• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.15 no.4
• /
• pp.22-28
• /
• 2006

Detection of exit burr is very important in manufacturing automation. In this paper, acoustic emission(AE) was used to detect the burr formation during milling. By using wavelet transformation, AE data was compressed without unnecessary details. Then the transformed data were used as selected features (inputs) of a back-propagation artificial neural net. In order to validate the proposed scheme, the wavelet based ANN results were compared with cutting condition(cutting speed, feed, depth of cut, etc.) based ANN results.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.13 no.5
• /
• pp.118-123
• /
• 2004

The compressor has one of important roles in refrigeration cycle and it determines refrigeration efficiency and quality This paper aims to monitor rotary compressors for room air conditioners by using Acoustic Emission(AE) technique. The reliability of rotary compressors has been evaluated through visual inspection on them after long term test. This paper describes methods for acquisition and processing AE raw signal to monitor the state of rotary compressor. A detecting method of abnormal compressor in real time is suggested and special-purpose monitoring system which can be applied to automatic manufacturing line is developed using one-chip microprocessor at low cost.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2003.04a
• /
• pp.363-370
• /
• 2003

The object of this study is to investigate the effect of compounded welding by using an acoustic emission (AE) signals and doing a source location for weld heat affected zone (HAZ) through tensile testing. This study was carried out a SM 490A high tension steel for electronic shielded metal arc welding (SMAW), $CO_2$ gas arc welding and TIG welding. Data displays are based on the measured parameters of the AE signals, along with environmental variables such as time and load. These history plots are displays showing the chronological course of the test. Also, source location gives the X- and Y-coordinates of the AE source.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.11 no.3
• /
• pp.39-44
• /
• 2002

As laser cutting process is widely used in industry, an automated on-line process control system has become very important. In this paper, development of a laser cutting monitoring system, which is regarded as the fundamental step toward automation of the process, is presented. Acoustic emission and an artificial neural network were used for the monitoring system. With given process Parameters including laser power and scanning speed the system can predict the suitability of laser beam for the cutting or a stainless steel (STS304) plate.

• Journal of Applied Reliability
• /
• v.13 no.2
• /
• pp.129-140
• /
• 2013

As a fundamental experimental study for reliability improvement of lithium ion secondary battery, degradation mechanism was investigated by microscopic observation and acoustic emission monitoring. Microstructural observation of the decomposed battery after cycle test revealed mechanical and chemical damages such as interface delamination, microcrack of the electrodes, and solid electrolyte interphase (SEI). Acoustic emission (AE) signal was detected during charge and discharge of lithium ion battery to investigate relationships among cumulative count, discharge capacity, and microdamages. With increasing number of cycle, discharge capacity was decreased and AE cumulative count was observed to increase. Observed damages were attributed to sources of the detected AE signals.

• Nuclear Engineering and Technology
• /
• v.35 no.1
• /
• pp.25-34
• /
• 2003

The research on the development of the fault monitoring system for the thermal reduction reactor has been performed preliminarily in order to support the successful operation of the thermal reduction reactor. The final task of the development of the fault monitoring system is to assure the integrity of the thermal$_3$ reduction reactor by the acoustic emission (AE) method. The objectives of this paper are to identify and characterize the fault-induced signals for the discrimination of the various AE signals acquired during the reactor operation. The AE data acquisition and analysis system was constructed and applied to the fault monitoring of the small- scale reduction reactor, Through the series of experiments, the various signals such as background noise, operating signals, and fault-induced signals were measured and their characteristics were identified, which will be used in the signal discrimination for further application to full-scale thermal reduction reactor.

• Journal of Ocean Engineering and Technology
• /
• v.15 no.2
• /
• pp.61-65
• /
• 2001

The fracture toughness of ceramics can be measure by such various methods as DT (double torsion), CN (chevron notch) etc. But, the application of these methods to the engineering ceramics is very difficult because of its very high hardness. So, IF (indentation fracture) method is generally used for the evaluation of fracture toughness of ceramics. The Median crack induced by the sharp Vickers indenter was compared with the detected AE (acoustic emission) signal. On the silicon nitride ceramics, the AE test results agree fairly well with the median crack occurance and growth process. But, on the alumina, very many complicated crack signals were detected besides median crack. It can be considered that the IF methods must be used in limited engineering ceramics materials.

• Composites Research
• /
• v.36 no.6
• /
• pp.429-434
• /
• 2023

In this study, aimed at improving the existing acoustic emission sensor for real time monitoring, a macro-fiber composite (MFC) transducer was employed as the acoustic emission sensor in the gas leak detection system. Prior to implementation, structural analysis was conducted to optimize the MFC's design. Consequently, the flexibility of the MFC facilitated excellent adherence to curved pipes, enabling the reception of acoustic emission (AE) signals without complications. Analysis of AE signals revealed substantial variations in parameter values for both high-pressure and low-pressure leaks. Notably, in the parameters of the Fast Fourier Transform (FFT) graph, the change amounted to 120% to 626% for high-pressure leaks compared to the case without leaks, and approximately 9% to 22% for low-pressure leaks. Furthermore, depending on the distance from the leak site, the magnitude of change in parameters tended to decrease as the distance increased. As the results, in the future, not only will it be possible to detect a leak by detecting the amount of parameter change in the future, but it will also be possible to identify the location of the leak from the amount of change.

• Geomechanics and Engineering
• /
• v.17 no.2
• /
• pp.215-225
• /
• 2019

The mechanical behavior of rock is essential to estimate the capacity and long-term stability of $CO_2$ storage in deep saline aquifers. As the depth of reservoir increases, the pressure and temperature that applied on the rock increase. To answer the question of how the confining pressure and temperature influence the mechanical behavior of reservoir rock, triaxial compression experiments were carried out on brine-saturated sandstone at elevated temperature. The triaxial compressive strength of brine-saturated sandstone was observed to decrease with increasing testing temperature, and the temperature weakening effect in strength enhanced with the increase of confining pressure. Sandstone specimens showed single fracture failures under triaxial compression. Three typical regions around the main fracture were identified: fracture band, damaged zone and undamaged zone. A function was proposed to describe the evolution of acoustic emission count under loading. Finally, the mechanism of elevated temperature causing the reduction of strength of brine-saturated sandstone was discussed.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.24 no.6
• /
• pp.429-436
• /
• 2014

Most mechanical systems are now operating consistently and getting faster due to the development of automation systems. Peoples' dependence on machines have increased as when problems occur within the mechanical system, personal injury and production loss may come as a result, as most of the mechanical system's malfunctions are caused by the failure of the rotational bearing. What we need now is a maintenance system that can warn us when it detects abnormal conditions before significant damage occurs to the bearing. In this study, we have developed an acoustic emissions sensor that can figure if the bearing works under the normal condition. With this acoustic emissions sensor, we can inspect the bearing for defects by using the Heterodyne technique, which converts the ultrasound signal into audio, as a signal conditioning process.