• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06c
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• pp.185-188
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• 1998

실제의 음성 인식 및 음성 통신 등의 음성 처리 시스템에서는 음성 신호를 손상시키는 배경 잡음 신호의 존재로 그 성능이 많이 저하된다. 특히 차량 내와 같은 잡음이 극심한 상황에서는 전처리 부분에서 이러한 잡음을 제거시켜 주어야한다. 본 연구는 자동차 내의 배경 잡음에 의해 손상된 음성에서 배경 잡음을 주파수 차감에 의하여 제거시킨다. 특히 음성 정보의 손실이 적은 잡음 추정 방법으로 가중치를 이용하여 잡음을 추정하는 가중치 주파수 차감법을 이용하였다. 이러한 가중치 주파수 차감법 사용의 전제 조건은 잡음의 변화가 완만한 경우에 적당하다. 그러나 실제적인 상황에서 배경잡음신호의 변화가 큰 경우가 존재한다. 이러한 이유에서 본 연구는 잡은 추정시 잡음 추정값을 이용하여 추정 잡음 경계값을 적응적으로 변화하는 차감법을 제안한다. 이러한 방법은 추정된 잡음 신호의 변화율을 이용하여 경계값을 상황에 따라 적응적으로 변화시키는 방법이다. 모의 실험에 의하여 고정적인 경계값을 갖는 가중치 주파수 차감법에 비해 제안한 적응적 경계값을 갖는 가중치 주파수 차감법의 출력 SNR이 증가함을 확인하였고, 음성 인식 시스템에 정용한 인식 실험에서도 성능이 향상됨을 확인하였다.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.6 s.52
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• pp.57-65
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• 2006

This paper presents hybrid structural damage monitoring system which performs both global damage assessment of structure and damage detection of local structural joints. Hybrid damage monitoring system is composed of vibration-based technique and electro/mechanic impedance technique. Vibration-based technique detects global characteristic change ot structure using modal characteristic change of structure, and electro/mechanical impedance technique detects damage existence of local structural joints using impedance change of PZT sensor. For the verification of the proposed hybrid monitoring system, a series of damage scenarios are designed to loosened bolts situations of the structural joints, and acceleration response and impedance response signatures are measured. The proposed hybrid monitoring system is implemented to monitor global damage-state and local damages in structural joints.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.5
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• pp.391-398
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• 2016

Acoustic emission (AE) is one of the most powerful techniques for detecting damages and identify damage location during operations. However, in case of the source location technique, there is some limitation in conventional AE technology, because it strongly depends on wave speed in the corresponding structures having heterogeneous composite materials. A compressed natural gas(CNG) pressure vessel is usually made of carbon fiber composite outside of vessel for the purpose of strengthening. In this type of composite material, locating impact damage sources exactly using conventional time arrival method is difficult. To overcome this limitation, this study applied the previously developed Contour D/B map technique to four types of CNG storage tanks to identify the source location of damages caused by external shock. The results of the identification of the source location for different types were compared.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5A
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• pp.421-431
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• 2009

This paper is the study on the verification of structural health monitoring (SHM) algorithm based on the ultrasonic guided wave. An active inspection system using Lamb wave (LW) for SHM was considered. The basic study about the application of this algorithm was performed for detecting the circular notch defect in steel plate. LW testing technique, pitch-catch method, was used for interpretation of circular notch defect with depth of 50% of plate thickness and 7 mm width. Damage characterization takes place by comparing $S_0$ mode sensor signals collected before and after the damage event. By subtracting the signals of both conditions from each other, a scatter signal is produced which can be used for damage localization. The continuous Gabor wavelet transform is used to attain the time between the arrivals of the scatter and sensor signals. A new practical damage monitoring algorithm, based on damage monitoring polygon and pitch-catch method, has been proposed and verified with good accuracy. The possible damage location can be estimated by the average on calculated location points and the damage extent by the standard deviation.

• Journal of Korean Society of Disaster and Security
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• v.11 no.2
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• pp.53-60
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• 2018

To diagnosis the local damages of the steel plates, magnetic flux leakage (MFL) method that is known as a adaptable non-destructive evaluation (NDE) method for continuum ferromagnetic members was applied in this study. To analysis the sensitivity according to thickness of steel plate in MFL method based damage diagnosis, several steel plate specimens that have different thickness were prepared and three depths of artificial damage were formed to the each specimens. To measured the MFL signals, a MFL sensor head that have a constant magnetization intensity were fabricated using a hall sensor and a magnetization yoke using permanent magnets. The magnetic flux signals obtained by using MFL sensor head were improved through a series of signal processing methods. The capability of local damage detection was verified from the measured MFL signals from each damage points. And, the peak to peak values (P-P value) extracted from the detected MFL signals from each thickness specimen were compared each other to analysis the MFL based local damage detection sensitivity according to the thickness of steel plate.

