Abstract:
Reusable launch vehicle is important to reduce the cost of launch service. This paper focuses on the modeling difficulty on the original fatigue load data of reusable launch vehicle engine. In this paper, the root mean square value is selected as the division standard for the original fatigue load data of the reusable launch vehicle. Original data are processed by modified short-time Fourier wave filtering, rain flow cycle counting and Gaussian distribution fitting for the identification and regularization of fatigue load data. Fatigue load data of reusable launch vehicle can be described by Gaussian distribution model. The Gaussian distribution parameter of abnormal fatigue load data is more than 3 times of normal fatigue load data. This method can be used to accurately identify the abnormal fatigue load data. Compared with traditional anomaly data identification methods, this method provides a quantitative index of abnormal data, which is a new analysis method for fatigue load design and real-time fault analysis and location of reusable launch vehicle.