• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회B
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• pp.3383-3388
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• 2007

To compare the sensor performance of AE leak diagnosis system which can measure valve leak conditions, AE activities such as RMS voltage level, AE signal trend, leak rate degree according to AE database, FFT spectrum were measured on valve of the simulated test system for power plant. AE activities were recorded and analyzed from various operating conditions including different temperature, pressure difference, valve size and fluid using both piezoelectric acoustic emission sensor and Pb-Free acoustic emission sensor. The results of this study are utilized to select the type of sensors, the frequency band for filtering and thereby to improve the signal-to-noise ratio for diagnosis or monitoring of valves in operation. As the final result of application study above, portable type leak diagnosis system by AE was developed. The outcome of the study can be definitely applied as a means of the diagnosis or monitoring system for energy saving and prevention of accident for power plant valve.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.560-565
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• 2001

Recently, machining process monitoring technique based on AE(acoustic emission) signal is used widely and becomes very important technique in machining process for improving the efficiency and the confidence of the systems. In this study, we fabricated a cheap acoustic emission sensor and monitoring system and estimated the properties of them through comparing with commercial AE sensor systems. In addition, we evaluated the performance of the fabricated sensor in polishing process. Futhermore, we are scheduled to develop the multi-point polishing process monitoring system through fabrication of the more AE sensors and complement of the monitoring system.

• Smart Structures and Systems
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• 제13권1호
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• pp.155-171
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• 2014

Various monitoring techniques are now available for structural health monitoring and Acoustic Emission (AE) is one of them. One of the major advantages of the AE technique is its capability to locate active cracks in structural members. AE crack locating approaches are affected by the signal attenuation and dispersion of elastic waves due to inhomogeneity and geometry of reinforced concrete (RC) members. In this paper, a novel technique is described based on signal processing and sensor arrangement to process multisensory AE data generated by the onset and propagation of cracks and is validated with experimental results from an in-situ load test. Considering the sources of uncertainty in the AE crack location process, a methodology is proposed to capture and locate events generated by cracks. In particular, the relationship between AE events and load is analyzed, and the feasibility of using the AE technique to evaluate the cracking behavior of two RC slab strips during loading to failure is studied.

• Smart Structures and Systems
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• 제8권3호
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• pp.321-341
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• 2011

Acoustic emission (AE) monitoring was conducted for mortar specimens under three types of static loading patterns (cubic-splitting, direct-shear and pull-out). Each of the applied loading patterns was expected to produce a particular fracture process. Subsequently, the AEs generated by various fracture or damage processes carried specific information on temporal micro-crack behaviors of concrete for post analysis, which was represented in the form of detected AE signal characteristics. Among various available characteristics of acquired AE signals, frequency content was of great interest. In this study, cement-based piezoelectric sensor (as AE transducer) and home-programmed DEcLIN monitoring system were utilized for AE monitoring on mortar. The cement-based piezoelectric sensor demonstrated enhanced sensitivity and broad frequency domain response range after being embedded into mortar specimens. This broad band characteristic of cement-based piezoelectric sensor in frequency domain response benefited the analysis of frequency content of AE. Various evaluation methods were introduced and employed to clarify the variation characteristics of AE frequency content in each test. It was found that the variation behaviors of AE frequency content exhibited a close relationship with the applied loading processes during the tests.

• Smart Structures and Systems
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• 제6권3호
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• pp.197-209
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• 2010

