• Journal of Advanced Navigation Technology
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• v.20 no.4
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• pp.298-304
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• 2016

In this paper, a wavelet packet transform method is proposed for improving the altitude control performance of quadrotor UAV using an ultrasonic rangefinder. A ground tests are conducted using an ultrasonic rangefinder that is much used for vertical takeoff and landing. An ultrasonic rangefinder suffers from signal's spike due to specular reflectance and acoustic noise. The occurred spikes in short time span need to be analyzed at both sides time and frequency domain. The analyzed spikes of the ultrasonic rangefinder using a wavelet packet transform. Compared with the discrete wavelet transform, the wavelet packet decomposition can obtain more abundant time-frequency localization information, so it is more suitable for analyzing and processing ultrasonic signals spike. Experimental results show that it can effectively remove the spikes of the ultrasonic rangefinder.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.4
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• pp.305-313
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• 2013

As an FMT (Filtered Multi-Tone) transmission method of Wideband VHF communication system specified by the ETS (European Telecommunications Standards) EN 300 392-2, this paper introduces three existing realization methods, i.e., the direct filtering method using different band SRRC (Square-Root Raised Cosine) filters for each subcarrier, the PPN-DFT method using the IDFT-PPN (Poly-Phase Network) and PPN-DFT at the transmitter and receiver, respectively, and the Extended DFT method. Then, it proposes the extended IDFT-SDFT (Sliding Discrete Fourier Transform) that computes the DFT values only for interested subcarriers every sample time, and shows that it has an advantage of blind symbol timing (using no training symbol) individually for each user signal (independently of other users' signals) in the multi-user environment where the subcarriers are assigned in contiguous or interleaved blocks to each user and each user signal possibly experiences different channels.

• Smart Structures and Systems
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• v.1 no.2
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• pp.185-215
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• 2005

Advanced signal processing techniques have been long introduced and widely used in structural health monitoring (SHM) and nondestructive evaluation (NDE). In our research, we applied several signal processing approaches for our embedded ultrasonic structural radar (EUSR) system to obtain improved damage detection results. The EUSR algorithm was developed to detect defects within a large area of a thin-plate specimen using a piezoelectric wafer active sensor (PWAS) array. In the EUSR, the discrete wavelet transform (DWT) was first applied for signal de-noising. Secondly, after constructing the EUSR data, the short-time Fourier transform (STFT) and continuous wavelet transform (CWT) were used for the time-frequency analysis. Then the results were compared thereafter. We eventually chose continuous wavelet transform to filter out from the original signal the component with the excitation signal's frequency. Third, cross correlation method and Hilbert transform were applied to A-scan signals to extract the time of flight (TOF) of the wave packets from the crack. Finally, the Hilbert transform was again applied to the EUSR data to extract the envelopes for final inspection result visualization. The EUSR system was implemented in LabVIEW. Several laboratory experiments have been conducted and have verified that, with the advanced signal processing approaches, the EUSR has enhanced damage detection ability.

• Journal of Biomedical Engineering Research
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• v.16 no.4
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• pp.507-516
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• 1995

The nonstationary identifier in the DCT domain is suggested in this study for the identification of AR parameters of above-lesion upper-trunk electromyographic (EMG) signals as a means of developing a reliable real time signal to control functional electrical stimulation (FES) in paraplegics to enable primitive walking. As paraplegic shifts his posture from one attitude to another, there is transition period where the signal is clearly nonstationary. Also as muscle fatigues, nonstationarities become more prevalent even during stable postures. So, it requires a develpment of time varying nonstationary EMG signal identifier. In this paper, time varying nonstationary EMG signals are transformed into DCT domain and the transformed EMG signals are modeled and analyzed in the transform domain. In the DCT domain, we verified reduction of condition number and increment of the smallest eigenvalue of input correlation matrix that influences numerical properties and mean square error were compared with SLS algorithm, and the proposed algorithm is implemented using IMS T-805 parallel processing computer for real time application.

• Journal of the Earthquake Engineering Society of Korea
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• v.22 no.6
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• pp.345-352
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• 2018

It is inevitable to use the distinct element method in the analysis of structural dynamics for stacked stone pagoda system. However, the experimental verification of analytical results produced by the discrete element method is not sufficient yet, and the theory of distinct element method is not universal in Korea. This study introduces how to model the stacked stone pagoda system using the distinct element method, and draws some considerations in the seismic analysis procedures. First, the rocking mode and sliding mode are locally mixed in the seismic responses. Second, the vertical stiffness and the horizontal stiffness on the friction surface have the greatest influence on the seismic behavior. Third, the complete seismic analysis of stacked stone pagoda system requires a set of the horizontal, vertical, and rotational velocity time histories of the ground. However, earthquake data monitored in Korea are limited to acceleration and velocity signals in some areas.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.819-825
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• 2007

In this paper, we propose a fault diagnosis algorithm of induction motors by DFT and wavelet. We extract a feature vector using a fault pattern extraction method by DFT in frequency domain and wavelet transform in time-frequency domain. And then we deal with a fusion algorithm for the feature vectors extracted from DFT and wavelet to classify the faults of induction motors. Finally, we provide an experimental results that the proposed algorithm can be successfully applied to classify the several fault signals acquired from induction motors.

• Journal of the Korean Society for Precision Engineering
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• v.9 no.2
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• pp.128-137
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• 1992

An automatic noise detection system is developed to sense abnormal noises in operating a microwave electronic range. A noise detection method is presented which accounts for the effects of backgound and dynamic noises of the range. A recursive formula used as a noise estimator is a special case of the discrete-time Kalman filter in stochastic processes. Noise levels were measured using a noise acquisition processor in a closed room free of background noise, and detected signals were processes using a microcomputer. The results obtaines showed that the fault detection system should be fast in response to the data acquired and should be high in accuracy and reliability.

• Phonetics and Speech Sciences
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• v.1 no.4
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• pp.97-103
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• 2009

This paper describes a new algorithm for encoding spectral envelope in the time domain alias cancellation (TDAC) part of G.729.1. The spectral envelope and modified discrete cosine transform (MDCT) coefficients of the weighted code-excited linear predictive (CELP) coding error in lower-band and the higher-band input signal are encoded in the TDAC part. In order to reduce allocation bits for spectral envelope coding, a new algorithm using sub-band correlation between adjacent frames is proposed. In addition, to improve the quality of decoded signals, two bit allocation strategies using reduced bits from the proposed algorithm are proposed. The performance of the proposed algorithm is evaluated in terms of objective quality and bit reduction rates. Experimental results show that the proposed algorithm increases the quality of sounds significantly.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.211-214
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• 2002

The detection of tool wear is very important in an automated manufacturing system. This paper presents a tool condition monitoring system based on the wavelet transform analysis of the AC servo motor current in a milling process. The current measurement is relatively simple and does not affect machining operations. The discrete wavelet transform was used to decompose the current of a spindle AC servo motor in the time and frequency domain. The feature vectors were extracted from the decomposed signals and compared to clarity normal and wear conditions. The results show the feasibility of the wavelet transform analysis for the tool condition monitoring.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2007.05a
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• pp.9-28
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• 2007

It is well known that wavelet transform is a signal processing technique which can display the signals on in both time and frequency domain. In this paper, we proposed a new approach based on stationary wavelet transform to provide an enhanced approach for eliminating noise. A 'stationary wavelet transform', where the coefficient sequences are not decimated at each stage, is described. The testing result on sample iris images has shown an enhanced image quality and also show that it has a superior performance than traditional discrete wavelet transform.