In the study of random vibration problems, Gaussian vibration and non-Gaussian vibrations are usually classified according to the excitation signal. The skewness and kurtosis are usually used to distinguish. Here we discuss a non-strict Gaussian signal, which is the error that exists in skewness and kurtosis and usually unavoidable in actual experiments or signals analysis. Through experiments and simulation calculations, the influence of this error on the traditional fatigue calculation method is discussed. The PSD approach will be discussed primarily, and time domain signals based on the rain-flow counting method will be recorded and verified. Total nine calculation model studied in this process. Finally, through a threshold, the range of skewness and kurtosis is indicated, that within this range, Gaussian signal-based calculations can be continued. By comparing the performance of different methods, a better method for signal adaptability can be obtained. 

Keywords: Random vibration fatigue, Damage cumulative calculation, and Gaussian random vibration.

References:

[1] Y. WANG, R. SERRA Life assessment of structures using random vibration testing, ENVIRORISK Bourges 3ème edition June 2018

[2] R. SERRA, L. KHALIJ et al. Effects de l'environnement vibratoire sur la durée de vie d'une éprouvette en aluminum. SF2M, 35èmes Journées de Printemps, Mai 2016.