CN112326917A - Water environment pollution traceability system - Google Patents
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- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 52
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- 238000004891 communication Methods 0.000 claims abstract description 17
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- 239000013535 sea water Substances 0.000 description 1
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Abstract
The invention provides a water environment pollution traceability system, which comprises a data acquisition module, a network communication module and a control center, wherein the data acquisition module is used for acquiring water environment pollution; the data acquisition module comprises a multispectral unmanned aerial vehicle inspection unit and an underwater unmanned aerial vehicle inspection unit; the multispectral unmanned aerial vehicle inspection unit and the underwater unmanned aerial vehicle inspection unit transmit acquired information to the control center through the network communication module; the underwater unmanned aerial vehicle inspection unit comprises an underwater unmanned aerial vehicle, a water quality sensor and an inspection system; the water quality sensor is arranged on the underwater unmanned aerial vehicle; the inspection system controls the underwater unmanned aerial vehicle to trace the source of pollution; the invention provides a water environment pollution traceability system, which can be used for autonomously searching a pollution source through an unmanned aerial vehicle and improving the efficiency of tracing the pollution source.
Description
Technical Field
The invention belongs to a water quality monitoring informatization system, and particularly relates to a water environment pollution traceability system.
Background
The water pollution is a difficult problem in rivers, lakes, reservoirs and sea areas in China. Particularly, some enterprises or individuals can illegally discharge sewage through some water outlets, so that sudden pollution is caused to the water area, the ecology around the pollution is affected, and underwater organisms are harmed. For example, for pollution in some shallow sea areas, large detection equipment cannot enter, the traditional method depends on field investigation and artificial evaluation, a large amount of manpower and time cost are consumed, the efficiency is low, remote sensing data are adopted for detection, the accuracy is low, and a pollution source cannot be well positioned.
Disclosure of Invention
Aiming at the existing problems, the invention provides a water environment pollution traceability system, which can be used for autonomously searching a pollution source in a shallow sea area through an unmanned aerial vehicle and improving the efficiency of pollution source traceability.
The invention is realized by the following modes:
a water environment pollution tracing system, which is characterized in that,
the system comprises a data acquisition module, a network communication module and a control center; the data acquisition module comprises a multispectral unmanned aerial vehicle inspection unit and an underwater unmanned aerial vehicle inspection unit; the multispectral unmanned aerial vehicle inspection unit and the underwater unmanned aerial vehicle inspection unit transmit acquired information to the control center through the network communication module; the underwater unmanned aerial vehicle inspection unit comprises an underwater unmanned aerial vehicle, a water quality sensor and an inspection system; the water quality sensor is arranged on the underwater unmanned aerial vehicle; the inspection system controls the underwater unmanned aerial vehicle to trace the source of pollution.
Further, the inspection system controls the unmanned aerial vehicle in the following way,
s101: the underwater unmanned aerial vehicle is thrown in a polluted water area and submerged, water quality data detection is carried out once when the underwater unmanned aerial vehicle submerges for a certain depth, and the water quality data detection is compared with a previous point of numerical value until the water quality data detection meets a preset condition;
s102: on the height plane positioned in S101, marking as a starting point, detecting the water quality pollution amount, randomly selecting a certain angle and walking for a certain step length, detecting the water quality pollution amount for the second time, then randomly selecting the angle and walking for a certain step length, and detecting the water quality pollution amount for the third time; and comparing the values of the starting point, the second detection and the third detection;
s103: point taking detection: after data comparison, selecting a point with the largest pollution value as a circle center, taking the distance from the point with the largest pollution value as a radius, and selecting 3 points forming an included angle of 90 degrees, 180 degrees and 270 degrees with the circle center for detection to form 4 detection points distributed in a circle;
s104: if the pollution amount of the detection points is higher than the circle center, selecting two points with the highest pollution amount, returning to the step S103, and newly performing new point taking detection;
and if the pollution amount of all the detection points is less than the pollution amount of the circle center, judging that the detection points are close to the pollution source.
