• Title/Summary/Keyword: AE monitoring

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Interfacial fracture analysis of human tooth/composite resin restoration using acoustic emission (음향방출법을 이용한 치아/복합레진 수복재의 계면부 파괴해석)

  • Gu, Ja-Uk;Choi, Nak-Sam;Arakawa, Kazuo
    • Composites Research
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    • v.22 no.6
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    • pp.45-51
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    • 2009
  • The marginal integrity at the composite resin-tooth interface has been analyzed in real time through acoustic emission (AE) monitoring during the polymerization shrinkage of composite resin subjected to the light exposure. It was found that AE signals were generated by the polymerization shrinkage. Most AE hit events showed a blast type signal having the principal frequency band of 100-200kHz. Bad bonding states were indicated by many hit events in the initial curing period of 1 minute with high contraction rate. The quantity of hit events for the human molar dentin specimen was much less than that for the steel ring specimen but more than that for the PMMA ring specimen. The better the bonding state, the less the AE hit events. The AE characteristics were related with the tensile crack propagation occurring in the adhesive region between the composite resin and the ring substrate as well as the compressive behavior of the ring substrate, which could be used for a nondestructive characterization of the marginal disintegrative fracture of the dental restoration.

Sensor Fusion and Neural Network Analysis for Drill-Wear Monitoring (센서퓨젼 기반의 인공신경망을 이용한 드릴 마모 모니터링)

  • Prasopchaichana, Kritsada;Kwon, Oh-Yang
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.17 no.1
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    • pp.77-85
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    • 2008
  • The objective of the study is to construct a sensor fusion system for tool-condition monitoring (TCM) that will lead to a more efficient and economical drill usage. Drill-wear monitoring has an important attribute in the automatic machining processes as it can help preventing the damage of tools and workpieces, and optimizing the drill usage. In this study, we present the architectures of a multi-layer feed-forward neural network with Levenberg-Marquardt training algorithm based on sensor fusion for the monitoring of drill-wear condition. The input features to the neural networks were extracted from AE, vibration and current signals using the wavelet packet transform (WPT) analysis. Training and testing were performed at a moderate range of cutting conditions in the dry drilling of steel plates. The results show good performance in drill- wear monitoring by the proposed method of sensor fusion and neural network analysis.

Acoustic Emission Monitoring of Incipient Failure in Journal Bearing Part II : Intervention of Foreign Particles in Lubrication (음향방출을 이용한 저어널 베어링의 조기파손감지(II) - 윤활유 이물질 혼입의 영향 및 감시 -)

  • Yoon, Dong-Jin;Kwon, Oh-Yang;Jung, Min-Hwa;Kim, Kyung-Woong
    • Journal of the Korean Society for Nondestructive Testing
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    • v.14 no.2
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    • pp.122-131
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    • 1994
  • Journal bearings in the rotating machineries are vulnerable to the contamination or the insufficient supply of lubricating oil, which is likely to be the cause of unexpected shutdown or malfunction of these systems. Various destructive and nondestructive testing methods had been used for the reduction of maintenance cost and the operational safety problems due to the accidents related to bearing damages. In this experimental approach, acoustic emission monitoring is employed to the detection of incipient failure caused by intervention of foreign particles most probable in the journal bearing systems. Experimental schedules for the intervention of foreign particles was composed to be more quantitative and systematic than last study in consideration of minimum oil film thickness and particle size. The experiment was conducted under such designed conditions as inserting alumina particles to the lubrication layer in the simulated journal bearing system. Several parameters such as AE rms level, waveform, AE energy distribution and other AE event parameters are used for analysis and characterization of damage source. The results showed that the history of damage was well correlated with the changes of AE rms level and the type of damage source signal can be verified using other informations such as waveform, distributions of AE parameters etc.

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Nondestructive Evaluation of Temporarily Repaired CFRP Laminates Subjected to Delaminations due to Localized Heating and Cyclic Loading Combined

  • Han, Tae-Young;Kwon, Oh-Yang
    • Journal of the Korean Society for Nondestructive Testing
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    • v.27 no.3
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    • pp.268-279
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    • 2007
  • The reliability of cold-bonding repair technique of carbon-fiber reinforced plastics (CFRP) laminates, often used as a temporary repair for the airplane maintenance, has been evaluated during cyclic loading and localized heating by nondestructive methods. Major concern was given to the evolution of damage after repair in the form of delaminations due to localized heating and cyclic loading combined. An area of interest both on the specimen repaired by cold-bonding and the specimen without repair where delaminations were induced by localized heating and cyclic loading was monitored by acoustic emission (AE) testing and further examined by pitch-catch low-frequency bond testing, and pulse-echo high-frequency ultrasonic testing. The results showed that the reliability of cold-bonding repair would be significantly reduced by the localized heating and cyclic loading combined rather than by the cyclic loading only. AE monitoring appeared to be an effective and reliable tool to monitor the integrity of temporarily repaired CFRP laminates in terms of the structural health monitoring (SHM) philosophy.

A Study on the Monitoring of Pressure Vessel Safety during Hydrotest by Acoustic Emission (AE에 의한 압력용기의 안전성평가에 관한 연구)

  • Lee, J.S.;Cho, K.S.;Choi, J.M.;Chang, H.K.;Oh, S.K.
    • Journal of the Korean Society for Nondestructive Testing
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    • v.8 no.1
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    • pp.12-21
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    • 1988
  • The behaviour of pressure vessel made of SS41 steel was investigated during hydrotest. AE tests were carried out for the vessels in as-manufactured, V-notched and weld-cracked state using microcomputer-based AE instrumentation. The following results were obtained: 1) In the case of source location using cylindrical program, to minimize the error of source location, the difference of max. Delta T values measured from each sensor should be kept as small as possible. 2) When crack grew, AE event rate increased continuously but AE event from the inclusions occurred intermittently, so by analyzing event rate, the source of AE could be derived. 3) From the spot welding part of supporter, many events with low energy occurred independent of Kaiser effect, which could be confirmed by analyzing energy parameter. 4) The b-value from the tensile specimen of was lower than that from normal specimen and the b-value from crack propagation was lower than that from deformation, so by analyzing peak amplitude distribution, the source mechanism could be derived from the b-value.

