• Journal of the Korean Society for Precision Engineering
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• v.27 no.6
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• pp.47-54
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• 2010

In this paper, the purpose is to study a method for detection of crack in clamped-clamped beams using the vibration characteristics. The natural frequency of beam is obtained by FEM and experiment. The governing differential equations of a Timoshenko beam are derived via Hamilton's principle. The two coupled governing differential equations are reduced to one fourth order ordinary differential equation in terms of the flexural displacement. The crack is assumed to be in the first mode of fracture and to be always opened during the vibrations. The differences between the actual and predicted crack positions and sizes are less than 9.8% and 28%, respectively.

• Journal of Animal Science and Technology
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• v.66 no.1
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• pp.31-56
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• 2024

Pig farming, a vital industry, necessitates proactive measures for early disease detection and crush symptom monitoring to ensure optimum pig health and safety. This review explores advanced thermal sensing technologies and computer vision-based thermal imaging techniques employed for pig disease and piglet crush symptom monitoring on pig farms. Infrared thermography (IRT) is a non-invasive and efficient technology for measuring pig body temperature, providing advantages such as non-destructive, long-distance, and high-sensitivity measurements. Unlike traditional methods, IRT offers a quick and labor-saving approach to acquiring physiological data impacted by environmental temperature, crucial for understanding pig body physiology and metabolism. IRT aids in early disease detection, respiratory health monitoring, and evaluating vaccination effectiveness. Challenges include body surface emissivity variations affecting measurement accuracy. Thermal imaging and deep learning algorithms are used for pig behavior recognition, with the dorsal plane effective for stress detection. Remote health monitoring through thermal imaging, deep learning, and wearable devices facilitates non-invasive assessment of pig health, minimizing medication use. Integration of advanced sensors, thermal imaging, and deep learning shows potential for disease detection and improvement in pig farming, but challenges and ethical considerations must be addressed for successful implementation. This review summarizes the state-of-the-art technologies used in the pig farming industry, including computer vision algorithms such as object detection, image segmentation, and deep learning techniques. It also discusses the benefits and limitations of IRT technology, providing an overview of the current research field. This study provides valuable insights for researchers and farmers regarding IRT application in pig production, highlighting notable approaches and the latest research findings in this field.

• Steel and Composite Structures
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• v.46 no.3
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• pp.319-334
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• 2023

Localizing damages is an essential task to monitor the health of the structures since they may not be able to operate anymore. Among the damage detection techniques, non-destructive methods are considerably more preferred than destructive methods since damage can be located without affecting the structural integrity. However, these methods have several drawbacks in terms of detecting abilities, time consumption, cost, and hardware or software requirements. Employing artificial intelligence techniques could overcome such issues and could provide a powerful damage detection model if the technique is utilized correctly. In this study, the crack localization in flat and folded plate structures has been conducted by employing a Backpropagated Artificial Neural Network (BPANN). For this purpose, cracks with 18 different dimensions in thin, flat, and folded structures having 15⁰, 30⁰, 45⁰, and 60⁰ folding angle have been modeled and subjected to free vibration analysis by employing the Classical Plate Theory with Finite Element Method. A Four-nodded quadrilateral element having six degrees of freedom has been considered to represent those structures mathematically. The first ten natural frequencies have been obtained regarding healthy and cracked structures. To localize the crack, the ratios of the frequencies of the cracked flat and folded structures to those of healthy ones have been taken into account. Those ratios have been given to BPANN as the input variables, while the crack locations have been considered as the output variables. A total of 500 crack locations have been regarded within the dataset obtained from the results of the free vibration analysis. To build the best intelligent model, a feature search has been conducted for BAPNN regarding activation function, the number of hidden layers, and the number of hidden neurons. Regarding the analysis results, it is concluded that the BPANN is able to localize the cracks with an average accuracy of 95.12%.

• Structural Engineering and Mechanics
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• v.80 no.5
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• pp.563-583
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• 2021

Composite materials, composed of multiple constituent materials with dissimilar properties, are actively adopted in a wide range of industrial sectors due to their remarkable strength-to-weight and stiffness-to-weight ratio. Nevertheless, the failure mechanism of composite materials is highly complicated due to their sophisticated microstructure, making it much harder to predict their residual material lives in real life applications. A promising solution for this safety issue is structural damage detection. In the present paper, damage detection of composite material via electrical resistance-based technique and infrared thermography is reviewed. The operating principles of the two damage detection methodologies are introduced, and some research advances of each techniques are covered. The advancement of IR thermography-based non-destructive technique (NDT) including optical thermography, laser thermography and eddy current thermography will be reported, as well as the electrical impedance tomography (EIT) which is a technology increasingly drawing attentions in the field of electrical resistance-based damage detection. A brief comparison of the two methodologies based on each of their strengths and limitations is carried out, and a recent research update regarding the coupling of the two techniques for improved damage detection in composite materials will be discussed.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.11 no.3
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• pp.229-234
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• 2001

