Pollution source identification method and device based on three-dimensional liquid chromatography fingerprints

Abstract

The invention discloses a pollution source identification method and device based on three-dimensional liquid chromatography fingerprints. The method comprises the steps of preprocessing a pollution source sample and a sample to be identified; collecting three-dimensional liquid chromatogram fingerprints of the pretreated pollution source sample and the sample to be identified, and pretreating the collected three-dimensional liquid chromatogram fingerprints; and establishing a pollution source identification model by using the pretreated three-dimensional liquid chromatogram fingerprints for pollution source identification so as to determine the pollution source to which the to-be-identified sample belongs. The device comprises a sample processing module, a fingerprint acquisition module and an identification module. The method is less in required equipment, small in sample size, rich in fingerprint information, low in cost and beneficial to large-scale popularization. The self-organizing neural network is utilized to realize automatic comparison and identification of three-dimensional liquid chromatogram fingerprints. The method has the characteristics of simplicity, intelligence and accuracy, and has important significance on source tracing of pollution sources.

Description

technical field [0001] The invention relates to the technical field of environmental supervision, in particular to a method for identifying pollution sources based on three-dimensional liquid chromatography fingerprints. Background technique [0002] Pollution source identification has always been a hot and difficult point in the field of environmental supervision. At present, the identification of pollution sources mainly relies on manual investigation. The manual investigation method based on the pollution source database can greatly reduce the workload of manual investigation and improve the timeliness of pollution source identification, which has become a popular method for pollution source identification in recent years. Previously, the database proposed by Wan Pingyu et al. of Beijing University of Chemical Technology contained anion types, organic matter types, metal element types and fluorescence information, but the operability was not strong. Wu Jing of Tsinghua ...

AI Technical Summary

Problems solved by technology

The databases of these methods are relatively complex and require more instruments and equipment, and these methods only provide a database establishment method, and do not provide an automatic comparison algorithm between contaminated samples and pollution source databases

In practical application, experienced experts are often required for manual comparison and judgment, which is highly subjective.

In the absence of experts, the accuracy is low, limiting the scope and application of the method

Images