Signal mode regrouping based on Gini index
The presented codes use a postprocessing step to solve the over-decomposition issues of the signal decomposition algorithm for the wide-band impulse signals. It can be combined with any signal decomposition method. It shows promissing advantages in detecting impulse signal components and can be widely used in machine fault diagnosis applications.
The codes permit to reproduce some results in the paper: Chen S, Wang K, Chang C, et al. A two-level adaptive chirp mode decomposition method for the railway wheel flat detection under variable-speed conditions, Journal of Sound and Vibration, 2021. Some of the scripts are adopted from the paper: Chen S, Dong X, Peng Z, et al, Nonlinear Chirp Mode Decomposition: A Variational Method, IEEE Transactions on Signal Processing, 2017. and the paper: Chen S, Yang Y, Peng Z, et al, Detection of Rub-Impact Fault for Rotor-Stator Systems: A Novel Method Based on Adaptive Chirp Mode Decomposition, Journal of Sound and Vibration, 2019.
For more information, please contact:
Shiqian Chen;
chenshiqian@swjtu.edu.cn;
https://www.researchgate.net/profile/Shiqian_Chen2
Cite As
shiqian chen (2024). Signal mode regrouping based on Gini index (https://www.mathworks.com/matlabcentral/fileexchange/87227-signal-mode-regrouping-based-on-gini-index), MATLAB Central File Exchange. Retrieved .
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Codes of two-level ACMD
Version | Published | Release Notes | |
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1.0.0 |