• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.1
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• pp.57-65
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• 2023

A vibration response-based detection system was used to investigate the adhesive areas of single-lap joints using a nonlinear transformation approach for deep learning. In industry or engineering fields, it is difficult to know the condition of an invisible part within a structure that cannot easily be disassembled and the conditions of adhesive areas of adhesively bonded structures. To address these issues, a detection method was devised that uses nonlinear transformation to determine the adhesive areas of various single-lap-jointed specimens from the vibration response of the reference specimen. In this study, a frequency response function with nonlinear transformation was employed to identify the vibration characteristics, and a virtual spectrogram was used for classification in convolutional neural network based deep learning. Moreover, a vibration experiment, an analytical solution, and a finite-element analysis were performed to verify the developed method with aluminum, carbon fiber composite, and ultra-high-molecular-weight polyethylene specimens.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.342-345
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• 2005

To detect external acoustic signal, fiber optic sensor array using Fabry-Perot interferometer which had benefit of minimize and light-weight was used. The sensor head has 1cm in length, total length of fiber is 9.5cm, and the sensor supported at both ends, simply. External sound applied in lateral direction and detected two signals were compared each other. It was confirmed that the Fabry-Perot interferometric sensor array detected acoustic signal, effectively.

• Journal of Korean Society for Quality Management
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• v.36 no.2
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• pp.36-44
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• 2008

In this paper a novel feature extraction and selection is carried out in order to improve the discriminating capability between healthy and damaged structure using vibration signals. Although many feature extraction and selection algorithms have been proposed for vibration signals, most proposed approaches don't consider the discriminating ability of features since they are usually in unsupervised manner. We proposed a novel feature extraction and selection algorithm selecting few wavelet coefficients with higher class discriminating capability for damage detection and class visualization. We applied three class separability measures to evaluate the features, i.e. T test statistics, divergence, and Bhattacharyya distance. Experiments with vibration signals from truss structure demonstrate that class separabilities are significantly enhanced using our proposed algorithm compared to other two algorithms with original time-based features and Fourier-based ones.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.6 s.99
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• pp.697-705
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• 2005

Vibration-based damage identification method using embedded sensitivity functions is discussed. The theory of embedded sensitivity functions is reviewed and applied to identify damage in a three degree-of-freedom system and a metallic panel. Embedded sensitivity functions are algebraic combinations of measured frequency response functions that reflect changes in the response of mechanical systems when mass, damping or stiffness parameters are changed. By comparing the embedded sensitivity functions with finite difference functions using undamaged and damaged frequency response functions, damage is shown to be properly detected, located and quantified in theory and practice assuming that structures of interest are only damaged in one location. Simulated and experimental results indicate that the technique is most effective when changes to frequency response functions are small to avoid distorsions in the estimated perturbations due to variations in the sensitivity functions.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.370-375
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• 2003

Optical fiber vibrations sensors (OFVSs) and extrinsic Fabry-Perot interferometer (EFPI) were used in damage monitoring of fiber-metal laminates(FML). The optical fiber vibration sensor and EFPI were applied in order to detect and evaluate the strain, damage and failure of FML. Damages in composites, such as matrix cracks, delamination and fiber breakage may occur as a result of excessive load, fatigue and low-velocity impacts. Tensile and indentation test was performed with the measurement of optical signal and acoustic emission (AE). The signals of the optical fiber vibration sensor due to damages were quantitatively evaluated by wavelet transform. It was found that damage information of comparable in quality to acoustic emission data could be obtained from the optical fiber vibration sensor signals.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.2
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• pp.179-184
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• 2013

In this article, we introduce the study case of technology that can automatically compensate the errors of these factors of a machine during processing on the machine tool's CNC(Computerized Numerical Controller) in real time. The biggest factors that lower the machining accuracy are thermal deformation and chatter vibration. This study is related to the detection and compensation of thermal deformation and chatter vibration that can compensate for faster and produce processed goods with more precision by autonomous compensation. In addition, this study is related to the active control of vibration during machining, monitoring of cutting force and auto recognition of machining axes origin. Thus, we attempt to introduce the related contents of the development we have made in this article.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.1127-1132
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• 2000

Impulsive acoustic and vibration signals within rotating machinery are often induced by irregular impacting. The detection of these impulses can be useful for fault diagnosis purposes. Recently there has been an increasing trend towards the use of higher order statistics for fault detection within mechanical systems based on the observation that impulsive signals tend to increase the kurtosis values. This paper considers the use of the third and fourth order Wigner moment spectra, called the Wigner bi- and tri- spectra receptively, for analysing such signals. Expressions for the auto-and cross-terms in these distributions are presented and discussed. It is shown that the Wigner trispectrum is a more suitable analysis tool and it performance is compared to its second order counterpart for detecting impulsive signals. These methods are also applied to measured data sets from an industrial gearbox.

• Proceedings of the KWS Conference
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• 2006.05a
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• pp.148-150
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• 2006

In this paper, the applicability of an UET(ultrasound excited thermography) for a defect detection of the welded receptacle is described. An UET(ultrasound excited thermography) is a defect-selective and fast imaging tool for damage detection. A high power ultrasound-excited vibration energy with pulse durations of 280ms is injected into the outer surface of the welded receptacle made of Al material. An ultrasound vibration energy sent into the welded receptacle propagate inside the sample until they are converted into the heat in the vicinity of the defect. The injection of the ultrasound excited vibration energy results in heat generation so that the defect is turned into a local thermal wave transmitter. Its local heat emission is monitored by the thermal infrared camera. And they are processed by the image recording system. Measurement was performed on aluminum receptacle welded by using Nd:YAG laser. The observed thermal image revealed two area of defects along the welded seam.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2003.04a
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• pp.42-45
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• 2003

Optical fiber vibrations sensors (OFVSs) and extrinsic Fabry-Perot interferometer (EFPI) were used in damage monitoring of fiber-metal laminates(FML). The optical fiber vibration sensor and EFPI were applied in order to detect and evaluate the strain, damage and failure of FML. Damages in composites, such as matrix cracks, delamination and fiber breakage may occur as a result of excessive load, fatigue and low-velocity impacts. Indentation test was performed with the measurement of optical signal and acoustic emission (AE). The signals of the optical fiber vibration sensor due to damages were quantitatively evaluated by wavelet transform. It was found that damage information of comparable in quality to acoustic emission data could be obtained from the optical fiber vibration sensor signals.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.1182-1188
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• 2001

The objective of this paper is to show the effectiveness of the wavelet transform by means of its capability to estimate the Lipschitz exponent. In particular, we show that the magnitude of the Lipschitz exponent can be used as a useful tool estimating the damage extent. An effective method based on the Lipschitz exponent is proposed and we present the results investigated both numerically and experimentally. The continuous wavelet transform by a Mexican hat wavelet having two vanishing moments is utilized for the estimation of the Lipschitz exponent.