• Journal of the Korean Society of Industry Convergence
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• v.25 no.3
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• pp.325-331
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• 2022

In this study, austenitic 316L stainless steel was rolled at three different temperatures (100℃, -50℃, -196℃) at five rolling degree (0, 16, 33, 50, 66 and 80%). The rolled specimen was examined for micro structure, and the volume fraction and mechanical properties were evaluated. In particular, the rolling specimen detected the elastic wave generated in tensile and investigated the relationship between the rolling degree and the dominant frequency. As the rolling degree increased, austenite decreased and martensite increased. The volume fraction of martensite more increased at lower temperatures, but increased rapidly at the rolling degree of 50% of all rolling temperature. Tensile strength increased rapidly with the increase of the rolling degree, and was larger at lower temperatures. The elongation decreased sharply to the rolling degree of 33%, but decreased gently thereafter. The dominant frequency highly appeared as the volume fraction of martensite increased, but the dominant frequency was higher at the low temperature rolling temperature. A similar trend was also observed in the relationship between tensile strength and dominant frequency.

• Smart Structures and Systems
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• v.33 no.6
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• pp.415-430
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• 2024

To control vertical and lateral compound vibration simultaneously using an integrated smart controller, passive tuned mass damper (TMD) and tuned liquid damper (TLD) are updated and combined to an adaptive-passive TMD-TLD (AP-TMD-TLD) system. As for the vertical AP-TMD part on top of the vertical spring, it can retune itself through varying the level of liquid in the tank to adjust its mass, while the lateral AP-TLD part at the bottom of the vertical spring can retune itself by changing the level of liquid. Further, for multimodal response control, the multiple AP-TMD-TLD (MAP-TMD-TLD) system is proposed as well. Each AP-TMD-TLD in the system can identify the structural vertical and lateral modal frequencies through the wavelet-transform (WT) based algorithm and retune its vertical and lateral natural frequencies both through adjusting the level of liquid in the AP-TMD and AP-TLD parts respectively. A cantilever cable-stayed landscape bridge which is sensitive to both human-induced and wind-induced vibrations is presented as a case study. For comparison, initial parameters of MAP-TMD-TLD are mistuned. Results show that the presented system can retune its vertical and lateral frequencies precisely, while the retuned system has a better bi-directional compound control effect than the mistuned system before the retuning operation and can improve the serviceability significantly.

• Composites Research
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• v.18 no.6
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• pp.26-33
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• 2005

The mechanical properties of composite materials may severely degrade 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 considerable 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 PVDF(polyvinylidene fluoride) film sensors were used for monitoring high-velocity 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 shows how various sensing techniques, PVDF sensor in particular, can be used to characterize high-velocity impact damage in advanced composite.

• Journal of Sensor Science and Technology
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• v.29 no.4
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• pp.249-254
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• 2020

It is difficult to control children who exhibit negative behavior in dental clinics. Various methods are used for preventing pediatric dental patients from being afraid and for eliminating the factors that cause psychological anxiety. However, when it is difficult to apply this routine behavioral control technique, sedation therapy is used to provide quality treatment. When the sleep anesthesia treatment is performed at the dentist's clinic, it is challenging to identify emergencies using the current breath detection method. When a dentist treats a patient that is under the influence of an anesthetic, the patient is unconscious and cannot immediately respond, even if the airway is blocked, which can cause unstable breathing or even death in severe cases. During emergencies, respiratory instability is not easily detected with first aid using conventional methods owing to time lag or noise from medical devices. Therefore, abnormal breathing needs to be evaluated in real-time using an intuitive method. In this paper, we propose a method for identifying abnormal breathing in real-time using an intuitive method. Respiration signals were measured using a 3M Littman electronic stethoscope when the patient's posture was supine. The characteristics of the signals were analyzed by applying the signal processing theory to distinguish abnormal breathing from normal breathing. By applying a short-time Fourier transform to the respiratory signals, the frequency range for each patient was found to be different, and the frequency of abnormal breathing was distributed across a broader range than that of normal breathing. From the wavelet transform, time-frequency information could be identified simultaneously, and the change in the amplitude with the time could also be determined. When the difference between the amplitude of normal breathing and abnormal breathing in the time domain was very large, abnormal breathing could be identified.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.7
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• pp.51-59
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• 2004

An experimental procedure to identify failure modes of impact damage using sensor signals and to analyze their general features is examined. A series of low-velocity impact tests from low energy to damage-induced high energy were performed on the instrumented drop weight impact tester to monitor the stress wave signals due to failure modes such as matrix cracking, delamination, and fiber breakage. The wavelet transform(WT) and Short Time Fourier Transform(STFT) are used to decompose the piezoelectric sensor signals in this study. The extent of the damage in each case was examined by means of a conventional ultrasonic C-scan. The PVDF sensor signals are shown to carry important information regarding the nature of the impact process that can be extracted from the careful signal processing and analysis.