CN108989416B - Intelligent real-time vibration monitoring system for wind turbine generator - Google Patents

Intelligent real-time vibration monitoring system for wind turbine generator Download PDF

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CN108989416B
CN108989416B CN201810746741.2A CN201810746741A CN108989416B CN 108989416 B CN108989416 B CN 108989416B CN 201810746741 A CN201810746741 A CN 201810746741A CN 108989416 B CN108989416 B CN 108989416B
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CN108989416A (en
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邱林新
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Guodian power Hunan Chenzhou Wind Power Development Co.,Ltd.
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Guodian Power Hunan Chenzhou Wind Power Development Co ltd
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Abstract

The invention provides an intelligent real-time monitoring system for wind turbine generator vibration, which comprises a data acquisition module for acquiring wind turbine generator vibration data, a storage module for storing the wind turbine generator vibration data and a display module for displaying the wind turbine generator vibration data; the data acquisition module and the display module are connected with the storage module.

Description

Intelligent real-time vibration monitoring system for wind turbine generator
Technical Field
The invention relates to the technical field of wind turbine generator monitoring, in particular to an intelligent real-time wind turbine generator vibration monitoring system.
Background
Wind energy is a clean and renewable energy source, and the generation of electricity by utilizing the wind energy is an extremely important and potential-developing electricity generation mode. Wind power generation is realized by a wind turbine which can convert wind power mechanical energy into electric energy. The wind turbine mainly comprises three parts, namely a blade, an engine room and a tower barrel, wherein a gear box, a generator and the like of the wind turbine are arranged in the engine room, and the blade is connected with the generator in the engine room through a main shaft so that the blade can drive the generator to generate electricity when rotating under the action of wind power, thereby realizing the conversion from wind power mechanical energy to electric energy. In the process that the wind turbine generator converts wind mechanical energy into electric energy, a plurality of parts of the wind turbine generator vibrate, and when the vibration reaches a certain degree, vibration faults occur, so that the whole wind turbine generator is damaged. Therefore, the method has important significance for monitoring the vibration condition of the wind turbine generator, rapidly making correct diagnosis in the fault premonition period and taking corresponding protective measures for the wind turbine generator.
Disclosure of Invention
Aiming at the problems, the invention provides an intelligent real-time vibration monitoring system for a wind turbine generator.
The purpose of the invention is realized by adopting the following technical scheme:
the system comprises a data acquisition module, a storage module and a display module, wherein the data acquisition module is used for acquiring vibration data of the wind turbine generator, the storage module is used for storing the vibration data of the wind turbine generator, and the display module is used for displaying the vibration data of the wind turbine generator; the data acquisition module and the display module are connected with the storage module.
Preferably, the data acquisition module comprises a sink node and a plurality of sensor nodes, the sink node and the sensor nodes construct a wireless sensor network with a clustering structure in a self-organizing manner, and the sensor nodes are clustered and a cluster head is selected according to a low-power-consumption self-adaptive clustering hierarchical protocol; the cluster head is mainly used for collecting the vibration data of the wind turbine generator collected by the sensor nodes in the cluster and sending the vibration data to the sink node; the sink node is mainly used for summarizing and sending the vibration data of the wind turbine generator, which are sent by each cluster head, to the storage module.
Preferably, the sensor node comprises at least one sensor, and the sensor node further comprises a signal adapter for converting a sensor signal into corresponding vibration data of the wind turbine generator, wherein the signal adapter is connected with the sensor; the device also comprises a controller used for controlling the acquisition frequency, wherein the controller is connected with the sensor. Preferably, the sensor is a low frequency vibration sensor or a high frequency vibration sensor; the low-frequency vibration sensor is arranged on a blade of the wind turbine generator to acquire a blade vibration signal, or arranged on the main shaft to acquire a main shaft vibration signal, or arranged on a tower cylinder to acquire a tower cylinder vibration signal; the high-frequency vibration sensor is arranged on a gear box of the wind turbine generator to acquire a gear box vibration signal, or is arranged on the generator to acquire a generator vibration signal.
The display module comprises any one or more of a display screen, a smart phone, a notebook computer and a desktop computer.
The invention has the beneficial effects that: the method and the device can intelligently acquire the vibration data of the wind turbine generator in real time, and are convenient for monitoring personnel to know the vibration information of the wind turbine generator in time, so that the state of the wind turbine generator is further analyzed according to the vibration information of the wind turbine generator, the wind turbine generator which is possibly in fault is checked in time, and the loss caused by the fault of the wind turbine generator is reduced.
