• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.582-587
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• 2011

Acoustic Emission(AE) is widely used for early detection of faults for rotating machinery in these days because of its high sensitivity. AE signal has to need for transferring to low frequency range for the spectrum analysis included the fault mechanism. In transferring process, we lose a lot of fault information caused by unusable signal processing method. Discrete Wavelet Transform(DWT) is a method of signal processing for AE signatures, but the pattern of its mother function is not optimized with AE signals. So, we can lose the fault information when we want to use the DWT for AE signal. Therefore, in this paper, we will propose a novel pattern for DWT mother function, which is optimized with AE signals. And it will be applied to compare the results of DWT by daubechie and novel pattern.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.269-273
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• 2000

This paper describes Active Noise Control (ANC) using Discrete Wavelet Transform (DWT) Domain Least Mean Square (LMS) Method. DWT-LMS is one of the transform domain input decorrelation LMS and improves the convergence speed of adaptive filter especially when the input signal is highly correlated. Conventional transform domain LMS's use Discrete Cosine Transform (DCT) because it offers linear band signal decomposition and fast transform algorithm. Wavelet transform can project the input signal into the several octave band subspace and offers more efficient sliding fast transform algorithm. In this paper, we propose Wavelet transform domain LMS algorithm and shows its performance is similar to DCT LMS in some cases using ANC simulation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.04a
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• pp.109-110
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• 2009

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.572-577
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• 2011

The acoustic emission (AE) technique is a well-known non-destructive test technique, both in research and for industrial applications. It is mainly used to monitor the onset of cracking processes in materials and components. Predicting and preventing the crack phenomenon has attracted the attention of many researchers and has continued to provide a large incentive for the use of condition monitoring techniques to detect the earliest stages of cracks. In this research, goal is in grasping features of AE signal caused by crack growth. The envelope analysis with discrete wavelet transform (DWT) is used to find the characteristic of AE signal. To estimate feature of divided into three by crack length, the time waveform and the power spectrum were generated by the raw signals and the transferred signal processed by envelope analysis with DWT.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.274-280
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• 2002

This paper addresses the vibration mode shape measurement technique utilizing a Continuous Scanning Laser Doppler Vibrometer (CSLDV). The continuous scanning capability is added to the conventional discrete Laser Doppler Vibrometer by reflecting the laser beams on the surface of the object using two oscillating mirrors. The bow scanning resulted from the proposed scanning method is eliminated by feedback control. The velocity output signal from the CSLDV is modulated to give the spatial velocity distribution in terms of coefficients which are obtained from the Fast Fourier Transformation of the time dependent velocity signal. Using the Chebyshev series form, the analysis of the vibration mode shape techniques for straight Bine scanning and 2 dimensional scanning are presented and discussed. The performance of the proposed SLDV is presented using the experimental results of the vibration mode shape of a plate

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.71-77
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• 2002

The spectrum of impulse response signal which is obtained from an impulse hammer testing is used for frequency response function, nevertheless it has serious faults when the record length for the signal processing is not very long. The faults cannot be avoided with the conventional signal analyzer that is processing all the signals as if they are always periodic. The signals generated by the impact hammer are undoubtedly non-periodic because of the damping, and are acquired for limited recording time due to the memory as well as the computation performance of the signal analyzer. This paper will make clear the relation between the faults and the length of recording time, and propose the way for solving the faults.

• The KSFM Journal of Fluid Machinery
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• v.7 no.2 s.23
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• pp.41-49
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• 2004

Condition monitoring is very important in turbo machinery because single failure could cause critical damages to its plant. So, automatic fault recognition has been one of the main research topics in condition monitoring area. We have used a relatively new fault recognition method, Hidden Markov Model(HMM), for mechanical system. It has been widely used in speech recognition, however, its application to fault recognition of mechanical signal has been very limited despite its good potential. In this paper, discrete HMM(DHMM) was used to recognize the faults of rotor system to study its fault recognition ability. We set up a rotor kit under unbalance and oil whirl conditions and sampled vibration signals of two failure conditions. DHMMS of each failure condition were trained using sampled signals. Next, we changed the setup and the rotating speed of the rotor kit. We sampled vibration signals and each DHMM was applied to these sampled data. It was found that DHMMs trained by data of one rotating speed have shown good fault recognition ability in spite of lack of training data, but DHMMs trained by data of four different rotating speeds have shown better robustness.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.3
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• pp.291-297
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• 2012

Conventional Fourier analysis can give only limited information about the dynamic characteristics of nonstationary signals. Instead, time-frequency analysis is widely used to investigate the nonstationary signal in detail. Several time-frequency analysis methods are compared for a typical acoustic emission burst generated during the impact between a ferrite ceramic and aluminum plate. This AE burst is inherently nonstationary and random containing many frequency contents, which leads to severe interference between cross terms in bilinear convolution type distributions. The smoothing and reassignment processes can improve the readability and resolution of the results. Spectrogram and scalogram of the AE burst are obtained and compared to get the characteristics information. Renyi entropies are computed for various bilinear time-frequency transforms to evaluate the randomness. These bilinear transforms are reassigned by using the improved algorithm in discrete computation.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1996.10a
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• pp.29-36
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• 1996

A procedure for the predictive control for structural vibration control in building subject to wind loads is presented. The building motions are modeled by the first mode of the response. Wind velocities are generated by the simulation using power spectral density function. Predictive control algorithm is the discrete-time formulation and that is developed as a control strategy that computes the control signal which makes the predicted process output equal to a desired process output. Results on the reduction of the dynamic response and control effectiveness of the algorithm are presented and discussed.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.4 s.109
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• pp.339-345
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• 2006

In this paper, a physically meaningful methodology which can assess the contribution of each vibration mode to various vibration response signals (displacement, velocity, acceleration) is developed. Based on these results, the problem of quantitative assessment of the relative importance of a structural system's vibrational modes is discussed. In addition, a direct method which ran assess the relative importance of each mode from uniformly sampled experimental data is also proposed.