The structural state of a bridge is currently examined by visual inspection or by wired sensor techniques, which are relatively expensive, vulnerable to inclement conditions, and time consuming to undertake. In contrast, wireless sensor networks are easy to deploy and flexible in application so that the network can adjust to the individual structure. Different sensing techniques have been used with such networks, but the acoustic emission technique has rarely been utilized. With the use of acoustic emission (AE) techniques it is possible to detect internal structural damage, from cracks propagating during the routine use of a structure, e.g. breakage of prestressing wires. To date, AE data analysis techniques are not appropriate for the requirements of a wireless network due to the very exact time synchronization needed between multiple sensors, and power consumption issues. To unleash the power of the acoustic emission technique on large, extended structures, recording and local analysis techniques need better algorithms to handle and reduce the immense amount of data generated. Preliminary results from utilizing a new concept called Acoustic Emission Array Processing to locally reduce data to information are presented. Results show that the azimuthal location of a seismic source can be successfully identified, using an array of six to eight poor-quality AE sensors arranged in a circular array approximately 200 mm in diameter. AE beamforming only requires very fine time synchronization of the sensors within a single array, relative timing between sensors of $1{\mu}s$ can easily be performed by a single Mote servicing the array. The method concentrates the essence of six to eight extended waveforms into a single value to be sent through the wireless network, resulting in power savings by avoiding extended radio transmission.

• 한국공작기계학회논문집
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• 제10권5호
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• pp.9-16
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• 2001

Turning experiments are conducted to investigate characteristics of acoustic emission due to wear of the coated tool. The AE signals are obtained with a sensor attached to tool holder side. Tool states are identified with scanning electron microscopy and optical microscopy. It is demonstrated that the AE signals provide reliable informations about the cutting processes and tool states. Moreover, tool wear can be detected successfully using the AE-RMS.

• 한국전기전자재료학회논문지
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• 제20권3호
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• pp.218-222
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• 2007

In this study, Acoustic emission(AE) sensors were fabricated using lead-free piezoelectric ceramics for prohibiting environmental pollution. Structure of AE sensors were designed as Langvin type air backing form. Here, the piezoelectic element was used as PZT(EC-65)(AE1) and NKN(AE2), respectively. The measured resonant frequency, the maximum sensitivity frequency and sensitivity of AE sensors were as follows ; 143 kHz, 29.4 kHz and 69.3 dB in AE1 and 179 kHz, 29.4 kHz and 66.3dB in AE2, respectively.

• 조명전기설비학회논문지
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• 제13권4호
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• pp.68-74
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• 1999

본 연구는 고분자재료에서 음향센서를 이용한 부분방전의 음향적 탐지를 행했다. 저밀도 폴리에틸렌에 대한 트리잉파괴 실험에서 음향센서로 얻어진 음향방출 특성의 시간순서대로 측정하여 통계처리를 행했다. 또한 5가지 특성량을 도입하고 $\psi$-AEA-n(위상-음향진폭-펄스수) 패턴을 분석한 결과, 보이드 시료의 AE평균개시진폭 $(\overline{AEA_{inc}})$과 AE 평균최대진폭$(\overline{AEA_{max}})$은 열화중기, AE펄스수, AE평균최대위상각$(\overline{\theta{max}})$은 열화말기를 진단하기 위해서 유용한 음향방출량임을 알 수 있다. 이들 음향방출량은 보이드 시료의 열화진단을 구별하는데 유용한 음향방출량임을 실험결과로부터 얻었다.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 춘계학술대회
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• pp.364-369
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• 2003

Crack propagation and AE characteristics of CFRP plain woven laminate composites are examined with acoustic sensor by AEDSP 32/16 board in PC system. AE signals are measured during the fracture behavior tests. The purpose of study is the estimation of the crack extension behavior effected between three kinds of fiber orientation for plain woven CFRP laminate composite and the relationship between AE characteristics and load-displacement curves and crack extension length.

• 한국정밀공학회지
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• 제16권5호통권98호
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• pp.186-193
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• 1999

Sensor feedback for process control is one of the essential elements is an automated deburring procedure. This paper presents the implementation of acoustic emission (AE), which has been developed as a feedback sensing technique for precision (mechanical) deburring, in a precision laser deburring process. AE signals were sampled for laser machining/deburring under various experimental conditions and analyzed using several signal-processing methods including AErms and spectral analysis. The results, such as the sensitivity of AE signals for different laser cutting depths, edge detection capability and the frequency analysis show a clear correlation between physical process parameters and the AE signals. A subsequent control strategy for deburring automation is also briefly discussed.