scholarly journals Shock Signal Trend Term Error Correction Method Based on Discrete Wavelet Transform and Low-Frequency Oscillator Combination

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Peng Wang ◽  
Ming Yan ◽  
Lei Zhang ◽  
Ning Yang
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Frequency Spectrum ◽  
Shock Loading ◽  
Response Spectrum ◽  
Low Frequency ◽  
Combination Method ◽  
Shock Acceleration ◽  
Discrete Wavelet ◽  
Frequency Oscillator

Shock response spectrum (SRS), calculated according to shock loading signal, is the primary metric for assessing the shock resistance ability of shipborne equipment. Nevertheless, the measured shock acceleration signal contains a trend term error that severely distorts the low frequency of the SRS. The accuracy of present correction methods cannot be assured due to a lack of reference. A discrete wavelet transform (DWT) and low-frequency oscillator combination method is proposed for correcting shock signals in this paper. The optimal wavelet parameters can be selected according to a low-frequency spectrum baseline fitted by the measured relative displacement to reject low-frequency trend term errors. Shock machine test results show that the average difference between the low-frequency spectrum baseline and uncorrected SRS is reduced from 89.8% to 3.2%, while the SRS slope rolled off to 5.8 dB/oct after imposing the proposed correction. The corrected SRS can faithfully show the actual shock loading characteristics of shipborne equipment in shock tests.

scholarly journals A Correction Method for the Underwater Shock Signals of Floating Shock Platforms Based on a Combination of FFT and Low-Frequency Oscillator

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Peng Wang ◽  
Ming Yan ◽  
Lei Zhang ◽  
Mingyuan Zhang
Keyword(s):  
Fourier Transform ◽  
Frequency Band ◽  
Response Spectrum ◽  
Low Frequency ◽  
Combination Method ◽  
Shock Acceleration ◽  
Floating Platform ◽  
Frequency Oscillator ◽  
Underwater Shock ◽  
Equal Displacement

Accurate shock loading is required for evaluating and analyzing the shock resistance of warship equipment. However, measured shock acceleration signals contain trend term errors, which cause serious low-frequency distortion of the shock response spectrum (SRS). We propose a combination method of fast Fourier transform (FFT) and low-frequency oscillator for correcting the underwater shock signals. Based on the equal displacement line fitted by the measured displacement response data, the Fourier transform spectrum of the shock acceleration signal is corrected for eliminating low-frequency errors. The results of underwater explosion tests on a floating platform indicate that the average difference between the equal displacement line and SRS in the low-frequency band (4∼20 Hz) can be reduced from 14.7% to 3.5%, and the mid-high-frequency band without the trend term is nearly unaffected. The corrected SRS can faithfully reflect the actual shock environment of the warship equipment at a specific installation location of the floating shock platform.

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.

Real-Time Vehicle License Plate Recognition Based on Scanning and 2D Haar Discrete Wavelet Transform

2013 ◽  
Vol 284-287 ◽  
pp. 2402-2406 ◽  
Author(s):  
Rong Choi Lee ◽  
King Chu Hung ◽  
Huan Sheng Wang
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Real Time ◽  
Recognition Rate ◽  
Low Frequency ◽  
Experimental Result ◽  
Discrete Wavelet ◽  
License Plate ◽  
License Plate Recognition ◽  
Image Pixels

This thesis is to approach license-plate recognition using 2D Haar Discrete Wavelet Transform (HDWT) and artificial neural network. This thesis consists of three main parts. The first part is to locate and extract the license-plate. The second part is to train the license-plate. The third part is to real time scan recognition. We select only after the second 2D Haar Discrete Wavelet Transform the image of low-frequency part, image pixels into one-sixteen, thus, reducing the image pixels and can increase rapid implementation of recognition and the computer memory. This method is to scan for car license plate recognition, without make recognition of the individual characters. The experimental result can be high recognition rate.

