• Journal of the korean Society of Automotive Engineers
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• v.9 no.2
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• pp.47-57
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• 1987

The objective of this study is to establish the comprehensive analytical relationship between acoustic emission and fundamental parameters of the orthogonal cutting process. The sources of acoustic emission in the orthogonal metal cutting process was identified as deformation in the shear zone and sliding friction at the chip-tool interface. The validity of this relationship is evaluated by a series of tests varing cutting speed and rake angle for A16063 tube. Strong dependence of the RMS voltage of acoustic emission on cutting speed and rake angle was observed. It was also found that the percentage contribution of AE energy at each zone for the total AE activity is constant in accordance with the change of cutting speed. The relationship between the RMS of acoustic emission and the fundamental cutting parameters was modified in order to be utilized independent of rake angle.

• Computers and Concrete
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• v.18 no.2
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• pp.267-278
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• 2016

In order to observe the internal damage of concrete in real time, we introduced acoustic emission nondestructive detecting technology into a series of fracture tests; the test results revealed the whole process that concrete undergoes when it sustains damage that leads to failure, according to the change rules of the acoustic emission parameters. The results showed that both the initiation and unstable loads can be accurately determined using the abrupt change of the acoustic emission rate curves and the turning point of the acoustic emission parameters' accumulative curves. The whole process, from damage to failure, includes five phases, beginning with damage, such as cracking, a stable crack growth process, a critical unstable stage, and unstable propagation. The brittle fracture characteristics of concrete change when steel bars are joined, because the steel bars and the concrete structure bond, which causes an increase in the acoustic emission signals within the fracture process of the reinforced concrete. The unstable propagation stage is also extended. Our research results provide a valid methodology and technical explanations, which can help researchers to monitor the cracking process of concrete structures, in real time, during actual projects.

• 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.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.4
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• pp.46-53
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• 1997

This paper presents a method of detection localized defects on tapered roller bearing in main spindle of machine tool system. The feature vectors, i.e. statistical parameters, in time-domain analysis technique have been calculated to extract useful features from acoustic emission signals. These feature vectors are used as the input feature of an neural network to classify and detect bearing defects. As a results, the detection of bearing defect conditions could be sucessfully performed by using an neural network with statistical parameters of acoustic emission signals.

• Tunnel and Underground Space
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• v.10 no.1
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• pp.59-69
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• 2000

Acoustic emission is n burst of microseismic waves generated by microscopic failure due to deformation in materials. The study on the detection of initiation and propagation of microcracks from acoustic emission measurement is very important for the evaluation of the stability of underground rock structures by the nondestructive letting method. In this study, acoustic emission was measured under uniaxial stiffness loading test used to obtain the complete stress-strain curves of marble and concrete used as reinforced materials of rock structures. The analysis of acoustic emission parameters and source location were performed to discuss the characteristics of the deformation and failure behavior of rock and concrete. And acoustic emission was measured under cyclic loading test to verify the Kaiser effect associated with the damage of materials, in situ stress of rock, and stress history of concrete structure.

• Journal of Power System Engineering
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• v.11 no.1
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• pp.45-50
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• 2007

Acoustic emission technology is applied to diagnosis the internal leak and operating conditions of the major valves at nuclear power plants. The purpose of this study is to verify availability of the acoustic emission as in-situ diagnosis method. In this study, acoustic emission tests are performed when the pressurized high temperature steam flowed through gate valve(1st stage reheater valve) and glove valve(main steam dump valve) on the normal size of 4 and 8". The valve internal leak diagnosis system for practical field was designed. The acoustic emission method was applied to the valves at the site, and the background noise was measured for the abnormal plant condition. To improve the reliability, a judgment of leak on the system was used various factors which are AE parameters, trend analysis, signal level analysis and RMS(root mean square) analysis of acoustic signal emitted from the valve operating condition internal leak.

• Transactions of the Korean Society of Mechanical Engineers
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• v.10 no.6
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• pp.906-915
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• 1986

This study reviewed the theory of acoustic emission applying generation of acoustic emission in metal cutting and proposed a relationship between fundamental cutting parameters and the root mean square (RMS) voltage of the acoustic emission on the basis of the mechanics of the orthogonal cutting operation. Experimental results are presented for 6063-T5 Auminum and the validity of this relationship is evaluated by a series of tests varying cutting speed, feed rate and rake angle in orthogonal cutting. The original formula derived theoretically has been modified in order to utilize independent of fundamental cutting parameters. RMS voltage of acoustic emission depends on cutting speed and strain rate, but it is not much affected by feed rate. Applying lubricant, the drop of RMS level has been observed.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.17 no.4
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• pp.42-47
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• 2009

Recently, the wide range of the composite materials is used for the making airplanes, trains and automobiles body for the lightweight. Despite having complex structures, composite materials usually have well defined mechanical characteristics. However, composite materials are difficult to understand the fracture mechanism clearly by simple mechanical test. Nondestructive evaluation (NDE) combined with mechanical testing can play a more important role and especially Acoustic Emission Testing (AET) would become known to be a useful tool to assess damage and fracture behavior of composites. In this study The experiment was performed to acquire the acoustic emission signal during tensile test using unidirectional CFRP specimen and the data was analyzed the acoustic emission parameters with the waveform.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.2
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• pp.133-139
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• 2002

A number of experimental studies on burr formation in face milling operations have been pursued. They usually focus on machining parameters such as depth of cut, leed rate, spindle speed and in-plane exit angle. But it if difficult to set the correlation between burrs and the parameters on burr when such parameters are considered at the same time. Therefore, in this paper, acoustic emission (AE) is considered as an alternate way to predict burr types regardless of machining conditions. AE signals during face milling were sampled and processed, then fed into an artificial neural network to classify burr types \\\"on-line\\\".\\\".uot;.

• 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.