两种周期型遥测数据建模模型及其初始化算法

Two Models for Periodical Telemetric Data and Its Parameter Initial Algorithm

在对某大型航天电子设备的遥测数据建模预测时,遇到多是不规则周期型数据,对其进行建模预测可以在早期及时发现设备性能异常。针对有周期规律的遥测数据,提出采用Fourier级数模型、sin函数和模型对遥测数据建模,给出了这种数据模型的表达式,研究了基于FFT的两种模型的参数初始化算法。通过数值实验说明模型参数初始化算法的有效性,为后续利用最优化理论求解模型精确参数提供了良好的初试点。

The telemetric data of the large-scale spaceflight electronic equipment usually appears the irregular period, and the performance abnormity would be discovered early through modeling and prediction on these data. In order to modeling the periodical telemetric data, two models of Fourier series and the sum of sin function were introduced. The formula of the two mathematic models was put forward. Then the initial algorithms for the parameters of these models were researched based on FFT. Lastly the numerical experiment results show the validity of these initial parameter algorithms, which afford the favorable initial start points for the subsequent optimization theory to compute the accurate model parameters.