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121.
针对矿用齿轮箱振动信号的特点,提出了一种基于经验模态分解(empirical mode decomposition,简称EMD)与同态滤波相结合的故障解调方法.利用EMD对某矿用皮带机齿轮箱故障信号进行分解,得到若干个本征模态函数(intrinsic mode functions,简称IMFs)分量,然后对其中较突出的IMFs进行同态滤波解调分析,提取出了频率为7.0Hz的调制故障信号.研究表明,EMD与同态滤波解调相结合是一种有效的齿轮箱故障诊断方法. 相似文献
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滚动轴承早期故障信号具有能量小、频带分布宽等特征,易受到其它能量较大振源信号的干扰。传统的希尔伯特-黄变换(HHT)对信噪比大、多频率调制信号常因不能对其所包含的固有模式函数(IMF)实现准确分离和去除调制干扰分量而失效。本文提出了基于HHT和独立分量分析(ICA)的滚动轴承诊断新方法。该方法首先利用经验模式分解(EMD)将滚动轴承振动信号分解成若干平稳的本征模式函数IMF分量,通过提取若干包含主要信息的IMF分量,应用带通滤波器和Hilbert变换获取IMF分量的高频包络波形,再应用ICA分离包络波形并进行频谱分析,进而判断滚动轴承的运行状况。仿真和试验分析结果验证了本方法的可行性。 相似文献
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旋转机械振动信号基于EMD的HT和STFT时频分析比较 总被引:2,自引:0,他引:2
基于经验模态分解(Empinrical Mode Decomposition,EMD)的希尔伯特变换(Hilbert Transformation,HT),是先把一列时间序列数据通过经验模态分解,然后经过希尔伯特变换获得频谱的信号处理新方法。介绍了该方法的理论和算法。对仿真和旋转机械油膜涡动故障振动信号分别用基于EMD和基于STFT(Short-Time Fourier Transformation,STFT)的时频分析进行了比较研究,研究结果说明,用基于EMD的HT方法对旋转机械的振动信号进行时频分析比STFT有效。 相似文献
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Vibrational measurement data are often nonstationary and modal parameter identification based on these data is of practical value for structural health monitoring and condition assessment. The empirical mode decomposition (EMD) is a most recent tool for analysis of nonstationary signals. An EMD-based random decrement (RD) technique is presented to identify modal parameters from monitoring vibrational data. The nonstationary measurement data are first decomposed into a series of quasi-stationary intrinsic mode functions (IMFs) by EMD. The RD technique is then applied to the selected IMFs to obtain the free-decay response. The modal frequencies and damping ratios are finally identified from the free-decay response by minimizing the error between the measured free-decay responses and the predicted responses from a parametric model. The present method is applied to extract the modal parameters of the Nanjing Yangtze River Bridge from the measured responses. The identification result is compared to those from finite element analysis as well as from the experimental result identified with the peak-picking (PP) method. In addition, the modal frequencies of the bridge loaded with heavy trains are also identified and compared to the ‘empty’ bridge. The EMD-based random decrement (RD) technique provides an effective and promising tool for modal parameter identification for large bridges and other structures. 相似文献
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A structural and micro-pore analysis of a series of heat treated electrolytic manganese dioxide (EMD) samples has been conducted. In terms of crystal structure, the original EMD with γ-MnO2 structure (orthorhombic unit cell) was found to progressively convert to β-MnO2 (tetragonal unit cell) at elevated temperatures. The structural transition was kinetically limited, with the higher temperatures leading to a greater degree of transformation. The orthorhombic γ-MnO2 unit cell was found to contract along the a and b axes, while along the c axis an expansion was observed only at the highest heat treatment temperatures. These changes occur as a result of manganese ion diffusion leading to the formation of a denser, more defect free material. The porosity of these heat treated EMD samples was also examined by N2 gas adsorption combined with various interpretive techniques such as the Kelvin equation, MP method, Dubinin–Radushkevich method, Dubinin–Astakhov method and a more modern density functional theory based approach. Despite shortcomings associated with certain techniques, all clearly indicated that the EMD micro-pore volume decreased and the meso- and macro-pore volume increased as the heat treatment temperature was increased. This was justified as a result of manganese ion movement during the structural rearrangement causing the small pores to be progressively sintered shut, while the larger pores were formed as a result of stress-induced cracking in the denser final product. 相似文献