• Structural Engineering and Mechanics
• /
• v.26 no.3
• /
• pp.315-341
• /
• 2007

A sudden change of stiffness in a structure, associated with the events such as weld fracture and brace breakage, will cause a discontinuity in acceleration response time histories recorded in the vicinity of damage location at damage time instant. A new damage index is proposed and implemented in this paper to detect the damage time instant, location, and severity of a structure due to a sudden change of structural stiffness. The proposed damage index is suitable for online structural health monitoring applications. It can also be used in conjunction with the empirical mode decomposition (EMD) for damage detection without using the intermittency check. Numerical simulation using a five-story shear building under different types of excitation is executed to assess the effectiveness and reliability of the proposed damage index and damage detection approach for the building at different damage levels. The sensitivity of the damage index to the intensity and frequency range of measurement noise is also examined. The results from this study demonstrate that the damage index and damage detection approach proposed can accurately identify the damage time instant and location in the building due to a sudden loss of stiffness if measurement noise is below a certain level. The relation between the damage severity and the proposed damage index is linear. The wavelet-transform (WT) and the EMD with intermittency check are also applied to the same building for the comparison of detection efficiency between the proposed approach, the WT and the EMD.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.6 no.7
• /
• pp.1126-1132
• /
• 2002

In this paper, we propose a new scheme of motion tracking based on fuzzy inference (Fl) and wavelet transform (WT) from image sequences. First, we present a WT to segment a feature extraction of dynamic image . The coefficient matrix for 2-level DWT tent to be clustered around the location of Important features in the images, such as edge discontinuities, peaks, and corners. But these features are time varying owing to the environment conditions. Second, to reduce the spatio-temperal error, We develop a fuzzy inference algorithm. Some experiments are performed 0 testify the validity and applicability of the proposed system As a result, proposed method is relatively simple compared with the traditional space domain method. It is also well suited for motion tracking under the conditions of variation of illumination.

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.32.1-32
• /
• 2002

The fault monitoring technique is presented for identifying the status of the agitator driving system in thermal reduction reactor. For identifying a fault such as bearing defect or clearance blocking, Wavelet transform (WT) is applied to vibration signals and features are extracted. For classification, the fuzzy ARTMAP is employed. With the features from WT, a single training epoch and a single learning iteration are sufficient for the fuzzy ARTMAP to classify the faults. The test results show the perfect classification though some features extracted from the test data are distorted against those in the training data

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2002.11a
• /
• pp.217-221
• /
• 2002

In this paper, we propose a new scheme of motion tracking based on fuzzy inference (FI)and wavelet transform (WT) from image sequences. First, we present a WT to segment a feature extraction of dynamic image . The coefficient matrix for 2-level DWT tent to be clustered around the location of important features in the images, such as edge discontinuities, peaks, and corners. But these features are time varying owing to the environment conditions. Second, to reduce the spatio-temporal error, We develop a fuzzy inference algorithm. Some experiments are peformed to testify the validity and applicability of the proposed system. As a result, proposed method is relatively simple compared with the traditional space domain method. It is also well suited for motion tracking under the conditions of variation of illumination.

• Proceedings of the Korean Society For Composite Materials Conference
• /
• 2003.10a
• /
• pp.158-162
• /
• 2003

The PVDF(polyvinylidene fluoride) film sensor as one of smart sensors has good characteristics to detect the impact damages of composite structures. The capabilities of the PVDF film sensor for evaluating impact behaviors and damages of Gr/Ep laminates subjected to low-velocity impact were examined. From sensor signals, the specific wave-forms implying the damage were detected. The wavelet transform(WT) and Short Time Fourier Transform(STFT) were used to decompose the piezoelectric sensor signals in this study. The impact behaviors of Gr/Ep laminates were simulated and the impact forces were reconstructed using the sensor signals. Finally, the impact damages were predicted by finite element analysis with the reconstructed forces. For experimental verification, a series of low-velocity impact tests from low energy to damage-induced energy were carried-out. The extent of damage in each case was examined by means of ultrasonic C-scan and the measured damage areas were agreed well with the predicted areas by the F.E.A.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.3
• /
• pp.729-739
• /
• 2015

