• Journal of the Korea Convergence Society
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• v.11 no.11
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• pp.249-255
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• 2020

This study developed the health monitoring method of press process using the acoustic emission (AE) sensor and high-pass filter. Also, the AE parameters such as ring-down count and peak amplitude are used. Based on this AE signal, the AE parameters were acquired and was utilized to detect the crack of the specimen. Since the defect detection is difficult due to noise and low magnitude of signal, the signal noise and press operation frequency were checked through the Short Time Fourier Transform(STFT) and damped. High-pass Filtering data was applied to AE parameters to select effective parameters. By using this signal processing techniques, the proposed AE parameters could improve the performance of defect detection in the press process.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.33 no.3
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• pp.231-238
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• 2020

This paper investigates the soundness of porcelain insulators associated with the acoustic emission (AE) technique. The AE technique is a popular non-destructive method that measures and analyzes the burst energy that occurs mainly when a crack occurs in a high-frequency region. Typical AE methods require continuous monitoring with frequent sensor calibration. However, in this study, the AE technique excites a porcelain insulator using only an impact hammer, and it applies a high-pass filter to the signal frequency range measured only in the AE sensor by comparing the AE and the acceleration sensors. Next, the extracted time-domain signal is analyzed for the damage assessment. In normal signals, the duration is about 2ms, the area of the envelope is about 1,000, and the number of counts is about 20. In the damage signal, the duration exceeds 5ms, the area of the envelope is about 2,000, and the number of counts exceeds 40. In addition, various characteristics in the time and frequency domain for normal and damage cases are analyzed using the short-time Fourier transform (STFT). Based on the results of the STFT analysis, the maximum energy of a normal specimen is less than 0.02, while in the case of the damage specimen, it exceeds 0.02. The extracted high-frequency components can present dynamic behavior of crack regions and eigenmodes of the isolated insulator parts, but the presence, size, and distribution of cracks can be predicted indirectly. In this regard, the characteristics of the surface crack region were derived in this study.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.4 no.2
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• pp.31-37
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• 1995

This study is focused on the prediction of appropriate tool life by clarifying the correlation between progressive tool wear and AE signal. when rcutting SM45C by End mill in machining center. First of all, end mill have a problem that position of sensor sticking because it is revolution tool, but I think that it can be bained specific character according to sticking Sensor in the Vise. Consequently, the following results have been obtained; 1. Each cutting speed of feed rate over 0.1mm had a tendency to increase linearly according to the RMSAE 2. The level of AE signal at the same cutting area was more sensitive to depth of cut tharn the variation of feed rate 3. In the range of cutting duringqr about 75minqr atqr cutting speed 27m/min flankqr wear turns up aboutqr 0.21mm, aboutqr 0.29mm in the caseqr of about 65minqr at 33/min, qr hereby RMSAE increased rapidly at 0.2mm flank wear, also AE-HIT and CUM-CNTS.

• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.6 s.165
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• pp.1011-1017
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• 1999

Electrolytic in-process dressing grinding technique which enables application of metal bond wheels with fine superabrasives in mirror surface grinding operations has developed. It is possible to make efficient precision machining of hard and brittle material such as ceramic and hard metal by the employment of this technique. However, in order to ensure the success of performances such as efficient machining, surface finish, and surface quality, it is important to sustain the insulating layer that has sharply exposed abrasives in wheel surface. Using AE(Acoustic Emission) sensor, this paper will show whether the insulating layer sustains stably or not in real grinding time. And by comparing AErms value and surface roughness their thresholds for stable electrolytic in-process dressing grinding will be determined.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.29 no.8
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• pp.466-469
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• 2016

In this study, in order to develop composition ceramics for Acoustic Emission (abbreviated as AE) sensor application, the PZT system ceramics was fabricated by conventional solid state reaction method. When x=0.48, the density, electromechanical coupling factor($k_p$), piezoelectric coefficient $d_{33}$ and piezoelectric voltage constant $g_{33}$ of the maximum values of $7.857g/cm^3$, 0.51, 190[pC/N], 52[$10^{-3}mV/N$] were obtained, respectively, suitable for AE sensor.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.24 no.6
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• pp.463-467
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• 2011

In this study, thickness shear mode piezoelectric devices for AE sensor with excellent displacement and sensitivity characteristics were simulated using ATILA FEM program, and then fabricated. Displacement and electro mechanical coupling factors of the piezoelectric devices were investigated. The simulation results showed that excellent displacement and electromechanical coupling factor was obtained when the ratio of Length/Thickness was 1. The piezoelectric device of L/T= 1 exhibited the optimum values of fr= 150 kHz, displacement= $6.23{\times}10^{-8}$[m], $k_{15}$= 0.598. The results show that the thickness shear mode piezoelectric device is a promising candidate for the application of AE sensor piezoelectric device.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.4
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• pp.95-99
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• 2004

In this study, the leak detection technique of pressure vessel by using acoustic emission(AE) signal is suggested experimentally. The leak of pressure vessel is located at the welding line due to welding defects. we measured the AE signal using Rl5I sensor, and examined the AE parameters in leak condition. It is investigated that the mean value of AE signal is dependent on leak source location. So the absolute mean value of AE signal is adopted as dominant AE parameter. We proposed leak detection algorithm using AE signal mean value for monitoring the leak source location.

• Proceedings of the KIEE Conference
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• 1999.07e
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• pp.2335-2337
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• 1999

In this paper, using AE (Acoustic Emission) sensor the electrical and emitted-sound signals are measured by treeing breakdown in the epoxy resin, and the corresponding frequency spectrum of the AE signals are analyzed. We also examined the relationship between partial discharge magnitude and pulse number of AE signals to diagnose the deterioration of the electrical insulation due to treeing breakdown. From these results, a frequency band of AE signals through treeing breakdown was set to about 230 [kHz], and it appeared that pulse number of AE signal was proportional to partial discharge magnitude.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.3
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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.