Further, in step S104, a straight line is made at the first and third detection points of the circumference, a straight line is made at the second and fourth detection points, the water area is divided into 4 sectors, and then the judgment is performed;
(1) if the pollution amount of 3 detection points is larger than the circle center, preliminarily judging that a plurality of pollution sources are suspected to exist and marking the circle center position, selecting two points with the highest pollution amount, and continuing to perform point taking detection;
(2) if the pollution amount of 2 detection points is larger than the circle center;
(21) if the second detection point and the fourth detection point are both larger than the circle center, judging that a plurality of polluted points are possible, and firstly taking a certain point from the plurality of polluted points and taking the circle center for point detection;
(22) if all the detection points in the S102 fall into a sector area, and one detection point and adjacent detection points in the sector area are both larger than the circle center, judging that a plurality of polluted points possibly exist, and firstly taking one point and the circle center to perform point taking detection;
(23) and if one detection point does not fall into one sector in the S102, selecting two points with the highest pollution amount to perform point-taking detection.
Further, the underwater unmanned aerial vehicle comprises a mother ship and a son ship; the inspection system is arranged on the mother ship; the primary ship controls the secondary ship to patrol through the patrol system, and data communication is realized between the secondary ship and the primary ship through an optical fiber cable.
Furthermore, the inspection system is communicated with the control center through the network communication module, transmits data and receives instructions.
According to the invention, through the linkage of the space multispectral unmanned aerial vehicle and the underwater unmanned aerial vehicle, the underwater pollution source formed in the water area with the established environmental model is quickly traced and transmitted to the control center, and assistance and basis are provided for decision making through an informatization means.
Drawings
FIG. 1 is a schematic structural view of the present invention;
FIG. 2 is a schematic diagram of a patrol method of an underwater unmanned aerial vehicle;
fig. 3 is another schematic diagram of the inspection mode of the underwater unmanned aerial vehicle.
Detailed Description
A water environment pollution traceability system is characterized by comprising a data acquisition module, a network communication module and a control center; the data acquisition module comprises a multispectral unmanned aerial vehicle inspection unit and an underwater unmanned aerial vehicle inspection unit; the multispectral unmanned aerial vehicle inspection unit and the underwater unmanned aerial vehicle inspection unit transmit acquired information to the control center through the network communication module; the underwater unmanned aerial vehicle inspection unit comprises an underwater unmanned aerial vehicle, a water quality sensor and an inspection system; the water quality sensor is arranged on the underwater unmanned aerial vehicle; the inspection system controls the underwater unmanned aerial vehicle to trace the source of pollution.
When the device is used, multispectral inspection is carried out through the multispectral unmanned aerial vehicle inspection unit, the water area possibly polluted is judged through multispectral images, water area status information is sent to the control center, the control center sends the status information to the underwater unmanned aerial vehicle inspection unit after receiving the information, the underwater unmanned aerial vehicle inspects the relevant area after receiving the instruction, and a pollution source is found.
The source of contamination is obtained by:
s101: the underwater unmanned aerial vehicle is thrown in a polluted water area and submerged, water quality data detection is carried out once when the underwater unmanned aerial vehicle submerges for a certain depth, and the water quality data detection is compared with a previous point of numerical value until the water quality data detection meets a preset condition;
s102: on the height plane positioned in S101, marking as a starting point, detecting the water quality pollution amount, randomly selecting a certain angle and walking for a certain step length, detecting the water quality pollution amount for the second time, then randomly selecting the angle and walking for a certain step length, and detecting the water quality pollution amount for the third time; and comparing the values of the starting point, the second detection and the third detection;
s103: point taking detection: after data comparison, selecting a point with the largest pollution value as a circle center, taking the distance from the point with the largest pollution value as a radius, and selecting 3 points forming an included angle of 90 degrees, 180 degrees and 270 degrees with the circle center for detection to form 4 detection points distributed in a circle;
s104: if the pollution amount of the detection points is higher than the circle center, selecting two points with the highest pollution amount, returning to the step S103, and newly performing new point taking detection;
and if the pollution amount of all the detection points is less than the pollution amount of the circle center, judging that the detection points are close to the pollution source.