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The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
FIG. 1 is a block diagram illustrating the structure of an intelligent real-time vibration monitoring system for a wind turbine generator according to an exemplary embodiment of the present invention;
fig. 2 is a block diagram schematically illustrating a structure of a sensor node according to an exemplary embodiment of the present invention.
Reference numerals:
the device comprises a data acquisition module 1, a storage module 2, a display module 3, a sensor 10, a signal adapter 20 and a controller 30.
Detailed Description
The invention is further described with reference to the following examples.
Referring to fig. 1, an embodiment of the present invention provides an intelligent real-time monitoring system for wind turbine generator vibration, where the system includes a data acquisition module 1 for acquiring wind turbine generator vibration data, a storage module 2 for storing wind turbine generator vibration data, and a display module 3 for displaying the wind turbine generator vibration data; the data acquisition module 1 and the display module 3 are both connected with the storage module 2.
In one embodiment, the data acquisition module 1 includes a sink node and a plurality of sensor nodes, the sink node and the sensor nodes construct a wireless sensor network with a cluster structure in a self-organizing manner, wherein the sensor nodes are clustered and a cluster head is selected according to a low-power-consumption self-adaptive cluster hierarchical protocol; the cluster head is mainly used for collecting the vibration data of the wind turbine generator collected by the sensor nodes in the cluster and sending the vibration data to the sink node; the sink node is mainly used for summarizing and sending the vibration data of the wind turbine generator, which are sent by each cluster head, to the storage module 2. In one implementation mode, in a link construction stage of a wireless sensor network, 2 sensor nodes are selected as relay nodes of a cluster where a cluster head is located within a communication range of the cluster head according to the positions of the sensor nodes and current residual energy, and an optimal path from the sensor nodes to each relay node in the cluster where the sensor nodes are located is determined; in the data sending stage, the sensor node selects one relay node as a target node for receiving the wind turbine generator vibration data to be sent, and then the wind turbine generator vibration data to be sent are sent out along an optimal path corresponding to the target node; the relay node receives the wind turbine generator vibration data sent by each sensor node, and sends the received wind turbine generator vibration data and the wind turbine generator vibration data collected by the relay node to the cluster head.
As shown in fig. 2, the sensor node includes a sensor 10 and a signal adapter 20 for converting a signal of the sensor 10 into corresponding vibration data of the wind turbine, and the signal adapter 20 is connected to the sensor 10; a controller 30 for controlling the acquisition frequency is also included, said controller 30 being connected to the sensor 10. The sensor 10 is a low-frequency vibration sensor or a high-frequency vibration sensor; the low-frequency vibration sensor is arranged on a blade of the wind turbine generator to acquire a blade vibration signal, or arranged on the main shaft to acquire a main shaft vibration signal, or arranged on a tower cylinder to acquire a tower cylinder vibration signal; the high-frequency vibration sensor is arranged on a gear box of the wind turbine generator to acquire a gear box vibration signal, or is arranged on the generator to acquire a generator vibration signal.
The display module 3 comprises any one or more of a display screen, a smart phone, a notebook computer and a desktop computer.
According to the embodiment of the invention, the vibration data of the wind turbine generator can be intelligently acquired in real time, so that monitoring personnel can conveniently know the vibration information of the wind turbine generator in time, the state of the wind turbine generator is further analyzed according to the vibration information of the wind turbine generator, the wind turbine generator which possibly fails is timely checked, and the loss caused by the failure of the wind turbine generator is reduced.
The method for selecting 2 sensor nodes as the relay nodes of the cluster where the cluster head is located in the communication range of the cluster head according to the positions of the sensor nodes and the current residual energy comprises the following steps:
(1) for any cluster head eiDefine cluster head eiAll sensor nodes in the communication range are the cluster head eiThe neighbor node of (2) acquires a cluster head eiPosition information and current residual energy information of each neighbor node;
(2) calculating a first weight of each neighbor node according to the position information and the current residual energy information of the neighbor nodes:
Figure BDA0001724547350000031
in the formula, Cj 1Indicating cluster head eiH (e) of the jth neighbor nodeiJ) denotes a cluster head eiDistance between its jth neighbor node, H (e)iK) denotes a cluster head eiThe distance between its kth neighbor node,
Figure BDA0001724547350000033
indicating cluster head eiThe number of neighbor nodes of (2); qjIs the current residual energy, Q, of the jth neighbor nodeminIs a set minimum energy value;
(3) selecting the neighbor node with the maximum first weight as a cluster head eiThe second weights of the other neighbor nodes except the first relay node are calculated:
Figure BDA0001724547350000032
in the formula, Cρ 2Representing a second weight, C, of the p-th neighbor node except the first relay nodeρ 1Representing a first weight of the ρ -th neighbor node except the first relay node; e.g. of the typei 1Indicating a selected cluster head eiFirst relay node of H (e)i 1Rho) is the rho-th neighbor node and a first relay node ei 1The distance of (a) to (b),
Figure BDA0001724547350000042
for the rest of the neighbor nodes except the first relay node and ei 1The sum of the distances of (a);
(4) selecting the neighbor node with the largest second weight as a cluster head eiThe second relay node of (1).
