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Extraction of weak fault transients using variational mode decomposition for fault diagnosis of gearbox under varying speed

机译:不同速度下变分模分值分解的磁箱故障诊断的弱故障瞬变提取

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摘要

Non-stationary vibration signals of a gearbox under varying speed display complicated modulations, which lead to intense sidebands thereby resulting in difficulty to identify the presence of a fault. Variational mode decomposition (VMD) being highly adaptive, effective in attenuating mode-mixing problem, low computational time requirement and therefore it is suitable to decompose a modulated multi-component non-stationary gearbox vibration signal. This research work thus utilizes the merits of VMD for demodulation and to diagnose localized gear tooth faults under real-time speed variation. In the present study, the vibration signals of a gearbox for different faults were acquired under complete speed variation (i.e., run-up, random fluctuation, and coast-down). To identify the symptoms confirming the presence of faults, the vibration signals were decomposed by VMD thereby demodulating the raw vibration signal. The decomposed VMFs exhibited the presence of transients due to faults and were analyzed statistically. To state the effectiveness of VMD in exhibiting fault by extracting fault transients, the performance of VMD was compared with the performance of recently developed wavelet based empirical wavelet transform (EWT) and flexible analytic wavelet transform (FAWT). The fault detection performance of VMD outperforms EWT as demonstrated by simulated signal and validated by the experimental investigations. FAWT was found ineffective in decomposing the vibration signal under varying speed.
机译:变速速度显示复杂调制下的齿轮箱的非静止振动信号,从而导致强烈的边带导致难以识别故障的存在。变形模式分解(VMD)高度自适应,有效地衰减模式混合问题,计算时间要求低,因此适合于分解调制的多分量非固定齿轮箱振动信号。因此,该研究采用VMD的优点进行了解调,并在实时速度变化下诊断局部齿轮齿断层。在本研究中,在完全速度变化下获得用于不同故障的齿轮箱的振动信号(即,加速,随机波动和海岸)。为了识别确认存在故障存在的症状,振动信号由VMD分解,从而解调原始振动信号。分解的VMFS由于故障而表现出瞬态的存在,并且统计学分析。为了说明VMD在通过提取故障瞬变参展故障的有效性,将VMD的性能与最近开发的小波的经验小波变换(EWT)和柔性分析小波变换(FAWT)进行了比较。 VMD的故障检测性能优于模拟信号所证明的EWT,并通过实验研究验证。发现FAWT在不同速度下分解振动信号时无效。

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