• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.271-274
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• 2005

For noise and vibration order-analysis on rotating machinery, it is compulsory to measure the RPM of the rotating part of the machine. Normally the RPM is measured using dedicated tacho-probes. In this paper we describe a new method that in real-time synthesizes a tacho signal from the measured noise or vibration signal thus eliminating the tacho probe. The method strengths and weaknesses are evaluated on practical signals.

• 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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.583-589
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• 2001

For several decades many researchers have studied various algorithms, known as non-destructive testing, to identify abnormalities within a structure. Damage detection technique using vibration signal is a kind of these methods. Many researchers have published lots of papers dealing vibration signal to identify structural damage. All the methods for damage detection using vibration signal can be divided into two big categories. The first category is the method that requires some reference model such as finite element model, and the second is the method that does not require any reference model but needs only experimental data. This paper will be devoted to classify damage detection methods that utilize vibration signal.

• 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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.607-610
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• 2009

The abnormal combustion in the running engine results to knocking which increases the pressure and temperature in the cylinder, thereby decreasing the generated power by reducing the thermal efficiency. When the temperature and pressure in the cylinder increased rapidly by knocking, abnormal combustion takes place and the engine power is decreased. To investigate the knocking phenomenon, accelerometers are installed in the cylinder head to monitor and diagnose the vibration signal. As method of signal analysis, the time-frequency analysis method was adapted for acquisition of vibration signal and analyzes engine combustion in the short time. In this experiment, after analyzing time data which is stored in the signal recorder in one unit work (4 strokes: 2 revolutions), the signal with frequency and Wavelet methods with extracted one engine combustion data was also analyzed. Then, normal condition with no knocking signal is analyzed at this time. Hereafter, the experiments made a standard for distinguishing normal and abnormal condition to be carried out in acquisition of vibration signal at all cylinders and extracting knocking signal. In addition, analyzing methods can be diverse with Symmetry Dot Patterns (SDP), Time Synchronous Average (TSA), Wigner-Ville Distribution (WVD), Wigner-Ville Spectrum (WVS) and Mean Instantaneous Power (MIP) in the cold test [2]. With signal processing of vibration from engine knocking sensor, the authors adapted a part of engine /rotor vibration analysis and monitoring system for marine vessels to prevent several problems due to engine knocking

• 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 Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.1133-1138
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• 2000

This paper describes a signal recognition method for diagnosing the rotating machinery using wavelet-aided Self-Organizing Feature Map(SOFM). The SOFM specialized from neural network is a new and effective algorithm for interpreting large and complex data sets. It converts high-dimensional data items into simple order relationships with low dimension. Additionally the Learning Vector Quantization(LVQ) is used for reducing the error from SOFM. Multi-resolution and wavelet transform are used to extract salient features from the primary vibration signals. Since it decomposes the raw timebase signal into two respective parts in the time space and frequency domain, it does not lose either information unlike Fourier transform. This paper is focused on the development of advanced signal classifier in order to automatize vibration signal pattern recognition. This method is verified by the experiment and several abnormal vibrations such as unbalance and rubbing are classified with high flexibility and reliability by the proposed methods.

• Journal of KSNVE
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• v.8 no.5
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• pp.929-935
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• 1998

Safety diagnosis of electric train driving system is performed using vibration signals of running electric train. Safety diagnosis is tried on the viewpoints of the appreciation of superannuation and the fault diagnosis of motor, reduction gear and bogie. The appreciation of superannuation is checked by the vibration levels of driving parts and the fault diagnosis is done by analyzing the frequencies of the vibration signals which are measured directly from a running electric train. The results shows that the vibration levels of each parts increase as the train gets older and each parts have their own frequency patterns of the vibration. Vibration propagation path is also investigated using calculated the coherence value between bogie and driving system. As the results, it is known that vibration signal can be utilized successfully for the safety diagnosis of the driving part of electric train.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.52 no.11
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• pp.516-520
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• 2003

A novel dual beam heterodyne Laser Doppler Vibrometer (LDV) in conjunction with FM demodulators, which utilizes a residual beam to eliminate the perturbationdue due to the vibrometer body vibration without any external reference surface, has been developed. Residual laser beam from the beam splitter is used to pick up the vibration of damper, which is mounted in the vibrometer, and combined with reference beam at the photodetector. The output signal of this detector and main signal are processed to extract the object vibration, using a least mean square adaptive algorithm. It is shown experimentally that the body vibration of 1-5 Hz can be effectively removed from the measured signal using DSP technology to extract unperturbed 100 Hz original signal.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.1
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• pp.77-84
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• 2017

Generally, a time-varying vibration signal is generated in a rotating machine system, and when there is a failure in the rotating machine, the signal contains noise. In this paper, we propose a system consisting of an adaptive predictor and a binary tree filter bank for analyzing time - varying vibration signals with noise. And the vibration signal analyzed results in this system is used for fault diagnosis of the rotating machine. The adaptive predictor of the proposed system predicts the periodic signal components, and the filter bank system decomposes the difference signal between the input signal and the predicted periodic signal into subband. Since each subband signal includes a noise signal component due to a failure, it is possible to diagnose the failure of the using rotary machine. The validity of the proposed vibration signal analysis method is shown in the simulations, where the periodic components cancelled vibrating signals are decomposed to 32 subband, and the signal characteristics related faults are analyzed.