Research on SPWVD Algorithm and its Application Based on Adaptive Combined Window Function
LI Xuantao
CHEN Youxing
WU Qizhou
ZHAO Xia
JIA Bei
Abstract：Aiming at the problem that smoothing pseudo-Wigller-Ville distribution(SPWVD)needs to use corresponding smoothing window parameters to achieve the optimal time-frequency distribution when dealing with different signals,a SPWVD al-gorithm based on adaptive combined window function is proposed.In this algorithm,Rényi entropy is taken as the time-frequency evaluation index,and the window length and coefficient of the combined window function are taken as the parameter library.Ran-dom gradient descent and disturbance random gradient descent are used to select the window length and coefficient respectively,and the calculation speed is 20 times and 9 times higher than that of the ergodic method.Respectively,finally the optimal time-fre-quency diagram of the signal is obtained.The improved method mentioned above is applied to the defect detection of carbon fiber re-inforced polymer.The results show that the SPWVD of adaptive combined window function can effectively select the optimal window function parameter for different signals.Compared with the SPWVD of fixed window function,the SPWVD of adaptive combined window function has better time-frequency aggregation effect,more complete signal characterization and quantitative analysis of de-fects.It has a good application prospect of defect detection.
Keywords：Smoothing Pseudo-Winger-Ville distribution(SPWVD)combined window functionStochastic Gradient De-scent(SGD)Perturbed Stochastic Gradient Descent(PSGD)Carbon Fiber Reinforced Polymer(CFRP)
Publication Date：2024-02-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 29-34 )