Journal ArticleDOI
The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
Norden E. Huang,Zheng Shen,Steven R. Long,Man-Li C. Wu,Hsing H. Shih,Quanan Zheng,Nai-Chyuan Yen,C. C. Tung,Henry H. Liu +8 more
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TLDR
In this paper, a new method for analysing nonlinear and nonstationary data has been developed, which is the key part of the method is the empirical mode decomposition method with which any complicated data set can be decoded.Abstract:
A new method for analysing nonlinear and non-stationary data has been developed. The key part of the method is the empirical mode decomposition method with which any complicated data set can be dec...read more
Citations
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A criterion for selecting relevant intrinsic mode functions in empirical mode decomposition
TL;DR: A stringent threshold by which relevant IMFs are distinguished from IMFs that may have been generated by numerical errors is established, dependent on the correlation coefficient between the IMFs and the original signal.
Journal ArticleDOI
Fault diagnosis of diesel engine based on adaptive wavelet packets and EEMD-fractal dimension
TL;DR: In this article, an adaptive wavelet threshold (AWT) de-noising, ensemble empirical mode decomposition (EEMD) and correlation dimension (CD) is used for diesel engine faults.
Journal ArticleDOI
A Fault Diagnosis Scheme for Rolling Bearing Based on Particle Swarm Optimization in Variational Mode Decomposition
Cancan Yi,Yong Lv,Zhang Dang +2 more
TL;DR: In this paper, a novel method of fault feature extraction based on the combination of VMD and particle swarm optimization (PSO) algorithm is proposed, which can be utilized as a potential method in extracting the faint fault information of rolling bearings compared with the common method of envelope spectrum analysis.
Journal ArticleDOI
An improved residual-based convolutional neural network for very short-term wind power forecasting
TL;DR: The proposed method outperformed the state-of-the-art deep learning architectures and demonstrated promising results for very short-term wind power forecasting due to its competitive performance.
Journal ArticleDOI
Feature Selection for Accelerometer-Based Posture Analysis in Parkinson's Disease
TL;DR: Assessment of the feasibility of using accelerometers to characterize the postural behavior of early mild PD subjects suggests that quantitative posture analysis using a single accelerometer and a simple test protocol may provide useful information to characterize early PD subjects.
References
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TL;DR: In this paper, the authors used the representations of the noise currents given in Section 2.8 to derive some statistical properties of I(t) and its zeros and maxima.
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