Chromatographic baseline noise reduction method and device

Abstract

The invention discloses a chromatographic baseline noise reduction method. The method comprises the following steps: S1, signal acquisition, S2, signal amplification, S3, Gaussian noise removal, S4, impulse noise removal, S5, calibration fitting and S6, component analysis. A SG filter is connected with a morphological filter in series so that the advantages of the SG filter and the morphological filter are integrated, while the defects of the SG filter and the morphological filter are eliminated, Gaussian noise is removed through the SG least square filtering algorithm, and then impulse noiseis removed through the morphological filtering algorithm. The method has the advantages that most of noise is removed through the SG least square filter, and the amplification effect of the morphological filter on the noise is avoided; and then the morphological filter is used to filter the problem of residual abnormal point interference of the SG filter. The sequence of the two steps cannot be reversed, otherwise, the defects of the two algorithms are amplified. Fnally, the two filtering algorithms in the invention are real-time algorithms, the acquired signals can be filtered in real time,and the delay is within 0.5 s.

Description

technical field [0001] The invention relates to the technical field of chromatographic baseline noise reduction, in particular to a chromatographic baseline noise reduction method and a device thereof. Background technique [0002] With the rapid development of industrialization and urbanization in my country and the continuous growth of energy consumption, the regional composite air pollution characterized by PM2.5 is becoming more and more prominent, and the frequency of heavy air pollution in the region is increasing, which seriously restricts The sustainable development of social economy threatens the health of the people. Volatile organic compounds (VOCs) are important precursors for the formation of secondary pollutants such as fine particulate matter (PM2.5) and ozone (O3), which can cause atmospheric environmental problems such as haze and photochemical smog. Key monitoring objects in the environmental field. [0003] There are many techniques for measuring VOCs, am...

AI Technical Summary

Problems solved by technology

However, the existing filtering methods have their specific applicable scenarios and shortcomings: median filtering can remove impulse noise, but improper selection of the filtering window will cause distortion; moving average filtering can remove high-frequency noise, but it wi

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