Hybrid Color Image Compression Using Discrete Cosine Transform and Discrete Wavelet Transform

2012 ◽  
Vol 198-199 ◽  
pp. 244-248 ◽  
Author(s):  
Ling Tang ◽  
Ming Ju Chen ◽  
Hong Song
Keyword(s):  
Wavelet Transform ◽  
Image Compression ◽  
Discrete Wavelet Transform ◽  
Discrete Cosine Transform ◽  
Color Image ◽  
Low Frequency ◽  
Huffman Coding ◽  
Discrete Wavelet ◽  
Cosine Transform ◽  
Color Image Compression

In this research we undertake a study of image compression based on the discrete cosine transform(DCT) and discrete wavelet transform(DWT). Then a hybrid color image compression algorithm based on DCT and DWT is proposed. This algorithm is implemented through transform the color image using DWT in the YCbCr space first, and then DCT in the low frequency, adopt huffman coding, RLE and arithmetic coding in the encoded mode. In experiments, the results outperform the only DCT and the only DWT typically higher in peak signal-to-noise ratio and have better visual quality.

scholarly journals Development of an Efficient Indoor Optical System using Different Wavelet Transforms

2021 ◽  
Author(s):  
Ankita Aggarwal ◽  
Gurmeet Kaur
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Communication System ◽  
Wavelet Transforms ◽  
Low Frequency ◽  
Digital Signal ◽  
Fluorescent Light ◽  
Discrete Wavelet ◽  
Stationary Wavelet Transform ◽  
Light Interference

For an effective communication system whether indoor or outdoor, the most important concern is minimum noise. In this paper, an efficient noise reduction technique is presented using various wavelet transform techniques for indoor optical wireless communication system (IOWC). In IOWC system, Fluorescent Light Interference (FLI) is main source of noise. Here, in this paper three methods are used to reduce the effect of noise from a digital signal. These are Discrete Wavelet Transform (DWT), Stationary Wavelet transform (SWT) and Discrete Wavelet transform-Stationary Wavelet Transform (DWT-SWT). Through sub band coding in DWT the signal is decomposed into lower sub bands of high and low frequency respectively of unequal size; while in SWT the decomposed signal have sub bands of equal size. In DWT-SWT the high frequency components of both DWT and SWT are added. Using Pulse Position Modulation, the comparison between these three techniques is described here to enhance the overall performance of the IOWC system.

scholarly journals An Iterative Hybrid Harmonics Detection Method Based on Discrete Wavelet Transform and Bartlett–Hann Window

2020 ◽  
Vol 10 (11) ◽  
pp. 3922 ◽  
Author(s):  
Guishuo Wang ◽  
Xiaoli Wang ◽  
Chen Zhao
Keyword(s):  
Wavelet Transform ◽  
Steady State ◽  
Discrete Wavelet Transform ◽  
High Frequency ◽  
Detection Method ◽  
Low Frequency ◽  
Discrete Wavelet ◽  
Detection Accuracy ◽  
Harmonic Detection ◽  
High Frequency Part

The current signal harmonic detection method(s) cannot reduce the errors in the analysis and extraction of mixed harmonics in the power grid. This paper designs a harmonic detection method based on discrete Fourier transform (DFT) and discrete wavelet transform (DWT) using Bartlett–Hann window function. It improves the detection accuracy of the existing methods in the low frequency steady-state part. In addition, it also separates the steady harmonics from the attenuation harmonics of the high frequency part. Simulation results show that the proposed harmonic detection method improves the detection accuracy of the steady-state part by 1.5175% compared to the existing method. The average value of low frequency steady-state amplitude detection of the proposed method is about 95.3375%. At the same time, the individual harmonic components of the signal are accurately detected and recovered in the high frequency part, and separation of the steady-state harmonics and the attenuated harmonics is achieved. This method is beneficial to improve the ability of harmonic analysis in the power grid.

scholarly journals Detection of ULF geomagnetic signals associated with seismic events in Central Mexico using Discrete Wavelet Transform

2010 ◽  
Vol 10 (12) ◽  
pp. 2557-2564 ◽  
Author(s):  
O. Chavez ◽  
J. R. Millan-Almaraz ◽  
R. Pérez-Enríquez ◽  
J. A. Arzate-Flores ◽  
A. Kotsarenko ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Geomagnetic Field ◽  
Seismic Activity ◽  
Seismic Event ◽  
Low Frequency ◽  
Field Measurements ◽  
Seismic Events ◽  
Discrete Wavelet ◽  
Fluxgate Magnetometer

