• 한국정밀공학회지
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• 제20권11호
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• pp.47-54
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• 2003

Research during the past several years has established the effectiveness of acoustic emission (AE)-based sensing methodologies for machine condition analysis and process. AE has been proposed and evaluated for a variety of sensing tasks as well as for use as a technique for quantitative studies of manufacturing process. STD11 has been known as difficult-to-cut materials. The micro-grooving machine was developed for this study and the experiments were performed using CBN blade for machining STD11. Evaluating the machining conditions, frequency spectrum analysis of acoustic emission (AE) signals according to each conditions were applied. Fuzzy clustering method for associating the preprocessor outputs with the appropriate decisions was followed by frequency spectrum analysis. FFT is used to decompose AE signal into different frequency bands in time domain, the root mean square (RMS) values extracted from the decomposed signal of each frequency band were used as features.

• International Journal of Precision Engineering and Manufacturing
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• 제7권3호
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• pp.14-17
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• 2006

To diagnosis abnormal compressor conditions in an air-conditioner, the acoustic emission (AE) signal, which is derived from wear condition, compressed air, and assembly error, was analyzed experimentally. Burst and continuous type AE signals resulted from metal contact and compressed air, and the raw AE signal of compressors was acquired in the production line. After extracting samples using waveforms, the Early Life Test (ELT) was conducted and the waveform was classified as normal or abnormal. Efficient parameters in the waveform pattern were investigated in time and frequency domains and a diagnosis algorithm for air-conditioners using Neural Network estimation is suggested.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2011년도 춘계학술대회 논문집
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• pp.572-577
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• 2011

The acoustic emission (AE) technique is a well-known non-destructive test technique, both in research and for industrial applications. It is mainly used to monitor the onset of cracking processes in materials and components. Predicting and preventing the crack phenomenon has attracted the attention of many researchers and has continued to provide a large incentive for the use of condition monitoring techniques to detect the earliest stages of cracks. In this research, goal is in grasping features of AE signal caused by crack growth. The envelope analysis with discrete wavelet transform (DWT) is used to find the characteristic of AE signal. To estimate feature of divided into three by crack length, the time waveform and the power spectrum were generated by the raw signals and the transferred signal processed by envelope analysis with DWT.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2008년도 춘계학술대회
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• pp.185-196
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• 2008

The objective of this study is to evaluate the mechanical behaviors and structural integrity of the weldment of high strength steel by using an acoustic emission (AE) techniques. Simple tension and AE tests were conducted against the 3 kind of welding test specimens. In order to analysis the effectiveness of weldability, joinability and structural integrity, we used K-means clustering method as a unsupervised learning pattern recognition algorithm for obtained multivariate AE main data sets, such as AE counts, energy, amplitude, hits, risetime, duration, counts to peak and rms signals. Through the experimental results, the effectiveness of the proposed method is discussed.

• Journal of Mechanical Science and Technology
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• 제17권11호
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• pp.1599-1607
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• 2003

The characteristics of elastic waves emanated from crack initiation in 6061 aluminum alloy subjected to fatigue loading are investigated through experiments. The objective of the study is to determine the differences in the properties of the signals generated from fatigue test and also to examine if the sources of the waves could be identified from the temporal and spectral characteristics of the acoustic emission (AE) waveforms. The signals are recorded using nonresonant, flat, broadband transducers attached to the surface of the alloy specimens. The time dependence and power spectra of the signals recorded during the tests were examined and classified according to their special features. Six distinct types of signals were observed. The waveforms and their power spectra were found to be dependent on the crack propagation stage and the type of fracture associated with the signals. The potential application of the approach in health monitoring of structural components using a network of surface mounted broadband sensors is discussed.

• KSTLE International Journal
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• 제3권2호
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• pp.114-118
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• 2002

In this work, head-disk interactions are studied when flying height becomes lower than laser bump height on the landing zone of a disk. With the reduction of the spinning speed in a spin stand, the flying height is decreased under the height of laser bumps. Conventional and padded pico sliders sweep between landing Bone and data zone and, then, the dynamic behavior of the pico sliders and head-disk impacts are investigated using AE and stiction/friction signals. After 200n cycle-sweep tests, bearing analysis and AFM analysis indicate that there are some signs of wear and plastic deformation in the landing zone of a disk, although AE and stiction/friction signals are not significantly changed during the sweep tests. The experimental results of this paper suggest that in CSS tests at component level, more rigorous examination methods of wear and plastic deformation might be necessary as flying height becomes getting lower.

• 한국생산제조학회지
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• 제8권1호
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• pp.52-59
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• 1999

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

• Tribology and Lubricants
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• 제19권2호
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• pp.102-108
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• 2003

The height of laser bumps has been considered as the limit of the minimum flying height in the contact start-stop (CSS) of hard disk drives. In this paper, tribological interactions at flying height under laser bumps are investigated in a spin stand for development of ultra-low flying head-disk interface. With the reduction of the spinning speed in a spin stand, the flying height is decreased under the height of laser bumps and, then, head-disk interactions are investigated using AE and stiction/friction signals. During seek tests and 20000 cycle-sweep tests, AE and stiction/friction signals are not significantly changed and there are no catastrophic failures of head-disk interface. Bearing analysis and AFM analysis show that there are signs of wear and plastic deformation on the disks. It is suggested that flying height could be as low as and, sometimes, lower than laser bump height.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2003년도 추계학술대회
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• pp.289-294
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• 2003

The object of this study is to investigate the effect of compounded welding by using acoustic emission (AE) signals fur weld heat affected zone (HAZ) in tensile testing. This study was carried out a SM 490A high tension steel for electronic shielded metal are welding (SMAW), $\textrm{CO}_2$ gas arc welding and TIG welding. And correspondingly, the root openings are 3, 4 and 2.8mm. Data displays are based on the measured parameters of the AE signals, along with environmental variables such as time and load. These history plots give us useful and powerful information to analyze the results of material evaluation testing.

• 한국기계가공학회지
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• 제11권4호
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• pp.154-159
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• 2012

Condition monitoring(CM) is a method based on Non-destructive test(NDT). Therefore, recently many kind of NDT were applied for CM. Acoustic emission(AE) is widely used for the early detection of faults in rotating machinery in these days also. Because its sensitivity is higher than normal accelerometers and it can detect low energy vibration signals. A machine tool consist of many parts such as the bearings, gears, process tools, shaft, hydro-system, and so on. Condition of Every part is connected with product quality finally. To increase the quality of products, condition monitoring of the components of machine tool is done completely. Therefore, in this paper, acoustic emission method is used to detect a machine fault seeded in a gearbox. The AE signals is saved, and power spectrums and feature values, peak value, mean value, RMS, skewness, kurtosis and shape factor, were determined through Matlab.