CN110677454B - Water pollution early warning system and method based on multi-agent network convergence algorithm - Google Patents

Water pollution early warning system and method based on multi-agent network convergence algorithm Download PDF

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CN110677454B
CN110677454B CN201910764155.5A CN201910764155A CN110677454B CN 110677454 B CN110677454 B CN 110677454B CN 201910764155 A CN201910764155 A CN 201910764155A CN 110677454 B CN110677454 B CN 110677454B
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周瑜佳
陈一帆
杨琼
吴益
方中帅
乐佳
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Zhejiang Institute of Hydraulics and Estuary
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Abstract

The invention relates to the technical field of environmental monitoring, in particular to a water pollution early warning system and a method based on a multi-agent network convergence control algorithm, which comprises the following steps: (1): considering a multi-agent network composed of n agent nodes (monitoring points), and constructing the whole network topology into a connected graph according to the node communication edge relation; (2): selecting z water environment evaluation standards, and selecting corresponding classification standards according to the water area function classification; configuring one or more sensors of corresponding monitoring indexes for the nodes; (3): and by adopting a distributed control protocol, when the water area state value monitored by the node exceeds a standard interval, the node judges that the water environment is polluted, so that early warning is triggered. By adopting the method, the response speed of the system can be effectively improved, the energy consumption of equipment is reduced, the operation reliability of the system is improved, the manufacturing cost of the whole system is reduced, and the method has considerable market prospect in the field of monitoring and early warning of water pollution environment.

Description

Water pollution early warning system and method based on multi-agent network convergence algorithm
Technical Field
The invention relates to the technical field of environmental monitoring, in particular to a water pollution early warning system and method based on a multi-agent network convergence control algorithm.
Background
With the continuous development of social economy, the living standard of people is continuously improved, and the problem of water pollution caused by the continuous development of social economy is very severe. A large amount of industrial, agricultural and domestic wastewater is directly discharged into rivers, lakes and oceans even without being treated, causing serious pollution to water quality, and simultaneously causing great damage to ecological environment safety, social stability, human health and national property safety. In a water pollution monitoring system, the method can be divided into three stages of quick early warning, deterministic detection and accurate authoritative detection, wherein a quick early warning link is the basis of the latter two-stage detection, and has a vital role in striving for the best processing opportunity and reducing the great environmental and economic losses.
The traditional water pollution early warning system based on the sensor network is basically realized through a centralized communication system, namely, each monitoring node is required to have the capability of communicating with a monitoring center node. The most main defects of the system are that the workload of the monitoring central node station is overlarge, and once the central node is knocked due to network failure, congestion, even network malicious attack and the like, the whole water pollution early warning system is paralyzed, so that the robustness is poor. Meanwhile, because the water pollution monitoring and early warning is a long-period work, in order to keep the system continuously and normally working, equipment devices must be replaced frequently (node energy is exhausted and fails), so that not only is the maintenance workload large, but also the operation cost is increased, and the use of the water pollution monitoring and early warning technology is limited to a certain extent.
A Multi-agent network (Multi-agent networks) refers to a network consisting of a large number of agent individuals with local sensing, execution, and communication capabilities. In recent years, due to the advantages of robustness, autonomy, low cost and the like of a multi-agent network, the method is widely applied to the fields of multi-robot systems, smart grid dispatching, unmanned aerial vehicles, wireless sensor networks and the like. The convergence algorithm is an important distributed algorithm in the current multi-agent network, and means that under the condition that a central node is not needed by nodes in the network, the nodes and respective neighbor nodes are in communication cooperation, and finally the state values of all the nodes in the system tend to be common.
The above background disclosure is only for the purpose of assisting understanding of the inventive concept and technical solutions of the present invention, and does not necessarily belong to the prior art of the present patent application, and should not be used for evaluating the novelty and inventive step of the present application in the case that there is no clear evidence that the above content is disclosed at the filing date of the present patent application.
Disclosure of Invention
The invention aims to provide a water pollution early warning method based on a multi-agent network convergence algorithm, which can effectively improve the response speed of a system, reduce the energy consumption of equipment, improve the running reliability of the system, reduce the manufacturing cost of the whole system and have considerable market prospect in the field of water pollution environment monitoring and early warning.
