• Composites Research
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• v.24 no.6
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• pp.49-55
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• 2011

The use of advanced composite materials in main structures of military and civil aircraft has been increased rapidly because of their considerable metals in high specific strength and stiffness. However, the mechanical properties of composite materials may severely degrade in the presence of damage. Especially, the high-velocity impact such as a hailstorm, and a small piece of tire or stone during high taxing, can cause considerable damage to the structures and sub-system in spite of a very small mass. However, it is not easy to detect the damage in composite plates using a single sensor or any conventional methods. In this paper, the PVDF sensors and AE sensors were used for monitoring high-velocity impact damage initiation and propagation in composite laminates. The WT(wavelet transform) is used to decompose the sensor signals. In the PVDF sensor and AE sensor signal analysis, amounts of high-frequency signals are increased when the impact energy is increased. PVDF sensor and AE sensor signal appeared similar results. This study shows how various sensing techniques can be used to characterize high-velocity impact damage of advanced composite laminates.

• Journal of the Korean Society for Nondestructive Testing
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• v.28 no.6
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• pp.469-476
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• 2008

Condition based maintenance(CBM) for the preventive diagnosis of important equipments related to safety or accident in power plant is essential by using the suitable methods based on actual power plant conditions. To improve the reliability and accuracy of the measured value at the minute leak situation, and also to monitor continuously internal leak condition of power plant valve, the development of a diagnosis and monitoring technique using multi-measuring method should be performed urgently. This study was conducted to estimate the feasibility of multi-measuring method using three different methods such as acoustic emission(AE) method, thermal image measurement and temperature difference$({\Delta}T)$ measurement that are applicable to internal leak diagnosis for the power plant valve. From the experimental results, it was suggested that the multi-measuring method could be an effective way to precisely diagnose and evaluate internal leak situation of valve.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.05a
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• pp.322-325
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• 2006

This study was conducted to develop the crack location technique for CFRP reinforced concrete beam using AE method. To experimentally prove the crack source location made of four reinforced concrete beams strengthened in shear with CFRP. The results compared the real cracking location with the source location has perceived by AE monitoring, before it is appeared the primary crack by visual observation. So, This study used by a basic data in constructing the system of the failure warning at application.

• Journal of the Korean Society for Nondestructive Testing
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• v.3 no.1
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• pp.12-18
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• 1983

This paper describes the procedures and results of an acoustic emission testing performed during hydrotest of spherical pressure vessel for propane storage. A computer based multi-channel real time monitoring and source location analysis AET-4900 system was used for AE testing. The vessel was extremely quiet throughout the entire test run and especially 6 to $14.5kg/cm^{2}$, it is normal operating pressure range. After exceeding $14.5kg/cm^{2}$, one of the 20 sections showed the most event in any one section 11 total but there were scattered at different locations. In order to confirm the events seen in horizontal weld line of that section, proof testing was performed with ultrasonics and radiography.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.131-137
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• 1994

Detection of grinding trouble occuring during the grinding process is classified into two types, i.e, based on the quantitative and qualitative knowledge. But, since the grinding operation is especially related with a large amount of functional parameters, it is actually defficult to cope with the grinding troubles occuring during process. Therefore, grinding trouble-shooting has difficulty in satisfying the requirement from the user. To cope with the grinding troubles occuring during the process, the application of neural network is on effective way. In this study, we identify the four parameters derived from the AE(Acoustic Emission) signals and present the grinding trouble-shooting system utilizing a back-propagation model of the neural network.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.11a
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• pp.245-248
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• 2006

The objective of this study is to take the first step in creating a user-friendly health monitoring system for recycled aggregate concrete structure using acoustic emission(AE). Each specimen was a cube, the edge of which was 150mm. For pull-out tests, a steel rebar, 13mm in diameter, was embedded in the center of each specimen and casting directions(i.e., vertical and horizontal) were considered in this paper. The AE parameters were analyzed for damage levels(i.e. internal cracking stage, pull-out stage) of all specimens. Results from this study show that event, duration versus amplitude of a signal, showed a clear difference for different loading stages depending upon the concrete casting directions.

