A multi-parameter monitoring system based on water body sample environment

Abstract

The application relates to the technical field of water quality monitoring, and specifically discloses a water body sample reservation environment multi-parameter monitoring system, which realizes adaptive filtering by using empirical mode decomposition and sample entropy analysis to generate an optimized time sequence by real-time collection of multi-dimensional parameters such as temperature, pH, dissolved oxygen, turbidity and conductivity; identifies pollution source characteristic components by dynamic principal component analysis and blind source separation; constructs a causal correlation network by using dynamic time warping and transfer entropy, and forms a multi-parameter collaborative response spectrum by combining with graph convolution topological feature extraction; realizes pollution type identification based on the spectrum by multi-scale morphological analysis and density clustering, generates an early warning report containing pollution level evaluation and trend prediction by using confidence weighted decision fusion; solves the technical problem of evidence distortion caused by sample state drift in the traditional sample reservation process, and realizes full-chain water quality monitoring from data collection to intelligent diagnosis.

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