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Nondestructive Evaluation of Damage Modes in a Bending Piezoelectric Composite Actuator Based on Waveform and Frequency Analyses (파형 및 주파수해석에 근거한 굽힘 압전 복합재료 작동기 손상모드의 비파괴적 평가)

  • Woo, Sung-Choong;Goo, Nam-Seo
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.31 no.8
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    • pp.870-879
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    • 2007
  • In this study, various damage modes in bending unimorph piezoelectric composite actuators with a thin sandwiched PZT plate during bending fracture tests have been evaluated by monitoring acoustic emission (AE) signals in terms of waveform and peak frequency as well as AE parameters. Three kinds of actuator specimens consisting of woven fabric fiber skin layers and a PZT ceramic core layer are loaded with a roller and an AE activity from the specimen is monitored during the entire loading using an AE transducer mounted on the specimen. AE characteristics from a monolithic PZT ceramic with a thickness of $250{\mu}m$ are examined first in order to distinguish different AE signals from various possible damage modes in piezoelectric composite actuators. Post-failure observations and stress analyses in the respective layers of the specimens are conducted to identify particular features in the acoustic emission signal that correspond to specific types of damage modes. As a result, the signal classification based on waveform and peak frequency analyses successfully describes the failure process of the bending piezoelectric composite actuator exhibiting diverse failure mechanisms. Furthermore, it is elucidated that when the PZT ceramic embedded actuators are loaded mechanical bending loads, the failure process of actuator specimens with different lay-up configurations is almost same irrespective of their lay-up configurations.

Data-Driven Modelling of Damage Prediction of Granite Using Acoustic Emission Parameters in Nuclear Waste Repository

  • Lee, Hang-Lo;Kim, Jin-Seop;Hong, Chang-Ho;Jeong, Ho-Young;Cho, Dong-Keun
    • Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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    • v.19 no.1
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    • pp.75-85
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    • 2021
  • Evaluating the quantitative damage to rocks through acoustic emission (AE) has become a research focus. Most studies mainly used one or two AE parameters to evaluate the degree of damage, but several AE parameters have been rarely used. In this study, several data-driven models were employed to reflect the combined features of AE parameters. Through uniaxial compression tests, we obtained mechanical and AE-signal data for five granite specimens. The maximum amplitude, hits, counts, rise time, absolute energy, and initiation frequency expressed as the cumulative value were selected as input parameters. The result showed that gradient boosting (GB) was the best model among the support vector regression methods. When GB was applied to the testing data, the root-mean-square error and R between the predicted and actual values were 0.96 and 0.077, respectively. A parameter analysis was performed to capture the parameter significance. The result showed that cumulative absolute energy was the main parameter for damage prediction. Thus, AE has practical applicability in predicting rock damage without conducting mechanical tests. Based on the results, this study will be useful for monitoring the near-field rock mass of nuclear waste repository.

Real-Time Source Classification with an Waveform Parameter Filtering of Acoustic Emission Signals (음향방출 파형 파라미터 필터링 기법을 이용한 실시간 음원 분류)

  • Cho, Seung-Hyun;Park, Jae-Ha;Ahn, Bong-Young
    • Journal of the Korean Society for Nondestructive Testing
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    • v.31 no.2
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    • pp.165-173
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    • 2011
  • The acoustic emission(AE) technique is a well established method to carry out structural health monitoring(SHM) of large structures. However, the real-time monitoring of the crack growth in the roller coaster support structures is not easy since the vehicle operation produces very large noise as well as crack growth. In this investigation, we present the waveform parameter filtering method to classify acoustic sources in real-time. This method filtrates only the AE hits by the target acoustic source as passing hits in a specific parameter band. According to various acoustic sources, the waveform parameters were measured and analyzed to verify the present filtering method. Also, the AE system employing the waveform parameter filter was manufactured and applied to the roller coaster support structure in an actual amusement park.

Development of Acoustic Emission Training Technique and Localization Method using Q-switched Laser and Multiple Sensors/Single Channel Acquisition (Q-switched 레이저와 다중센서/단일채널 신호수집을 이용한 복합재 구조 음향방출 트레이닝 및 위치탐지 기법 개발)

  • Choi, Yunshil;Lee, Jung-Ryul
    • Composites Research
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    • v.31 no.4
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    • pp.145-150
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    • 2018
  • Various structural health monitoring (SHM) systems have been suggested for aerospace industry in order to increase its life-cycle and economic efficiency. In the case of aircraft structure madden with metal, a major concern was hot spots, such as notches, bolts holes, and where corrosion or stress concentration occurs due to moisture or salinity. However, with the increasing use of composites in the aerospace industry, further advanced SHM systems have been being required to be applied to composite structures, which have much complex damage mechanism. In this paper, a method of acoustic emission localization for composite structures using Q-switched laser and multiple Amplifier-integrated PZTs have been proposed. The presented technique aims at localization of the AE with an error in distance of less than 10 mm. Acoustic emission simulation and the localization attempt were conducted in the composite structure to validate the suggested method. Localization results, which are coordinates of detected regions, grid plots and color intensity map have been presented together to show reliability of the method.