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Denoising time-domain induced polarisation data using wavelet techniques

机译:使用小波技术对时域感应极化数据进行去噪

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Time-domain induced polarisation (TDIP) methods are routinely used for near-surface evaluations in quasi-urban environments harbouring networks of buried civil infrastructure. A conventional technique for improving signal to noise ratio in such environments is by using analogue or digital low-pass filtering followed by stacking and rectification. However, this induces large distortions in the processed data. In this study, we have conducted the first application of wavelet based denoising techniques for processing raw TDIP data. Our investigation included laboratory and field measurements to better understand the advantages and limitations of this technique. It was found that distortions arising from conventional filtering can be significantly avoided with the use of wavelet based denoising techniques. With recent advances in full-waveform acquisition and analysis, incorporation of wavelet denoising techniques can further enhance surveying capabilities. In this work, we present the rationale for utilising wavelet denoising methods and discuss some important implications, which can positively influence TDIP methods.
机译:时域感应极化(TDIP)方法通常用于具有掩埋的民用基础设施网络的准城市环境中的近地表评估。在这样的环境中改善信噪比的常规技术是使用模拟或数字低通滤波,然后进行叠加和整流。但是,这在处理后的数据中引起很大的失真。在这项研究中,我们进行了基于小波的降噪技术在处理原始TDIP数据中的首次应用。我们的研究包括实验室和现场测量,以更好地了解该技术的优点和局限性。已经发现,使用基于小波的去噪技术可以大大避免传统滤波引起的失真。随着全波形采集和分析的最新进展,合并小波去噪技术可以进一步增强测量能力。在这项工作中,我们提出了利用小波去噪方法的基本原理,并讨论了一些可以对TDIP方法产生积极影响的重要含义。

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