Search

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.

The fatigue feature of LY12-CZ aluminum alloy under atmospheric corrosion environment is studied and the corrosion law is analyzed. Atmosphere data of the service place is collected and the accelerating environment spectrum is built through weighting analysis. The accelerating experiment of LY12-CZ aluminum alloy is carried out and the accelerating factor of spectrum is calculated by analyzing the effective theory of corrosion and declining rule of fatigue life.

Through inversion of the satellite remote sensing data, the values of the environmental factors in the corresponding research area are obtained. By synthesizing the influence of marine environment on damage of the structure, equipment or system, the specific affecting factors in the research area are determined. The inversion results are verified by the measured data. Based on two-year satellite remote sensing data in a certain sea area, the inversion data result is analyzed with the fuzzy clustering theory to determine the optimized solution for clustering number, so as to establish the marine environmental spectrum of that sea area. [ABSTRACT FROM AUTHOR]