A study on a derivation method for stationary acoustic environment conditions using sound pressure spectral equalization to ensure the equivalence of extreme response and cumulative fatigue with a non-stationary acoustic environment
Year: 2025
Type: article
Abstract: Spacecraft systems are exposed to a random and non-stationary acoustic environment inside the rocket fairing during launch, necessitating acoustic testing to verify their vibro-acoustic resilience. The conventional approach for deriving stationary acoustic environment conditions for these tests typically employs octave band analysis based on the short-time Fourier transform (STFT). However, this method has been criticized for its inadequacy in ensuring equivalence in extreme response and cumulative fatigue experienced by the test structure. The authors previously proposed a method for deriving stationary acoustic environment conditions by applying the extreme response spectrum (ERS) and the fatigue damage spectrum (FDS), ensuring that the extreme response and cumulative fatigue induced in the structure are equivalent to those caused by a non-stationary acoustic environment. However, this method relies on the assumption that the distribution of extreme responses follows a Rayleigh distribution, which may not always guarantee equivalence when the vibration response exhibits a broadband random process. This study proposes a new method for adjusting the sound pressure spectrum to ensure equivalence in extreme response and cumulative fatigue between the stationary and non-stationary acoustic environments. The proposed method was applied to flight telemetry of acoustic pressure inside an actual rocket fairing, demonstrating its capability to derive more appropriate stationary acoustic environment conditions with respect to ensuring equivalence in extreme response and cumulative fatigue to a non-stationary acoustic environment.
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $602
OpenAlex ID: W4413014809