• Proceedings of the Korea Contents Association Conference
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• 2012.05a
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• pp.251-252
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• 2012

모바일 환경에서의 모니터링 시스템은 경량 디바이스의 특징을 고려하여 설계 및 구현해야 한다. 이에 적합한 기법이 서비스 기반의 모바일 응용 기술이다. 대부분의 기능을 서버에 두고 클라이언트에서 호출하여 사용하는 구조이다. 이 논문에서는 안드로이드 기반의 스마트폰을 연동한 모니터링 시스템의 구조를 설계한다. 또한 서버와 클라이언트의 구현 내용을 기술한다. 서버는 JAVA로 구현하고, 클라이언트는 안드로이드를 이용하여 구현하는 내용을 제시한다.

• Smart Structures and Systems
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• v.26 no.2
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• pp.227-239
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• 2020

Despite proven effectiveness and accuracy in laboratories, the existing damage assessment based on guided ultrasonic waves (GUWs) or acoustic emission (AE) confronts challenges when extended to real-world structural health monitoring (SHM) for railway tracks. Central to the concerns are the extremely complex signal appearance due to highly dispersive and multimodal wave features, restriction on transducer installations, and severe contaminations of ambient noise. It remains a critical yet unsolved problem along with recent attempts to implement SHM in bourgeoning high-speed railway (HSR). By leveraging authors' continued endeavours, an SHM framework, based on actively generated diffuse ultrasonic waves (DUWs) and a benchmark-free condition contrast algorithm, has been developed and deployed via an all-in-one SHM system. Miniaturized lead zirconate titanate (PZT) wafers are utilized to generate and acquire DUWs in long-range railway tracks. Fatigue cracks in the tracks show unique contact behaviours under different conditions of external loads and further disturb DUW propagation. By contrast DUW propagation traits, fatigue cracks in railway tracks can be characterised quantitatively and the holistic health status of the tracks can be evaluated in a real-time manner. Compared with GUW- or AE-based methods, the DUW-driven inspection philosophy exhibits immunity to ambient noise and measurement uncertainty, less dependence on baseline signals, use of significantly reduced number of transducers, and high robustness in atrocious engineering conditions. Conformance tests are performed on HSR tracks, in which the evolution of fatigue damage is monitored continuously and quantitatively, demonstrating effectiveness, adaptability, reliability and robustness of DUW-driven SHM towards HSR applications.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.245-250
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• 2002

A successful on-line monitoring system for conventional machining operations has the potential to reduce cost, guarantee consistency of product quality, improve productivity and provide a safer environment for the operator. In fee-shape machining, typical signs of tool problems such as vibration, noise, chip flow characteristics and visual signs are almost unnoticeable without the use of special equipment. These characteristics increase the importance of automatic monitoring in fine-shape machining; however, sensing and interpretation of signals are more complex. In addition, the shafts of the micro-tools break before the typical extensive cutting edge of the tool gets damaged. In this study, the existence of a relationship between the characteristics of the cutting force and tool usage was investigated, and tool breakage detection algorithm was developed and the fellowing results are obtained. In data analysis, didn't use a relative error compare which mainly used in established experiment and investigated tool breakage detection algorithm in time domain which can detect AE and cutting force signals more effective and accurate.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.05a
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• pp.987-990
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• 2000

In modern manufacturing industry such as aerospace, vehicle and die/mold industry, the high hardness malarial which is remarkable in aspects of durability is effectively used. The high-speed and precision machining technology has been applied in these fields. In this study, efficient sensors in high-speed machining by observing similar tendency through comparing cutting force with AE signal, gap sensor signal and accelerometer signal are selected, and machinability of high-speed machining is experimentally evaluated. We performed a basic research for sensing system construction to monitor a machine tool and machining condition.