• Title/Summary/Keyword: AE-signals

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A study on Quench Characteristics considering Winding Tension in Superconducting Coil using Acoustic Emission Technique (권선장력을 고려한 초전도 계자코일의 퀀치특성 및 AE 신호특성에 관한 연구)

  • 이준현;이민래;손명환;권영길
    • Progress in Superconductivity and Cryogenics
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    • v.1 no.2
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    • pp.8-14
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    • 1999
  • In this study, acoustic emission(AE) technique has been applied to detecting quench which is one of the serious peoblems to assure the integrity of superconducting coil at cryogenic temperature. The characteristics of AE parameters have been analyzed by correlating with the number of quenches, whinding tension of superconducting coil and charge rate of transport current. The quench localization was also performed using AE signals and there was also good correlation between quench current and AE parameters such as AE energy and AE events. In this study, it was confirmed that AE signals were mainly due to the conductor motion which caused by premature quenching. It was also found that optimized winding tension at superconducting coil was needed to prevent quench caused by conductor motion.

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Proposition and Application of Novel DWT Mother Function for AE signature (AE 신호를 위한 새로운 DWT 기저함수 제안 및 적용)

  • Gu, Dong-Sik;Kim, Jae-Gu;Choi, Byeong-Keun
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2011.04a
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    • pp.582-587
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    • 2011
  • Acoustic Emission(AE) is widely used for early detection of faults for rotating machinery in these days because of its high sensitivity. AE signal has to need for transferring to low frequency range for the spectrum analysis included the fault mechanism. In transferring process, we lose a lot of fault information caused by unusable signal processing method. Discrete Wavelet Transform(DWT) is a method of signal processing for AE signatures, but the pattern of its mother function is not optimized with AE signals. So, we can lose the fault information when we want to use the DWT for AE signal. Therefore, in this paper, we will propose a novel pattern for DWT mother function, which is optimized with AE signals. And it will be applied to compare the results of DWT by daubechie and novel pattern.

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Attenuation Characteristics of AE/MA Waves in Charcoal Granite (차콜 화강암에서의 AE/MA파의 감쇄특성)

  • 김교원
    • The Journal of Engineering Geology
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    • v.6 no.3
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    • pp.131-136
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    • 1996
  • Attenuation characteristics of AF/MA motions which involve high frequencies were investigated through pencil-lead fracture tests on a fine-grained granite specimen. For the study, calibrated six transducers were employed to detect the signals and the pencil-lead was fractured as a step unloading force to generate AE/MA signals. The arnplitude AE/MA waves is affected by the relative orientation of source and transducer as well as the source distance. The attenuation constant for Charcoal granite is obtained as 1.058 which could be applied for a given ray-path regardless of the relative orientation of source and transducer.

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Study and Experimentation on Detection of Nicks inside of Porcelain with Acoustic Emission

  • Jin, Wei;Li, Fen
    • Journal of Korea Multimedia Society
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    • v.9 no.12
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    • pp.1572-1579
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    • 2006
  • An usual acoustic emission(AE) event has two widely characterized parameters in time domain, peak amplitude and event duration. But noise in AE measuring may disturb the signals with its parameters and aggrandize the signal incertitude. Experiment activity of detection of the nick inside of porcelain with AE was made and study on AE signal processing with statistic be presented in this paper in order to pick-up information expected from the signal with noise. Effort is concentrated on developing a novel arithmetic to improve extraction of the characteristic from stochastic signal and to enhance the voracity of detection. The main purpose discussed in this paper is to treat with signals on amplitudes with statistic mutuality and power density spectrum in frequency domain, and farther more to select samples for neural networks training by means of least-squares algorithm between real measuring signal and deterministic signals under laboratory condition. By seeking optimization with the algorithm, the parameters representing characteristic of the porcelain object are selected, while the stochastic interfere be weakened, then study for detection on neural networks is developed based on processing above.

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SENSORS IN DEVURRING AUTOMATION

  • Lee, Seoung-Hwan
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 1999.10a
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    • pp.560-564
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    • 1999
  • Burr sensing for burr size measurement and deburring process control is one of the essential elements in an automated deburring procedure. This paper presents the implementation of capacitance sensing and acoustic emission (AE) to deburring. The first application is the "on-line" measurement of burrs using a capacitance sensor. A non-contact capacitance gauging sensor is attached to an ultra precision milling machine which was used as a positioning system. The setup is used to measure burr profiles along machined workpiece edges. The proposed scheme is shown to be accurate, easy to setup, and with minor modifications, readily applicable to automatic deburring processes. As the second example, AE signals were sampled and analyzed for the sensor feedback of a precision deburring process - laser deburring -. The results, such as the sensitivity of AE signals to burr shapes and edge detection capability show a clear correlation between physical process parameters and the AE signals. A subsequent control strategy for deburring automation is also briefly discussed.

