Overlapping peak treatment method and device applied to chromatographic analysis

Abstract

The invention discloses a chromatographic overlapping peak treatment device. The device comprises a data collection module, a data analysis module, a baseline noise reduction module, a calibration fitting module and an overlapping peak treatment module. Wherein the data collection module is connected with the data analysis module, the data analysis module is connected with the baseline noise reduction module, the baseline noise reduction module is connected with the calibration fitting module, and the marking fitting module is connected with the overlapping peak treatment module. According tothe invention, the overlapped peak treatment module firstly determines a peak position by adopting a derivative method; overlapped peaks are determined through base point grouping, a simplex method isused for fitting a peak shape curve, so that information such as peak heights, peak widths and protrusions of all components of the overlapped peaks is determined, the peak position determining precision is high, the information precision of all the components of the overlapped peaks is high, peak division intervals can be automatically defined, and the number of sub-peaks in the overlapped peakscan be automatically determined.

Description

technical field [0001] The invention relates to the technical field of separation of chromatographic overlapping peaks, in particular to a method and device for processing overlapping peaks applied to chromatographic analysis. Background technique [0002] Gas chromatograph is an instrument for analyzing and detecting components in a mixed gas. It is widely used in petroleum, chemical industry, biochemistry, medicine and health, food industry, environmental protection, etc. The data analysis part includes data acquisition, filtering, Six aspects including baseline correction, peak detection, peak separation and quantitative analysis, among which the separation of overlapping peaks has a great impact on the analysis results, which will cause difficulties and errors in quantitative calculations. [0003] The so-called separation of overlapping peaks is to use mathematical means to separate the chromatographic peaks that cannot be completely separated by the instrument, and to ...

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Problems solved by technology

[0002] Gas chromatograph is an instrument for analyzing and detecting components in mixed gases. It is widely used in petroleum, chemical industry, biochemistry, medicine and health, food industry, environmental protection, etc. The data analysis part includes data acquisition, filtering, Six aspects including baseline correction, peak detection, peak separation and quantitative analysis, among which the separation of overlapping peaks has a great impact on the analysis results, which will cause difficulties and errors in quantitative calculations

[0003] The so-called separation of overlapping peaks is to use mathematical means to separate the chromatographic peaks that cannot be completely separated by the instrument, and obtain the estimated value of the information of each sub-peak in the overlapping peaks. The current popular overlapping peak separation methods can be divided into two categories: geometric The geometric method is further divided into the vertical method, the tangent method, and the triangular method. Its characteristics are that the decomposition method is intuitive and the calculation speed is fast, and it can be used for real-time online processing of chromatographic data. When the chromatographic peaks overlap seriously, the calculation accuracy of each peak area is very poor. In the algebraic method, the most commonly used method is the function fitting method. The idea is: first establish the function model of the chromatographic peak, and then use the least squares Multiplication, neural network and other methods are used to fit overlapping peak data, and some optimization method is used to optimize all undetermined parameters in the function through continuous iteration, so that the fitting curve is continuously approaching the actual curve, and finally a set of optimal estimated values ​​is obtained , and the information of each sub-peak is obtained from these parameter values. The problem with this method is that the amount of calculation is very large, and it is difficult to meet the requirements of online real-time and fast processing.

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