Two-dimensional empirical mode decomposition by finite elements

2006 ◽  
Vol 462 (2074) ◽  
pp. 3081-3096 ◽  
Author(s):  
Y Xu ◽  
B Liu ◽  
J Liu ◽  
S Riemenschneider
Keyword(s):  
Finite Element ◽  
Linear Combination ◽  
Empirical Mode Decomposition ◽  
Spline Interpolation ◽  
Basis Functions ◽  
Two Dimensional ◽  
Element Analysis ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Mode Decomposition

Empirical mode decomposition (EMD) is a powerful tool for analysis of non-stationary and nonlinear signals, and has drawn significant attention in various engineering application areas. This paper presents a finite element-based EMD method for two-dimensional data analysis. Specifically, we represent the local mean surface of the data, a key step in EMD, as a linear combination of a set of two-dimensional linear basis functions smoothed with bi-cubic spline interpolation. The coefficients of the basis functions in the linear combination are obtained from the local extrema of the data using a generalized low-pass filter. By taking advantage of the principle of finite-element analysis, we develop a fast algorithm for implementation of the EMD. The proposed method provides an effective approach to overcome several challenging difficulties in extending the original one-dimensional EMD to the two-dimensional EMD. Numerical experiments using both simulated and practical texture images show that the proposed method works well.

scholarly journals How well does a linear static finite element analysis predict measured strains from a nuclear package tie-down system during rail transportation?

2016 ◽  
Vol 232 (1) ◽  
pp. 222-237 ◽  
Author(s):  
Andrew Cummings ◽  
Glynn Rothwell ◽  
Christian Matthews
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Element Model ◽  
Radioactive Material ◽  
Element Analysis ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Dangerous Goods ◽  
Codes Of Practice ◽  
Low Pass

Freight rail is often the preferred method for transportation of dangerous goods. One particular application is the use of rail to convey radioactive material in purpose-built packages. During transit, packages are secured to a rail wagon bed with a tie-down system. The design of tie-down systems varies considerably depending on the package type and rail vehicle; for example, shackles, turnbuckles, tie rods, gravity wells or transport frames are all commonly used. There are also a large number of different packages in existence that all vary in size and mass, typically 1–7 m in length and 100 kg–100 t in mass. Despite the uniqueness of many transport configurations, the design of tie-down systems is always carried out using a limited set of design load cases as defined in the appropriate Codes of Practice and Standards. Many authors have suggested that the load cases within the standards need revision or question which load cases should apply to which scenario. In a previous experiment, accelerations and strains have been measured on a freight wagon and transport frame of a heavy package during a routine rail journey. From these data, a new insight into the magnitude and nature of loading has been gained. In the present study, the measured accelerations have been used as input to a finite element model of the transport frame, and a method based on correlation between predicted and measured strains has been developed to determine an appropriate low-pass filter cut-off frequency, fc, which separates quasi-static loading from raw dynamic data. The residual dynamic measurements have been assessed using signal processing techniques to understand their significance. The finite element model has also been used to assess the presence of contact and boundary nonlinearities and how they affect the agreement between measured and predicted strains.

scholarly journals Removal of Baseline Wander from Electrocardiogram using Ensemble Empirical Mode Decomposition and Low Pass Filter

2019 ◽  
Vol 8 (4) ◽  
pp. 2771-2774
Keyword(s):  
Empirical Mode Decomposition ◽  
Human Heart ◽  
Signal To Noise Ratio ◽  
Normal Sinus Rhythm ◽  
Ensemble Empirical Mode Decomposition ◽  
Comparative Performance ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Mode Decomposition ◽  
Baseline Wander

Electrocardiogram (ECG) is a graphical visualization of the electrical activity of human heart. The biomedical signal, such as ECG, has a major issue of separating the pure signal from artifacts due to baseline wander (BW), electrode artifacts, muscle artifacts, and power-line interference. Reduction of these artifacts is vital for clinical purposes for diagnosis and interpretation of the human heart condition. This paper presents removal of BW from ECG using ensemble empirical mode decomposition (EMD) with multiband filtering approach. A comparative performance analysis of EMD and ensemble EMD for synthetic as well as real BW on normal sinus rhythm and arrhythmia ECG signal are presented. This method can remove the BW in different inherent signal to noise ratio (SNR) including negative and positive as well. This method shows that quantitative and qualitative results with miniscule signal distortion via experiments on several ECG records.

scholarly journals An Improved EMD and Its Applications to Find the Basis Functions of EMI Signals

