97 results about "Chemical index" patented technology

The invention discloses a method and a system for analyzing a pollution source of a rainwater pipe network. The method comprises the following steps of: 1, obtaining a first key fluorescence characteristic parameter combination according to basic physicochemical indexes by adopting a fluorescence characteristic parameter prediction model; 2, three-dimensional fluorescence characteristic parameters of the pollution source are obtained, and a pollution source three-dimensional fluorescence characteristic data set is obtained; screening by adopting a multivariate statistical method to obtain a second key fluorescence characteristic parameter combination; 3, determining a fluorescence characteristic parameter combination according to the first key fluorescence characteristic parameter combination and the second key fluorescence characteristic parameter combination; 4, inputting the fluorescence characteristic parameter combination into the Bayesian mixture model to obtain the contribution rate of the pollution source to the receptor water quality, and completing the analysis of the pollution source of the rainwater pipe network; according to the method, the DOM fluorescent fingerprint information is predicted by adopting basic data; and based on the three-dimensional fluorescence characteristic parameters and in combination with a Bayesian mixture model, precise quantitative analysis of the pipe network pollution source is realized.

The invention discloses a river nitrogen pollutant source analysis method based on drainage basin nitrogen turnover and isotope, and particularly relates to the technical field of water treatment.The river nitrogen pollutant source analysis method comprises the following steps that a drainage basin to be researched is selected, river water and soil samples in the drainage basin are systematically collected, and physical and chemical indexes and isotope indexes # imgabs0 # of the collected samples are tested. Nitrate marked by nitrogen isotope delta 15N / delta 18O and # imgabs1 # are used as key indication marks to perform high-precision identification on nitrogen sources in a river and an environmental system, the contribution proportion of different nitrogen sources to the nitrate concentration in a water body is quantified through a stable isotope analysis model, and the concentration of the nitrate in the water body is calculated. And in combination with data, the rates of denitrification and anaerobic ammonia oxidation in environmental samples, sediments and soil are directly measured through combined application of an isotopic tracer technology and a membrane inlet mass spectrometer technology.

The invention discloses a water environment safety early warning method and system based on the Internet of Things, and relates to the technical field of water environment monitoring and safety alarming, and the main scheme is as follows: firstly, collecting water quality physical and chemical parameters and water quantity parameters of a current detection period, then respectively calculating each subentry index, and calculating the water quality index; comprising temperature, turbidity, conductivity index and the like obtained by physical parameters, dissolved oxygen, pH value, lead content index and the like obtained by chemical parameters, and water quantity index, so as to obtain water quality physical index, chemical index and water environment safety index, and then judge whether to trigger safety real-time alarm or not; and acquiring data of a previous cycle to calculate a historical water environment safety index and an index growth rate, and comparing with corresponding threshold values to judge whether to give a delayed alarm. According to the method, multi-parameter and multi-cycle data are integrated, a comprehensive and accurate judgment basis is provided for water environment safety monitoring, the monitoring accuracy and reliability are effectively improved, and the water environment safety is guaranteed.

The invention discloses a soil physical and chemical parameter spectrum inversion method based on an SVM and a BP neural network. The method comprises the steps that near infrared spectrum data of soil samples with different water contents are collected and preprocessed; training and verifying a pre-constructed dry and wet soil sample classification model based on an SVM (Support Vector Machine) by utilizing the near infrared spectrum data of the preprocessed soil samples with different water contents, and dividing the soil samples into dry soil and wet soil by utilizing the trained dry and wet soil sample classification model; and respectively training and verifying a pre-constructed soil physical and chemical parameter prediction model based on a BP neural network by using the near infrared spectrum data after the pretreatment of the dry soil and wet soil samples and the measured values of the physical and chemical parameters of the soil samples to obtain soil physical and chemical parameter prediction models corresponding to the dry soil and wet soil samples respectively. The model not only can improve the accuracy and efficiency of soil physical and chemical index analysis, but also can provide a scientific basis for agricultural production and environmental protection.

The invention provides a method and system for determining a water quality risk value of industrial sewage, and the method comprises the steps: obtaining water quality monitoring data of different monitoring points, obtaining a physical index parameter, a chemical index parameter and a biological index parameter, and constructing a water quality parameter of a target water area; the method comprises the following steps: training historical physical index parameters, historical chemical index parameters and historical biological index parameters of historical water quality monitoring data to obtain a water quality monitoring deduction model, and deducing water quality parameters of a target water area through the water quality monitoring deduction model to obtain an initial water quality risk value; the corresponding actual index parameters are obtained by updating the water quality monitoring data of different monitoring points in real time, the parameters of the water quality monitoring deduction model are optimized, and the optimized water quality risk value is obtained through deduction again. The industrial sewage is subjected to multi-index analysis, the water quality risk trend is predicted, and the water quality monitoring accuracy of the industrial sewage is improved.