Abstract
Low-frequency errors are a type of testing errors commonly existing in pyroshock experiments due to the harsh mechanical environment that lead to inaccuracy and contamination of pyroshock data. It is necessary to eliminate such low-frequency errors from pyroshock data via data analysis. Two methods based on discrete wavelet transform (DWT) and ensemble empirical mode decomposition (EEMD) are proposed, respectively, in this article. Firstly, the principle and operating process of these two methods are introduced, where four correlation coefficients are defined to determine the decomposition level for quantitative correction. Then, the two methods are applied to remove the integral zero shift from a set of pyroshock test data, respectively, and the capability and effectiveness of the two methods are compared. It is revealed from the comparison studies that both methods are capable of removing integral zero shift effectively to correct the shock response spectrum and improve the accuracy of pyroshock data. The correlation coefficients constructed here can help to realize quantitative selection of key parameters for the two methods. The DWT method shows better correction performance for extracting accurate parameters, whereas the EEMD method is more concise and convenient for application.
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Data Availability Statement
All data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors acknowledge support from the National Natural Science Foundation of China (Grant Nos. 11902286 and 11972204).
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Published In
Journal of Aerospace Engineering
Volume 35 • Issue 5 • September 2022
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Jan 21, 2022
Accepted: Apr 8, 2022
Published online: May 27, 2022
Published in print: Sep 1, 2022
Discussion open until: Oct 27, 2022
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