• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.688-706
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• 2024

Austenitic stainless steels (ASS) are extensively employed in various sectors such as nuclear, power, petrochemical, oil and gas because of their excellent structural strength and resistance to corrosion. SS304 and SS316 are the predominant choices for piping, pressure vessels, heat exchangers, nuclear reactor core components and support structures, but they are susceptible to stress corrosion cracking (SCC) in chloride-rich environments. Over the course of several decades, extensive research efforts have been directed towards evaluating SCC using diverse methodologies and models, albeit some uncertainties persist regarding the precise progression of cracks. This review paper focuses on the application of Acoustic Emission Technique (AET) for assessing SCC damage mechanism by monitoring the dynamic acoustic emissions or inelastic stress waves generated during the initiation and propagation of cracks. AET serves as a valuable non-destructive technique (NDT) for in-service evaluation of the structural integrity within operational conditions and early detection of critical flaws. By leveraging the time domain and time-frequency domain techniques, various Acoustic Emission (AE) parameters can be characterized and correlated with the multi-stage crack damage phenomena. Further theories of the SCC mechanisms are elucidated, with a focus on both the dissolution-based and cleavage-based damage models. Through the comprehensive insights provided here, this review stands to contribute to an enhanced understanding of SCC damage in stainless steels and the potential AET application in nuclear industry.

• Journal of the Korean Society of Visualization
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• v.22 no.2
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• pp.35-43
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• 2024

Microparticle separation has demonstrated significant potential for biological, chemical, and medical applications. We introduce a surface acoustic wave (SAW)-based microfluidic device for separation of elastic and rigid microspheres based on their property and size. By tuning the SAWs to match the resonant frequencies of certain microspheres, those particles could be selectively separated from the other microspheres. When microspheres are exposed to an acoustic field, they experience the SAW-induced acoustic radiation force (ARF), whose magnitude is dependent on the microparticle size and properties. We modeled the SAW-induced ARF based on elastic sphere theory and conducted a series of experiments to separate elastic and rigid microspheres. We further utilized the acoustofluidic method for the separation of Thalassiosira Eccentrica microalgae based on the differences in their sizes with purity exceeding 90%. We anticipate that our technique will open up new possibilities for sample preparation, detection, and diagnosis in various emerging biological and medical analyses.

• Journal of Ocean Engineering and Technology
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• v.20 no.1 s.68
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• pp.69-76
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• 2006

The design of efficient search path to maximize the Cumulative Detection Probability(CDP) is mainly dependent on experience and intuition when searcher detect the target using SONAR in the ocean. Recently with the advance of modeling and simulation method, it has been possible to access the optimization problems more systematically. In this paper, a method for the optimal search path calculation is developed based on the combination of the genetic algorithm and the calculation algorithm for detection range. We consider the discrete system for search path, space, and time, and use the movement direction of the SONAR for the gene of the genetic algorithm. The developed algorithm, OASPP(Optimal Acoustic Search Path Planning), is shown to be effective, via a simulation, finding the optimal search path for the case when the intuitive solution exists. Also, OASPP is compared with other algorithms for the measure of efficiency to maximize CDP.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.5
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• pp.289-297
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• 2003

The performance of a bimodal system is affected by the accuracy of the endpoint detection from the input signal as well as the performance of the speech recognition or lipreading system. In this paper, we propose the endpoint detection method which detects the endpoints from the audio and video signal respectively and utilizes the signal to-noise ratio (SNR) estimated from the input audio signal to select the reliable endpoints to the acoustic noise. In other words, the endpoints are detected from the audio signal under the high SNR and from the video signal under the low SNR. Experimental results show that the bimodal system using the proposed endpoint detector achieves satisfactory recognition rates, especially when the acoustic environment is quite noisy.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.2
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• pp.185-190
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• 2010

