相空间稀疏化的信号压缩感知与重构方法

发布时间：2018-01-15 04:12

本文关键词：相空间稀疏化的信号压缩感知与重构方法　出处：《振动.测试与诊断》2017年02期 　论文类型：期刊论文

【摘要】：针对旋转机械振动信号受强噪声干扰导致传统FFT频域稀疏性差,难以进行正交匹配重构的问题,提出了相空间稀疏化结合正交匹配追踪(orthogonal matching pursuit,简称OMP)的信号压缩感知(compressed sensing,简称CS)方法。首先,对信号进行相空间重构(phase space reconstruction,简称PSR),并采用主分量分析(principal component analysis,简称PCA)提取主要分量和重构信号,以提高信号的频域稀疏性;然后,采用随机高斯矩阵测量及压缩频域稀疏性得到优化的信号;最后,采用正交匹配追踪算法重构信号。仿真信号和转子典型不对中信号的分析结果表明,该方法可以提高受强噪声干扰的振动信号在频域内的稀疏性,实现转子振动信号的有效压缩和准确重构。
[Abstract]:In order to solve the problem that the vibration signal of rotating machinery is disturbed by strong noise, the sparsity of traditional FFT in frequency domain is poor, so it is difficult to carry out orthogonal matching reconstruction. In this paper, the phase space sparseness combined with orthogonal matching tracing is proposed for orthogonal matching pursuit. OMP-based signal compression sensing (CSM) method. First of all. Phase space construction for the signal. The principal component analysis (PCA) is used to extract the main components and reconstruct the signal to improve the frequency domain sparsity of the signal. Then, the optimized signal is obtained by using random Gao Si matrix measurement and compression frequency domain sparsity. Finally, the orthogonal matching tracking algorithm is used to reconstruct the signal. The analysis results of the simulation signal and the typical misalignment signal of the rotor show that the method can improve the sparsity of the vibration signal in the frequency domain caused by strong noise interference. Effective compression and accurate reconstruction of rotor vibration signal are realized.
【作者单位】：西安交通大学机械工程学院;
【基金】：国家自然科学基金资助项目(51365051,51421004) 教育部新世纪优秀人才支持计划资助项目(NCET-13-0461) 中央高校基本科研业务费专项资金资助项目
【分类号】：TH17;TN911.7
【正文快照】： 引言旋转机械(如离心式压缩机、风力发电机组、大型汽轮发电机组等)是现代大型企业中的核心设备,在石油、化工等领域得到了广泛应用[1-3]。为保障转子、轴承和齿轮箱等核心部件长期安全稳定运行,实时监测其运行状态尤为重要。然而,当前旋转机械信息的采集通常表现出测点多、传

【相似文献】