• Journal of Ocean Engineering and Technology
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• v.13 no.3B
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• pp.73-82
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• 1999

In this research, an experimental study is presented to check the possibilities of offshore structures monitoring using AE techniques. The underwater transducer and preamplifier are fabricated. And, it is proved that this unit can be used for the detection of AE in offshore structures. Wave propagation studies have shown that supplementary attenuations due to seawater are significantly reducing the detection range of the sensors. It excludes the possibility of offshore structures monitoring with a small number of sensors. We conclude that AE waves would be correctly detected for a path of about 3m. Tubular joints have been tested in air and underwater using simulated elastic wave. Ability of AE techniques to detect and locate cracks early in their evolution has been demonstrated. Several parameters of AE generation have been set in evidence. It has also been shown that crack development goes with an increase of AE parameter. Conclusively, it is shown that AE techniques can provide practical alternatives to present methods being used for inspection of deep-water offshore structures undergoing structural degradation due to fatigue crack growth.

• Computers and Concrete
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• v.8 no.5
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• pp.563-581
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• 2011

The signal-based acoustic emission (AE) characterization of concrete fracture process utilizing home-programmed AE monitoring system was performed for three kinds of static loading tests (Cubic-splitting, Direct-shear and Pull-out). Each test was carried out to induce a distinct fracture mode of concrete. Apart from monitoring and recording the corresponding fracture process of concrete, various methods were utilized to distinguish the characteristics of detected AE waveform to interpret the information of fracture behavior of AE sources (i.e. micro-cracks of concrete). Further, more signal-based characters of AE in different stages were analyzed and compared in this study. This research focused on the relationship between AE signal characteristics and fracture processes of concrete. Thereafter, the mode of concrete fracture could be represented in terms of AE signal characteristics. By using cement-based piezoelectric composite sensors, the AE signals could be detected and collected with better sensitivity and minimized waveform distortion, which made the characterization of AE during concrete fracture process feasible. The continuous wavelet analysis technique was employed to analyze the wave-front of AE and figure out the frequency region of the P-wave & S-wave. Defined RA (rising amplitude), AF (average frequency) and P-wave & S-wave importance index were also introduced to study the characters of AE from concrete fracture. It was found that the characters of AE signals detected during monitoring could be used as an indication of the cracking behavior of concrete.

• Smart Structures and Systems
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• v.6 no.3
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• pp.197-209
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• 2010

The structural state of a bridge is currently examined by visual inspection or by wired sensor techniques, which are relatively expensive, vulnerable to inclement conditions, and time consuming to undertake. In contrast, wireless sensor networks are easy to deploy and flexible in application so that the network can adjust to the individual structure. Different sensing techniques have been used with such networks, but the acoustic emission technique has rarely been utilized. With the use of acoustic emission (AE) techniques it is possible to detect internal structural damage, from cracks propagating during the routine use of a structure, e.g. breakage of prestressing wires. To date, AE data analysis techniques are not appropriate for the requirements of a wireless network due to the very exact time synchronization needed between multiple sensors, and power consumption issues. To unleash the power of the acoustic emission technique on large, extended structures, recording and local analysis techniques need better algorithms to handle and reduce the immense amount of data generated. Preliminary results from utilizing a new concept called Acoustic Emission Array Processing to locally reduce data to information are presented. Results show that the azimuthal location of a seismic source can be successfully identified, using an array of six to eight poor-quality AE sensors arranged in a circular array approximately 200 mm in diameter. AE beamforming only requires very fine time synchronization of the sensors within a single array, relative timing between sensors of $1{\mu}s$ can easily be performed by a single Mote servicing the array. The method concentrates the essence of six to eight extended waveforms into a single value to be sent through the wireless network, resulting in power savings by avoiding extended radio transmission.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.05a
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• pp.330-333
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• 2006

In this paper experimental tests were performed to evaluate velocities of the acoustic waves through prestressed concrete beam and source locations using AE technique. Seven AE sensors are mounted on the surface of 5m length test beam with equal spacing and using Schmidt Hammer AE events are made 18 locations. The velocities of AE signals are evaluated using the time differences of arrival times and the distances between the AE source loactions and the AE sensor locations. In addition, using the Least Square Method, the AE source locations are re-evaluated reversely using both of the arrival times and the velocities of AE signals. Test results show the average velocity of the AE signals is about 4,000m/sec and the velocity decreased with the increase of the trevalling times due to the effect of attenuation. Based on the estimation of the source locations, it is observed that the accuracy of source location is increased when the velocity of each AE sensor used rather than the average velocity.