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Acoustic Emission Feedback for Precison Laser Deburring (정밀 레이저 디버링을 위한 어쿠스틱 에미션 피드백)

  • Lee, Seoung-Hwan
    • Journal of the Korean Society for Precision Engineering
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    • v.16 no.5 s.98
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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.

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A Study on the Evaluation of Machining States in the Cylindrical Plunge Grinding using the Current Signals of a Spindle Motor (주축모터전류신호를 이용한 원통 연삭시 가공 상태 평가에 관한 연구)

  • 송지복;이은상;김남훈
    • Journal of the Korean Society for Precision Engineering
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    • v.17 no.6
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    • pp.76-82
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    • 2000
  • This paper describes the machining characteristics of cylindrical plunge grinding. The study investigates the process using the current signals of a spindle motor through a hall sensor. Grinding experiments were conducted under various conditions such as wheel speeds, workpiece speeds and infeed rates with a conventional vitrified bonded wheel. Analyzing the current signal of the spindle motor, a relationship between current signals and the metal removal rate in terms of the in(red rate is induced. It was also shown that a hall sensor has similar capabilities in evaluation of grinding behavior compared to the AE signals, which are useful far monitoring the grinding process.

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Discrimination of Acoustic Emission Signals using Pattern Recognition Analysis (형상인식법을 이용한 음향방출신호의 분류)

  • Joo, Y.S.;Jung, H.K.;Sim, C.M.;Lim, H.T.
    • Journal of the Korean Society for Nondestructive Testing
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    • v.10 no.2
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    • pp.23-31
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    • 1990
  • Acoustic Emission(AE) signals obtained during fracture toughness test and fatigue test for nuclear pressure vessel material(SA 508 cl.3) and artificial AE signals from pencil break and ultrasonic pulser were classified using pattern recognition methods. Three different classifiers ; namely Minimum Distance Classifier, Linear Discriminant Classifier and Maximum Likelihood Classifier were used for pattern recognition. In this study, the performance of each classifier was compared. The discrimination of AE signals from cracking and crack surface rubbing was possible and the analysis for crack propagation was applicable by pattern recognition methods.

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Monitoring Technique using Acoustic Emission and Microseismic Event (AE와 MS 이벤트를 이용한 계측기술)

  • Cheon, Dae-Sung;Jung, Yong-Bok;Park, Chul-Whan;Synn, Joong-Ho;Park, Eui-Seob
    • Tunnel and Underground Space
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    • v.18 no.1
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    • pp.1-9
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    • 2008
  • Acoustic emission (AE) and Microseimsic (MS) activities are law-energy seismic events associated with a sudden inelastic deformation such as the sudden movement of existing fractures, the generation of new fractures or the propagation of fractures. These events rapidly increase before major failure and happen within a given rock volume and radiate detectable seismic waves. The main difference between AE and MS signals is that the seismic motion frequencies of AE signals are higher than those of MS signals. As the failure of geotechnical structures usually happens as a high velocity and small displacement, it is nat easy ta determine the precursor and initiation stress level of failure in displacement detection method. To overcame this problem, AE/MS techniques far detection of structure failure and damage have recently adapt in civil engineering. This study deal with the basic theory of AE/MS and state of arts in monitoring technique using AE/MS.

A Study on AE Signal Analysis of Composite Materials Using Matrix Piezo Electric Sensor (매트릭스형 피에조센서를 이용한 복합재료 AE신호 분석에 관한 연구)

  • Yu, Yeun-Ho;Choi, Jin-Ho;Kweon, Jin-Hwe
    • Journal of the Korean Society for Nondestructive Testing
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    • v.27 no.1
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    • pp.1-7
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    • 2007
  • As fiber reinforced composite materials are widely used in aircraft, space structures and robot arms, the study on non-destructive testing methods has become an important research area for improving their reliability and safety. AE (acoustic emission) can evaluate the defects by detecting the emitting strain energy when elastic waves are generated by the initiation and growth of crack, plastic deformation, fiber breakage, matrix cleavage, or delamination. In the paper, AE signals generated under uniaxial tension were measured and analyzed using the $8{\times}8$ matrix piezo electric sensor. The electronic circuit to control the transmitting distance of AE signals was designed and constructed. The optical data storage system was also designed to store the AE signal of 64channels using LED (light emitting diode) elements. From the tests, it was shown that the source location and propagation path of AE signals in composite materials could be detected effectively by the $8{\times}8$ matrix piezo electric sensor.