• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.14-19
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• 2000

A machine tool has some serous stability problem in the from of tool chatter during the cutting process. Chatter vibration deteriorates the surface finish, reduce tool and machine life, accelerate machine tool system component wear, and may lead to an unacceptable noise sound in the working environment. In this study, in order to moni색 of the chatter vibration on the cutting process, the behavior of spectral density of AE signal and principal cutting force signal has been investigated. Furthermore, its reliability from obtained the results has been studied to evaluate and confirm the proposed method with the application procedure and the experimental results.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.8-13
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• 2000

Die polishing technology is very critical to determine quality and performance of the final products. Die polishing processes have not been automated because the automation requires a great deal of experience and skill of experts. Thus, to implement a fully automated polishing process, the development of polishing status monitoring system replacing the skill of experts is critical. AE is known to be closely related to material removal rate(MRR). As the surface is rougher, MRR gets larger and AE increased. The surface roughness can be indirectly estimated using the AE signal measured during automatic die polishing process. In this study, The polishing state monitoring system using AEms signal was developed. This system can be not only to monitor the abnormal state but also to estimate a state of surface roughness of polishing surface qualitatively.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.4
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• pp.330-336
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• 2014

The continuous chip generated in cutting process deteriorates workpiece, tool, and machine tool system. It is necessary to treat this continuous chip in ductile material machining condition for stable cutting. This paper deals with the chip control method using acoustic emission(AE) signal in pure copper turning operation. AE raw signals, root mean square(RMS) signals and wavelet transformed signals measured in turning process are introduced to analysis for chip patterns. With analysis of AE signals, it is obtained that the produced chip patterns are correlated with the specified AE signals which are transformed by fuzzy pattern algorithm. By this experimental investigation, the chip patterns can be classified at significant level in pure copper machining process and controlled from continuous chips to reduced-length stable chips.

• Korean Journal of Materials Research
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• v.5 no.1
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• pp.12-21
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• 1995

The study was performed to study the effects of strain rate on acoustics emission( AE) during bulging test in corrosive environmentsynthetic sea water. The strain rates used were in the range $4 \times 10^{-6}S^{-1}$ to $1 \times 10^{-4} \times S^{-1}$ and the parameters used to evaluate AE signal characteristics were AE hit and amplitude. It can be observed that the cumulative AE hit and average amplitude during fracture process increase highly at decreasing strain rates while the equivalent fracture strain and the crack length of circumferencial direction become decrease. The peak point of AE signal characteristic parameters approach to the first half of test. When the average amplitude per unit equivalent fracture strain was above 20dB, it was definitly observed stress corrosion cracking phenomena. Additional, we knew that the AE test had the possibility to evaluate SCC susceptibility with various strain rates.

• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.5
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• pp.409-414
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• 2013

In this work, corrosion of 304 stainless steel was evaluated by using acoustic emission(AE) technique. AE measurement system was set for detecting acoustic signal during accelerated corrosion test of the specimen. AE signal started to be detected after the time of pitting corrosion initiation was evaluated by anodic polarization curve. Pitting corrosion damage was confirmed by optical microscopic observation of the surface morphology. AE cumulative counts and amplitude according to corrosion time could be divided into three stages. These trends were discussed in relation with changing pitting corrosion mechanism. Feasibilities of AE technique for evaluation of corrosion damage and mechanism were suggested.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.4
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• pp.308-315
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• 2009

Because the attenuation of AE signal in composite materials is relatively higher than that of metallic materials, it is required to develop a damage assessment technique less affected by the attenuation property of composite materials in order to use AE sensing as a damage detection method. In the signal processing procedure, it is profitable to use the leading wave that arrives first because the leading wave is less influenced by the boundary conditions. Using wavelet transform, we investigated the frequency characteristics of impact induced AE signals focused on the leading wave in advance and chose the key factors to discriminate the damaged condition quantitatively. In this research, we established a damage assessment technique using the sharing percentage of the wavelet detail components of AE signal, and conducted a low-velocity impact test on composite laminates to confirm the feasibility of the proposed signal processing method.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.2
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• pp.97-104
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• 2007