In the embodiment, 2 sensor nodes are selected as the relay node of the cluster where the cluster head is located in the communication range of the cluster head according to the positions of the sensor nodes and the current residual energy, the relay node is responsible for gathering the vibration data of the wind turbine generator collected by the sensor nodes in the cluster, and compared with a mode of gathering the vibration data of the wind turbine generator only through the cluster head or a single relay node, the load of the cluster head or the single relay node can be effectively shared, excessive consumption of energy of the cluster head or the single relay node is avoided, so that the transmission energy consumption of the vibration data of the wind turbine generator in the cluster is effectively balanced, and the clustering stability is improved.
The embodiment further provides a mode for selecting the relay node according to the first weight and the second weight, the mode can enable the selected relay node to have better capability to be responsible for data collection, and the two relay nodes are ensured to be far away from each other, so that the energy consumption of the vibration data of the wind turbine generator set transmitted to the relay node by each sensor node is balanced, and the reliability of the vibration data transmission of the wind turbine generator set is improved.
In one embodiment, the determining an optimal path from a sensor node to each relay node in a cluster based on an ant colony optimization algorithm includes:
(1) defining sensor nodes generating forward ant messages as source nodes, generating a set number of forward ant messages by the source nodes, selecting the nearest sensor nodes in a cluster to forward, starting a timeout clock, wherein the forward ant messages carry identification information of active nodes and link total cost, and the link total cost is 0 at the beginning;
(2) when the forward ant message reaches the sensor node i, the sensor node i selects a neighbor node from neighbor nodes which are located in the same cluster and do not forward the forward ant message, as a next hop node, and continuously forwards the forward ant message:
Figure BDA0001724547350000041
in the formula, FiwRepresenting the probability that the sensor node i selects the w-th neighbor node as the next hop node; m isiThe number of neighbor nodes which are in the neighbor node set of the sensor node i, are positioned in the same cluster with the sensor node i and do not forward the forward ant message is not counted; l (i, w) is the pheromone concentration of a link from the sensor node i to the w-th neighbor node, and H (i, w) is the sensorDistance, Q, from node i to the w-th neighbor nodewIs the current residual energy, Q, of the w-th neighbor nodeminIs the set minimum energy value; gamma represents the gamma-th neighbor node which is located in the same cluster with the sensor node i and does not forward the forward ant message in the neighbor node set of the sensor node i, L (i, gamma) is the pheromone concentration of the link from the sensor node i to the gamma-th neighbor node, H (i, gamma) is the distance from the sensor node i to the gamma-th neighbor node, and Q (i, gamma) is the distance from the sensor node i to the gamma-th neighbor nodeγIs the current remaining energy of the gamma-th neighbor node; 11、12Is a set weight coefficient;
(3) if the sensor node j is the next hop node, adding the node identification information of the sensor node j into an address chain table of the forward ant message to indicate that the forward ant message has accessed the sensor node j, and updating the total link overhead carried by the forward ant message according to the following formula:
Vt＝Vt-1+H(i,j)×V
in the formula, VtRepresents the updated link overhead, Vt-1Representing the total link cost before updating, wherein V is a set unit distance link cost value; h (i, j) is the distance between the sensor node i and the sensor node j;
(4) continuously forwarding the forward ant message according to the steps (2) and (3) until the forward ant message is sent to any relay node; the relay node k starts a timeout clock when receiving a forward ant message generated by a source node alpha, does not receive the forward ant message generated by the source node alpha after the timeout clock is overtime, and only selects the forward ant message with the minimum link total cost to generate a corresponding backward ant message for all the forward ant messages generated by the source node alpha, and sends out the corresponding backward ant message along the reverse path of the forward ant message with the minimum link total cost, wherein the corresponding backward ant message carries the node identification information of the relay node k and the address linked list of the forward ant message with the minimum link total cost;
(5) when the sensor node i receives a backward ant message sent by the sensor node j, extracting node identification information of the sensor node j and relay node identification information carried by the backward ant message, storing the node identification information and the relay node identification information in the sensor node j locally, and updating the pheromone concentration of a link from the sensor node i to the sensor node j according to the following formula:
Figure BDA0001724547350000051
in the formula, L (i, j)' represents the pheromone concentration of the link from the sensor node i to the sensor node j after updating, L (i, j) is the pheromone concentration of the link from the sensor node i to the sensor node j before updating, the link pheromone concentration is 0 initially, tau is the volatility of the pheromone, and S is the total hop count of sending a backward ant message from the relay node to the corresponding source node; Δ L is a preset constant representing the total amount of pheromones released in one update;
(6) the current sensor node continuously forwards the backward ant message according to the information indicated by the address linked list of the backward ant message until the backward ant message reaches the source node;
(7) and (5) after the source node receives the backward ant messages generated by the two relay nodes, extracting and updating corresponding information according to the step (5), and storing the information locally.
