基于相空间重构的PHM数据处理算法研究

Research on Data Processing of PHM Algorithm Based on Phase Space Reconstruction

摘要:

采集数据的非线性特性极大地限制了故障预测与健康管理技术(PHM)在飞机自主保障能力中的应用,提出了一种基于相空间重构的数据处理方法;首先,对PHM技术进行了系统研究,并对数据处理进行了分析；然后,根据数据处理的特点,分别采用自相关法、复自相关法、FNN法和C-C法计算相关的延迟时间及嵌入维数；最后,通过仿真对比分析以上几种方法得到的延迟时间与嵌入维数;结果表明作为一种联合计算延迟时间和嵌入维数的数据处理方法,C-C法可以同时计算延迟时间τ为3和嵌入维数m为6。

Abstract:

For the nonlinear characteristics of data collection, which greatly limit the capability of Prognostics and Health Management (PHM) technology to apply to the self-protection ability of aircraft, a method of data processing based on phase space reconstruction is proposed. Firstly, the PHM technology has been systematic studied and its core (data processing) is also analyzed. Secondly, according to the characteristics of the data processing, the delay time and embedding dimension can be calculated using autocorrelation, multiple autocorrelation method, FNN method and the C-C method respectively. Lastly, compared with the embedding dimension and delay time through the above method, the simulation results show that as a kind of data processing method for combined calculation, C-C method has higher computational efficiency in the analysis of original data of PHM.