Study and comparison of two automatic identification methods on spectrums captured by X-ray fluorescence spectrometers with LABVIEW

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.