• Proceedings of the KSME Conference
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• 2000.11a
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• pp.522-528
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• 2000

Dynamic characteristics of seated human body were investigated by measuring apparent masses of eight different seating subjects exposed to vertical vibration. Two types of vibration signals - one is random signals over 1 to 30Hz having flat spectral density and the other is signals measured on seat rail in passenger car under driving conditions - were employed. It was found that the apparent masses are highly dependent on vibration level rather than type of the vibration signals. Based on the apparent mass measurements, a mathematical model of the human body in seating posture was developed by using genetic algorithm. Three-degree-of-freedom model was satisfactory in describing apparent mass of seated human body.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.12 no.4
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• pp.136-145
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• 1998

This paper describes the FFT and coefficient analysis of vibration signals for preventive diagnosis of a mold transformer at normal and abnormal state. Varying applied voltage, loading current and temperature as control variables for he experiment, measurement variables such as magnitude of vibration signals, frequency spectrum and time series coefficient were analyzed. The vibration signals by variation of control variables were measured by acceleration sensor adhered on the surface of winding and core, and measurement variables were calculated using dat acquisition system. After analyzing the normal state, the structural distortion was also simulated. The vibration signals at abnormal state were measured by the same control variables variation as the normal state. As a result, vibration signals between normal and abnormal state could be distinguished by comparison of the perpendicular and horizontal vibration signal.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.611-616
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• 2002

Bearing diagnostics is difficult in a gearbox because bearing signals are masked by the strong gear signals. Self adaptive noise cancellation(SANC) is useful technique to seperate bearing signals from gear signals. While gear signals are correlated with a long correlation length, bearing signals are not correlated with a short length. SANC seperates two components on the basis of correlation length. Then we can find defect frequency component in the envelope spectrum of the bearing signals.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11a
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• pp.362.2-362
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• 2002

Bearing diagnostics is difficult in a gearbox because bearing signals are masked by the strong gear signals. Self adaptive noise cancellation(SANC) Is useful technique to seperate bearing signals from gear signals. While gear signals are correlated with a long correlation length, bearing signals are not correlated with a short length. SANC seperates two components on the basis of correlation length. (omitted)

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.7 s.178
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• pp.1731-1739
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• 2000

The Vibration signals of a gear driving system is often associated with gear tooth faults. Many studies have been done on the detection of impulsive vibration signals, which characterize the breaka ge of a gear tooth. Also, most of the studies on gear fault diagnosis are only about the fault existence at one gear-pair. This study concerns on the several possible faults of a geared motor that has three gear pairs. The measurement and analysis on the vibration signals of a running geared motor shows the relationship between the gear faults and the vibration signals. This study also shows that adaptive interference canceling technique can be appropriately applicable to detect which gear-pair has the fault, and that wavelet is better than spectrogram to figure out the gear fault.

• Journal of KSNVE
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• v.9 no.4
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• pp.835-840
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• 1999

Cause of excessive vibration signals with twice the rotational speed of a 2-pole generator rotor in balancing for fossil power plants was investigated. The 2-pole generator rotor is treated as a typically asymmetric rotor in vibration analysis, and produces asynchronous vibration with twice the rotational speed for its own inertia and stiffness asymmetry. This paper introduces practical balancing procedure and experimental vibration data of the asymmetric 2-pole rotor in balancing, and presents the results of investigation into sources of the excessive vibration signals.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.234-237
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• 2002

To detect external vibration signals on the latticed fence structure, distributed fiber optic sensor using Sagnac interferometer was fabricated and tested. The latticed structure fabricated with dimension of 170cm in width and 180cm in height, the optical fiber, 50m in length, distributed and fixed on the latticed structure. It was verified the sensitivity of the Sagnac interferometer using the PZT phase modulator. Fiber optic external vibration signal spplied to the latticed fence structure from 100Hz to several kHz. The interferometeric fiber optic sensor detected the excited vibration signal very effectively without any signal processing. The detected optical signals were compared and analyzed to the detected acclerometer signals.

• Journal of Biosystems Engineering
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• v.26 no.6
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• pp.503-508
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• 2001

In this paper, time-fiequency analysis and multi-dimensional spectral analysis methods are applied for source identification and diagnosis of non-stationary sound/vibration signals. Sound or vibration problems of general vehicle and agricultural machinary are under 500 Hz. So We used linearly increased chirp signals under 500 Hz. By checking the coherences on concerned time, fur time-variant non-stationary signals, this simulation it very well coincident to expected results.

• Journal of the Society of Naval Architects of Korea
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• v.49 no.6
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• pp.498-503
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• 2012

Independent component analysis (ICA) technique based on statistical independency of the signals is known as suitable to identify the source signals by measuring and separating mixed signals through transfer paths and has successfully applied in the field of medical care, communications and so forth. In this study, the ICA technique is introduced for the identification of excitation sources from measured vibration signals of structures, which can be done by evaluating negentropy of centered and whitened vibration signals and correlation of separated signals. To validate the method, numerical analyses are carried out for a plate and a cylinder structure. The results show that the method can be applied efficiently to source identification of complex structures. Nevertheless, additional studies would be required to complement problems of occasional inaccuracy.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.2
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• pp.27-30
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• 2019

Factory monitoring systems are gaining importance in wide areas of industry. Especially, there have been many efforts in implementation of vibration measurement and analysis for monitoring the status of rotating machines. In this paper, a digital signal processor (DSP) based monitoring system dedicated to the vibration monitoring and analysis on rotating machines is discussed. Vibration signals are acquired and processed for the continuous monitoring of the machine status. Time domain signals and fast Fourier transform (FFT) are used for vibration analysis. All of the signal processing procedures are done in the DSP to reduce the production and maintenance cost. The developed system could also provide remote and mobile monitoring capabilities to operator via internet connection. This paper describes the overview of the functional blocks of the implemented system. Test results based on signals from small-size single phase motors are discussed for monitoring and defect diagnosis of the machine status.