In order to achieve the above object, the present invention adopts the following three aspects.
In a first aspect, a water pollution early warning method based on a multi-agent network convergence algorithm comprises the following steps:
step (1): considering a multi-agent network composed of n agent nodes (monitoring points), constructing the whole network topology into a connected graph according to the node communication edge relation, namely starting from any node in the network, and reaching any other node in the network through the adjacent node directed edges;
step (2): according to the 'surface water environment quality standard' (GB3838-2002), selecting z water environment evaluation standards, and selecting corresponding classification standards according to water area function classes; configuring one or more sensors of corresponding monitoring indexes for the nodes;
and (3): suppose Ni(t) is a neighbor node set of the node i at the time t, a distributed control protocol is adopted, and the design of the control protocol is according to the following rules: the node i sorts the information sent by the neighbor node j collected at the time t, and when the water area state value monitored by the node exceeds a standard interval, the node judges that the water environment is polluted, so that early warning is triggered, and a controller corresponding to the early warning triggers intervention.
It should be noted that the present invention only relates to the situation that at most one neighbor node information exceeds the threshold value at the same time in the system, that is, only one of the situations that a certain node state value is higher than the upper threshold value or lower than the lower threshold value occurs in the system, and the simultaneous occurrence of the two situations is not considered. However, the system and method of the present application have the following advantages: compared with the existing design method, only single state information of adjacent nodes needs to be transmitted, so that the communication traffic in the system is reduced, and the communication pressure of the system is reduced; meanwhile, based on the events of the system, namely, the monitoring value triggers an early warning mechanism, so that the energy consumption of the system is reduced; when designing the convergence control protocol, namely step 3 of the method, each node only needs to select the maximum or minimum neighbor value as the state value of the node at the next moment, so that the distributed event-driven consistency protocol is obtained. Compared with the traditional method, the design process of the control protocol is greatly simplified; the threshold triggering mechanism and the early warning algorithm based on the mechanism are implemented only by utilizing the information of the node and the adjacent nodes capable of performing information interaction with the node in the network, and the overall design method is based on a distributed control architecture, has the characteristics of low cost, strong expandability, high robustness and the like, and is particularly suitable for large-area water source environment monitoring and early warning under the condition of accessing a large number of distributed sensors.
Further, in step (1), the multi-agent network composed of n agent nodes (monitoring points) may be denoted as G ═ V, E, where V ═ 1,2, …, n represents a node set,
Figure BDA0002171371930000031
representing a communication edge set between nodes; (i, j) ∈ E indicating that node i can receive information from node j.
Further, in step (2), X is made to be [ X ]i,k，k，Lngi，Lati]K ∈ Z, Z ═ 1,2i,kIndicating the kth monitoring index (i.e., state value), Lng, of the ith nodeiIndicating the longitude, Lat, of node iiRepresenting the latitude of node i.
Furthermore, the method for selecting the corresponding category standard according to the water area function category in the step (2) comprises the following steps:
step (2.1): determining the water area function category C belonging to the water body, wherein the category C belongs to C, C is { C1, C2, C3, C4, C5}, { I type water, II type water, III type water, IV type water and V type water };
step (2.2): selecting corresponding standard corresponding to function category, and establishing monitoring standard value interval
Figure BDA0002171371930000032
Wherein
Figure BDA0002171371930000033
x c,kRespectively representing the standard upper limit and the standard lower limit of the kth monitoring index of the C-type water, and C belongs to C.
Further, in the step (3),
neighbor node set
Figure BDA0002171371930000034
Distributed control protocol U ═ U1,u2,...,un}；
The control protocol is designed according to the following rules: node i collects neighbor nodes j at time t, j belongs to NiThe transmitted information is arranged and ordered
Figure BDA0002171371930000035
When the water area state value monitored by the node exceeds the standard interval, the early warning system is started, namely when the water area state value monitored by the node exceeds the standard interval
Figure BDA0002171371930000036
When, or xk,m(t)<x kWhen the corresponding controller triggers the intervention, the specific controller protocol is
Figure BDA0002171371930000037
Figure BDA0002171371930000038
Or
Figure BDA0002171371930000039
After the controller is intervened, the state value of each node in the system is updated.
