• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1997.04a
• /
• pp.832-836
• /
• 1997

An experimental study on the grinding temperature, surface roughness and Acoustic Emission(AE) signal was conducted with different shapes of wheel. The grinding characteristics by slotted shapes of wheel changed by width and helical angle,were compared with those by general one. Lower grinding temperature was obtained for 30 .deg. helical angel with 10mm width and Root Mean Square(RMS) values of AE signals were lower for slotted shapes rather than general one. Surface roughness characteristic of slotted shapes found to be rough,but the value of roughness for 45 .deg. helical angel with 6mm width, represented to similar tendency general one.

• Proceedings of the Korean Society For Composite Materials Conference
• /
• 2003.04a
• /
• pp.42-45
• /
• 2003

Optical fiber vibrations sensors (OFVSs) and extrinsic Fabry-Perot interferometer (EFPI) were used in damage monitoring of fiber-metal laminates(FML). The optical fiber vibration sensor and EFPI were applied in order to detect and evaluate the strain, damage and failure of FML. Damages in composites, such as matrix cracks, delamination and fiber breakage may occur as a result of excessive load, fatigue and low-velocity impacts. Indentation test was performed with the measurement of optical signal and acoustic emission (AE). The signals of the optical fiber vibration sensor due to damages were quantitatively evaluated by wavelet transform. It was found that damage information of comparable in quality to acoustic emission data could be obtained from the optical fiber vibration sensor signals.

• Journal of Mechanical Science and Technology
• /
• v.14 no.7
• /
• pp.773-781
• /
• 2000

The focus of this study is the development of a credible fault detection system of the cylindrical plunge grinding process. The acoustic emission (AE) signals generated during machining were analyzed to determine the relationship between grinding-related faults and characteristics of changes in signals. Furthermore, a neural network, which has excellent ability in pattern classification, was applied to the diagnosis system. The neural network was optimized with a momentum coefficient, a learning rate, and a structure of the hidden layer in the iterative learning process. The success rates of fault detection were verified.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.8 no.6
• /
• pp.71-77
• /
• 1999

Monitoring of Cutting tool wear is a critical issue in automated machining system and has been extensively studied for many years. An austempered ductile iron(ADI) exhibits the excellent mechanical properties and the wear resistance. ADI has generally the poor machinability due to the characteristic. This paper presents the in-process detection of flank wear of cutting tools using the acoustic emission sensor and the digital oscilloscope. The amplitude level of AE signal(AErms) is mainly affected by cutting speed and it is proportional to cutting speed. There have been the relationship of direct proportion between the amplitude level of AE signals and the flank wear width of cutting tool. The flank wear with corresponding to the tool life is successfully detected with the monitor-ing system used in this study.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1996.11a
• /
• pp.115-119
• /
• 1996

An estimation of surface roughness value is a very important and difficult issue in grinding process. The definition of the D.A.R.F(Dimensionless Average Roughness Factor) has been made including the absolute average and tile standard deviation that are the parameters of the AE(Acoustic Emission) sign. The theoretical equation of the surface roughness applying the D.A.R.F has been derived from the regressive analysis and specified with respect to the availability through the experimental approach on the machine.

• Journal of the Korean Society for Precision Engineering
• /
• v.18 no.10
• /
• pp.208-213
• /
• 2001

High speed milling(HSM) is one of the emerging cutting process having tremendous potential not only in increased metal removal rates but also in improved surface finish, burr free edge, dimensional accuracy and a virtually stress free component after machining. The High efficiency and accuracy in machining of die/mold materials can be obtained in high speed machining, so it is necessary to analytic the mechanism of high speed cutting process : cutting force, acoustic emission signal.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1996.11a
• /
• pp.328-332
• /
• 1996

The compressor is one of important elements in refrigerator cycle and play an important role of refrigeration efficiency and quality. Therefore it is very important to monitor state of normal and abnormal compressor. In this research, technic of AE is used for monitoring abnormal rotary compressor and an AE parameter which is a most proper parameter to monitor the abnormal state of compressor is determined by signal processing, Finally, the monitoring result of rotary compressor is agreement with the result of life test.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1994.10a
• /
• pp.73-78
• /
• 1994

Wear and fracture mode of ceramic tool for hardened SKD11 steel was investigated by face milling in this study. The cutting force and Acoustic Emission(AE) signal were utilized to detect the wear and fracture of ceramic tool. The following conclusions were obtained : (1) The wear and fracture modes of ceramic tool are characterized by three types: \circled1wear which has normal wear and notch wear, \circled2 wear caused by scooping on the rake face, \circled3 large fracture caused by thermal crack in the rake face. (2) The wear behaviour of ceramic tool can be detected by the increase of mean cutting force and the variation of the AE RMS voltage. (3) The catastrophic fracture of ceramic tool can be detected by the cutting force(Fz-component). (4) As the hardness of work material increased, Acoustic Emission RMS value and mean cutting force(Fz) increased linearly, but the tool life decreased.

• Journal of the Korean Society of Safety
• /
• v.20 no.1 s.69
• /
• pp.49-54
• /
• 2005

Recently, many kinds of advanced composite materials have been used in various industry fields. Among them, fabric CFRP composites are being used as primary structural components in many applications because of their superior properties. However, the complexity of the fabric structure makes understanding of their failure behavior very difficult. The mechanical strength and crack propagation of plain woven carbon fiber fabric laminate composites are examined by acoustic emission(AE) method. AE signals are acquired during the tensile test and fracture tests. Thus, the relationship between AE signal and mechanical behavior curves and crack extension length are shown. Also the interlaminar fracture toughness in terms of AE characteristics are discussed in viewpoint of crack propagation behavior.

• Proceedings of the Korea Concrete Institute Conference
• /
• 2006.11a
• /
• pp.245-248
• /
• 2006

The objective of this study is to take the first step in creating a user-friendly health monitoring system for recycled aggregate concrete structure using acoustic emission(AE). Each specimen was a cube, the edge of which was 150mm. For pull-out tests, a steel rebar, 13mm in diameter, was embedded in the center of each specimen and casting directions(i.e., vertical and horizontal) were considered in this paper. The AE parameters were analyzed for damage levels(i.e. internal cracking stage, pull-out stage) of all specimens. Results from this study show that event, duration versus amplitude of a signal, showed a clear difference for different loading stages depending upon the concrete casting directions.