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首页> 外文会议>International Conference on Mechatronic Sciences, Electric Engineering and Computer >Study and comparison of two automatic identification methods on spectrums captured by X-ray fluorescence spectrometers with LABVIEW
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Study and comparison of two automatic identification methods on spectrums captured by X-ray fluorescence spectrometers with LABVIEW

机译：用LABVIEW研究和比较X射线荧光光谱仪捕获的光谱的两种自动识别方法

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摘要

The way to improve the accuracy and reliability of automatic unscrambling and identification technology on X-ray fluorescence spectrometer spectrum is studied in this essay. Accordingly, two different automatic identification methods based on Fast Fourier Transform and Wavelet Transform are presented. By the tool LABVIEW, such two methods are applied to the qualitative analysis on X-ray fluorescence spectrums, and the features of such two methods are compared. Based on the experiments and analysis on hundreds of samples, it can be concluded that the automatic identification method based on the Wavelet transform theory is better than the other method for the former has a better local resolution. Therefore, the characteristic values of the singular points are more clearly recognized by the method based on the Wavelet transform. Through the study in this essay, theories on automatic identification are enriched, which set a foundation for further studied in future.
机译：本文研究了提高X射线荧光光谱仪光谱自动解识别技术准确性和可靠性的方法。因此，提出了两种基于快速傅立叶变换和小波变换的自动识别方法。通过工具LABVIEW，将这两种方法应用于X射线荧光光谱的定性分析，并比较了这两种方法的特性。通过对数百个样本的实验和分析，可以得出结论，基于小波变换理论的自动识别方法优于其他方法，因为前者具有更好的局部分辨率。因此，通过基于小波变换的方法，可以更清楚地识别奇异点的特征值。通过本文的研究，丰富了自动识别理论，为以后的进一步研究奠定了基础。

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