• Proceedings of the Korean Society For Composite Materials Conference
• /
• 2005.04a
• /
• pp.13-16
• /
• 2005

The mechanical properties of composite materials may degrade severely in the presence of damage. Especially, the high-velocity impact such as bird strike, a hailstorm, and a small piece of tire or stone during high taxing, can cause sever damage to the structures and sub-system in spite of a very small mass. However, it is not easy to detect the damage in composite plates using a single technique or any conventional methods. In this paper, the PYDF(polyvinylidene fluoride) film sensors and strain gages were used for monitoring impact damage initiation and propagation in composite laminates. The WT(wavelet transform) and STFT(short time Fourier transform) are used to decompose the sensor signals. A ultrasonic C-scan and a digital microscope are also used to examine the extent of the damage in each case. This research demonstrate how various sensing techniques, PVDF sensor in particular, can be used to characterize high-velocity impact damage in advanced composites.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.21 no.3
• /
• pp.261-268
• /
• 2001

An investigation on nondestructive evaluation of thermal stress-nduced damage in the composite laminates (3mm in thickness and $[+45_6/-45_6]_s$ lay-up angles) has been performed using the thermo-acoustic emission technique. Reduction of thermo-AE events due to repetitive thermal load cycles showed a Kaiser effect. An analysis of the thermo-AE behavior determined the stress free temperature of composite laminates. Fiber fracture and matrix cracks were observed using the optical microscopy, scanning electron microscopy and ultrasonic C-sean. Short-Time Fourier Transform of thermo-AE signals offered the time-frequency characteristics which might classily the thermo-AE as three different types to estimate the damage processes of the composites.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.24 no.4
• /
• pp.331-340
• /
• 2004

Deployment of an advanced on-line monitoring of the component integrity offers a prospect of improved performance, enhanced safety, and reduced overall cost for nuclear power plants. Ultrasonic guided waves have been known as one of the promising techniques that could be utilized for on-line monitoring. The present work is aimed at developing a new method for on-line monitoring of the pipes during the operation period of nuclear power plants. For this purpose, the steam generator (S/G) tube was selected as an object of tile experiment. Dispersion corves and the incident angles corresponding to the specific modes were calculated for the S/G tube. The modes of guided waves were identified by the time-frequency diagrams obtained by the short time Fourier transform. It was experimentally confirmed that there was no mode conversion when the ultrasonic guided waves passed over the curved region of the S/G tube. An optimum mode of guided wave for the S/G tube was suggested and verified by the experiment.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2010.05a
• /
• pp.578-579
• /
• 2010

최근 내연 기관에서 엔진상태 및 잠재적인 결함의 발견을 위해 연료분사, 실린더 내 연소과정, 실린더 내부와 피스톤 마모상태, 흡 배기 밸브 및 과급기 (turbocharger) 등의 상태 모니터링을 통해서 결함에 대한 진단 및 경향관리에 대한 연구들이 진행되고 있다. 본 연구에서는 기 개발된 선박용 대형디젤엔진에 대한 상시 모니터링 시스템을 이용하여 엔진상태 및 잠재적인 결함을 진단하고자 하였으며, 일차적으로 가속도 신호를 이용하여 실린더 내 연소과정에서 정상적인 상태와 착화실패에 따른 진동 양상을 비교 분석하였다. 신호 분석 기법으로 시간-주파수 분산 기법들은 충격파 신호인 엔진 폭발신호를 분석하는데 적합하였으며, 그 기법들 중 Short Time Fourier Transform 기법과 Wavelet Transform 기법을 이용하였다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2003.11a
• /
• pp.361-364
• /
• 2003

The safe operation and reliable maintenance of nuclear power plants is one of the most fundamental and important tasks. It is known that a loose part such as a disengaged and drifting metal inside of reactor coolant systems might lead to a serious damage because of their impact on the components of the coolant system. In order to estimate the impact position of a loose par, three accelerometers attached to the wall of the coolant system have been used. These accelerometers measure the vibration of the coolant system induced by loose part impact. In the conventional analysis system, the low pass filtered version of the vibration data was used for the estimation of the position of a loose part. It is often difficult to identify the initial point of the impact signal by using just a low passed time signal because the impact wave is dispersed during propagation into the sensor. In this paper, the impact signal is analysed by use of various time frequency methods including the short time Fourier transform(STFT), the wavelet transform, and the Wigner-Vill distribution for finding a convenient way to identify the starting point of a impact signal and their advantages and limits are discussed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2005.11a
• /
• pp.513-517
• /
• 2005