Furthermore, in step (3), after the controller intervenes, the update equation of the state values of the nodes in the system is as follows:
Figure BDA00021713719300000310
further, the method also comprises the step (4): the node i acquires and acquires a monitoring state value x of a self region at the moment ti,k(t); when state value
Figure BDA0002171371930000041
The node takes no action; when it is satisfied
Figure BDA0002171371930000042
Figure BDA0002171371930000043
When the node is in a condition, the node judges that the water environment is polluted, so that early warning is triggered, and from the moment, the node i maintains the state value of the node i to be xi,k(t) is fixed and passes this fixed value to its neighboring nodes; other nodes in the network update the state value of the next moment per se according to the formula (1) and synchronize the node information Xi,k(t+1)＝[xi,k(t +1), k, longitude coordinate i, latitude coordinate i]And transmitting the polluted coordinate address and the polluted state value in the whole network system until all network nodes are synchronized.
Further, the method for synchronously delivering the multi-agent network information in the step (4) comprises the following steps:
substeps (4.1): the node acquires a data set x at the time t through a corresponding sensori,k(t), obtaining longitude and latitude information through self GPS positioning (or manual setting according to the position of the area where the node is located in advance);
substeps (4.2): when the number monitored by the node i is in a normal interval, namely the number does not exceed a set threshold interval, the node i does not take any measures; if the state value measured by the node exceeds the threshold interval, the node i records the abnormal value at the moment, and then all the moments are the number fixed;
substeps (4.3): after the node i detects the abnormal value, triggering an early warning mechanism, and starting to send the abnormal state value to the adjacent node by using a wireless communication protocol;
substeps (4.4): the adjacent node j updates the state value of the adjacent node j through a maximum/minimum similarity algorithm, and transmits the updated state value to the adjacent node;
substeps (4.5): and through local information interaction, the abnormal value is continuously transmitted to the diffusion until the abnormal value is synchronized to be consistent with all nodes of the whole network.
In a second aspect, a water pollution early warning system based on a multi-agent network convergence algorithm comprises:
-a monitoring module: the system comprises a multi-agent network consisting of n agent nodes (monitoring points), wherein the whole network topology is constructed into a connected graph;
-a sensor module: the system is configured at a node and can detect corresponding indexes of the corresponding node, z water environment evaluation standards are selected according to the quality standard of surface water environment (GB3838-2002), and corresponding classification standards are selected according to the function classification of a water area;
-a control module: the node comprises a distributed control protocol, wherein the protocol is used for judging that the water environment is polluted when the water area state value monitored by the node exceeds a standard interval, so that early warning is triggered, and a controller corresponding to the early warning is triggered to intervene;
the control module further comprises a storage medium containing a program for implementing any of the methods of the first aspect.
In a third aspect, the use of any one of the methods of the first aspect above in water pollution warning.
The invention has the beneficial effects that:
1. compared with the existing design method, only single state information of adjacent nodes needs to be transmitted, the communication traffic in the system is reduced, and the communication pressure of the system is reduced. Meanwhile, based on the events of the system, namely, the monitoring value triggers an early warning mechanism, so that the energy consumption of the system is reduced;
2. when designing the convergence control protocol, namely step 3 of the method, each node only needs to select the maximum or minimum neighbor value as the state value of the node at the next moment, so that the distributed event-driven consistency protocol is obtained. Compared with the traditional method, the design process of the control protocol is greatly simplified;
3. the threshold triggering mechanism and the early warning algorithm based on the mechanism are implemented only by utilizing the information of the node and the adjacent nodes capable of performing information interaction with the node in the network, and the overall design method is based on a distributed control architecture, has the characteristics of low cost, strong expandability, high robustness and the like, and is particularly suitable for large-area water source environment monitoring and early warning under the condition of accessing a large number of distributed sensors.
The invention adopts the technical scheme to provide the model essay, makes up the defects of the prior art, and has reasonable design and convenient operation.
