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A method for improving wavelet threshold denoising in laser-induced breakdown spectroscopy

机译:一种改善激光诱导击穿光谱中小波阈值去噪的方法

摘要

The wavelet threshold denoising method is an effective noise suppression approach for noisy laser-induced breakdown spectroscopy signal. In this paper, firstly, the noise sources of LIBS system are summarized. Secondly, wavelet multi-resolution analysis and wavelet threshold denoising method are introduced briefly. As one of the major factors influencing the denoising results in the process of wavelet threshold denoising, the optimal decomposition level selection is studied. Based on the entropy analysis of noisy LIBS signal and noise, a method of choosing optimal decomposition level is presented. Thirdly, the performance of the proposed method is verified by analyzing some synthetic signals. Not only the denoising results of the synthetic signals are analyzed, but also the ultimate denoising capacity of the wavelet threshold denoising method with the optimal decomposition level is explored. Finally, the experimental data analysis implies that the fluctuation of the noisy LIBS signals can be decreased and the weak LIBS signals can be recovered. The optimal decomposition level is able to improve the performance of the denoising results obtained by wavelet threshold denoising with non-optimal wavelet functions. The signal to noise ratios of the elements are improved and the limit of detection values are reduced by more than 50% by using the proposed method.
机译:小波阈值去噪方法是一种有效的噪声抑制方法,用于噪声大的激光诱导击穿光谱信号。本文首先总结了LIBS系统的噪声源。其次,简要介绍了小波多分辨率分析和小波阈值去噪方法。作为影响小波阈值去噪过程中去噪效果的主要因素之一,研究了最优分解水平的选择。基于噪声LIBS信号和噪声的熵分析,提出了一种选择最佳分解水平的方法。第三,通过分析一些合成信号验证了该方法的性能。不仅分析了合成信号的去噪效果,而且还探索了具有最佳分解水平的小波阈值去噪方法的最终去噪能力。最后,实验数据分析表明,可以减少噪声较大的LIBS信号的波动,并可以恢复较弱的LIBS信号。最优分解级别能够提高通过非最优小波函数进行小波阈值去噪获得的去噪结果的性能。通过使用所提出的方法,改善了元件的信噪比,并且将检测值的极限降低了50%以上。

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