488 results about "Pollution monitoring" patented technology

The invention relates to the field of detection of heavy metal pollution in soil , in particular to an unmanned-aerial-vehicle hyperspectral inversion based monitoring method of heavy metal pollution in soil. The method is characterized by including: field sampling; sample pretreatment; using an x-ray fluorescence analyzer to collect content of main research elements of heavy metal pollution sources of samples; using a field spectrometer to collect laboratory hyperspectral reflectance of the samples; performing data processing on original spectral reflectance data; performing correlation analysis on measured content of the main research elements respectively with laboratory hyperspectral original reflectance data, reciprocal, logarithms, first derivative data and second derivative data with a partial least squares regression algorithm and verification and modification on models to acquire an optimal transformation method, using an unmanned aerial vehicle equipped with a hyperspectral imaging spectrometer to collect research-area hyperspectral reflectance data as to-be-measured data, and performing extensive inversion of the heavy metal content. The unmanned-aerial-vehicle hyperspectral inversion based monitoring method has the advantages of large range detachable, non-invasive and non-contact quick sample detection and the like.

The invention discloses a pollution space analysis method and device based on massive atmosphere pollution concentration data, and belongs to the field of atmosphere pollution monitoring. The method comprises the steps of obtaining the atmosphere pollution concentration data of a target area monitored by a ground high-density monitoring network; arranging the obtained atmosphere pollution concentration data in a matrix mode to obtain an atmosphere pollution concentration data matrix; conducting biclustering treatment on the atmosphere pollution concentration data matrix to obtain multiple biclustering blocks of different sensor monitoring stations; interpolating the atmosphere pollution concentration data after biclustering treatment is conducted into a grid of an air quality model, and conducting grid treatment; comparing the atmosphere pollution concentration in each grid with that in a surrounding grid to determine a high-concentration exhaust grid and obtain high-value areas of the different biclustering blocks. According to the pollution space analysis method and device based on the massive atmosphere pollution concentration data, air quality change precise characteristics in the district and county level can be obtained, local pollution source characteristics are discriminated, and more systematized technical support is formed for environment management.

The invention discloses a method and system for monitoring air pollution, computer equipment and a storage medium, and relates to the field of environmental monitoring. The method comprises the following steps of dividing a monitoring area into a plurality of area grids; acquiring pollutant concentration monitoring data in each area grid; obtaining satellite remote sensing data and meteorologicaldata from the monitoring area; and obtaining an air pollution monitoring result of the monitoring area through a pre-trained machine learning model based on the satellite remote sensing data and meteorological data from the monitoring area, and the pollutant concentration monitoring data in each area grid. The method can use big data technology and artificial intelligence technology in conjunctionwith regional gridded real-time pollutant monitoring data, can accurately locate the source of pollution, track the continuously spreading pollution area, and show the real-time status of air pollution, which, compared with traditional technology, can show the air pollution situation in the monitoring area more comprehensively and accurately.

A multi-objective optimization method for groundwater pollution monitoring network, which mainly includes four steps: groundwater numerical value simulation, groundwater vulnerability assessment, the establishment of the monitoring network optimization model, and the solving of the optimization model. The core of the method is to establish a multi-objective optimization model aimed at establishing the least monitoring wells, monitoring the maximum pollutant concentration, and monitoring the maximum regional vulnerability value. Solving the optimization model by the algorithm and considering the relationship between the quality error and the number of monitoring wells comprehensively to determine the well number and location of the monitoring network.

The invention discloses an embedded energy data acquisition unit, which comprises a main board and a shell, wherein a central processing unit (CPU), a data acquisition module which is connected with the input/output (I/O) interface of the CPU and a wireless functional plug-in are embedded into the main board; the CPU is an embedded processor which is based on a WinCE operating system, supports anOLE for process control (OPC)-service data specification and a real-time database, is solidified with a data acquisition communication protocol, directly acquires energy data through the data acquisition module, and acquires information data in a terminal instrument and field equipment for displaying and storing; the shell is connected with a human-computer interface display, and is provided witha human-computer interface input unit interface which is connected with the CPU and is used for writing working parameters or inputting operation commands; and through an Ethernet port for connectinga communication network with a monitoring station, a storage equipment interface, an input/output interface and a power supply interface can be expanded. The data acquisition unit is suitable for data acquisition and monitoring of places where mains supply is difficult to reach such as forecasting of hydrology, real-time monitoring of water resources, monitoring of irrigated areas, environmental monitoring, pollution monitoring, urban water supply, monitoring of pipe networks and the like.