The EDXRF(Energy Dispersive X-ray Fluorescence Spectrometer) technique was applied to the determination of heavy metals in welding fume. The EDXRF method designed in this study was a non-destructive analysis method. Samples were analyzed directly by EDXRF without any pre-treatment such as digestion and dilution. The samples used to evaluate this method were laboratory samples exposed in a chamber connected with a welding fume generator. The samples were first analyzed using a non-destructive EDXRF method. The samples subsequently were analyzed using AAS method to verify accuray of the EDXRF method. The purpose of this study was to evaluate the possibility of the non-destructive analysis of heavy metals in welding fume by EDXRF. The results of this study were as follow: 1.When the samples were collected under the open-face sampling condition, a surface distribution of welding fume particles on sample filters was uniform, which made non-destructive analysis possible. 2. The method was statistically evaluated according to the NIOSH(National Institute for Occupational Safety and Health) and HSE(Health and Safety Executive) method. 3. The overall precision of the EDXRF method Was calculated at 3.45 % for Cr, 2.57 % for Fe and 3.78 % for Mn as relative standard deviation(RSD), respectively. The limits of detection were calculated at $0.46{\mu}g$/sample for Cr, $0.20{\mu}g$/sample for Fe and $1.14{\mu}g$/sample for Mn, respectively. 4. A comparison between the results of Cr, Fe, Mn analyzed by EDXRF and AAS was made in order to assess the accuracy of EDXRF method. The correlation coefficient between the results of EDXRF and AAS was 0.9985 for Cr, 0.9995 for Fe and 0.9982 for Mn, respectively. The overall uncertainty was determined to be ${\pm}12.31%$, 8.64 % and 11.91 % for Cr, Fe and Mn, respectively. In conclusion, this study showed that Cr, Fe, Mn in welding fume were successfully analyzed by the EDXRF without any sample pre-treatment such as digestion and dilution and a good correlation between the results of EDXRF and AAS was obtained. It was thus possible to use the EDXRF technique as an analysis method of working environment samples. The EDXRF method was an efficient method in a non-destructive analysis of heavy metals in welding fume.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.2
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• pp.153-169
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• 2018

A submarine has a pressure hull that can withstand high hydraulic pressure and therefore, requires the use of highly advanced shipbuilding technology. When producing a pressure hull, periodic inspection, repair, and maintenance are conducted to maintain its soundness. Of the maintenance methods, Non-Destructive Testing (NDT) is the most effective, because it does not damage the target but sustains its original form and function while inspecting internal and external defects. The NDT process to detect defects in the welded parts of the submarine is applied through Magnetic particle Testing (MT) to detect surface defects and Ultrasonic Testing (UT) and Radiography Testing (RT) to detect internal defects. In comparison with RT, UT encounters difficulties in distinguishing the types of defects, can yield different results depending on the skills of the inspector, and stores no inspection record. At the same time, the use of RT gives rise to issues related to worker safety due to radiation exposure. RT is also difficult to apply from the perspectives of the manufacturing of the submarine and economic feasibility. Therefore, in this study, the Phased Array Ultrasonic Testing (PAUT) method was applied to propose an inspection method that can address the above disadvantages by designing a probe to enhance the precision of detection of hull defects and the reliability of calculations of defect size.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.1
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• pp.41-48
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• 2010

Non-contacting, laser-based resonant ultrasound spectroscopy (L-RUS) was applied to characterize the microstructure of a material. L-RUS is widely used by virtue of its many features. Firstly, L-RUS can be used to measure mechanical damping which related to the microstructural variations (grain boundary, grain size, precipitation, defects, dislocations etc). Secondly, L-RUS technology can be applied to various areas, such as the noncontact and nondestructive quality test for precision components as well as noncontact and nondestructive materials characterization. In addition, L-RUS technology can measure the whole field resonant frequency at once. In this paper, we evaluated material characteristics such as resonant frequency, nonlinear propagation characteristic through the development of Laser-Based Resonant Ultrasound spectroscopy (Laser-RUS) System for the detection of Micro Crack in Materials.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.3
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• pp.36-43
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• 2016

Carbon fiber-reinforced silicon carbide (Cf-SiC) and SiC / SiC composites have high thermal conductivity, and excellent corrosion and wear resistance, a low coefficient for thermal expansion and are lightweight. This is why they are commonly used in parts of the aerospace industry to develop an aircraft thrust deflector, jet vane, combustion chamber, elevens, body flap, and a shingle. So, understanding how this state-of-the-art Cf-SiC affects both internal and external crack detection and determining issues during the manufacturing process of composite materials, should be evaluated according to valuation techniques in the external environment. In this paper, we apply a non-contact air ultrasonic technique of non-destructive testing techniques to perform a study on internal defect detection identification and assessment of carbon-fiber reinforced silicon carbide composites to perform basic research and applied research.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.2
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• pp.68-71
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• 2006

Active thermography has been used for several years in the field of remote non-destructive testing. It provides thermal images for remote detection and imaging of damages. Also, it is based on propagation and reflection of thermal waves which are launched from the surface into the inspected component by absorption of modulated radiation. For energy deposition, it use external heat sources (e.g., halogen lamp or convective heating) or internal heat generation (e.g., microwaves, eddy current, or elastic wave). Among the external heat sources, the ultrasound is generally used for energy deposition because of defect selective heating up. The heat source generating a thermal wave is provided by the defect itself due to the attenuation of amplitude modulated ultrasound. A defect causes locally enhanced losses and consequently selective heating up. Therefore amplitude modulation of the injected ultrasonic wave turns a defect into a thermal wave transmitter whose signal is detected at the surface by thermal infrared camera. This way ultrasound thermography(UT) allows for selective defect detection which enhances the probability of defect detection in the presence of complicated intact structures. In this paper the applicability of UT for fast defect detection is described. Examples are presented showing the detection of defects in PCB material. Measurements are performed on various kinds of typical defects in PCB materials (both Cu metal and non-metal epoxy). The obtained thermal image reveals area of defect in row of thick epoxy material and PCB.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.3
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• pp.185-192
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• 2015

Since real-time monitoring systems, such as early fault detection, have been very important, an infrared thermography technique was proposed as a new diagnosis method. This study focused on damage detection and temperature characteristic analysis of ball bearings using the non-destructive, infrared thermography method. In this paper, for the reliability assessment, infrared experimental data were compared with finite element analysis (FEA) results from ANSYS. In this investigation, the temperature characteristics of ball bearing were analyzed under various loading conditions. Finally, it was confirmed that the infrared thermography technique was useful for the real-time detection of damage to bearings.