ACTA AERONAUTICAET ASTRONAUTICA SINICA >
Fast algorithm for non-Gaussian stochastic processes based on translation processes
Received date: 2023-11-29
Revised date: 2023-12-13
Accepted date: 2024-01-24
Online published: 2024-02-02
In the non-Gaussian stationary random vibration environment testing technology， testing techniques based on probability density functions can more accurately reproduce the test environment. However， existing simulation algorithms based on probability density functions suffer from efficiency issues， making it challenging to apply them to engineering. A fast algorithm for simulating non-Gaussian stationary stochastic processes is proposed in this paper based on the translation process theory of stochastic processes. To address the difficulties and slow computation speed in critical double integral calculations of the field transformation theory， we expand the correlation coefficient functions of two random processes in series. This approach transforms a complicated double integral with an implicit function into a simple definite integral， which is efficiently solved using the Gauss-Hermite quadrature rule. Numerical simulations validate that this method can improve the efficiency of simulating non-Gaussian stationary random processes without compromising simulation accuracy， meeting the real-time requirement for generating random signals in the context of random vibration environment experiments.
Jinming LIU , Xing TAN , Weiting CHEN , Huan HE . Fast algorithm for non-Gaussian stochastic processes based on translation processes[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2024 , 45(18) : 229923 -229923 . DOI: 10.7527/S1000-6893.2024.29923
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