The invention provides a non-point source pollution calculation method based on a remotely sensed image element. The method comprises the following steps of: 1, constructing a land utilization database and a vegetation coverage database; 2, constructing a soil type database, a soil nitrogen and phosphorus attribute database and a gradient and slope length geographic space database; 3, constructing a farmland nitrogen and phosphorus balance amount space database; 4, calculating dissolved state non-point source loads and adsorption type non-point source loads of non-point source pollutants under different pollution types according to database information in the steps from 1 to 3 and the pollution types; and 5, calculating a total amount of non-point source pollutants in a river according to the dissolved state non-point source loads and the adsorption type non-point source loads. By the method, under the condition that a data condition is limited, a non-point source pollution space distribution feature and a source intensity feature can be quickly obtained based on remotely sensed data; effective pollution monitoring measures can be supplied to a pollution prevention, treatment and management department; and important technology support can be supplied to flow domain pollution management.

The invention discloses a visual water quality information monitoring system based on the Internet of Things and a big data technology. The system comprises a server part, a device layer and a communication layer, and the server layer is a PC terminal and is composed of a plurality of servers; the device layer comprises a water quality monitoring sensor, an underwater imaging system, an underwater unmanned aerial vehicle, an unmanned ship, a Big Dipper/GPS positioning device, a solar battery and a power supply management module; the communication layer is composed of wireless communication devices; and the servers respectively realize fixed water quality monitoring and dynamic water quality monitoring. The system can realize the all-weather remote three-dimensional automatic monitoring of the monitored water quality, can completely record the dynamic change process and the visual display of the water quality data of every monitoring point, provides analysis data, and provides a basis for decision makers. The system can preserve and analyze a large number of water quality data, and can be effectively used in the fields of marine environmental monitoring, pollution monitoring and tracing, and aquaculture detection.

The invention relates to a method for identifying industrial thermal anomaly region based on multi-source satellite remote sensing data, which comprises the following steps: acquiring multi-source satellite remote sensing data of pollution monitoring region; obtaining visible light data, near infrared data and thermal infrared sensing data from multi-source satellite remote sensing data; the vegetation index, surface type information and specific surface emissivity of the pollution monitoring area being calculated; calculating the brightness temperature of thermal infrared radiation in the pollution monitoring area; calculating the surface temperature data of the monitoring area; extracting ground image data of monitoring area from multi-source satellite remote sensing data, and dividing the ground image data into a plurality of sub-area image data; extracting region feature information of each sub-region image data; fuzzy classification of sub-region image data to obtain potential industrial region image data; industrial thermal anomaly regions being identified based on surface temperature data and potential industrial region image data.

The invention discloses an urban smog treatment coordinating system. The urban smog treatment coordinating system comprises two subsystems, namely an urban smog online monitoring system and an urban three-dimensional smog treatment system, wherein the urban smog online monitoring system comprises a cloud server and a plurality of terminals of Internet of things; the urban three-dimensional smog treatment system comprises a smog jetting system and a smog cannon system. The system can effectively monitor the dust content of all regions, analyze air conditions in real time, release monitoring results in time and bring great convenience to the production and living of the public. Smog eliminating operation is carried out through the regulation and control of the smog jetting system and the smog cannon system. The terminals of Internet of things are provided with smog knowledge, smog prevention and emission reduction knowledge modules, and smog knowledge dissemination and smog early warning guidance functions can be achieved. Big data analysis is carried out on monitoring data collected by the cloud server, and a large quantity of key data can be accumulated for meteorological department and environmental protection department about urban smog emission sources and pollution monitoring.