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Hongyi Li ◽  
Chaojie Wang ◽  
Di Zhao
Keyword(s):  
Empirical Mode Decomposition ◽  
Spline Interpolation ◽  
Basis Functions ◽  
B Spline ◽  
Minimal Points ◽  
Mode Decomposition ◽  
Lower Envelopes ◽  
The Mean ◽  
The Cost ◽  
Emd Method

A B-spline empirical mode decomposition (BEMD) method is proposed to improve the celebrated empirical mode decomposition (EMD) method. The improvement of BEMD on EMD mainly concentrates on the sifting process. First, instead of the curve that resulted from computing the average of upper and lower envelopes, the curve interpolated by the midpoints of local maximal and minimal points is used as the mean curve, which can reduce the cost of computation. Second, the cubic spline interpolation is replaced with cubic B-spline interpolation on account of the advantages of B-spline over polynomial spline. The effectiveness of BEMD compared with EMD is validated by numerical simulations and an application to find the basis functions of EMI signals.

CONVERGENCE OF A CONVOLUTION-FILTERING-BASED ALGORITHM FOR EMPIRICAL MODE DECOMPOSITION

2009 ◽  
Vol 01 (04) ◽  
pp. 561-571 ◽  
Author(s):  
CHAO HUANG ◽  
LIHUA YANG ◽  
YANG WANG
Keyword(s):  
Empirical Mode Decomposition ◽  
Iterative Algorithm ◽  
Moving Average ◽  
Limit Function ◽  
Continuous Variables ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Mode Decomposition ◽  
Low Pass ◽  
Convolution Filters

Lin et al. propose the iterative Toeplitz filters algorithm as an alternative iterative algorithm for Empirical Mode Decomposition (EMD). In this alternative algorithm, the average of the upper and lower envelopes is replaced by certain "moving average" obtained through a low-pass filter. Performing the traditional sifting algorithm with such moving averages is equivalent to iterating certain convolution filters (finite length Toeplitz filters). This paper studies the convergence of this algorithm for signals of continuous variables, and proves that the limit function of this iterative algorithm is an ideal high-pass filtering process.

Diagnosis of Low-Speed Helical Gears Based on Hilbert Demodulation and Empirical Mode Decomposition

2013 ◽  
Vol 572 ◽  
pp. 443-446
Author(s):  
Bao Yu Song ◽  
Zhi Jie Xie ◽  
Feng Zhang ◽  
Jin Ping Yang
Keyword(s):  
Fault Diagnosis ◽  
Empirical Mode Decomposition ◽  
Vibration Signal ◽  
Intrinsic Mode Functions ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Helical Gears ◽  
Low Speed ◽  
Mode Decomposition ◽  
Vibration Signal Analysis

As the vibration signal of helical gears is nonlinear and nonstationary, it is very difficult to diagnose their faults based on the vibration signal analysis and processing, particularly when the gears rotate at low speed. In this paper, an applicable fault diagnosis approach is proposed based on Hilbert demodulation and EMD (empirical mode decomposition). Firstly, the modulated signals are extracted through Hilbert envelope demodulationand low pass filter. Furthermore, EMD is used to decompose the multi-component demodulated signal into a series of intrinsic mode functions (IMFs) whose instantaneous frequencies have a physically meaningful characterization of the original signal. Finally, the fault features of low-speed helical gear are obtained by the spectrum analysis to each IMF. The experiments of tooth broken fault diagnosis show that this method is more effective than traditional Hilbert demodulation analysis.

Two-Dimensional Full-Vectorial Finite Element Analysis of NRD Guide Devices

2021 ◽  
Vol 31 (4) ◽  
pp. 345-348
Author(s):  
Yasuhide Tsuji ◽  
Keita Morimoto ◽  
Akito Iguchi ◽  
Tatsuya Kashiwa ◽  
Shinji Nishiwaki
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Two Dimensional ◽  
Element Analysis ◽  
Nrd Guide

Rayleigh-Ritz Analysis of Vibrating Plates Based on a Class of Eigenfunctions

2009 ◽  
Author(s):  
Giuseppe Catania ◽  
Silvio Sorrentino
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Boundary Conditions ◽  
Linear Combination ◽  
Equation Of Motion ◽  
Extensive Literature ◽  
Shape Functions ◽  
Element Analysis ◽  
Vibrating Plates ◽  
General Basis

In the Rayleigh-Ritz condensation method the solution of the equation of motion is approximated by a linear combination of shape-functions selected among appropriate sets. Extensive literature dealing with the choice of appropriate basis of shape functions exists, the selection depending on the particular boundary conditions of the structure considered. This paper is aimed at investigating the possibility of adopting a set of eigenfunctions evaluated from a simple stucture as a general basis for the analysis of arbitrary-shaped plates. The results are compared to those available in the literature and using standard finite element analysis.

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