The invention discloses a water quality pollution warning method, including the following steps: 1) within a preset time period, continuously monitoring time sequence data of various water quality parameters at the same monitoring point before pollution, and the time sequence data of various water quality parameters during the pollution process, and splicing the data to form total time sequence data in the time period; 2) according to preset initial time sequence window length, selecting a time sequence data, which is used for performing typical correlation analysis in every time, from the total time sequence data so as to perform typical correlation coefficient calculation to obtain a first typical correlation coefficient and a second typical correlation coefficient in every time of typical correlation analysis; 3) according to the first typical correlation coefficient and the second typical correlation coefficient in every time of the typical correlation analysis and preset first typical correlation coefficient threshold and second typical correlation coefficient threshold, performing accuracy and recall rate calculations; and 4) when the accuracy and recall rate are all located in an acceptable range, performing real-time warning to the pollution event. The method can improve accuracy and reliability of pollution warning.

Water quality pollution warning method

The invention discloses an environmental pollution monitoring system based on an RBF neural network optimized by a genetic algorithm The system includes a signal input module, a signal processing module, a computer cloud server processing module, a database, an alarm module and a pollution indicator display module A visible light signal is input through the signal input module input and is then subjected to analog-to-digital conversion, digital signal processing and digital-to-analog conversion in turn through the signal processing module The signal is input into the computer cloud server processing module, and a pollution indicator is displayed through the pollution indicator display module If a threshold is exceeded, the alarm module will alarm, and the data in the whole process from the signal input to the signal output will be stored in the database In the invention, the system does not need a special network environment or hardware equipment, is low in cost and has a high adaptability The system also has the function of monitoring environmental pollution, can achieve real-time accurate monitoring for a variety of pollution indicators and is powerful

Environmental pollution monitoring system based on RBF neural network optimized by genetic algorithm

The invention provides a method for early warning abnormal working conditions of a water supply network, comprising the following steps: collecting water quality parameter data; conducting data preprocessing on the collected water quality parameter data; extracting data features from the preprocessed data and constructing feature vectors; utilizing the feature vectors to train a model, so as to optimize the model; utilizing the optimized model to determine abnormal working conditions of the water supply network, so as to give early warning of the abnormal working conditions of the water supplynetwork. The method utilizes the relevance of a plurality of water quality indicators to amplify minor exceptional variation characteristics of each single water quality indicator, which can quicklydiscover pollution after an pollution accident happens, reduce hazards of the accident and guarantee user health and safety, so as to improve accuracy and reliability of pollution warning.

Method for early warning abnormal working conditions of water supply network

The invention discloses a method for evaluating the time of sudden heavy metal water pollutants flowing into rivers based on fish toxicity effect, which is applicable to the risk evaluation of pollutants in sudden heavy metal pollution events that cause fish death. The method comprises the following steps: performing gradient dilution on the raw water according to the concentration of characteristic pollutants determined by detections in the raw water of the pollution source, and detecting the heavy metal concentration of the diluted water; observing and recording in detail behavioral abnormalities and occurrence times of medaka in each concentration gradient solution; contrasting and analyzing the conditions of the fish deaths at the scene of the pollution accident and the abnormal conditions of the fish in each gradient experiment, and deriving the heavy metal concentration of the water during fish death caused by the pollution accidents; evaluating the time of heavy metal pollutantsflowing into the river according to the discharge time of the pollution source, the hydrological parameters of the polluted river section, and the hydrological parameters. The invention is only slightly improved based on GB/T 13267-91, the method is easy to implement, the cost is low, and the operation is easy.

Method for evaluating the time of sudden heavy metal water pollutants flowing into rivers based on fish toxicity effect

The invention provides a method and a device for determining time sources of atmospheric pollutants. The method comprises the following steps: acquiring emission concentrations of pollutants at different times in a timing duration, wherein the timing duration is time from a timing starting moment to a target moment; dividing the timing duration into N detection durations according to a preset steplength, and comparing N with M; if N is greater than M, determining the pollutant concentration contributed to the target detection duration by the emission concentration in the last M continuous detection durations in the N detection durations, wherein the target detection duration is the detection duration of the target moment, and the emission concentration in the Mth detection duration counted from the target detection duration according to the time from back to front is the accumulated value of the emission concentration in the first N-(M+1) detection durations in the timing duration; and if N is less than or equal to M, determining the pollutant concentration contributed by the emission concentration in the N detection durations to the target detection duration. Source analysis of atmospheric pollutants from different time sources is realized, and computing resources are saved.

Method and device for determining time sources of atmospheric pollutants

The invention provides a rapid pollution incident detection method based on a traditional online monitor, and belongs to the technical field of environmental engineering water treatment The method includes the steps: building a pollution-free background database and a polluted background database; building composite sequences, presetting model parameters and optimizing training to obtain optimal parameters; building optimized pollution incident detection recognition matrixes, and recognizing pollution incidents in real time The pollution incidents can be determined in a short time by the aid of traditional online monitors universally mounted at current monitoring points when abrupt pollution incidents happen, misinformation of the pollution incidents caused by instrument noise fluctuation is effectively avoided, online monitoring cost of the pollution incidents can be greatly reduced as compared with emerging online monitoring technology, all pollutants possibly causing the pollution incidents are covered, and safety and reliability of a water system are furthest guaranteed

Wu Xue

Papers

Rapid pollution incident detection method based on traditional online monitor