The invention relates to a quick fault-tolerance detection method for monitoring an abnormal event by a wireless sensor network, and belongs to the technical field of the Internet of things. The sensor network is formed by self-organizing a large number of low-end sensor nodes; each node has finite power energy, communication capacity, calculation capacity and storage capacity and is generally arranged in an unattended severe environment; the possibility that each node makes a mistake is extremely high; and if the node makes a mistake, the network probably misjudges an event in a monitoring region. According to the method, the states of the nodes are adaptively managed by using confidence level, and failed nodes are removed from the sensor network, so that the influence of the failed nodes on abnormal event detection is reduced; and furthermore, a sliding window matching mechanism is used for detecting the change tendency of node monitoring data, so that whether the nodes can detect the abnormal event is forecasted. A simulation test shows that the reliability and the timeliness of detecting the abnormal event are improved, and the method can be widely applied to the fields of safety production monitoring, geological disaster monitoring, environment pollution monitoring and the like.

A method and apparatus for performing water based mud-filtrate contamination monitoring in real time through evaluation of downhole water sampling.

The invention discloses a method for quickly tracing to source by means of back flow based on a one-way river, and relates to the field of environment monitoring and environment pollution control. The method comprises the following steps: determining an upstream direction and a downstream direction of the one-way river; converting a map layer coordinate system of the one-way river into a projection coordinate system; performing average split on the one-way river to acquire split one-way river data; determining a river section in which pollution monitoring sites are located; determining a river section in which a suspect pollution source is located; determining the range of the suspect pollution source; determining the pollution source. The aim of quickly finding pollution discharge enterprises causing the river water body pollution is fulfilled, and data support is provided for environment protection departments to take measures in time.

The invention relates to an environment monitoring river patrol robot system and method. According to the environment monitoring river patrol robot system and method, a ground workstation is connectedwith a shipborne platform; the shipborne platform is provided with an intelligent control terminal; the intelligent control terminal is connected with an automatic driving unit, a wireless communication unit, a data storage unit, a radar measuring instrument, a sonar detector, a laser measuring instrument, a water quality monitor, a flow meter, a camera group and a comprehensive meteorological monitor, wherein the automatic driving unit is provided with an attitude control sensor and a satellite positioning device; the intelligent control terminal is provided with a river channel state analysis device and a fish school analysis device. With the environment monitoring river patrol robot system and method of the invention adopted, the pollution of a river is automatically monitored; besidesconventional pollution monitoring, the pollution condition of the river is generally judged through a fish swarm observation mode; detection and judgment are further conducted once problems are found; the problem that special monitoring is incomprehensive is avoided; and monitoring is simplified. The system and method of the invention have the advantages of high automation degree, strong on-siteautonomous control capability, flexible and changeable reaction capability and all-weather working capability.

The invention discloses a continuously tunable laser device based on a stimulated Raman scattering effect. The laser device comprises a semiconductor laser pump source with fiber-coupled output, an end face pump light beam coupling system composed of a first convex lens and a second convex lens, an injection lens, a laser gain medium (or a bonding crystal), a Q-switched device, an optical tuning device, a middle lens, a Raman gain medium and an output lens. A method for achieving continuously tunable laser by the laser device comprises the steps of stimulating the laser gain medium with a wide emission line by the semiconductor pump source with a specific wavelength to generate fundamental frequency light, continuously tuning the frequency of the fundamental frequency light by using the optical tuning device, and when the fundamental frequency light enters a Raman resonant cavity, shifting the frequency of the fundamental frequency light to be continuously tunable laser with the longer wavelength for outputting via stimulated Raman scattering. The laser device expands the wavelength range of the continuously tunable laser, and has wide applications in aspects of spectroscopy, biomedicine and pollution monitoring.