The condition monitoring of rotating machinery such as turbines, pumps and compressors, determine what repairs are needed to avoid shutdown and disassembly of the machine in an industrial plant Many diagnosis methods have been developed for use when the machine is running at steady state, the stationary condition. But much information can be gained about a rotor's condition during non-stationary conditions such as run-up and run-down. Order tracking analysis is a powerful tool for analyzing the condition of a rotating machine when its speed changes over time. Powerful OTA using digital signal processing has some advantages(cheap hardware, the powerful methods, the accurate post processing) and also some disadvantages(calculation time, high speed sampling). New OTA tool based on the chirplet transform is similar to the short time Fourier transform. But, it has good resolution at high speed like other OTA methods based STFT and more resolution for constant frequency components than re-sampling OTA.

• Korean Journal of Remote Sensing
• /
• v.38 no.5_1
• /
• pp.587-596
• /
• 2022

Sea levels are rising as a result of climate change, and low-lying areas along the coast are at risk of flooding. Therefore, we tried to investigate the relationship between sea level change and climate indices using satellite altimeter data (Topex/Poseidon, Jason-1/2/3) and southern oscillation index (SOI) and the Pacific decadal oscillation (PDO) data. If time domain data were converted to frequency domain, the original data can be analyzed in terms of the periodic components. Fourier transform and Wavelet transform are representative periodic analysis methods. Fourier transform can provide only the periodic signals, whereas wavelet transform can obtain both the periodic signals and their corresponding time location. The cross-wavelet transformation and the wavelet coherence are ideal for analyzing the common periods, correlation and phase difference for two time domain datasets. Our cross-wavelet transform analysis shows that two climate indices (SOI, PDO) and sea level height was a significant in 1-year period. PDO and sea level height were anti-phase. Also, our wavelet coherence analysis reveals when sea level height and climate indices were correlated in short (less than one year) and long periods, which did not appear in the cross wavelet transform. The two wavelet analyses provide the frequency domains of two different time domain datasets but also characterize the periodic components and relative phase difference. Therefore, our research results demonstrates that the wavelet analyses are useful to analyze the periodic component of climatic data and monitor the various oceanic phenomena that are difficult to find in time series analysis.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.6
• /
• pp.1120-1129
• /
• 2015

In this paper, we propose an algorithm to detect movement noise in PPG(Photoplethysmography) measurements. Movement noise significantly deteriorate PPG signals in measurement, so that a movement noise detection algorithm is critical before using measured PPG signals for applications such as diagnosis. To detect movement noise, we apply wavelet transform to PPG signals instead of short-time Fourier transform and decide if the measured signlas include movement noise. To that end, we adaptively choose a wavelet, which is the most similar to the subject's PPG pattern. In the case when movement noise is intentionally added in the 20% and 30% of the total experiment time, our algorithm detects time-slots including movement and outperforms previous works.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.23 no.5
• /
• pp.429-438
• /
• 2003

The effects of fiber orientation on acoustic emission(AE) characteristics have been studied for the unidirectional and satin-weave, continuous glass-fiber reinforced plastic(UD-GFRP and SW-GFRP) tensile specimens. Reflection and transmission optical microscopy was used for investigation of the damage zone of specimens. AE signals were classified as different types by using short time fourier transform(STFT) : AE signals with high intensity and high frequency band were due to fiber fracture, while weak AE signals with low frequency band were due to matrix and interfacial cracking. The feature in the rate of hit-events having high amplitudes showed a process of fiber breakages, which expressed the characteristic fracture processes of individual fiber-reinforced plastics with different fiber orientations and with different notching directions. As a consequence, the fracture behavior of the continuous GFRP could be monitored as nondestructive evaluation(NDE) through the AE technique.

• Journal of the Korea Convergence Society
• /
• v.11 no.11
• /
• pp.249-255
• /
• 2020

This study developed the health monitoring method of press process using the acoustic emission (AE) sensor and high-pass filter. Also, the AE parameters such as ring-down count and peak amplitude are used. Based on this AE signal, the AE parameters were acquired and was utilized to detect the crack of the specimen. Since the defect detection is difficult due to noise and low magnitude of signal, the signal noise and press operation frequency were checked through the Short Time Fourier Transform(STFT) and damped. High-pass Filtering data was applied to AE parameters to select effective parameters. By using this signal processing techniques, the proposed AE parameters could improve the performance of defect detection in the press process.