A discrete wavelet transform approach to discriminating among inrush current, external fault, and internal fault in power transformer using low-frequency components differential current only

2014 ◽  
Vol 9 (3) ◽  
pp. 302-314 ◽  
Author(s):  
Atthapol Ngaopitakkul ◽  
Chaiyan Jettanasen
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Power Transformer ◽  
Low Frequency ◽  
Discrete Wavelet ◽  
Inrush Current ◽  
Internal Fault ◽  
Frequency Components ◽  
Differential Current

A New Algorithm for Three-Phase Power Transformer Differential Protection Considering Effect of Ultra-Saturation Phenomenon Based on Discrete Wavelet Transform

2018 ◽  
Vol 20 (1) ◽  
Author(s):  
Bahram Noshad
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Power Transformer ◽  
Discrete Wavelet ◽  
Inrush Current ◽  
Differential Protection ◽  
Inductive Load ◽  
Saturation Phenomenon ◽  
Three Phase ◽  
Transformer Differential Protection

Abstract One of transient phenomena that lead to the false trip of the power transformer differential protection during the energization of a loaded power transformer is the ultra-saturation phenomenon. This paper presents, at first, a new algorithm for three-phase power transformer differential protection considering effect of the ultra-saturation phenomenon based on Discrete Wavelet Transform (DWT). To model the ultra-saturation phenomenon, the nonlinear characteristic of the transformer core and the effect of the saturation of the current transformers are taken into account. It is assumed that the load of the transformer is a resistive and inductive load. In this algorithm, the ultra-saturation phenomenon, the external and internal faults of power transformer and the magnetic inrush current are simulated. To distinguish between these phenomena, appropriate criteria using DWT by the use of standard deviation of coefficients are presented. Also, one of the most important criteria for the digital relays is the time for making a decision. Thus, to determine the time of decision, the experimental results will be presented.

scholarly journals Discrete wavelet transform coupled with ANN for daily discharge forecasting into Três Marias reservoir

2014 ◽  
Vol 364 ◽  
pp. 100-105 ◽  
Author(s):  
C. A. G. Santos ◽  
P. K. M. M. Freire ◽  
G. B. L. Silva ◽  
R. M. Silva
Keyword(s):  
Time Series ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Model Performance ◽  
Low Frequency ◽  
Discrete Wavelet ◽  
Ann Model ◽  
Frequency Components ◽  
Daily Discharge ◽  
Três Marias Reservoir

Abstract. This paper proposes the use of discrete wavelet transform (DWT) to remove the high-frequency components (details) of an original signal, because the noises generally present in time series (e.g. streamflow records) may influence the prediction quality. Cleaner signals could then be used as inputs to an artificial neural network (ANN) in order to improve the model performance of daily discharge forecasting. Wavelet analysis provides useful decompositions of original time series in high and low frequency components. The present application uses the Coiflet wavelets to decompose hydrological data, as there have been few reports in the literature. Finally, the proposed technique is tested using the inflow records to the Três Marias reservoir in São Francisco River basin, Brazil. This transformed signal is used as input for an ANN model to forecast inflows seven days ahead, and the error RMSE decreased by more than 50% (i.e. from 454.2828 to 200.0483).

scholarly journals Multi-focus Image Fusion Using an Effective Discrete Wavelet Transform Based Algorithm

2014 ◽  
Vol 14 (2) ◽  
pp. 102-108 ◽  
Author(s):  
Yong Yang ◽  
Shuying Huang ◽  
Junfeng Gao ◽  
Zhongsheng Qian
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
Discrete Wavelet Transform ◽  
High Frequency ◽  
Low Frequency ◽  
Objective Evaluation ◽  
Discrete Wavelet ◽  
Evaluation Indexes ◽  
Fused Image ◽  
Focus Image

Abstract In this paper, by considering the main objective of multi-focus image fusion and the physical meaning of wavelet coefficients, a discrete wavelet transform (DWT) based fusion technique with a novel coefficients selection algorithm is presented. After the source images are decomposed by DWT, two different window-based fusion rules are separately employed to combine the low frequency and high frequency coefficients. In the method, the coefficients in the low frequency domain with maximum sharpness focus measure are selected as coefficients of the fused image, and a maximum neighboring energy based fusion scheme is proposed to select high frequency sub-bands coefficients. In order to guarantee the homogeneity of the resultant fused image, a consistency verification procedure is applied to the combined coefficients. The performance assessment of the proposed method was conducted in both synthetic and real multi-focus images. Experimental results demonstrate that the proposed method can achieve better visual quality and objective evaluation indexes than several existing fusion methods, thus being an effective multi-focus image fusion method.

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