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In order to make the aforementioned and other objects, features, and advantages of the invention, as well as others which will become apparent, reference is made to the following description taken in conjunction with the accompanying drawings in which:
FIG. 1 is a schematic flow diagram of the present invention;
fig. 2 is a schematic structural diagram of a wireless sensor according to the present invention.
Detailed Description
Unless defined otherwise, technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The present invention uses the methods and materials described herein; other suitable methods and materials known in the art may be used. The materials, methods, and examples described herein are illustrative only and are not intended to be limiting. All publications, patent applications, patents, provisional applications, database entries, and other references mentioned herein, and the like, are incorporated by reference herein in their entirety. In case of conflict, the present specification, including definitions, will control.
Example 1:
the embodiment provides a water pollution early warning system and method based on a multi-agent network convergence algorithm, which comprises the following steps:
step (1): consider a multi-agent network consisting of n agent nodes (monitoring points), denoted G ═ V, E, where V ═ 1,2,. multidata, n represents a set of nodes,
Figure BDA0002171371930000061
representing a communication edge set between nodes; (i, j) E represents that the node i can receive the information from the node j; according to the node communication edge relation, the whole network topology is constructed into a connected graph, namely, any node in the network starts, and any other node in the network can be reached through the directed edge of the adjacent node.
Step (2): according to the 'surface water environment quality standard' (GB 3838-; let X be ═ Xi,k，k，Lngi，Lati]K ∈ Z, Z ═ 1,2i,kIndicating the kth monitoring index (i.e., state value), Lng, of the ith nodeiIndicating the longitude, Lat, of node iiRepresenting the latitude of the node i;
the method for selecting the corresponding category standard according to the water area function category in the step (2) comprises the following steps:
step (2.1): determining the water area function category C belonging to the water body, wherein the category C belongs to C, C is { C1, C2, C3, C4, C5}, { I type water, II type water, III type water, IV type water and V type water };
step (2.2): selecting corresponding standard corresponding to function category, and establishing monitoring standard value interval
Figure BDA0002171371930000062
Wherein
Figure BDA0002171371930000063
x c,kRespectively representing the standard upper limit and the standard lower limit of the kth monitoring index of the C-type water, wherein C belongs to C;
in the embodiment, the pH index of I-type water is selected as one of monitoring and early warning states, and the pH value is designated as the 1 st index, namely k is 1; if the pH value is within the normal threshold range of 6-9 in the table 1 ' standard limit value of basic items of surface water environment quality standard ' in the table of ' surface water environment quality standard
Figure BDA0002171371930000064
x c,k＝x 1,1＝6。
And (3): suppose Ni(t) is the set of neighbor nodes for node i at time t,
Figure BDA0002171371930000065
Figure BDA0002171371930000066
adopting distributed control protocol U ═ U1,u2,...,unAnd (4) designing a control protocol according to the following rules: node i collects neighbor nodes j at time t, j belongs to NiThe transmitted information is arranged and ordered
Figure BDA0002171371930000067
Figure BDA0002171371930000068
When the water area state value monitored by the node exceeds the standard interval, the early warning system is started, namely when the water area state value monitored by the node exceeds the standard interval
Figure BDA0002171371930000069
When, or xk,m(t)<x kWhen the corresponding controller triggers the intervention, the specific controller protocol is
Figure BDA00021713719300000610
Or
Figure BDA00021713719300000611
Figure BDA0002171371930000071
After the controller intervenes, the update equation of each node in the system is as follows:
Figure BDA0002171371930000072
it should be noted that the present invention only relates to the situation that at most one neighbor node information exceeds the threshold value at the same time in the system, that is, only one of the situations that a certain node state value is higher than the upper threshold value or lower than the lower threshold value occurs in the system, and the simultaneous occurrence of the two situations is not considered.