In the embodiment, the link total cost of the path is used as an evaluation index of the optimal path, and the optimal path from the sensor node to each relay node in the cluster where the sensor node is located is determined based on an ant colony optimization algorithm, so that each source node has 2 optimal paths, wherein one optimal path leads to a first relay node in the cluster, and the other optimal path leads to a second relay node in the cluster; in the embodiment, a probability formula in the ant colony optimization algorithm is improved, and the distance of a link, the pheromone concentration and the residual energy of a next hop node are used as influence factors of the probability, so that the selection of the next hop node with too low energy by the sensor nodes is favorably limited, the energy consumption of each sensor node is balanced, and the path length is shortened.
In one embodiment, the sensor node selects one of the relay nodes as a destination node for receiving the wind turbine generator vibration data to be sent, and then sends out the wind turbine generator vibration data to be sent along an optimal path corresponding to the destination node, specifically:
(1) the sensor node a periodically calculates the optimal value of each optimal path, and the optimal path set of the sensor node a is set as
Figure BDA0001724547350000061
The optimal path from the sensor node a to the p-th relay node is represented, and the calculation formula of the set optimal value is as follows:
Figure BDA0001724547350000062
in the formula (I), the compound is shown in the specification,
Figure BDA0001724547350000063
representing an optimal path
Figure BDA0001724547350000064
The preferred value of (a) is,
Figure BDA0001724547350000065
for the optimal path
Figure BDA0001724547350000066
Available buffer size, U, of the next hop node up as sensor node aminCaching for a preset minimum;
Figure BDA0001724547350000067
for the optimal path
Figure BDA0001724547350000068
Link overhead of, VmaxPresetting maximum link total cost; x is the number of1、x2Is a set weight coefficient;
(2) the sensor node selects a relay node corresponding to the optimal path with the maximum current preferred value as a target node, and sends out the vibration data of the wind turbine generator to be sent along the optimal path with the maximum current preferred value.
Because the sensor node has two optimal paths to choose when sending the vibration data of the wind turbine to the corresponding cluster head, the embodiment further sets a selection mechanism of the optimal path, wherein a calculation formula of an optimal value of the optimal path is set according to the cache of the next hop node and the total cost of the link in the path. In this embodiment, the sensor node selects the relay node corresponding to the optimal path with the largest current preferred value as the destination node, and sends out the vibration data of the wind turbine generator to be sent along the optimal path with the largest current preferred value, which is favorable for balancing the cache of each next-hop node, balancing the load of each optimal path, and improving the reliability of the transmission of the vibration data of the wind turbine generator to a certain extent.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the protection scope of the present invention, although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims (6)

1. The intelligent real-time monitoring system for the vibration of the wind turbine generator is characterized by comprising a data acquisition module for acquiring the vibration data of the wind turbine generator, a storage module for storing the vibration data of the wind turbine generator and a display module for displaying the vibration data of the wind turbine generator; the data acquisition module and the display module are connected with the storage module; the data acquisition module comprises a sink node and a plurality of sensor nodes, the sink node and the sensor nodes construct a wireless sensor network with a clustering structure in a self-organizing manner, and the sensor nodes are clustered and a cluster head is selected according to a low-power-consumption self-adaptive clustering hierarchical protocol; the cluster head is mainly used for collecting the vibration data of the wind turbine generator collected by the sensor nodes in the cluster and sending the vibration data to the sink node; the sink node is