Vehicle platform vibration (VPV) directly affects the measurement accuracy of precise measuring instrument (PMI) fixed on it. In order to reduce the influences of VPV on measurement accuracy, it is necessary to perform vibration isolation between vehicle platform and PMI. Analysis of vibration characteristics is a prerequisite for vibration isolation. However, empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD) reveal that there is obvious mode mixing phenomenon in the collected VPV signals. In this paper, a noise stretch ensemble empirical mode decomposition (NSEEMD) method is proposed to suppress mode mixing, and the specific operation process of NSEEMD is expounded. By NSEEMD, mode mixing of the collected platform vibration data is well suppressed, and the principal component of platform vibration can be obtained.

中文翻译：

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基于经验模态分解的车辆平台振动分析

车辆平台振动（VPV）直接影响固定在其上的精密测量仪器（PMI）的测量精度。为了减少VPV对测量精度的影响，有必要在车辆平台和PMI之间进行隔振。振动特性分析是隔振的前提。然而，经验模态分解（EMD）和整体经验模态分解（EEMD）表明，在所收集的VPV信号中存在明显的模态混合现象。本文提出了一种噪声拉伸集成经验模态分解（NSEEMD）方法来抑制模式混合，并阐述了NSEEMD的具体工作过程。通过NSEEMD，可以很好地抑制所收集平台振动数据的模式混合，并且可以获得平台振动的主要成分。