Method for identifying spectrum

Abstract

Provided is a method for identifying spectrum, suitable for utilizing an electronic apparatus to identify the compounds comprised by a to-be-tested spectrum. The method for identifying spectrum comprises the following steps: executing pre-processing operation over the to-be-tested spectrum, thus to obtain the corrected spectrum; executing regression operation and hypothesis verification over the standard spectrum of multiple compounds, thus to obtain the similarity order of the compounds; selecting one by one among the compounds to add to the to-be-tested compound combination by starting from the highest one of the similarity order, thus to calculate the coefficient of rank correlation between the to-be-tested compound combination and the corrected spectrum; outputting the currently-selected to-be-tested compound combination if the coefficient of rank correlation of the currently-selected to-be-tested compound combination is smaller than that of the previously selected to-be-tested compound combination.

Description

technical field [0001] The present invention relates to a method for spectral analysis, and in particular to a method for identifying spectra that can automatically identify compounds in the spectra. Background technique [0002] Fourier Transform Infrared Spectroscopy (FTIR) is an important technique for obtaining infrared spectra. Certain chemical species absorb specific frequencies of infrared radiation energy and change their vibrational energy levels, resulting in different spectra. Compounds with FTIR absorption characteristics have unique spectral patterns. According to this principle, FTIR can be used to detect compounds in the environment. [0003] In many on-site measurements, the presence of water vapor, carbon dioxide and other components will seriously affect the quality of spectral graphics, and many spectral graphics will also cause baseline drift due to changes in the measurement environment. These problems increase the difficulty of spectral graph analysis...

AI Technical Summary

Problems solved by technology

[0003] In many on-site measurements, the presence of water vapor, carbon dioxide and other components will seriously affect the quality of spectral graphics, and many spectral graphics will also vary due to measurement environment, resulting in baseline drift

These problems increase the difficulty of spectral graph analysis, requiring more manpower and time to analyze spectral graphs, seriously affecting the timeliness of instrument measurement results

[0004] In traditional FTIR analysis, it is generally required to be analyzed by professional and experienced spectral pattern interpreters

In other words, FTIR analysis is quite dependent on the experience and professionalism of analysts, and it is not easy for ordinary operators to use it. Therefore, the technical bottleneck of analyzing spectral graphics is relatively high, and there is no objective interpretation criterion.

In addition, the speed of human interpretation is limited, so that it is time-consuming to interpret a large number of spectral patterns

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