mainly used for summarizing and sending the vibration data of the wind turbine generator set sent by each cluster head to the storage module; in a link construction stage of a wireless sensor network, selecting 2 sensor nodes in a communication range of a cluster head according to the positions of the sensor nodes and the current residual energy as relay nodes of the cluster head, and determining an optimal path from the sensor nodes to each relay node in the cluster; in the data sending stage, the sensor node selects one relay node as a target node for receiving the wind turbine generator vibration data to be sent, and then the wind turbine generator vibration data to be sent are sent out along an optimal path corresponding to the target node; the relay node receives the wind turbine generator vibration data sent by each sensor node, and sends the received wind turbine generator vibration data and the wind turbine generator vibration data collected by the relay node to the cluster head; the method for selecting 2 sensor nodes as the relay nodes of the cluster where the cluster head is located in the communication range of the cluster head according to the positions of the sensor nodes and the current residual energy comprises the following steps:
(1) for any cluster head eiDefine cluster head eiAll sensor nodes in the communication range are the cluster head eiThe neighbor node of (2) acquires a cluster head eiPosition information and current residual energy information of each neighbor node;
(2) calculating a first weight of each neighbor node according to the position information and the current residual energy information of the neighbor nodes:
Figure FDA0002825911000000011
in the formula, Cj 1Indicating cluster head eiH (e) of the jth neighbor nodeiJ) denotes a cluster head eiDistance between its jth neighbor node, H (e)iK) denotes a cluster head eiThe distance between its kth neighbor node,
Figure FDA0002825911000000012
indicating cluster head eiThe number of neighbor nodes of (2); qjIs the current residual energy, Q, of the jth neighbor nodeminIs a set minimum energy value;
(3) selecting the neighbor node with the maximum first weight as a cluster head eiThe second weights of the other neighbor nodes except the first relay node are calculated:
Figure FDA0002825911000000013
in the formula, Cρ 2Representing a second weight, C, of the p-th neighbor node except the first relay nodeρ 1Representing a first weight of the ρ -th neighbor node except the first relay node; e.g. of the typei 1Indicating a selected cluster head eiFirst relay node of H (e)i 1Rho) is the rho-th neighbor node and a first relay node ei 1The distance of (a) to (b),
Figure FDA0002825911000000014
for the rest of the neighbor nodes except the first relay node and ei 1The sum of the distances of (a);
(4) selecting the neighbor node with the largest second weight as a cluster head eiThe second relay node of (1).
2. The intelligent real-time monitoring system for the vibration of the wind turbine generator according to claim 1, wherein the sensor node comprises at least one sensor, the sensor node further comprises a signal adapter for converting a sensor signal into corresponding vibration data of the wind turbine generator, and the signal adapter is connected with the sensor.
3. The intelligent real-time vibration monitoring system for the wind turbine generator set according to claim 2, wherein the sensor node further comprises a controller for controlling the acquisition frequency, and the controller is connected with the sensor.
4. The intelligent real-time vibration monitoring system for the wind turbine generator set according to claim 1, wherein the display module comprises any one or more of a display screen, a smart phone, a notebook computer and a desktop computer.
5. The intelligent real-time vibration monitoring system for the wind turbine generator according to claim 2, wherein the sensor is a low-frequency vibration sensor or a high-frequency vibration sensor; the low-frequency vibration sensor is arranged on a blade of the wind turbine generator to acquire a blade vibration signal, or arranged on the main shaft to acquire a main shaft vibration signal, or arranged on a tower cylinder to acquire a tower cylinder vibration signal; the high-frequency vibration sensor is arranged on a gear box of the wind turbine generator to acquire a gear box vibration signal, or is arranged on the generator to acquire a generator vibration signal.
