基于VMD-PWVD的内燃机振动信号时频分析方法

发布时间：2018-05-24 00:22

本文选题：内燃机 + 振动信号　；参考：《武汉科技大学学报》2016年05期

【摘要】：针对Wigner-Ville分布(WVD)在分析多分量信号时交叉干扰项与时频聚集性相互矛盾的问题,提出一种基于变分模态分解的伪魏格纳分布法(VMD-PWVD),以抑制WVD分布中的交叉项。该方法首先对信号进行VMD分解,将信号在频域上进行剖分,得到一组相互独立的具有不同频率的固有模态函数(IMF)分量,然后对每个IMF分量进行PWVD分析,最后把各个IMF分量的PWVD分析结果线性叠加,重构原始信号的时频分布。仿真结果表明,该方法在有效地从频域和时域双向抑制WVD交叉项的同时,又保留了WVD分布法原有的优良特性。将VMD-PWVD应用于内燃机缸盖振动信号的时频分析中,能很好地刻画出不同工况信号的特征信息,各时频分量物理意义明确,是一种有效的时频分析方法。
[Abstract]:In view of the contradiction between the cross-interference term and time-frequency aggregation when Wigner-Ville distribution is used to analyze multi-component signals, a pseudo-Wigner distribution method based on variational mode decomposition (VMD) is proposed to suppress the cross term in WVD distribution. In this method, the signal is decomposed by VMD, and the signal is partitioned in frequency domain to obtain a set of independent intrinsic mode functions with different frequencies. Then, each IMF component is analyzed by PWVD. Finally, the PWVD analysis results of each IMF component are stacked linearly to reconstruct the time-frequency distribution of the original signal. The simulation results show that the proposed method can effectively suppress WVD crossover terms in frequency domain and time domain, while preserving the original excellent characteristics of WVD distribution method. The application of VMD-PWVD to the time-frequency analysis of cylinder head vibration signals of internal combustion engines can well depict the characteristic information of the signals under different working conditions. The physical meaning of each time-frequency component is clear, so it is an effective time-frequency analysis method.
【作者单位】：火箭军工程大学理学院;
【基金】：国家自然科学基金资助项目(51405498) 陕西省自然科学基金资助项目(2013JQ8023) 中国博士后科学基金资助项目(2015M582642)
【分类号】：TK401;TN911.6

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