• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.371-376
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• 1994

This paper presents an on-line modeling method approach for the machine condition. the machine condition is continuously monitored with a sensor such as, a vibration, a current, an acoustic emission (AE) sensor. In this study, neural network modeling by radial basis function is designed for analysis a prediction error. An on-line learning algorithm is designed using the RLS(recursive least square) estimation and the existing clustering method of Kohonen neural network. Experimental results show that the proposed RBNN modeling is suitable for predicting simulated data.

• 제어로봇시스템학회논문지
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• 제11권8호
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• pp.662-668
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• 2005

This paper presents a realization of check valve condition monitoring system based on fault diagnosis algorithm and Fieldbus communication. We first acquired AE(acoustic emission) sensor data at the check valve test loop, extract fault features through the teamed neural network, and send the processed data to a remote site. The overall system has been implemented and experimented results are given to show its effectiveness.

• 조명전기설비학회논문지
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• 제18권2호
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• pp.36-43
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• 2004

본 연구에서는 운전중인 직류전동기의 브러시를 임의로 회전하여 브러시와 정류자편에 불꽃을 발생시켰을 때, 초음파센서와 AE센서를 이용하여 각각의 기계적 노이즈 신호를 검출하였으며, 이를 주파수 스펙트럼으로 분석하였다. 또한 직류전동기의 브러시가 중성축에 정상적으로 위치하여 운전하고 있을 때, 초음파센서와 AE센서를 이용하여 각각의 자기적 노이즈 신호를 검출하였으며, 이를 주파수 스펙트럼으로 분석하였다. 그리고 직류전동기의 브러시를 임의로 회전한 경우의 기계적 노이즈 신호 및 브러시가 중성축에 위치한 경우의 자기적 노이즈 신호를 비교ㆍ분석하였다. 실험 결과, 운전중인 직류전동기의 브러시를 회전방향으로 임의로 회전하여 검출한 초음파의 기계적 노이즈 신호는 브러시가 중성축에 정상적으로 위치하여 검출한 초음파의 자기적 노이즈 신호보다 대략 2.5∼3.0배 증가되었다. 또한 운전중인 직류전동기의 브러시를 회전방향으로 임의로 회전하여 불꽃을 발생시켰을 때, AE의 기계적 노이즈 신호를 검출하여 주파수 스펙트럼으로 분석한 결과 주된 주파수 영역이 대략 1.3[MHz]∼l.5[MHz]인 것으로 나타났다

• 한국생산제조학회지
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• 제9권1호
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• pp.38-44
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• 2000

The background of this study lies in he investigation of the formation mechanism of ductile mode(nkanometer-size) chips of brittle materials such as fine ceramics glass and silicon. As the first step to achieve this purpose this paper intends to observe the micro-deformation behavior of these materials in sub${\mu}{\textrm}{m}$ depth indentation tests using a diamond indentor. In this study it was developed Ultra-Micro Indentation. Device using the PZT actuator. Experimentally by using the Ultra-Micro Indentation device the micro fracture behavior of the silicon wafer was investigated. It was possible that ductile-brittle transition point in ultimate surface of brittle material can be detected by adding an acoustic emission sensor system to the Ultra-Micro Indentation appartus.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1993년도 춘계학술대회 논문집
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• pp.300-304
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• 1993

Chip formation control is an important problem in the automation of manufacturing process, since the continuous chip can cause catastrophic failures of the tooling and entangle the workpiece causing damage. However, it is impossible to predict chip form correctly due to the complex nature of cutting process. In order to detect the chip form for unmanned manufacturing, a new identification method is proposed. The feasibility of using acoustic emission signals from the sensing plate for identification of chip form is investigated. Experiments were conducted under the various cutting conditions. When the acoustic emission sensor is attached to the sensing plate, it turns out that the moving averaged AE signals correlated well with the collision of segmented chips with the plate. The sensitivity of moving averaged AE signals to chip congestions due to continuous chip formation is illustrated as well.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 춘계학술대회논문집
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• pp.324-328
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• 2007

Vibration monitoring of rolling element bearings is probably the most established diagnostic technique for rotating machinery. Acoustic Emission (AE) Analysis is an extremely powerful technology that can be used within a wide range of applications of non destructive testing. Therefor, this paper investigates the detection methods using AE for rolling element bearings about low-speed. Two transducers, the accelerometer and acoustic emission sensor, are used to acquire data and the results are compared for the capacity of early fault detection.

• 한국생산제조학회지
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• 제8권6호
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• pp.71-77
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• 1999

Monitoring of Cutting tool wear is a critical issue in automated machining system and has been extensively studied for many years. An austempered ductile iron(ADI) exhibits the excellent mechanical properties and the wear resistance. ADI has generally the poor machinability due to the characteristic. This paper presents the in-process detection of flank wear of cutting tools using the acoustic emission sensor and the digital oscilloscope. The amplitude level of AE signal(AErms) is mainly affected by cutting speed and it is proportional to cutting speed. There have been the relationship of direct proportion between the amplitude level of AE signals and the flank wear width of cutting tool. The flank wear with corresponding to the tool life is successfully detected with the monitor-ing system used in this study.

• 한국정밀공학회지
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• 제22권10호
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• pp.90-98
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• 2005

A monitoring system is necessary to make the polishing process more reliable in order to ensure the high quality and performance of the final products. Generally, AE (Acoustic Emission) is known to be closely related to the material removal rate (MRR). As the surface becomes rougher, the MRR and AE increase. Therefore, the surface roughness can be indirectly estimated using the AE signal measured during the polishing. In this study, an AE sensor-based monitoring system was fabricated to detect the very small AE signal resulting from the friction between a tool and a workpiece during polishing. The performance of this monitoring system was estimated according to polishing conditions, the relation between the level of the AE RMS and the surface roughness during the polishing was investigated.

• 한국생산제조학회지
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• 제20권3호
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• pp.304-309
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• 2011

A monitoring system for magnetic abrasive polishing process is necessary to ensure the polishing products the high quality and integrity. Acoustic emission (AE) signal is known to reflect the material removal phenomena in other machining processes. In a case of the magnetic abrasive polishing of non-magnetic materials, application of AE method is very difficult because of lower machining force on the surface of workpiece and the level of AE signal is extremely lower. In this study, AE sensor-based monitoring system is applied to the magnetic abrasive polishing. The relation between the level of the AE RMS and the surface roughness during the magnetic abrasive polishing of magnesium alloy steel is investigated.

• 대한토목학회논문집
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• 제33권2호
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• pp.433-442
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• 2013

이 논문에는 길이가 50m인 프리스트레스트 콘크리트 박스거더를 이용한 1차원, 2차원 음원위치 산정을 위한 실험연구 내용을 수록하였다. 슈미트 햄머를 이용하여 콘크리트 표면에 타격하여 충격음파를 발생시켰으며 PSC박스거더 복부판에 평균 9.34m 간격으로 부착한 AE센서를 통해 충격 음파를 감지하였다. 공용중인 PSC박스거더 교량에 발생할 수 있는 잡음을 고려하여 음파의 도달시간을 음파의 세기가 0Volt, 0.5Volt, 그리고 1.0Volt일 때를 기준으로 산정하였다. 음파의 도달시간들에 대한 측정결과를 토대로 충격음파의 음원위치를 최소제곱법을 이용해 산정하였다. 실험결과를 토대로 2차원 음원위치 산정시 오차를 최소화하기 위해 필요한 음향센서 간격과 음향센서의 네트워크에 대해 고찰하였다.