Noisy Data Processing of Solid Rocket Motors Based on the Ada-S-WTD Model

This paper proposes an adaptive wavelet threshold denoising model (Ada-S-WTD) for thrust data refinement in solid rocket motors, integrating an Improved Soft-Hard (ISH) threshold function with Pelican Optimization Algorithm (POA). The ISH function combines logistic S-shaped transitions and adaptive parameter adjustment to suppress pseudo-Gibbs oscillations while preserving signal features. Experimental results using db3 wavelet basis demonstrate the high accuracy of the AVOA algorithm(F=8.2724) and using sym4 wavelet basis demonstrate comprehensive improvements: 59% data validity (EDR_F) with 78.57% enhancement over SA-WTD, 22.897dB signal-to-noise ratio (16.92% higher than IC-WTD), and 52.55% thrust fluctuation (V_flu) reduction from raw data. The model resolves traditional noise-feature trade-offs through synergetic optimization of theoretical metrics (SNR) and engineering indicators (EDR_F/V_flu).