• 한국정밀공학회지
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• 제16권1호통권94호
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• pp.26-33
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• 1999

Automatic monitoring of cutting process is one of the most important technologies for increasing the stability and the reliability of unmanned manufacturing system. In this study, basic methods which use the acoustic emission (AE) signals and cutting forces were proposed to monitor flank wear (width of flank wear) quantiatively. First, in order to detect flank wear, it was investigated that the influence of cutting conditions, that is, cutting velocity, feed and depth of cut, on AE signals (${AE_rms}$) and cutting forces. Furthermore, the relation between flank wear and the measured signals (${AE_rms}$, cutting force) was discussed.

• Computers and Concrete
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• 제20권5호
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• pp.595-603
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• 2017

Piezoceramic transducers have been widely used in the health monitoring of civil structures. However, in most cases, they are used as sensors either to measure strain or receive stress waves. This paper proposes a method of using piezoelectric transducers as strain gauges and acoustic emission (AE) sensors simultaneously. The signals received by piezoceramic transducers are decomposed into different frequency components for various analysis purposes. The low-frequency signals are used to measure strain, whereas the high-frequency signals are used as acoustic emission signal associated with local damage. The b-value theory is used to process the AE signal in piezoceramic transducers. The proposed method was applied in the bending failure experiments of two reinforced concrete beams to verify its feasibility. The results showed that the extracted low-frequency signals from the piezoceramic transducers had good agreement with that from the strain gauge, and the processed high-frequency signal from piezoceramic transducers as AE could indicate the local damage to concrete. The experimental results verified the feasibly of structural health monitoring using piezoceramic transducers as strain gauges and AE sensors simultaneously, which can advance their application in civil engineering.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2000년도 춘계학술대회 논문집
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• pp.51-56
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• 2000

Demand for new nondestructive evaluations is growing to detect tensile crack growth behavior to predict long term performance of materials and structure in aggressive environments, especially when they are in non-visible area. Acoustic emission technique is well suited to these problems and has drawn a keen interests because of its dynamic detection ability, extreme sensitivity and location of growing defects. In this study, we analysed acoustic emission signals obtained in tensile test of high strength fire resistance steel for frame structure with time frequency analysis methods. The results obtained are summaries as follows ; In the T and TN specimen consisting of ferrite and pearlite grains, most of acoustic emission events were produced near yield point, mainly due to the dislocation activities during the deformation. However, B specimen under $600^{\circ}C$ - 10min had a two peak which was attribute to the presence of martensite phase. The first peak is before yield point the second is after yield point. The sources of second acoustic emission peak were the debonding of martensite-martensite interface and the micro-cracking of brittle martensite phase. In $600^{\circ}C$-30min to $700^{\circ}C$-60min specimens, many signals were observed from area before yield point and counts were decreased after yield point.

• 한국공작기계학회논문집
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• 제16권1호
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• pp.26-32
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• 2007

This study was carried out fusion-welded butt joints in SWS 490A high strength steel subjected to tensile test that load-deflection curve. The windowed or short-time Fourier transform(WFT or STFT) makes possible for the analysis of non-stationary or transient signals into a joint time-frequency domain and the wavelet transform(WT) is used to decompose the acoustic emission(AE) signal into various discrete series of sequences over different frequency bands. In this paper, for acoustic emission signal analysis to use a continuous wavelet transform, in which the Gabor wavelet base on a Gaussian window function is applied to the time-frequency domain. A wavelet transform is demonstrated and the plots are very powerful in the recognition of the acoustic emission features. As a result, the technique of acoustic emission is ideally suited to study variables which control time and stress dependent fracture or damage process in metallic materials.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2005년도 춘계학술대회 논문집
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• pp.342-348
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• 2005

This study was carried out fusion-welded butt joints in SWS 490A high strength steel subjected to tensile test that load-deflection curve. The windowed or short-time Fourier transform (WFT or SIFT) makes possible for the analysis of non-stationary or transient signals into a joint time-frequency domain and the wavelet transform (WT) is used to decompose the acoustic emission (AE) signal into various discrete series of sequences over different frequency bands. In this paper, for acoustic emission signal analysis to use a continuous wavelet transform, in which the Gabor wavelet base on a Gaussian window function is applied to the time-frequency domain. A wavelet transform is demonstrated and the plots are very powerful in the recognition of the acoustic emission features. As a result, the technique of acoustic emission is ideally suited to study variables which control time and stress dependent fracture or damage process in metallic materials.

• International Journal of Ocean Engineering and Technology Speciallssue:Selected Papers
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• 제4권1호
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• pp.51-55
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• 2001

The characteristics of elastic waves emanating from crack initiation in 2024 and 5052 aluminum alloys subject to static and fatigue loading are investigated through laboratory experiments. The objective of the study is to determine difference in the properties of the signals generated from static and fatigue tests 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 recoded using non-resonant, 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. Three distinct types of signals were observed. The waveforms and their power spectra were found to be dependent on the material and the type of fracture associated with the signals. Analysis of the waveforms indicated that some signals could be attributed to plastic deformation associated with static tests. The potential application of the approach in health monitoring of aging aircraft structures using a network of surface mounted broadband sensors is discussed.

• 한국생산제조학회지
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• 제6권4호
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• pp.46-53
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• 1997

This paper presents a method of detection localized defects on tapered roller bearing in main spindle of machine tool system. The feature vectors, i.e. statistical parameters, in time-domain analysis technique have been calculated to extract useful features from acoustic emission signals. These feature vectors are used as the input feature of an neural network to classify and detect bearing defects. As a results, the detection of bearing defect conditions could be sucessfully performed by using an neural network with statistical parameters of acoustic emission signals.

• 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.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 춘계학술대회논문집A
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• pp.73-78
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• 2000

On this study, the fatigue crack propagation of super duplex stainless steel is investigated in conditions of various volume fraction of austenite phase by changing heat treatment temperature. And we analysed acoustic emission signals during the fatigue test by time-frequency analysis methods. As the temperature of heat treatment increased, volume fraction of austenite decreased and coarse grain was obtained. The specimen heat treated at $1200^{\circ}C$ had longer fatigue life and slower rate of crack growth. As a result of time-frequency analyze of acoustic emission signals during fatigue test, main frequency was $200{\sim}300kHz$ having no correlation with heat treatment and crack length, and 500kHz was obtained by dimple and separate of inclusion

• Smart Structures and Systems
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• 제8권4호
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• pp.385-398
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• 2011

This paper discusses the applicability of Acoustic Emission (AE) to assess the damage in reinforced concrete (RC) structures subjected to complex dynamic loadings such as those induced by earthquakes. The AE signals recorded during this type of event can be complicated due to the arbitrary and random nature of seismicity and the fact that the signals are highly contaminated by many spurious sources of noise. This paper demonstrates that by properly filtering the AE signals, a very good correlation can be found between AE and damage on the RC structure. The basic experimental data used for this research are the results of fourteen seismic simulations conducted with a shake table on an RC slab supported on four steel columns. The AE signals were recorded by several low-frequency piezoelectric sensors located on the bottom surface of the slab. The evolution of damage under increasing values of peak acceleration applied to the shake table was monitored in terms of AE and dissipated plastic strain energy. A strong correlation was found between the energy dissipated by the concrete through plastic deformations and the AE energy calculated after properly filtering the signals. For this reason, a procedure is proposed to analyze the AE measured in a RC structure during a seismic event so that it can be used for damage assessment.