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Resonant frequency band estimation using adaptive wavelet decomposition level selection

机译:利用自适应小波分解电平选择的共振频带估计

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The vibrations induced by machine faults help in diagnosis and prognosis of the machine. It is crucial for the fault diagnostic system to extract resonant frequency band which carries useful information about the defect frequencies and contains maximum signal to noise ratio. The spectral orientation of the resonant frequency band varies with the variation in machine dynamics. The existing techniques which employ wavelet transformation to exploit the signal energy distribution among different frequency sub-bands, are based on fixed decomposition level and do not optimize the wavelet parameters according to varying machine dynamics. The proposed study develops a novel technique: Adaptive Wavelet Decomposition and Resonance Frequency Estimation (AWRE) which estimates the positioning of the resonant frequency band based on adaptive selection of the wavelet decomposition levels. The results for the simulated as well as actual vibration data demonstrate that the proposed technique estimates the bandwidth of the resonant frequency band quite effectively.
机译:机器故障引起的振动有助于机器的诊断和预后。对于故障诊断系统而言,至关重要的是提取共振频带,该频带携带有关缺陷频率的有用信息并包含最大信噪比。谐振频带的频谱方向随机器动力学的变化而变化。现有的利用小波变换来利用不同频率子带之间的信号能量分布的现有技术基于固定的分解水平,并且没有根据变化的机器动力学来优化小波参数。提出的研究开发了一种新技术:自适应小波分解和共振频率估计(AWRE),它基于小波分解级别的自适应选择来估计共振频带的位置。仿真和实际振动数据的结果表明,所提出的技术相当有效地估计了谐振频带的带宽。

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