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- Title
A Noise Reduction Method for Multiple Signals Combining Computed Order Tracking Based on Chirplet Path Pursuit and Distributed Compressed Sensing.
- Authors
Guangfei Jia; Fengwei Guo; Zhe Wu; Suxiao Cui; Jiajun Yang
- Abstract
With the development of multi-signal monitoring technology, the research on multiple signal analysis and processing has become a hot subject. Mechanical equipment often works under variable working conditions, and the acquired vibration signals are often non-stationary and nonlinear, which are difficult to be processed by traditional analysis methods. In order to solve the noise reduction problem of multiple signals under variable speed, a COT-DCS method combining the Computed Order Tracking (COT) based on Chirplet Path Pursuit (CPP) and Distributed Compressed Sensing (DCS) is proposed. Firstly, the instantaneous frequency (IF) is extracted by CPP, and the speed is obtained by fitting. Then, the speed is used for equal angle sampling of time-domain signals, and angle-domain signals are obtained by COT without a tachometer to eliminate the nonstationarity, and the angledomain signals are compressed and reconstructed by DCS to achieve noise reduction of multiple signals. The accuracy of the CPP method is verified by simulated, experimental signals and compared with some existing IF extraction methods. The COT method also shows good signal stabilization ability through simulation and experiment. Finally, combined with the comparative test of the other two algorithms and four noise reduction effect indicators, the COT-DCS based on the CPP method combines the advantages of the two algorithms and has better noise reduction effect and stability. It is shown that this method is an effective multi-signal noise reduction method.
- Subjects
COMPRESSED sensing; CHIRPLET transform (Signal processing); MECHANICAL equipment in buildings; NOISE control; FAULT diagnosis
- Publication
Structural Durability & Health Monitoring (SDHM), 2023, Vol 17, Issue 5, p383
- ISSN
1930-2983
- Publication type
Article
- DOI
10.32604/sdhm.2023.026885