"智能化顺序注射微量注样测定环境水质中亚硝酸盐和正磷酸盐"

In this dissertation, the development and application of an intelligent on-line dilution system based on micro-sampling using sequential injection analysis technique for the determination of nitrite and phosphate in environmental water samples is discussed. The system utilizes a sequential injection analysis technique, which allows for precise and controlled sampling and analysis of water samples. By utilizing machine learning algorithms, the system is able to intelligently adjust the dilution factor based on the concentration of the target analytes in the sample. This results in more accurate and efficient measurements compared to traditional manual methods. The dissertation provides a detailed overview of the system, including the design, operation, and performance evaluation. The system was successfully applied to the spectrophotometric determination of nitrite and phosphate in various environmental water samples, demonstrating its effectiveness in on-line dilution and analysis. Overall, the intelligent on-line dilution system based on sequential injection micro-sampling presents a novel approach to automated analysis of environmental water samples. By integrating machine learning algorithms into the system, the accuracy and efficiency of the analysis process are significantly improved, making it a valuable tool for environmental monitoring and analysis.