According to the limitations of wavelet threshold in de-noising method, we approached a combining algorithm of the stationary wavelet transform with adaptive filter. The stationary wavelet transformation can suppress Gibbs phenomena in traditional DWT effectively, and adaptive filter is introduced at the high scale wavelet coefficient of the stationary wavelet transformation. It would remove baseline wander and keep the shape of low frequency and low amplitude P wave, T wave and ST segment wave of ECG signal well. That is important for analyzing ECG signal of other feature information.
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Math Biosci Eng
December 2024
School of Information Engineering, Nantong Institute of Technology, Nantong 226002, Jiangsu, China.
As an essential component of mechanical systems, bearing fault diagnosis is crucial to ensure the safe operation of the equipment. However, vibration data from bearings often exhibit non-stationary and nonlinear features, which complicates fault diagnosis. To address this challenge, this paper introduces a novel multi-scale time-frequency and statistical features fusion model (MTSF-FM).
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January 2025
Department of Electrical Power and Machines Engineering, The Higher Institute of Engineering at El- Shorouk City, El-Shorouk Academy, Cairo, 11837, Egypt.
The paper presents a comprehensive analysis of the IEEE-16 bus system under different operating conditions. It discusses the selection of suitable decomposition level and wavelet function for analyzing non-stationary signals to enhance power distribution network fault detection. MATLAB/Simulink is used to simulate the system, and transient fault current signals are processed with the MATLAB Wavelet Toolbox.
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December 2024
Shandong Agricultural University, Taian, 271018, China.
Acoustic emission information can describe the damage degree of rock samples in the process of failure. However, as a discrete non-stationary signal, acoustic emission information is difficult to be effectively processed by conventional methods, while wavelet analysis is an effective method for non-stationary signal processing. Therefore, acoustic emission signal is deeply studied by using wavelet analysis method.
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December 2024
Cancer Epidemiology Department, H. Lee Moffitt Cancer Center and Research Institute, 12902 Bruce B. Downs Blvd, Tampa, FL, 33612, USA.
An archetype signal dependent noise (SDN) model is a component used in analyzing images or signals acquired from different technologies. This model-component may share properties with stationary normal white noise (WN). Measurements from WN images were used as standards for making comparisons with SDN in both the image domain (ID) and Fourier domain (FD).
View Article and Find Full Text PDFJ Xray Sci Technol
December 2024
School of Electrical and Information Engineering, Tianjin University, Nankai District, Tianjin, China.
Background: Airport security is still a main concern for assuring passenger safety and stopping illegal activity. Dual-energy X-ray Imaging (DEXI) is one of the most important technologies for detecting hidden items in passenger luggage. However, noise in DEXI images, arising from various sources such as electronic interference and fluctuations in X-ray intensity, can compromise the effectiveness of object identification.
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