The invention discloses a river water environment environmental protection treatment pollution source monitoring and management system based on big data. The system comprises a river channel region division module, a region water body sampling module, a region water quality parameter acquisition module, a region water quality parameter comparison and analysis module, a pollution sub-region inflowport statistics module, a water quality parameter database, an inflow port water body quality parameter acquisition module, an analysis cloud platform and a display terminal. According to the system,the whole riverway is subjected to regional division, the water quality parameters of the sub-regions are compared with the water quality parameters of the adjacent sub-regions to determine the sub-regions with pollution, and meanwhile, the water quality parameters are collected at the flow inlets in the sub-regions with pollution so that the pollution flow inlets of the sub-regions with pollutionare counted, the monitoring efficiency is improved, the monitoring period is shortened, the cost of monitoring equipment is reduced, and the requirement for monitoring the water environment pollutionof the river channel with a large length and a large number of inflow ports is met.

The invention discloses an oil pollution monitoring and cleaning and filtering device of an embedded hydraulic power system, which comprises a main oil way A of the hydraulic system, a second electronic-magnetic or electronic-liquid steering valve which is arranged between the inlet and the outlet of the main oil way A of the hydraulic system. The device is characterized in that a branch oil way B is parallelly arranged on the inlet and the outlet of main oil way A of the hydraulic system, a branch oil way B is provided with a first electronic-magnetic or electric-liquid steering valve, a filter or a one-way valve and the filter is parallelly connected with a pressure gradient oil pollution monitoring and display device. The filtering device aims at not influencing the normal operation of the system when the attachment as the hydraulic equipment is embedded into the design of the hydraulic power system, monitoring results can better show the practical operation of oil.

The invention discloses a water body water color abnormity identification method and device based on time sequence remote sensing images, and belongs to the field of water environment pollution monitoring. The method comprises the following steps: preprocessing a multi-time-sequence remote sensing image to obtain water body remote sensing reflectivity images with different time sequences; performing spectral statistical analysis on the remote sensing reflectivity image to obtain water body pixel statistical characteristic values of different wave band long-time sequences, and establishing different wave band reference characteristic values and pixel characteristic values; making a spectral characteristic analysis on the to-be-detected remote sensing image, and creating waveband characteristic values of different wavebands; preliminarily judging whether the to-be-detected image has abnormal water color or not by comparing the wave band characteristic value of the to-be-detected image with the corresponding wave band reference characteristic value; analyzing the wave band with the abnormal water color of the to-be-detected image pixel by pixel, comparing the wave band with the pixelcharacteristic value of the corresponding wave band, obtaining the spatial distribution pixel of the abnormal water color, and obtaining the spatial distribution of the abnormal water color of the water body. According to the invention, the water color abnormity identification precision and speed of the water body are improved.

The present invention relates to the field of pollution monitoring equipment and in particular to aspirated particle detector systems, which detect particles in air sampled from a number of locations The present invention provides a method and apparatus for determining flow in an aspirated particle detector systems said system comprising a plurality of carriers in fluid communication with a particle detector, comprising means for detecting the flow rate in at least one of the carriers comprising sensing a signal transmitted between a first and a second signal transceiver (44a-d, 42) wherein the first transceiver (42) is adapted to transceive signals in at least two of the carriers. In a preferred embodiment, the invention relates to the use of an ultrasonic means of flow sensing within an aspirated smoke detector system.

The invention discloses an intelligent monitoring and management system and method for river water pollution monitoring and early warning and belongs to the field of monitoring technologies. With theintelligent monitoring and management system and method adopted, the problems of high manpower consumption, long monitoring period, and low river pollution control efficiency of existing river monitoring can be solved. According to the technical schemes of the invention, the system includes a network communication module, a water and rainfall information monitoring module, a water quality monitoring module, a gate pump monitoring module, a video monitoring module, a monitoring center, a river management module and a user terminal; the network communication module includes a GPRS network and anoptical fiber network; the water and rainfall information monitoring module includes a water and rainfall information monitoring device and a water and rainfall information monitoring center station;the water quality monitoring module includes a water quality monitoring station and a first server; the gate pump monitoring module, the river management module and the user terminal are all connected with the monitoring center; and the video monitoring module includes a video collection device and a second server. With the intelligent monitoring and management system and method for river water pollution monitoring and early warning adopted, river water pollution can be monitored in real time, and the efficiency of river water pollution control can be improved.

