performed on each defect area, binarization was performed using the Otsu algorithm. For automated detection, the boundary tracking algorithm was used. The number of pixels was calculated and the detectability using RMSE was evaluated. Clarification of defective objects using image segmentation detectability evaluation technique using RMSE was presented