An investigation has been made on the relationship between characteristics of Acoustic Emission (AE) signal in welding flaw and the stress corrosion defect in-service for the high pressure pipe steel. In order to tackle the problem of welding flaw in high pressure pipe, specimens were made by the aid of the application of both corrosion liquid usage and a quenching method after local heating. The amplitude of signal was $60{\sim}75\;dB$ in the territory which is suspected for defect, and the specimens which only have welding flaw showed gradients of 0.034, 0.034, 0.035. Moreover, there is a certain increase in gradient even though the differences are very slight. That is, corrosion specimens showed new gradients of 0.040, 0.039, 0.041 which put welding flaw and corrosion mechanism together. After pressurizing 3 minutes, AE signal has been detected from welding flaw easily in each part of the section. It is possible to predict the occurrence and also prevent the damage of stress corrosion crack which has characteristics of cleavage fracture.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.2
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• pp.36-43
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• 2004

In this paper, the frequency spectra from respective mechanical noise signals detected using ultrasonic wave and AE(Acoustic Emission) sensor were analysed to under spark generation between brush and commutator side with arbitrarily 15$^{\circ}$ rotation for brush from the DC motor in operation. Also, the frequency spectra from respective magnetizing noise signals detected using ultrasonic wave and AE sensor were analysed to under neutral point for brush from the DC motor in normal operation. And the analyses and comparison between the mechanical noise signal and magnetizing noise signal of ultrasonic wave with brush location change from the DC motor in operation. As the experimental results, tile mechanical noise signal of ultrasonic wave under spark generation between brush and commutator side with brush location change from the DC motor in operation were increased about 2.5∼3.0 times than magnetizing noise signal of ultrasonic wave form the DC motor in normal operation. Also, the main frequency band for mechanical noise signals of AE under spark generation between brush and commutator side with brush location change from the DC motor in operation, appeared about 1.3[MHz]∼l.5[MHz] by the fast fourier transform.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2011.04a
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• pp.419-423
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• 2011

Unlike other non-destructive inspection method, AE Structural defects that are likely to grow in the operation status can be detected, and the advantage of being due to the continuous monitoring of large structures has been widely used to evaluate the stability. AE sensor used to detect sound wave that occurs between 20kHz to 20MHz. and Sound wave result may vary depending on sensor's sensitivity. In this paper, Tensile test conducted on STS 304 and SS400, and tries to detect the crack signal. In tensile test, specimens were conducted using different sensor sensitivity to the same tensile test condition. The crack signal parameters divided into 4 types of communities by conducting cluster analysis. It was demonstrated that crack signal of two sensor is not different by statistical analysis of null hypotheses. Based on the results, waveform of this tension test is crack signal.

• Smart Structures and Systems
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• v.23 no.2
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• pp.173-184
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• 2019

The main objective of this study is to evaluate the true fracture energy and monitor the damage progression in steel fibre reinforced concrete (SFRC) specimens using acoustic emission (AE) features. Four point bending test is carried out using pre-notched plain and fibre reinforced (0.5% and 1% volume fraction) - concrete under monotonic loading. AE sensors are affixed at different locations of the specimens and AE parameters such as rise time, AE energy, hits, counts, amplitude and duration etc. are obtained. Using the captured and processed AE event data, fracture process zone is identified and the true fracture energy is evaluated. The AE data is also employed for tracing the damage progression in plain and fibre reinforced concrete, using both parametric- and signal- based techniques. Hilbert - Huang transform (HHT) is used in signal based processing for evaluating instantaneous frequency of the acoustic events. It is found that the appropriately processed and carefully analyzed acoustic data is capable of providing vital information on progression of damage on different types of concrete.