Experimental Study on Rapid Detection Technology for Soil Heavy Metal Pollution Based on Intelligent Machinery
Abstract：In order to improve the efficiency and accuracy of soil heavy metal pollution detection, this study constructs a multi-modal sensing fusion detection system based on intelligent machinery, integrating X-ray fluorescence spectroscopy, electrochemical sensors, and near-infrared spectroscopy technology. Combined with deep learning algorithms to optimize the data analysis model, it enhances detection stability in complex environments. The research results show that the system can achieve ppb-level detection of heavy metal ions, with higher detection accuracy than traditional methods and a response time reduced by more than 85%. It also has good environmental adaptability. The optimized pollution risk assessment model enhances the ability to predict the dynamic migration of pollutants, providing technical support for large-scale soil environmental monitoring and precise pollution control.
Keywords：Intelligent machinerySoil heavy metal pollutionMulti-modal sensingRapid detection
Publication Date：2025-09-25
Online Publishing Date：2025-11-07(First online date of this platform, not the publication date of the document)
Pages：4( 26-29 )