And (4): the node i acquires and acquires a monitoring state value x of a self region at the moment ti,k(t); when state value
Figure BDA0002171371930000073
Figure BDA0002171371930000074
The node takes no action. When it is satisfied
Figure BDA0002171371930000075
When the node is in a condition, the node judges that the water environment is polluted, so that early warning is triggered, and from the moment, the node i maintains the state value of the node i to be xi,k(t) is fixed and passes this fixed value to its neighboring nodes; other nodes in the network update the state value of the next moment per se according to the formula (1) and synchronize the node information Xi,k(t+1)＝[xi,k(t +1), k, longitude coordinate i, latitude coordinate i]Transmitting the polluted coordinate address and the polluted state value in the whole network system until all network nodes are synchronized;
the method for synchronously transmitting the multi-agent network information in the step (4) comprises the following steps:
substeps (4.1): the node acquires a data set x at the time t through a corresponding sensori,k(t), obtaining longitude and latitude information through self GPS positioning (or manual setting according to the position of the area where the node is located in advance);
substeps (4.2): when the number monitored by the node i is in a normal interval, namely the number does not exceed a set threshold interval, the node i does not take any measures; if the state value measured by the node exceeds the threshold interval, the node i records the abnormal value at the moment, and then all the moments are the number fixed;
substeps (4.3): after the node i detects the abnormal value, triggering an early warning mechanism, and starting to send the abnormal state value to the adjacent node by using a wireless communication protocol;
substeps (4.4): the adjacent node j updates the state value of the adjacent node j through a maximum/minimum similarity algorithm, and transmits the updated state value to the adjacent node;
substeps (4.5): and through local information interaction, the abnormal value is continuously transmitted to the diffusion until the abnormal value is synchronized to be consistent with all nodes of the whole network.
Conventional techniques in the above embodiments are known to those skilled in the art, and therefore, will not be described in detail herein.
While the above detailed description has shown, described, and pointed out novel features as applied to various embodiments, it will be understood that various omissions, substitutions, and changes in the form and details of the device or method illustrated may be made without departing from the spirit of the disclosure. In addition, the various features and methods described above may be used independently of one another, or may be combined in various ways. All possible combinations and sub-combinations are intended to fall within the scope of the present disclosure. Many of the embodiments described above include similar components, and thus, these similar components are interchangeable in different embodiments. While the invention has been disclosed in the context of certain embodiments and examples, it will be understood by those skilled in the art that the invention extends beyond the specifically disclosed embodiments to other alternative embodiments and/or uses and obvious modifications and equivalents thereof. Accordingly, the invention is not intended to be limited by the specific disclosure of preferred embodiments herein.

Claims (10)

1. A water pollution early warning method based on a multi-agent network convergence algorithm is characterized by comprising the following steps:
step (1): a multi-agent network composed of n agent nodes (monitoring points), wherein the whole network topology is constructed into a connected graph according to the node communication edge relation, namely, any node in the network starts, and any other node in the network can be reached through the adjacent node directed edges;
step (2): according to the 'surface water environment quality standard' (GB3838-2002), selecting z water environment evaluation standards, and selecting corresponding classification standards according to water area function classes; configuring one or more sensors of corresponding monitoring indexes for the nodes;
and (3): suppose Ni(t) is a neighbor node set of the node i at the time t, a distributed control protocol is adopted, and the design of the control protocol is according to the following rules: the node i sorts the information sent by the neighbor node j collected at the time t, and when the water area state value monitored by the node exceeds a standard interval, the node judges that the water environment is polluted, so that early warning is triggered, and a controller corresponding to the early warning triggers intervention.
2. The method of claim 1, wherein: in step (1), the multi-agent network composed of n agent nodes (monitoring points) may be denoted as G ═ V, E, where V ═ 1,2, …, n represents a node set,
Figure FDA0003339712050000011
representing a communication edge set between nodes; (i, j) ∈ E indicating that node i can receive information from node j.
3. The method of claim 2, wherein: in step (2), let X ═ Xi,k，k，Lngi，Lati]K ∈ Z, Z ═ 1,2i,kIndicating the kth monitoring index (i.e., state value), Lng, of the ith nodeiIndicating the longitude, Lat, of node iiRepresenting the latitude of node i.
