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Magnetic Flux Leakage Detection Defect of Oil Storage Tank Applying Variational Mode Decomposition

机译:磁通漏液漏油检测缺陷储油罐应用变分模式分解

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Corrosion, stress and mechanical damage of oil storage tank can lead to disastrous consequences. Therefore, it is very important to study a reasonable and effective method for detecting tank defect. Signal processing and defect recognition technique is one of the most important techniques in oil tank inspection magnetic flux leakage system, the paper discussed its signal processing procedure. First the noise robustness of the variational modal decomposition (VMD) is analyzed, and compared with wavelet decomposition and empirical mode decomposition (EMD) respectively to verify the superiority of VMD in signal-to-noise ratio. Especially in the low-band signal decomposition processing VMD has obvious advantages. Detection is then discussed the application of the magnetic flux leakage method in the tank defects, and verified the feasibility by the magnetic flux leakage detection in a laboratory platform. Finally, the VMD algorithm is used to decompose and reconstruct the magnetic flux leakage signal of the oil storage tank wall, and the leakage magnetic signal is effectively decomposed to achieve the de-noising effect and the modal function of the required frequency band is extracted to achieve the purpose of denoising. The validity of the proposed method is proved by means of the magnetic flux leakage detection technique based on VMD.
机译:储油罐的腐蚀,应力和机械损坏会导致灾难性的后果。因此,研究一种合理有效的检测罐缺陷方法非常重要。信号处理和缺陷识别技术是油箱检测磁通漏电系统中最重要的技术之一,本文讨论了其信号处理程序。首先,分析变分模型分解(VMD)的噪声稳健性,并分别与小波分解和经验模式分解(EMD)进行比较,以验证信噪比中VMD的优越性。特别是在低频信号分解处理中,VMD具有明显的优点。然后讨论了磁通泄漏方法在罐缺陷中的应用,并通过实验室平台中的磁通量泄漏检测验证了可行性。最后,VMD算法用于分解和重建储油罐壁的磁通漏信号,并且有效地分解漏磁信号以实现去噪效果,并且提取所需频带的模态功能达到去噪的目的。通过基于VMD的磁通漏电检测技术证明了所提出的方法的有效性。

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