Condition monitoring(CM) is a method based on non-destructive test(NDT). So, recently many kind of NDT were applied for CM. Acoustic emission(AE) is widely used for the early detection of faults in rotating machinery in these days because of high sensitivity than common accelerometers and detectable low energy vibration signals. And crack is considered one of severe fault in the rotating machine. Therefore, in this paper, study on early detection using AE has been accomplished for the crack of the low-speed shaft. There is a seeded initial crack on the shaft then the AE signal had been measured with low-speed rotation as the applied load condition. The signal detected from crack in rotating machine was detected by the AE transducer then the trend of crack growth had found out by using some of feature values such as peak value, skewness, kurtosis, crest factor, frequency center value(FC), variance frequency value(VF) and so on.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1142-1148
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• 2006

Actually, a present traffic accident detection system is subsisting limitation of accurate distinction under the crowded condition at intersection because the system depend upon mainly the image information at intersection and digital image processing techniques nearly all. To complement this insufficiency, this article aims to estimate the level of present technology and a realistic possibility by analyzing the acoustic characteristic of crash sound that we have to investigate fur improvement of traffic accident detection rate at intersection. The skid sound of traffic accident was showed the special pattern at 1[KHz])$\sim$3[KHz] bandwidth when vehicles are almost never operated in and around intersection. Also, the frequency bandwidth of vehicle crash sound was showed sound pressure difference over 30[dB] higher than when there is no occurrence of traffic accident below 500[Hz].

• Journal of the Korean Society for Nondestructive Testing
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• v.24 no.5
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• pp.465-475
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• 2004

This paper is the first part of the study on the development of a smart active layer (SAL) sensor, which consists of two parts. In this first part, the theory and concept of the SAL sensor is investigated, which is designed for the detection of elastic waves caused by internal cracks and damages in structures. For the development SAL sensor, (i) the basic theory of elastic waves was studied, (ii) the feasible study of the SAL as an elastic waves detection sensor using the finite element analysis (FEA) with respect to a piezoceramic disc was performed. (iii) the comparison of performances between some piezoceramic sensors and a commercial acoustic emission (AE) sensor was accomplished to ensure the applicability by the experimental means, such as a pencil lead break test. Also, the conceptional study for the SAL sensor, which can be utilized for the effective detection and locating of defects by the arrangement of regularly distributed sensors, was discussed.

• Journal of the Korea Society of Computer and Information
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• v.19 no.4
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• pp.55-62
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• 2014

This paper proposes a fault detection method utilizing converted images of acoustic emission signals and texture analysis for identifying bearing's multi-faults which frequently occur in an induction motor. The proposed method analyzes three texture features from the converted images of multi-faults: multi-faults image's entropy, homogeneity, and energy. These extracted features are then used as inputs of a fuzzy-ARTMAP to identify each multi-fault including outer-inner, inner-roller, and outer-roller. The experimental results using ten times trials indicate that the proposed method achieves 100% accuracy in the fault classification.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.1
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• pp.45-52
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• 2016

Blast furnaces are crucial equipment for steel production. A typical furnace risks unexpected accidents caused by contraction and expansion of the walls under an environment of high temperature and pressure. In this study, an acoustic emission (AE) monitoring system was tested for evaluating the large-scale structural health of a blast furnace. Based on the growth of shell cracks with the emission of high energy levels, severe damage can be detected by monitoring increases in the AE energy parameter. Using this monitoring system, steel mill operators can establish a maintenance period, in which actual shell cracks can be verified by cross-checking the UT. From this study, we expect that AE systems permit early fault detection for structural health monitoring by establishing evaluation criteria based on the severity of shell cracking.

• Tunnel and Underground Space
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• v.10 no.1
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• pp.59-69
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• 2000

Acoustic emission is n burst of microseismic waves generated by microscopic failure due to deformation in materials. The study on the detection of initiation and propagation of microcracks from acoustic emission measurement is very important for the evaluation of the stability of underground rock structures by the nondestructive letting method. In this study, acoustic emission was measured under uniaxial stiffness loading test used to obtain the complete stress-strain curves of marble and concrete used as reinforced materials of rock structures. The analysis of acoustic emission parameters and source location were performed to discuss the characteristics of the deformation and failure behavior of rock and concrete. And acoustic emission was measured under cyclic loading test to verify the Kaiser effect associated with the damage of materials, in situ stress of rock, and stress history of concrete structure.