履带车辆传动系统载荷信号的分形延拓研究

Research of the Fractal Extrapolation of Transmission System Load Signal of Tracked Vehicle

针对重载履带车辆中传动系统载荷测试数据量过大,信息提取率不高的问题,对该数据的内在分形层次规律进行了研究,证实了该数据具备典型的分形特征并获得了某路况下履带车辆传动系统载荷数据的分形参数。在保证数据统计精度和分形特征的前提下,建立了一种新的分形插值方法,实现了对精简数据的信息延拓,通过与线性插值、样条插值的计算结果进行对比,证明了将"低频长时"数据采集与该分形延拓分析相结合的方法,能够提高载荷历程的测试效率,精确地表征高频采样数据的复杂混沌特征,并为重载履带车辆传动系统动态混沌特性的研究提供一种分析手段。

Aiming at the problem of load test data volume of transmission system of heavy tracked vehicles（HTVs） is huge and extraction rate of effective information is low,the inherent fractal hierarchical rule of this data is studied,this data have the typical fractal characteristic is verified and the fractal parameter of the tracked vehicle transmission system load data under a certain road condition.Under the premise of ensurse data accuracy and fractal character,a new fractal interpolation method（FIM） is built,the continuation to simplify data information is realized.Moreover,obvious advantages could be observed in the results of the FIM,comparing to those of the linear interpolation method and the spline interpolation method.It could be concluded that by combining a’low-frequency-and-long- time’ sampling approach and the proposed FIM,the test efficiency of load history can be improved,the complex chaotic feature of high frequency sampling data can be represented.And a analysis way for researching the dynamic chaos characteristic of the HTVs transmission system is provided.