Abstract. The geomagnetic observatory of Juriquilla Mexico, located at longitude –100.45° and latitude 20.70°, and 1946 m a.s.l., has been operational since June 2004 compiling geomagnetic field measurements with a three component fluxgate magnetometer. In this paper, the results of the analysis of these measurements in relation to important seismic activity in the period of 2007 to 2009 are presented. For this purpose, we used superposed epochs of Discrete Wavelet Transform of filtered signals for the three components of the geomagnetic field during relative seismic calm, and it was compared with seismic events of magnitudes greater than Ms > 5.5, which have occurred in Mexico. The analysed epochs consisted of 18 h of observations for a dataset corresponding to 18 different earthquakes (EQs). The time series were processed for a period of 9 h prior to and 9 h after each seismic event. This data processing was compared with the same number of observations during a seismic calm. The proposed methodology proved to be an efficient tool to detect signals associated with seismic activity, especially when the seismic events occur in a distance (D) from the observatory to the EQ, such that the ratio D/ρ < 1.8 where ρ is the earthquake radius preparation zone. The methodology presented herein shows important anomalies in the Ultra Low Frequency Range (ULF; 0.005–1 Hz), primarily for 0.25 to 0.5 Hz. Furthermore, the time variance (σ2) increases prior to, during and after the seismic event in relation to the coefficient D1 obtained, principally in the Bx (N-S) and By (E-W) geomagnetic components. Therefore, this paper proposes and develops a new methodology to extract the abnormal signals of the geomagnetic anomalies related to different stages of the EQs.

A Method of Audio Digital Watermark Based on Discrete Wavelet Transform and Quantization Index Modulation

2011 ◽  
Vol 55-57 ◽  
pp. 970-974
Author(s):  
Pan Li He ◽  
Tie Sheng Fan
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Low Frequency ◽  
Digital Watermark ◽  
Audio Signal ◽  
Discrete Wavelet ◽  
Quantization Index Modulation ◽  
Index Modulation

When a digital watermark is directly embedded into low frequency part of audio, sensitive noises maybe occur. In the paper, a method of audio digital watermark based on quantization index modulation is proposed to solve the problem. At first, audio signal is divided to fragment by audio mask effect. Then low frequency part of discrete wavelet transform (DWT) is extracted. Scrambling watermark is embedded into the low frequency part by quantization index modulation (QIM). The experiment results show that the presented method has a good capacity to fight many attacks.

scholarly journals Speckle Noise Reduction Technique for SAR Images Using Statistical Characteristics of Speckle Noise and Discrete Wavelet Transform

2019 ◽  
Vol 11 (10) ◽  
pp. 1184 ◽  
Author(s):  
Hyunho Choi ◽  
Jechang Jeong
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Multiplicative Noise ◽  
Additive Noise ◽  
Low Frequency ◽  
Speckle Noise ◽  
Discrete Wavelet ◽  
Sar Images ◽  
Soft Threshold ◽  
Speckle Noise Reduction

Synthetic aperture radar (SAR) images map Earth’s surface at high resolution, regardless of the weather conditions or sunshine phenomena. Therefore, SAR images have applications in various fields. Speckle noise, which has the characteristic of multiplicative noise, degrades the image quality of SAR images, which causes information loss. This study proposes a speckle noise reduction algorithm while using the speckle reducing anisotropic diffusion (SRAD) filter, discrete wavelet transform (DWT), soft threshold, improved guided filter (IGF), and guided filter (GF), with the aim of removing speckle noise. First, the SRAD filter is applied to the SAR images, and a logarithmic transform is used to convert multiplicative noise in the resulting SRAD image into additive noise. A two-level DWT is used to divide the resulting SRAD image into one low-frequency and six high-frequency sub-band images. To remove the additive noise and preserve edge information, horizontal and vertical sub-band images employ the soft threshold; the diagonal sub-band images employ the IGF; while, the low- frequency sub-band image removes additive noise using the GF. The experiments used both standard and real SAR images. The experimental results reveal that the proposed method, in comparison to state-of-the art methods, obtains excellent speckle noise removal, while preserving the edges and maintaining low computational complexity.

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