6. The intelligent real-time vibration monitoring system for the wind turbine generator according to claim 1, wherein the determining of the optimal path from the sensor node to each relay node in the cluster based on the ant colony optimization algorithm comprises:
(1) defining sensor nodes generating forward ant messages as source nodes, generating a set number of forward ant messages by the source nodes, selecting the nearest sensor nodes in a cluster to forward, starting a timeout clock, wherein the forward ant messages carry identification information of active nodes and link total cost, and the link total cost is 0 at the beginning;
(2) when the forward ant message reaches the sensor node i, the sensor node i selects a neighbor node from neighbor nodes which are located in the same cluster and do not forward the forward ant message, as a next hop node, and continuously forwards the forward ant message:
Figure FDA0002825911000000021
in the formula, FiwRepresenting the probability that the sensor node i selects the w-th neighbor node as the next hop node; m isiIs in the neighbor node set of the sensor node i, is positioned in the same cluster with the sensor node i and does not forward the forward ant reportThe number of neighbor nodes of the text; l (i, w) is the pheromone concentration of a link from the sensor node i to the w-th neighbor node, H (i, w) is the distance from the sensor node i to the w-th neighbor node, and QwIs the current residual energy, Q, of the w-th neighbor nodeminIs the set minimum energy value; gamma represents the gamma-th neighbor node which is located in the same cluster with the sensor node i and does not forward the forward ant message in the neighbor node set of the sensor node i, L (i, gamma) is the pheromone concentration of the link from the sensor node i to the gamma-th neighbor node, H (i, gamma) is the distance from the sensor node i to the gamma-th neighbor node, and Q (i, gamma) is the distance from the sensor node i to the gamma-th neighbor nodeγIs the current remaining energy of the gamma-th neighbor node; lambda [ alpha ]1、λ2Is a set weight coefficient;
(3) if the sensor node j is the next hop node, adding the node identification information of the sensor node j into an address chain table of the forward ant message to indicate that the forward ant message has visited the sensor node j, and updating the total link overhead carried by the forward ant message according to the following formula:
Vt＝Vt-1+H(i，j)×V
in the formula, VtRepresents the updated link overhead, Vt-1Representing the total link cost before updating, wherein V is a set unit distance link cost value; h (i, j) is the distance between the sensor node i and the sensor node j;
(4) continuously forwarding the forward ant message according to the steps (2) and (3) until the forward ant message is sent to any relay node; the relay node k starts a timeout clock when receiving a forward ant message generated by a source node alpha, does not receive the forward ant message generated by the source node alpha after the timeout clock is overtime, and only selects the forward ant message with the minimum link total cost to generate a corresponding backward ant message for all the forward ant messages generated by the source node alpha, and sends out the corresponding backward ant message along the reverse path of the forward ant message with the minimum link total cost, wherein the corresponding backward ant message carries the node identification information of the relay node k and the address linked list of the forward ant message with the minimum link total cost;
(5) when the sensor node i receives a backward ant message sent by the sensor node j, extracting node identification information of the sensor node j and relay node identification information carried by the backward ant message, storing the node identification information and the relay node identification information in the sensor node j locally, and updating the pheromone concentration of a link from the sensor node i to the sensor node j according to the following formula:
Figure FDA0002825911000000031
in the formula, L (i, j)' represents the pheromone concentration of the link from the sensor node i to the sensor node j after updating, L (i, j) is the pheromone concentration of the link from the sensor node i to the sensor node j before updating, the link pheromone concentration is 0 initially, tau is the volatility of the pheromone, and S is the total hop count of sending a backward ant message from the relay node to the corresponding source node; Δ L is a preset constant representing the total amount of pheromones released in one update;
(6) the current sensor node continuously forwards the backward ant message according to the information indicated by the address linked list of the backward ant message until the backward ant message reaches the source node;
(7) and (5) after the source node receives the backward ant messages generated by the two relay nodes, extracting and updating corresponding information according to the step (5), and storing the information locally.
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20130044044A (en) * 2011-10-21 2013-05-02 목포대학교산학협력단 Method of cluster-based routing supporting fault tolerance in vessel sensor networks
CN103260206A (en) * 2013-06-08 2013-08-21 南昌大学 Mixing dynamic wireless router effective search convergence method based on influence degree factors
CN105427566A (en) * 2015-12-09 2016-03-23 华南理工大学 Wind power plant remote real-time monitoring system and method based on wireless sensor network
CN107462289A (en) * 2017-09-30 2017-12-12 韦彩霞 A kind of water quality safety monitoring system

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20130044044A (en) * 2011-10-21 2013-05-02 목포대학교산학협력단 Method of cluster-based routing supporting fault tolerance in vessel sensor networks
CN103260206A (en) * 2013-06-08 2013-08-21 南昌大学 Mixing dynamic wireless router effective search convergence method based on influence degree factors
CN105427566A (en) * 2015-12-09 2016-03-23 华南理工大学 Wind power plant remote real-time monitoring system and method based on wireless sensor network
CN107462289A (en) * 2017-09-30 2017-12-12 韦彩霞 A kind of water quality safety monitoring system

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