Feature mode decomposition (FMD)

Version 1.0.1 (155 KB) by Yonghao Miao

FMD uses the machinery fault feature, i.e. impulsiveness and periodicity of the signal, as the decomposition objective.

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Updated 24 Oct 2022

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Feature mode decomposition (FMD) is an adaptive decomposition method. FMD uses the machinery fault feature, i.e. impulsiveness and periodicity of the signal, as the decomposition objective.

The MATLAB codes of FMD permit to reproduce some results in the papers:

Y. Miao, B. Zhang, C. Li, J. Lin, D. Zhang, Feature Mode Decomposition: New Decomposition Theory for Rotating Machinery Fault Diagnosis, IEEE Transactions on Industrial Electronics, 70 (2023) 1949-1960.

Copyright (c) belongs to the authors of the papers. An acknowledgment for the codes and the citations about all the papers above must be included in the publications as long as the codes are used.

Our works and full texts can refer

https://www.researchgate.net/profile/Yonghao-Miao

https://scholar.google.com.hk/citations?user=gRZ_iZsAAAAJ&hl=zh-CN&oi=ao

Cite As

Yonghao Miao (2024). Feature mode decomposition (FMD) (https://www.mathworks.com/matlabcentral/fileexchange/108099-feature-mode-decomposition-fmd), MATLAB Central File Exchange. Retrieved April 20, 2024.

Yonghao, Miao, et al. “Feature Mode Decomposition: New Decomposition Theory for Rotating Machinery Fault Diagnosis.” IEEE Transactions on Industrial Electronics, Institute of Electrical and Electronics Engineers (IEEE), 2022, pp. 1–1, doi:10.1109/tie.2022.3156156.

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MATLAB Release Compatibility

Created with R2018a

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03-FMD

Version	Published	Release Notes
1.0.1	24 Oct 2022	FMD	Download
1.0.0	17 Mar 2022		Download

MLA	Yonghao, Miao, et al. “Feature Mode Decomposition: New Decomposition Theory for Rotating Machinery Fault Diagnosis.” IEEE Transactions on Industrial Electronics, Institute of Electrical and Electronics Engineers (IEEE), 2022, pp. 1–1, doi:10.1109/tie.2022.3156156.
APA	Yonghao, M., Zhang, B., Li, C., Lin, J., & Zhang, D. (2022). Feature Mode Decomposition: New Decomposition Theory for Rotating Machinery Fault Diagnosis. IEEE Transactions on Industrial Electronics, 1–1. Institute of Electrical and Electronics Engineers (IEEE). Retrieved from https://doi.org/10.1109%2Ftie.2022.3156156
BibTeX	@article{Yonghao_2022, doi = {10.1109/tie.2022.3156156}, url = {https://doi.org/10.1109%2Ftie.2022.3156156}, year = 2022, publisher = {Institute of Electrical and Electronics Engineers ({IEEE})}, pages = {1--1}, author = {Miao Yonghao and Boyao Zhang and Chenhui Li and Jing Lin and Dayi Zhang}, title = {Feature Mode Decomposition: New Decomposition Theory for Rotating Machinery Fault Diagnosis}, journal = {{IEEE} Transactions on Industrial Electronics} }