As shown in fig. 2, specifically, the underwater unmanned aerial vehicle starts to dive at a point a, records the pollution amount p (n) every dive distance n, continues to dive when p (n + 1) > p (n), and stops diving if p (n + 1) < p (n), and uses the depth of the highest pollution amount as a detection surface.
Then, detecting the pollution amount p (a 1) at a detection surface starting point a, randomly selecting a certain angle and walking a certain step length to detect the water quality pollution amount p (a 2), randomly selecting the angle and walking a certain step length, and detecting the water quality pollution amount p (a 3) for the third time; a3 and a1 are not necessarily the same. And then comparing p (a 1), p (a 2) and p (a 3), selecting two points with the maximum p value to be connected, and if p (a 3) > p (a 2) > (a 1), performing point-taking detection once by taking p (a 3) as a center and the distance from p (a 2) as a radius, and additionally selecting points b, c and d for detection, wherein the points a2, b, c and d are separated by an angle of 90 degrees. Meanwhile, comparing p (b), p (c), p (d) with p (a 3), and then entering into judgment,
(1) if at least one point has a value higher than p (a 3), continuously and repeatedly selecting two points with the highest pollution amount for fixed point detection and performing point detection;
(2) and if the pollution amount of all the detection points is less than the pollution amount of the circle center, judging that the detection points are close to the pollution source.
After the pollution source is approached, the step length can be shortened, and the point detection can be continuously carried out in a small range.
And an underwater unmanned aerial vehicle can be used for underwater observation in a small range to determine a final pollution source.
After the approach of the contamination source is judged, the steps from S102 to S104 are newly performed to reduce the step size.
Preferably, in step S104, a straight line is drawn between the first and third detection points of the circle, a straight line is drawn between the second and fourth detection points, the water area is divided into 4 sectors, and then the determination is performed;
(1) if the pollution amount of 3 detection points is larger than the circle center, preliminarily judging that a plurality of pollution sources are suspected to exist and marking the circle center position, selecting two points with the highest pollution amount, and continuing to perform point taking detection;
(2) if the pollution amount of 2 detection points is larger than the circle center;
(21) if the second detection point and the fourth detection point are both larger than the circle center, judging that a plurality of polluted points are possible, and firstly taking a certain point from the plurality of polluted points and taking the circle center for point detection;
(22) if all the detection points in the S102 fall into a sector area, and one detection point and adjacent detection points in the sector area are both larger than the circle center, judging that a plurality of polluted points possibly exist, and firstly taking one point and the circle center to perform point taking detection;
(23) and if one detection point does not fall into one sector in the S102, selecting two points with the highest pollution amount to perform point-taking detection.
Specifically, a3 and c, b and d are connected by a connecting line; forming 4 sectors.
As shown in fig. 2, if p (b) > p (c) > p (d) > p (a 3), it is determined that there are multiple contamination sources, b and c are selected for point detection until the contamination sources are found, and then the process returns to a3, and d and a3 are used for point detection to find the contamination sources.
If p (b) and p (d) are both larger than p (a 3), judging that a plurality of pollution sources are suspected to exist, firstly selecting a3 and b for point detection, and searching for the pollution sources; and returning to the point a3, and performing point detection by using a3 and d to find a pollution source.
As shown in fig. 3, if p (b) and p (c) are both greater than p (a 3), and a1, a2 and a3 are all in the same sector, then it is determined that there are multiple contamination sources, and point detection is performed at a3 and b to find the contamination source; then returning to a3, between a3 and c, a source of contamination is sought.
If a1 is outside the sector, point detection is performed with b and c to find the pollution source.
Preferably, the underwater unmanned aerial vehicle comprises a mother ship and a son ship; the inspection system is arranged on the mother ship; the primary ship controls the secondary ship to patrol through the patrol system, and data communication is realized between the secondary ship and the primary ship through an optical fiber cable.
Carry out communication through the optic fibre cable, can improve data transfer's bandwidth, let unmanned aerial vehicle under water can transmit real-time image and video.
Preferably, the inspection system is communicated with the control center through a network communication module, transmits data and receives instructions.
