• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.1063-1066
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• 2002

The wavelet transform is a popular tool for studying intermittent and localized phenomena in signals. In this study the wavelet transform of cutting force signals was conducted for the detection of a tool failure in turning process. We used the Daubechies wavelet analyzing function to detect a sudden change in cutting signal level. A preliminary stepped workpiece which had intentionally a hard condition was cut by the inserted cermet tool and a tool dynamometer obtained cutting force signals. From the results of the wavelet transform, the obtained signals were divided into approximation terms and detailed terms. At tool failure, the approximation signals were suddenly increased and the detailed signals were extremely oscillated just before tool failure.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.247-250
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• 2001

In this paper, we propose an growing and pruning algorithm to design the adaptive structure of modular wavelet neural network(MWNN) with F-projection and geometric growing criterion. Geometric growing criterion consists of estimated error criterion considering local error and angle criterion which attempts to assign wavelet function that is nearly orthogonal to all other existing wavelet functions. These criteria provide a methodology that a network designer can constructs wavelet neural network according to one's intention. The proposed growing algorithm grows the module and the size of modules. Also, the pruning algorithm eliminates unnecessary node of module or module from constructed MWNN to overcome the problem due to localized characteristic of wavelet neural network which is used to modules of MWNN. We apply the proposed constructing algorithm of the adaptive structure of MWNN to approximation problems of 1-D function and 2-D function, and evaluate the effectiveness of the proposed algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1580-1586
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• 2009

Wavelet transform is utilized to the field of the signal processing and the digital communication. In this paper, the performance for wavelets is analyzed for Haar and Daubechies series in the wavelet shift keying. It is mainly utilized to Haar, Daubechies 4tap, 8tap and 12tap in this paper. The analysis scheme is utilized by the eye pattern and the error probability. As a results of simulation, we confirmed that the proposed scheme was superior to performance when the number of the filler coefficient is small.

• Journal of KSNVE
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• v.9 no.4
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• pp.813-821
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• 1999

This paper presents the technique using wavelet analysis to solve the seismic response of a steam turbine-generator rotor system subjected to earthquake excitations. A brief review of the wavelet transform and its discretization, time-frequency representation of the earthquake wave and the seismic response for a rotor system is presented. The Daubechies wavelet has been used for describing the time-frequency characteristics of the input and the response in case of a recorded accelerogram during 1995 Hyogoken Nanbu earthquake. Also, the results in the wavelet domain has been illustrated through comparison with the time domain simulation results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.1
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• pp.70-78
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• 2004

This paper presents study of efficiency of wavelet transformation for on-line chatter detection during hard fuming process. From comparison with other time series and statistical methods such as fast fourier transformation (FFT), Kurtosis and standard deviation (STD), wavelet transform is better than others in on-line chatter detection. With using wavelet function with pseudo frequency corresponding to chatter frequency, chatter could be detected more sensitively. And for both force signal from dynamometer and displacement signal from capacitance type cylindrical sensor (CCS), wavelet transform with DB2 function on level 4 could be well used for chatter detection in hard turning process.

• Journal of the Korean Graphic Arts Communication Society
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• v.20 no.1
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• pp.28-44
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• 2002

Wavelet transformation in image compression is to offer higher image compressibility and high-quality by quantization and entropy encoding. More image quality is good that reconstructed image by wavelet calculation than acquire cosine transform. Therefore, wavelet itself is function if it is wavelet's feature, in this function, do processing applying difference scale and resolution. That is, this is not that fixed resolution has been decided like existent compression way, when it regulated scale, damage goes in pixel and picture looks like break without giving damage entirely in reflex even if magnify or curtail Decoding. Therefore, this paper is in Image that using new wavelet application compression way research that see applies comparing In each image noted this time compressing step by step with circle image compression efficiency recognize. Also, estimated quality pass through by printing of compressed image, investigated compression ratio of most suitable that get print of high quality and elevation of transmission speed.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.3
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• pp.169-174
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• 2000

In this paper, Haar wavelet-based neural network is described for the identification and control of discrete-time nonlinear dynamical systems. Wavelets are suited to depict functions with local nonlinearities and fast variations because of their intrinsic properties of finite support and self-similarity. Due to the orthonormal properties of Haar wavelet functions, wavelet neural networks result in a greatly simplified training problem. This wavelet-based scheme performs adaptively both the identification of nonlinear functions and the control of the overall system, while the multilayer neural network is applied to the control system just after its sufficient learning of the unknown functions. Simulation shows that the wavelet network can be a good alternative to a multilayer neural network with backpropagation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.8
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• pp.1139-1145
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• 2002

Wavelet transformed data can filter signal with each frequency band, because it includes detail information about original signal. Therefore, in this paper, important two noises were removed by wavelet. About AWGN environment UDWT(undecimated discrete wavelet transform), applying hard-threshold, was used and about impulse noise environment, it can be possible to recognize edge of original signal as well as superior denoising effect by using two methods, denoising by threshold and slope of signal by wavelet. SNR was used as a judgemental criterion of a denoising effect and Blocks and DTMF(dual tone multi frequency) were used as a test signal.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.8
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• pp.369-373
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• 2000

High impedance fault(HIF) is defined as a fault that the general overcurrent relay can not detect or interrupt. Especially when HIF occurs in residential areas, energized high voltage conductor results in fire hazard, equipment damage or personal threat. This paper proposes a fault location estimation algorithm for high impedance fault using wavelet transform. The algorithm is based on the wavelet analysis of the fault voltage and current signals. The performance of the proposed algorithm is tested on a typical 154kV korean transmission line system under various fault conditions. From the tests presented in this paper it can be concluded that a fault location estimation algorithm using wavelet transform can precisely calculate the fault point for HIF.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.12
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• pp.78-85
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• 2002

The wavelet transform is a popular tool fer studying intermittent and localized phenomena in signals. In this study the wavelet transform of cutting force signals was conducted for the detection of a tool failure in turning process. We used the Daubechies wavelet analyzing function to detect a sudden change in cutting signal level. A preliminary stepped workpiece which had intentionally a hard condition was cut by the inserted cermet tool and a tool dynamometer obtained cutting force signals. From the results of the wavelet transform, the obtained signals were divided into approximation terms and detailed terms. At tool failure, the approximation signals were suddenly increased and the detailed signals were extremely oscillated just before tool failure.