An algorithm for fault detection and classification method for wide-area protection in Korean transmission systems is proposed. The modeling of 345-kV and 765-kV Korean power system transmission networks using the Electro Magnetic Transient Program - Restructured Version (EMTP-RV) is presented and the algorithm for fault detection and classification in transmission lines is developed. The proposed algorithm uses the Wavelet Transform (WT) and Singular Value Decomposition (SVD). The Singular value of Approximation coefficient (SA) and part Sum of Detail coefficient (SD) are introduced. The characteristics of the SA and SD at the fault conditions are analyzed and used in the algorithm for fault detection and classification. The validation of the proposed algorithm is verified by various simulation results.

• Journal of Internet Computing and Services
• /
• v.8 no.1
• /
• pp.125-132
• /
• 2007

This paper presents an approach to detect premature ventricular contractions(PVC) using the neural network with weighted fuzzy membership functions(NEWFM), NEWFM classifies normal and PVC beats by the trained weighted fuzzy membership functions using wavelet transformed coefficients extracted from the MIT-BIH PVC database. The eight most important coefficients of d3 and d4 are selected by the non-overlap area distribution measurement method. The selected 8 coefficients are used for 3 data sets showing reliable accuracy rates 99,80%, 99,21%, and 98.78%, respectively, which means the selected input features are less dependent to the data sets. The ECG signal segments and fuzzy membership functions of the 8 coefficients enable input features to interpret explicitly.

• The Journal of the Acoustical Society of Korea
• /
• v.20 no.3
• /
• pp.34-41
• /
• 2001

In an IMBE (Improved Multi-band Excitation) speech coder, initial pitch estimation occupies most of the total computing time for the coder due to complex cost function and exhaustive search over candidate pitches. Future frames in initial pitch estimation cause inevitable time delay. Therefore, it is difficult to implement a real-time coder. Furthermore, unvoiced frames use the unnecessary pitch estimation as in the voiced frames. In this paper, each frame is determined voiced or unvoiced by Dyadic Wavelet Transform (DyWT) and, then, initial pitch estimation is performed only for voiced frame. Therefore different pitch estimation algorithms are employed between voiced and unvoiced frames incurring reduced time delay at transmitter and receiver. Simulation result show that the relative complexity of initial pitch estimation is reduced by 23％, and the processing time decreases down to 1/10 ∼ 1/1l of the IMBE coder while speech quality is almost maintained.

• Composites Research
• /
• v.16 no.3
• /
• pp.58-67
• /
• 2003

To perform the realtime strain and fracture monitoring of the smart composite structures, two optical fiber sensor systems are proposed. The two types of the coherent sources were used for fracture signal detection - EDFA with FBG and EDFA with Fabry-Perot filter. These sources were coupled to EFPI sensors imbedded in composite specimens. To understand the characteristics of matrix crack signals, at first, we performed tensile tests using surface attached PZT sensors by changing the thickness and width of the specimens. This paper describes the implementation of time-frequency analysis such as short time Fourier transform (STFT) and wavelet transform (WT) for the quantitative evaluation of fracture signals. The experimental result shows the distinctive signal features in frequency domain due to the different specimen shapes. And, from the test of tensile load monitoring using optical fiber sensor systems, measured strain agreed with the value of electric strain gage and the fracture detection system could detect the moment of damage with high sensitivity to recognize the onset of micro-crack fracture signal.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.38 no.5
• /
• pp.65-76
• /
• 2001

In this paper, performance of frequency-based watermarking methods is compared, which are used to protect copyright of image data. For performance comparison of each transform method, a test image is transformed into frequency domain by a full- and block-discrete cosine transforms and wavelet transform, and after general image processing, robustness of each transform is evaluated with using the same watermark signals. Simulation results show that the watermarking method based on DCTs are more robust than WT. Especially, $8{\times}8$ BDCT is most robust for JPEG lossy compression and sharpening, while $8{\times}8$ FDCT is best. for smoothing and scaling. In addition, watermarking based on BDCT shows decreasing robustness for a larger block size, compared with general image processing.