Recognition of non-stationary signal instantaneous frequency with LMSSGST based on sliding window width optimization

Here, to improve the recognition effect of instantaneous frequency of non-stationary response signals, a local maximum synchronous squeezing generalized S-transform ( LMSSGST ) based on sliding window width optimization was proposed. Firstly, this method could perform a generalized S-transform for non-stationary response signals to obtain corresponding time-frequency coefficients. Secondly, the power spectral density characteristic curve of response signals was used to determine sliding window width in LMSS operator. Once again, time-frequency rearrangement was performed with local maximum synchronous squeezing operator. Finally, the modulus maximum value improvement algorithm was used to extract the instantaneous frequency curve. The effectiveness of the proposed method was verified with two numerical examples, a sliding window width parametric analysis and a time-varying cable test. The study results showed that using power spectral density characteristic curve can effectively determine sliding window width and the extraction range of the modulus maximum value algorithm; compared to LMSST algorithm, LMSSGST based on sliding window width optimization has the better recognition effect on instantaneous frequency. © 2024 Chinese Vibration Engineering Society. All rights reserved.