4. The method of claim 3, wherein: the method for selecting the corresponding category standard according to the water area function category in the step (2) comprises the following steps:
step (2.1): determining the water area function category C belonging to the water body, wherein the category C belongs to C, C is { C1, C2, C3, C4, C5}, { I type water, II type water, III type water, IV type water and V type water };
step (2.2): selecting corresponding standard corresponding to function category, and establishing monitoring standard value interval
Figure FDA0003339712050000012
Wherein
Figure FDA0003339712050000013
xc,kRespectively representing the standard upper limit and the standard lower limit of the kth monitoring index of the C-type water, and C belongs to C.
5. The method of claim 4, wherein: in the step (3), the step (c),
neighbor node set
Figure FDA0003339712050000014
Distributed control protocol U ═ U1,u2,...,un}；
The control protocol is designed according to the following rules: node i collects neighbor nodes j at time t, j belongs to NiThe transmitted information is arranged and ordered
Figure FDA0003339712050000021
When the water area state value monitored by the node exceeds the standard interval, the early warning system is started, namely when the water area state value monitored by the node exceeds the standard interval
Figure FDA0003339712050000022
When, or xk,m(t)<x kWhen the corresponding controller triggers the intervention, the specific controller protocol is
Figure FDA0003339712050000023
Figure FDA0003339712050000024
Or
Figure FDA0003339712050000025
After the controller is intervened, the state value of each node in the system is updated.
6. The method of claim 5, wherein: in the step (3), after the controller intervenes, the update equation of the state value of each node in the system is as follows:
Figure FDA0003339712050000026
7. the method of claim 6, wherein: further comprising the step (4): the node i acquires and acquires a monitoring state value x of a self region at the moment ti,k(t); when state value
Figure FDA0003339712050000027
The node takes no action; when it is satisfied
Figure FDA0003339712050000028
When the node is in a condition, the node judges that the water environment is polluted, so that early warning is triggered, and from the moment, the node i maintains the state value of the node i to be xi,k(t) is fixed and passes this fixed value to its neighboring nodes; other nodes in the network update the state value of the next moment per se according to the formula (1) and synchronize the node information Xi,k(t+1)＝[xi,k(t +1), k, longitude coordinate i, latitude coordinate i]And transmitting the polluted coordinate address and the polluted state value in the whole network system until all network nodes are synchronized.
8. The method of claim 7, wherein: the method for synchronously transmitting the multi-agent network information in the step (4) comprises the following steps:
substeps (4.1): the node acquires a data set x at the time t through a corresponding sensori,k(t), obtaining longitude and latitude by self GPS positioning (or manually giving according to the position of the area where the node is positioned in advance)Information;
substeps (4.2): when the number monitored by the node i is in a normal interval, namely the number does not exceed a set threshold interval, the node i does not take any measures; if the state value measured by the node exceeds the threshold interval, the node i records the abnormal value at the moment, and then all the moments are the number fixed;
substeps (4.3): after the node i detects the abnormal value, triggering an early warning mechanism, and starting to send the abnormal state value to the adjacent node by using a wireless communication protocol;
substeps (4.4): the adjacent node j updates the state value of the adjacent node j through a maximum/minimum similarity algorithm, and transmits the updated state value to the adjacent node;
substeps (4.5): and through local information interaction, the abnormal value is continuously transmitted to the diffusion until the abnormal value is synchronized to be consistent with all nodes of the whole network.
9. A water pollution early warning system based on multi-agent network convergence algorithm is characterized by comprising:
-a monitoring module: the system comprises a multi-agent network consisting of n agent nodes (monitoring points), wherein the whole network topology is constructed into a connected graph;
-a sensor module: the system is configured at a node and can detect corresponding indexes of the corresponding node, z water environment evaluation standards are selected according to the quality standard of surface water environment (GB3838-2002), and corresponding classification standards are selected according to the function classification of a water area;
-a control module: the node comprises a distributed control protocol, wherein the protocol is used for judging that the water environment is polluted when the water area state value monitored by the node exceeds a standard interval, so that early warning is triggered, and a controller corresponding to the early warning is triggered to intervene;
the control module also comprises a storage medium, and the storage medium contains a program capable of realizing the method of any one of claims 1 to 8.
10. Use of the method of any one of claims 1 to 8 in water pollution warning.
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