A new approach for measuring RMS value and phase angle of fundamental harmonic based on Wavelet Packet Transform

Vatansever, Fahri; Özdemir, Ayhan

doi:10.1016/j.epsr.2006.12.009

Cited by 24 publications

(12 citation statements)

References 3 publications

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“…Fig.2(a) presents the wavelet packet tree of ECG signal of reconstruction. In contrast, Fig.2(b) represents the optimal wavelet packet tree in which node (3,2) to node (3,5) are eliminated according to the best basis method and the MDL (minimum description length) criterion. TABLE I shows the entropy of every node of the optimal wavelet packet tree (Fig.2(b)) in the three groups.…”

Section: Resultsmentioning

confidence: 96%

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Wavelet and wavelet packet transform analysis in the ECG signals of Atrial Fibrillation

Qiao

Zhou

2007

2007 IEEE/ICME International Conference on Complex Medical Engineering

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In this paper, the application of wavelet transform (WT) and wavelet packet transform (WPT) for ECG signals of atrial fibrillation (AF) is presented. Original ECG signals of AF are de-noised, reconstructed and decomposed by WT and WPT. Entropies of each node of the reconstructed ECG signal of AF are calculated. Based on the best basis method and the MDL (minimum description length) criterion, for the given entropy-'log energy' entropy, the optimal wavelet packet tree of the reconstructed ECG signal of AF is established. Ultimately, the non-terminating and the short-time terminating AF are successfully differentiated via the difference of entropies of two types of AF.

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Section: Resultsmentioning

confidence: 96%

“…The continuous wavelet transform (CWT) W1(s,u) for a signal f (t) is defined as WfS,U) = (*(),,I;Tt )) where g [n] and h[n] are length 2 U low-pass and high-pass filters, respectively; WO(t) = (t) is called scaling function and W1(t) = (t) is called wavelet function [5].…”

Section: B Methods 1) Wavelet Analysismentioning

confidence: 99%

Wavelet and wavelet packet transform analysis in the ECG signals of Atrial Fibrillation

Qiao

Zhou

2007

2007 IEEE/ICME International Conference on Complex Medical Engineering

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“…Fourier-based methods [10]. Although the computational burden of the wavelet transform is higher than that of the Fourier transform [11] In wavelet-based methods, the input signal must be sampled so that the frequency of all harmonics is located in the center of extracted frequency bands to enhance the calculation accuracy.…”

Section: Wavelet Packet Transform (Wpt)-based Methods Have Been Propomentioning

confidence: 99%

A new combined method for RMS calculation based on wavelet packet and Hilbert transform

Hooshmand¹,

Modarresi²

2016

Turk J Elec Eng & Comp Sci

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Among several methods used for calculating the root mean square (RMS) of electrical signals, Fourier and wavelet transforms are the most common approaches. The latter also has the advantage of being able to analyze both stationary and nonstationary signals. However, in the wavelet-based methods, the presence of both odd and even harmonics in the input signal causes the harmonic components not to be in the center of the extracted frequency bands and this will reduce the accuracy of the RMS calculation. In order to remove this drawback, this paper proposes a new method based on wavelet and Hilbert transforms, in which the frequency of all harmonic components is increased by half of the main frequency by using a preprocessing technique. In simulation results, the RMS value of a real signal of the steel electric arc furnace of the Esfahan Mobarakeh Steel Company is calculated by using the suggested method. The results clearly show that the accuracy of the proposed approach is better than that of conventional and grouping methods.

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“…However, there isn't much work on applying wavelets to RMS measurements required for overcurrent protection as the discrete wavelet transform (DWT) technique is not suitable for harmonic analysis because the resulting frequency bands do not have the same width and the results do not give easy insight into the time behaviour of the harmonics [10]. To overcome this limitation, wavelet packet transform (WPT) method is proposed that decomposes a given power system waveform into a set of harmonic bands with same frequency width, and each of these bands represents that part of the original instantaneous RMS occurring at that particular time and in that particular frequency band [11][12]. In wavelet packet analysis, the details as well as the approximations can be split as shown in Figure (…”

Section: -Applying Wavelet Packets Transform (Wpt) As a Signal Procementioning

confidence: 99%

Detection and location of distribution systems faults using Wavelet packet transform based overcurrent relay

Ibrahim

Aziz

Fattah³

et al. 2012

The International Conference on Electrical Engineering

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This paper presents a scheme to increase the sensitivity of overcurrent protection. The proposed scheme applies wavelet packet transform, since it can preserve both time and frequency information with high resolution. The proposed scheme demonstrates its feasible performance in detecting short circuit faults, calculating fault location with moderate accuracy and detecting nonlinear high impedance faults. In addition, the proposed scheme examines the load current continuously and has the ability of changing the relay pick up value adaptively. The examined tested cases include different internal short circuit fault conditions, different nonlinear high impedance faults, and non fault situations such as normal load changing. The obtained results indicate that the developed scheme is fast, robust, reliable and suitable for power distribution systems.

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A new approach for measuring RMS value and phase angle of fundamental harmonic based on Wavelet Packet Transform

Cited by 24 publications

References 3 publications

Wavelet and wavelet packet transform analysis in the ECG signals of Atrial Fibrillation

Wavelet and wavelet packet transform analysis in the ECG signals of Atrial Fibrillation

A new combined method for RMS calculation based on wavelet packet and Hilbert transform

Detection and location of distribution systems faults using Wavelet packet transform based overcurrent relay

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