Time-Frequency Analysis Based on PNN for Nonstationary Random Vibration of Spacecraft
Authors
Hai Yang1, Wei Cheng, Hong Zhu, None None
1Institute of Solid Mechanics, Beijing University of Aeronautics and Astronautics
Corresponding Author
Hai Yang
Available Online October 2007.
- DOI
- 10.2991/iske.2007.75How to use a DOI?
- Keywords
- time-varying parameter; power spectrum; process neural network; EMD
- Abstract
In view of the disadvantages of the traditional time-varying algorithm about nonstationary random vibration signal of a spacecraft with close spaced modal frequency. A process neural network (PNN) based on the empirical mode decomposition (EMD) method is put forward. First, the EMD method is utilized to decompose the signal into several intrinsic mode functions (IMFs). Then for each IMF, The PNN is established and time-varying auto-spectral density is obtained. Finally, the time-varying auto-spectral density of the signal can be reconstituted by linear superposing. The example analyzed results suggest effectiveness of this new method in time-frequency analysis.
- Copyright
- © 2007, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Hai Yang AU - Wei Cheng AU - Hong Zhu AU - None None PY - 2007/10 DA - 2007/10 TI - Time-Frequency Analysis Based on PNN for Nonstationary Random Vibration of Spacecraft BT - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007) PB - Atlantis Press SP - 447 EP - 453 SN - 1951-6851 UR - https://doi.org/10.2991/iske.2007.75 DO - 10.2991/iske.2007.75 ID - Yang2007/10 ER -