The communication mode of the network communication module can be various modes such as 4G/5G/NBIoT/LoRa/optical fiber and the like.
The system further comprises a side-scan modeling unit, wherein the side-scan modeling unit adopts a multi-beam side-scan sonar, and before tracing the source of the pollution source, the shallow sea water area can be firstly modeled by multi-beam side-scan sonar detection, so that a water area environment map is established. Thereby realize making unmanned aerial vehicle can be in the more accurate location of relevant waters.
While the invention has been described with reference to specific embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the scope of the invention. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the invention without departing from its scope. Therefore, it is intended that the invention not be limited to the particular embodiment disclosed, but that the invention will include all embodiments falling within the scope of the appended claims.
Claims (5)
1. A water environment pollution traceability system is characterized by comprising a data acquisition module, a network communication module and a control center; the data acquisition module comprises a multispectral unmanned aerial vehicle inspection unit and an underwater unmanned aerial vehicle inspection unit; the multispectral unmanned aerial vehicle inspection unit and the underwater unmanned aerial vehicle inspection unit transmit acquired information to the control center through the network communication module; the underwater unmanned aerial vehicle inspection unit comprises an underwater unmanned aerial vehicle, a water quality sensor and an inspection system; the water quality sensor is arranged on the underwater unmanned aerial vehicle; the inspection system controls the underwater unmanned aerial vehicle to trace the source of pollution.
2. The system of claim 1, wherein the routing inspection system controls the drone by,
s101: the underwater unmanned aerial vehicle is thrown in a polluted water area and submerged, water quality data detection is carried out once when the underwater unmanned aerial vehicle submerges for a certain depth, and the water quality data detection is compared with a previous point of numerical value until the water quality data detection meets a preset condition;
s102: on the height plane positioned in S101, marking as a starting point, detecting the water quality pollution amount, randomly selecting a certain angle and walking for a certain step length, detecting the water quality pollution amount for the second time, then randomly selecting the angle and walking for a certain step length, and detecting the water quality pollution amount for the third time; and comparing the values of the starting point, the second detection and the third detection;
s103: point taking detection: after data comparison, selecting a point with the largest pollution value as a circle center, taking the distance from the point with the largest pollution value as a radius, and selecting 3 points forming an included angle of 90 degrees, 180 degrees and 270 degrees with the circle center for detection to form 4 detection points distributed in a circle;
s104: if the pollution amount of the detected points is higher than the circle center, selecting two points with the highest pollution amount, returning to the step S103, and detecting from the newly-taken points;
and if the pollution amount of all the detection points is less than the pollution amount of the circle center, judging that the detection points are close to the pollution source.
3. The system of claim 2, wherein in step S104, a straight line is drawn between the first and third detection points of the circle, a straight line is drawn between the second and fourth detection points, and the water area is divided into 4 sectors, after which the determination is made;
(1) if the pollution amount of 3 detection points is larger than the circle center, preliminarily judging that a plurality of pollution sources are suspected to exist and marking the circle center position, selecting two points with the highest pollution amount, and continuing to perform point taking detection;
(2) if the pollution amount of 2 detection points is larger than the circle center;
(21) if the second detection point and the fourth detection point are both larger than the circle center, judging that a plurality of polluted points are possible, and firstly taking a certain point and a round point to perform point taking detection;
(22) if all the detection points in the S102 are located in a sector area, and one detection point and adjacent detection points in the sector area are larger than the dots, judging that a plurality of polluted points possibly exist, and firstly taking one point and the circle center to perform point taking detection;
(23) and if one detection point does not fall into one sector in the S102, selecting two points with the highest pollution amount to perform point-taking detection.
4. The system of claim 1, wherein the underwater drone comprises a mother ship and a daughter ship; the inspection system is arranged on the mother ship; the primary ship controls the secondary ship to patrol through the patrol system, and data communication is realized between the secondary ship and the primary ship through an optical fiber cable.
5. The system of claim 4, wherein the routing inspection system communicates with the control center via a network communication module to transmit data and receive commands.
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