• Journal of Sensor Science and Technology
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• v.8 no.6
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• pp.469-475
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• 1999

The chips may be produced in the form of either broken chips or unbroken chips in turning process. The unbroken chips are dangerous to the operator and difficult to handle at high speed machining. The signal of Acoustic Emission is related to cutting conditions, tool materials, test conditions and tool geometry in turning. The relationship between AE signal and chip formation was experimentally investigated. The experimental results show that two types of chip formations are possible to classify from the statistical analysis of the amplitude of AE signal. The AE-sensor could be used to monitor the chip condition in turning.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.142-145
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• 1995

It is important from prevention of the malfunction and an important accident by the failuer, to detect a failuer in revolution devices. The acoustic emission(AE) method is expected as means that defects an abnormal phenomenon of revolution devices earlily and utilized. Although a research example by the AE method is reported regarding a gears, little reserch has been conducted using the AE method for running gears in a bending fatigue process of spur gear teeth. Therefore, in this report, with two micro AE sensors attached to the side of the gear, AE was measured in a bending fatigue process of a carburizing gear by using the power circurating-type machine and AE source location in gear teeth were required. By various analysis in these data, the AE characteristics in the fatigue damaging process of the gear tooth were determined.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.13 no.6
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• pp.502-508
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• 2000

In order to detect the partial discharge with the metallic particle in GIS the AE(Acoustic Emission) sensor was designed and simulated by ANSYS 5.5 and manufactured as the coupled vibration mode. The measured resonant frequency and the maximum sensitivity frequency of three coupled AE sensors were as follows ; 147.88 kHz in 8.1mm $\Phi$$\times$8.1mm 128.82 kHz and 58.8 kHz in 9.5 mm$\Phi$$\times$9.5mm, 85.22 kHz and 32.6 kHz in 14.3 mm$\Phi$$\times$14.3 mm, resonant frequency of the AE sensor. The AE sensor of 9.5 mm$\Phi$$\times$9.5mm responded higher than the other coupled vibration mode AE sensor at the partial discharge detection in GIS.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.315-318
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• 1997

In terms of productivity, the speed of machining process has been increasing in most of engineering part. But the tapping process does not reach at enough level compared with other machining processes because of its complicate cutting mechanism. In the high speed tapping process, the one of important elements is tool monitoring system to prevent tool breakage. This paper describes tool monitoring system by acoustic emission(AE) in the tapping process. We used 2 types of AE sensors in this test. The one is commercial sensor which is used in other machining monitoring system like polishing and the other is a self-fabricated sensor for this test. In this test we purpose to find out the frequency of AE signal in tapping process and verify the possibility of applying AE sensor in in-process tapping monitoring system. Also grasp of characteristic of tapping process by AE signal is handled.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 1999.11a
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• pp.127-131
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• 1999

In this paper, using a wide-band AE sensor with the frequency range from 100[kHz], the frequency spectra of AE signals generated from the corona discharges of the needle-plane electrode was analyzed to determine the proper ultrasonic sensor. We also examined the relationship between the magnitude of corona discharge and the magnitude of AE signals in peak-to-peak value under the application of 60[Hz] AC high-voltage in oil. From these results, the main frequency spectra of AE signals emitted from the corona discharges of the needle-plane gap were found to be 130[kHz] by the fast fourier transform. The magnitude of AE signals was proportional to the magnitude of corona discharge and discharge current pulse with increasing the applied voltages. Also the detection of corona discharge point location by AE signals was found to be possible by using two sensors.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.3
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• pp.96-102
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• 2005

Acoustic Emission(AE) technique has been applied to not only material characterization evaluation but also on-line monitoring of the structural integrity. The AE source location technique is very important to identify the source, such as crack, leak detection. Since the AE waveforms obtained from sensors are very difficult to distinguish the defect signals, therefore, it is necessary to consider the signal analysis of the transient wave-form. In this study, we have divided the region of interest into a set finite elements, and calculated the arrival time differences between sensors by using the velocities at every degree from 0 to 90. A new technique for the source location of acoustic emission in fiberboard plates has been studied by introducing Wavelet Transform(WT) do-noising technique. WT is a powerful tool for processing transient signals with temporally varying spectra. If the WT de-noising was employed, we could successfully filter out the errors of source location in fiberboard plates by arrival time difference method. The accuracy of source location appeared to be significantly improved.