• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.6
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• pp.429-436
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• 2014

Most mechanical systems are now operating consistently and getting faster due to the development of automation systems. Peoples' dependence on machines have increased as when problems occur within the mechanical system, personal injury and production loss may come as a result, as most of the mechanical system's malfunctions are caused by the failure of the rotational bearing. What we need now is a maintenance system that can warn us when it detects abnormal conditions before significant damage occurs to the bearing. In this study, we have developed an acoustic emissions sensor that can figure if the bearing works under the normal condition. With this acoustic emissions sensor, we can inspect the bearing for defects by using the Heterodyne technique, which converts the ultrasound signal into audio, as a signal conditioning process.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.4
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• pp.68-74
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• 1999

Ths paper does acoustic detection of partial discharge using acoustic sensor in polymer. Time sequential rreasurement of acoustic emission characteristic obtained acoustic sensor deal with statistics process. and 5 characteristic quantities were introduced into this paper. Resulting fann analysis of $\psi$-AEA-n pattern (phase-acoustic emission amplitude-pulse number) and AE quantities ,it can know useful statistics quantities that AE average inception amplitude TEX>$(\overline{AEA_{inc}})$ and AE average maximum amplitude TEX>$(\overline{AEA_{max}})$ make diagnosis of the middle stage of deterioration, AE pulse number and AE average maximum phase $(\overline{\theta{max}})$ make diagnosis of the last stage of deterioration. it obtained that these AE quantities are useful for dias,mosis deterioration form experiment results.esults.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.20 no.3
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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.

• Journal of the Korea institute for structural maintenance and inspection
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• v.22 no.4
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• pp.121-125
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• 2018

This paper presents the assessment of 7-wire strand monitoring using acoustic emission technique for bridges. 7-wire strand is widely used construction materials to provide additional tensile force to bridges. PSC (PreStressed Concrete) bridge and cable-stayed bridge are representatives for such cases. However, as the bridge aging progresses recently, corrosion problems of strand are emerging. For this reason, various NDT (Non-Destructive Test) methods for cable inspection are being studied and applied to the field. One of the NDT methods, acoustic emission technique, is known as an effective technique to detect cable damage and breakage. In this study, to evaluate the applicability of acoustic emission technique to bridges, acoustic emission signals according to damage of the strand were acquired and analyzed by tensile test. Moreover, The optimal AE sensor type was selected for field application. As a result, it is considered that the acoustic emission technique will be able to detect corrosion breakage and signs of rupture.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.1
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• pp.78-83
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• 2005

Currently in Japan, the use of the small wind turbine is an upward trend. There are already many well established small wind turbine generators in use and their various failures have been reported. The most commonly sighted failure is blade damage. Thus the research purpose was set to develop a simple failure diagnostic system, where an Acoustic Emission (AE) signal was produced from the failure part of a blade which was measured by AE sensor. The failure diagnostic technique was thoroughly examined. Concurrently, the damage part of the blade was imitated, the AE signal was measured, and a FFT(Fast Fourier Transform) analysis was carried out, and was compared with the output characteristic. When one sheet of a blade was damaged 40mm or more, the level was computed at which failure could be diagnosed.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2198-2202
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• 2005

In this paper we have presented a condition monitoring method of check valve using neural network. The acoustic emission sensor was used to acquire the condition signals of check valve in direct vessel injection (DVI) test loop. The acquired sensor signal pass through a signal conditioning which are consisted of steps; rejection of background noise, amplification, analogue to digital conversion, extract of feature points. The extracted feature points which represent the condition of check valve was utilized input values of fault diagnosis algorithms using pre-learned neural network. The fault diagnosis algorithm proceeds fault detection, fault isolation and fault identification within limited ranges. The developed algorithm enables timely diagnosis of failure of check valve’s degradation and service aging so that maintenance and replacement could be preformed prior to loss of the safety function. The overall process has been experimented and the results are given to show its effectiveness.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.5
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• pp.657-673
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• 2019

A monitoring method based on acoustic emission (AE) sensor has been widely used to evaluate the damage of structures in underground rock. The acoustic emission signal generated from cracking in material is analyzed as various acoustic emission parameters in time and frequency domain. To investigate from initial crack generation to final failure of rock material, it is important to understand the characteristics of acoustic emission parameters according to the stress ratio and rock strength. In this study, uniaxial compression tests were performed using very strong and weak rock specimen in order to investigate the acoustic emission parameters when the failure of specimen occurred. In the results of experimental tests, the event, root-mean-square (RMS) voltage, amplitude, and absolute energy of very strong rock specimen were larger than those of the weak rock specimen with an increase of stress ratio. In addition, the acoustic emission parameters related in frequency were more affected by specification (e.g., operation and resonant frequency) of sensors than the stress ratio or rock strength. It is expected that this study may be meaningful for evaluating the damage of underground rock when the health monitoring based on the acoustic emission technique will be performed.

• Proceedings of the KIEE Conference
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• 2003.07c
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• pp.1659-1661
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• 2003

Recently, diagnostic techniques have been investigated to defect a partial discharge in high voltage electrical equipment. We have studied the characteristics of the acoustic partial discharge originating from the electrical defects in cubicle GIS(C-GIS). An acoustic emission(AE) sensor is used on the enclosure to detect partial discharge source because the sensor is sensitive to stress waves in its frequency range that may not be from a partial discharge source. AE signal is analyzed with phase-magnitude-frequency number(${\Phi}$-V-n) and pulse per second(PPS). Experience result has shown that the omitted acoustic signal has phase dependency and phase shift characteristic according to increase with applied voltage. These result will be helpful to the pattern recognition of the acoustic partial discharge in a C-GIS.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.101-104
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• 1995

A acoustic emission (AE) sensor has been used to monitor tool were during milling process. The relation between tool wear and AE RMS (Root mean Square) signal was investigated experimentally. A avaliable monitoring index for monitoring toolwear was newly extracted form AE RMS. And on-line monitoring program was developed. The proposed monitoring system has verified experimentally by roughing end milling titanium alloy with TIN coated HSS tool.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.366-368
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• 2006

This paper analyzes partial discharge pattern using Rogowski coil and acoustic emission sensor to power transformer. Therefore, the location of partial discharge and pattern is deduced as obtaining reliable data to establish core structure in transformer.