• Composites Research
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• v.14 no.1
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• pp.1-7
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• 2001

In this study, damage evaluation of glass fiber reinforced thermoplastic composites was investigated with acoustic emission method. Specimens of 1.7mm thickness laminate were made from PET and 7 layers o171ass fabrics. Notch and impact loading were added to the specimen and normal tensile test and tensile test with the dead load were carried out. AE signal was measured as the functions of notch ratio to the width0 and impact energy in order to find out the correlation between fracture mode and AE parameters. The result has shown that low amplitude of AE signal was due to the microcrack of matrix and its growth, whereas the amplitude in the mid range was the response to the delamination and interfacial separation. In the range of high amplitude above 90dB. the fracture of glass fabric was found. Tensile strength decreased with increasing notch ratio to the width and impact energy because of tile effect or delamination, the cracking of matrix and stress concentration. In proportion to the size of damaged area. AE signal showed its wider range of frequency and energy as well as increased number of hits.

• Journal of IKEEE
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• v.24 no.4
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• pp.1122-1128
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• 2020

Bandwidth Extension refers to restoring and expanding a narrow band signal(NB) that is damaged or damaged in the encoding and decoding process due to the lack of channel capacity or the characteristics of the codec installed in the mobile communication device. It means converting to a wideband signal(WB). Bandwidth extension research mainly focuses on voice signals and converts high bands into frequency domains, such as SBR (Spectral Band Replication) and IGF (Intelligent Gap Filling), and restores disappeared or damaged high bands based on complex feature extraction processes. In this paper, we propose a model that outputs an bandwidth extended signal based on an autoencoder among deep learning models, using the residual connection of one-dimensional convolutional neural networks (CNN), the bandwidth is extended by inputting a time domain signal of a certain length without complicated pre-processing. In addition, it was confirmed that the damaged high band can be restored even by training on a dataset containing various types of sound sources including music that is not limited to the speech.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.8
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• pp.780-788
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• 2009

AE technique was applied to the static structural test of the composite wing structure to evaluate the structural integrity and damage. During the test, strain and displacements measurement technique were used to figure out for static structural strength. AE parameter analysis and source location technique were used to evaluate the internal damage and find out damage source location. Design limit load test, the 1st and 2nd design ultimate load tests and fracture test were performed. Main AE source was detected by an sensor attached on skin near by front lug. Especially, at the 1st design ultimate test, strain and displacements results didn't show internal damage but AE signal presented a phenomenon that the internal damage was formed. At the fracture test, AE activities were very lively, and strain and displacements results showed a tendency that the load path was changed by severe damage. The internal damage initiation load and location were accurately evaluated during the static structural test using AE technique. It is certified from this paper that AE technique is useful technique for evaluation of internal damage at static structural strength test.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2009.04a
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• pp.2-5
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• 2009

본 논문에서는 오실레이터 센서와 램파 센서를 결합하여 구조물 손상 진단을 위한 통합된 압전 센서 시스템을 제안한다. 구조물 손상으로 인한 공진주파수 변화를 관측할 수 있는 오실레이터 센서는 손상 정도에 민감하게 반응하고 구조가 단순한 장치이지만 측정 범위가 센서 주위로 제한되는 특성을 가진다. 반면에 램파를 이용한 진단 시스템은 원거리에 위치한 구조물의 손상부를 감지하기에 유용하다. 본 논문에서는 오실레이터 센서를 이용한 취약 지점의 국부적인 손상 진단 방식과 램파를 이용한 광역적인 손상 진단 방식을 결합하여 각 시스템의 장점들을 활용할 수 있는 센서 시스템의 적용가능성을 연구하였다. PZT소자를 알루미늄 판에 적용하여, 알루미늄판의 손상 정도에 따른 오실레이터 공진주파수의 변화와 램파 신호의 Time of flight, 그리고 진폭의 변화를 이용하여 구조물 손상형태의 판별 가능성을 제시하고 실험을 통하여 그 타당성을 검증하였다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.6
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• pp.615-632
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• 2008

The bridge health monitoring has become an important research topic in conjunction with damage assessment and safety evaluation of structures owing to the improvement of structural modeling techniques incorporating response measurements and the advancements in signal analysis and information processing capabilities. The bridge monitoring systems are generally composed of hardwares such as sensors, data acquisition equipment, data transmission systems, etc, and softwares such as signal processing, damage assessment, display and management, etc. In this paper, the research and development(R&D) activities on the information processing for structural health monitoring of bridges are reviewed. After a brief introduction to the process of bridge health monitoring, various information processing techniques including various signal processing and damage detection algorithms are introduced in detail. Several challenges addressing critical issues in the current bridge health monitoring system and future R&D activities are discussed.