当前对于车辆进行非平稳振动模拟时一般仅考虑其强度的非平稳性。受到地面-车辆系统中多种因素的影响，实测振动谱在频域上往往也是非平稳的。通过对车辆振动信号进行小波包分解，并对其小波包系数矩阵的归一化列向量进行模糊C均值聚类，可实现对振动谱中振动模式的自动分类与统计。进而依据聚类结果，提出了一种可产生具有与原采集谱相似的频域非平稳特性的重构振动谱的方法。通过将该方法应用于某试验场块石路响应谱的重构模拟，所生成的重构谱与原采集谱相比，在时域、频域以及幅值概率密度等方面均具有理想的相似程度，验证了所提方法在车辆振动谱模拟方面的正确性和实用性。为车辆乃至各类机械结构的振动模拟试验提供了一种能够产生更为真实的具有频域非平稳特性重构振动谱的方法。
Abstract
At present, non-stationary vibration simulation for vehicles only considers the non-stationarity of their vibration intensity.Due to effects of various factors in a ground-vehicle dynamic system, the actual vehicle vibration spectrum may also be non-stationary in frequency domain.Here, the wavelet packet decomposition was conducted for vehicle vibration signals, and the normalized column vectors of the wavelet packet coefficient matrix were clustered with the fuzzy C-mean clustering algorithm to realize automatic classification and statistics of vibration modes in vehicle vibration spectra.According to clustering results, a method that could produce a reconstructed vibration spectrum with frequency domain non-stationary characteristics similar to those of the original collected spectrum was proposed.This method was employed in reconstruction simulation for vehicle response spectrum on a block stone road of a certain test field.Compared with the original collected spectrum, the reconstructed spectrum has an ideal similarity in time domain, frequency one and amplitude probability density.The correctness and practicability of the proposed method was verified.The study results provided a method producing a reconstructed vibration spectrum with more realistic frequency domain non-stationary characteristics for vibration simulation tests of vehicles and other mechanical structures.
关键词
车辆振动 /
小波包变换 /
模糊C均值聚类 /
非平稳 /
道路模拟
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Key words
vehicle vibration /
wavelet packet transform /
fuzzed c-means clustering /
non-stationary /
road simulation
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