The invention discloses a remote sensing extraction method, a remote sensing extraction device and a remote sensing extraction system for polluted water body at drainage outlets and belongs to the field of pollution monitoring for water body. The method includes the steps of: a) on the basis of a high-spatial-resolution remote-sensing reflectance image, constructing spectral libraries of a polluted water body and a normal water body, calculating characteristic values of different wave bands in the spectral data of the polluted water body and the normal water body, and screening a characteristic wave band by comparing the characteristic values between the polluted water body and the normal water body, and respectively setting threshold values according to the characteristic value of the characteristic wave band of spectrum of the polluted water body; b) performing comparison to every pixels in the remote-sensing reflectance image waveband by waveband, if a comparison result is true, marking the pixel as a polluted water body pixel; and c) performing extraction of position information and counting of pixel number to the polluted water body pixels so as to acquire position and area of the polluted water body. The method has stronger pertinence to extraction of the polluted water body and greatly increases precision of recognizing the position and area of the polluted water body, thereby high-effectively, quickly and accurately extracting the distribution range and area of the polluted water body.

The present invention discloses a pre-selected water quality monitoring network multi-objective optimized deployment method for some monitoring points. The method comprises the following steps: selecting all candidate monitoring points according to the water area of the monitoring area; performing hydraulic modeling and simulating water pollution incidents at any candidate monitoring point in themonitoring area; determining an optimization objective function, and pre-selecting monitoring points according to monitoring requirements and expert experience; and calculating the average pollution monitoring time and the successful monitoring probability according to the cost function, and updating the pbest and gbest sets, ensuring that the preselected some monitoring points are included in thesolution set, and finally finding the Pareto front as the optimal solution set including the preselected monitoring points. The method disclosed by the present invention is applied to the optimized deployment of the water quality monitoring system under the condition that certain monitoring points have been determined, and optimization can be performed according to different objectives, so that the detection time is the least, the detection reliability is the highest, and the graph center is the best.

The invention relates to the technical field of agricultural land environment pollution evaluation, and particularly relates to a method for evaluating heavy metal pollution and potential ecological risks of agricultural land. The method comprises the following steps: firstly, performing sampling, then chemically measuring the content of heavy metals in soil, and on the basis of analyzing the pollution degree of agricultural land by adopting a land accumulation index method and an improved inner Meiluo comprehensive pollution index method, providing a set of new evaluation method for comprehensively considering the soil, the pollution space-time trend, the diagenetic effect, the influence of human activities on the environment and other aspects. According to the method, the limitation of atraditional potential ecological risk evaluation method is overcome; accuracy and scientificity of agricultural land heavy metal pollution risk evaluation are improved to a certain extent, ecologicalrisks of heavy metals in soil can be comprehensively and accurately evaluated, and substantial method guidance is provided for agricultural land heavy metal pollution monitoring, environmental management and ecological protection.

The invention provides a method for diagnosing soil pollution condition by using earthworm biomarkers, and belongs to the technical field of soil pollution monitoring and control. In the method, artificially cultured earthworm is used as a standard test animal; four oxidative damage test indexes, namely oxygen free radical, malondialdehyde content, protein carboxyl content and reductive glutathione-oxidative glutathione proportion, are used as the biomarkers for diagnosing soil pollution; clean artificial soil is used as standard soil; and the pollution condition of the tested soil can be quickly and sensitively diagnosed by analyzing the difference of the four oxidative damage indexes in vivo of the earthworm after the earthworm is cultured in the clean artificial soil and the tested soil for certain time. The method can be used for comprehensively diagnosing the soil pollution condition and the health degree, and the method has good sensitivity for trace pollutants in the soil and can be used as a monitoring method for soil pollution early warning. Compared with a chemical analysis method, the method has the characteristics of simple operation and low cost.