Affiliation:
1. College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
2. Beijing Aeronautical Engineering Technology Research Center, Beijing 100076, China
Abstract
The flight service environment spectrum is essential to the evaluation of the life of components in aeroengines; however, real altitude, as an important flight parameter, introduces considerable challenges when compiling the service environment spectrum because of its non-stationary and non-ergodic characteristics. In this article, by solving trend terms from original data and removing redundancy from peak–valley values, an altitude feature extraction method is developed for the Frequency of Climb–Descent Flight (FCDF). Then, taking the 2D vector, composed of the maximum flight altitude and FCDF, as the input of fuzzy clustering, the service environment spectrum is compiled. Some examples are given to illustrate the presented methods. The results show that the FCDF does not increase with the maximum altitude; during high-altitude flight, the FCDF is the largest, while during mid- to low-altitude flight, the time proportion is the largest. On the other hand, mid-altitude or low-altitude flight not only has a small training frequency for climb–descent actions but also a low time proportion. The research results will provide a reference for the compilation of a service environment spectrum that considers maneuvering flight actions.
Funder
National Science and Technology Major Project