• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.9
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• pp.943-949
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• 2009

Many studies for measuring vibration using image signal are suggested. These methods can measure vibration of multi-points simultaneously. However, it has the disadvantage that is very sensitive to an environment. If the measured environment is not good, image signals can be measured including much background noise. So, it is difficult to obtain accurate vibration from the measured image signals. Another problem is that camera imaging has a resolution limit. Because the resolution of the camera image is relatively much lower than that of a data acquisition system, accurate measuring vibration cannot be performed. In this paper, we proposed the enhanced technique for measuring vibration using camera signal. The key word of this paper is a curve fitting. The curve fitting can exactly detect the measurement line of interested object. So, we can measure the vibration in noisy environment. Also, it can overcome the resolution limit.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.12
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• pp.1145-1151
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• 2007

In this paper, vibration sources of an electric forklift are identified and the forklift vibrations are reduced by structural modification. For vibration identification, vibration signals are measured by an accelerometer when the forklift is moving. These signals are presented in a waterfall plot in order to find the dependency of frequency components on the forklift speed. It is found that main vibration source is tire pattern excitation. From some experiments and finite element analyses, it is also found that resonances occur because the natural frequencies of the forklift exist in usual driving speed range. To shift the natural frequencies outside the driving speed range, the connection parts between main body and loader are modified to increase stiffness. It is verified that considerable amount of vibration are reduced by the structural modification.

• 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 Korean Society for Noise and Vibration Engineering Conference
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• 1998.04a
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• pp.173-178
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• 1998

An automatic Q. C. tester for a production line of electric grinder is developed using vibration signals. The methods of measuring and analyzing the vibration signals are found through several experiments at laboratory and production line. The experiments show that checking a vibration signal at running condition only, without any sound signal, is enough to judge whether the product is good or not. The Q. C. tester is made of accelerometer and PC. Measured vibration signal using accelerometer is transmitted to PC through A/D board. Vibration level are calculated using FFT algorithm in PC for already selected five frequency bands, which can specify the cause of fault. The Judging criteria of vibration levels of each bands are decided through a lot of experiment with the comparison of manual judgement.

• Journal of KSNVE
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• v.5 no.3
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• pp.361-371
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• 1995

The vibration of reactor internals should be monitored and diagnosed for the early detection of the failure of reactor pressure vessel. This can be performed by analyzing the time-history signals from the excore neutron flux detertors. The conventional method is an on-demand system which generates power spectra through Fast Fourier Transform(FFT) algorithm. The operator can make his own decision to detect abnormal vibration using these spectra. This post- processing method, however, requires special expertise in the reactor noise analysis and signal processing for random data. It may mislead the operator into erroneous decision-making, if he is a novice in reactor noise analysis. Hence this study is focused on the automated monitoring and diagnosis procedure for the reactor noise analysis, especially on the Fuzzy algorithm to recognize the pattern of the vibration of Core Suport Barrel. The excore neutron signals of Yonggwang Nuclear Power Plant unit 3 is acquired and analyzed using conventional FFT spectra and tested to adopt the Fuzzy method. An Automated Monitoring and Diagnosis System for CSB Vibration using this Fuzzy method is proposed. Furthermore, vibration data for CSB of Youggwang Nnclear Power Plant unit 3 is presented.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.1
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• pp.18-24
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• 2007

If an error occurs in a product that contains a source of vibration, an abnormal noise vibration will occur. Recently a system that has been modified from the previous method of noise detection-a method of appraising the quality of manufactured automobile part by using human ears-is being implemented in the industries of automobile parts. This new system distinguishes the product's vibration signals by measuring and analyzing the signals. Following the recent trend, it has been concluded that the appraisal process of Window Regulator Module needed an improvement. Thus, a vibration monitoring system using LabVIEW, which measures and analyzes vibration signals from a sector gear's connected part by using an accelerometer, has been developed. By analyzing the characteristics of vibration signals of both inferior and superior goods, now the quality of the product can be evaluated much more accurately.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.481-485
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• 2014

In service robots, a number of human movements are analyzed using a variety of sensors. Vibration signals from walking movements of a human provide useful information about the distance and the movement direction of the human. In this paper, we measure the intensity of vibrations and detect both human walking pace and direction. In our experiments, vibration signals detected by microphone sensors provide good estimation of the distance and direction of a human movement. This can be applied to HRI (Human-Robot Interaction) technology.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1558-1565
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• 2015

In this paper, we propose a new method for detecting bearing faults using vibration signals. The proposed method is based on support vector machines (SVMs), which treat the harmonics of fault-related frequencies from vibration signals as fault indices. Using SVMs, the cross-validations are used for a training process, and a two-stage classification process is used for detecting bearing faults and their status. The proposed approach is applied to outer-race bearing fault detection in three-phase squirrel-cage induction motors. The experimental results show that the proposed method can effectively identify the bearing faults and their status, hence improving the accuracy of fault diagnosis.

• Journal of the Korean Society for Railway
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• v.2 no.2
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• pp.13-20
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• 1999

The vibration signals of driving parts of electric train are distorted its signal patterns due to the impact components, which occurs when wheel passes rail joints. An elimination method of the impact components is investigated using adaptive signal processing technique in this study The result shows that adaptive interference canceling method seems to be more effective than line enhancement technique. The application of adaptive interference canceling method to the signal measured at bogie shows that the extractions of the signals of driving parts of traction motor, reduction gear, and axle bearing are successful. Therefore, only the signals of bogie, which is the place to attach an accelerometer easily, is sufficient for the fault diagnosis and the safety evaluation of electric train. Also, adaptive interference canceling method can be applicable to evaluate the performance of vibration isolation between bogie and car body and to investigate the characteristics of indoor sound.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2002.10a
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• pp.161-164
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• 2002

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 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. EFPI was less sensible to the damage signals compared with the optical fiber vibration sensor. It was found that damage information of comparable in quality to acoustic emission data could be obtained from the optical fiber vibration sensor signals.