CN115955491A - A thermal station operation monitoring system based on Internet of Things technology - Google Patents

Abstract

The invention belongs to the field of monitoring, and discloses a heating power station operation monitoring system based on the technology of the Internet of things, which comprises a wireless sensor node, a base station and a monitoring center, wherein the wireless sensor node is connected with the base station; the base station is used for periodically partitioning the monitoring range of the wireless sensor nodes to obtain partitioning results, clustering the wireless sensor nodes according to the partitioning results to obtain clustering results and sending the clustering results to the wireless sensor nodes; the wireless sensor nodes are used for forming a transmission network according to the clustering result; the wireless sensor node is used for acquiring state data of the heating station and sending the state data to the base station through the transmission network; the base station is also used for sending the state data to the monitoring center. The heat station detection system of the invention transmits various state data in the heat station by forming the wireless sensor nodes into a transmission network through the base station, thereby greatly expanding the monitoring range which can be covered by a single base station and effectively saving the monitoring cost.

Description

A thermal station operation monitoring system based on Internet of Things technology

technical field

The invention relates to the field of monitoring, in particular to a thermal station operation monitoring system based on Internet of Things technology.

Background technique

The heating station of a district heating system is the connection point between the heating network and the heat consumers. It is used to adjust and convert the heat medium conveyed by the heat network according to the working conditions and different conditions of the heat network, distribute the heat to heat users to meet the needs of users, and perform centralized metering and detection of the parameters of the heat medium for heating according to the needs and quantity.

In the prior art, in order to realize the monitoring of the thermal station, various types of sensors are generally used to obtain data of various aspects of the thermal station, and then the data are transmitted to the monitoring center to realize the operation monitoring of the thermal station.

However, in the existing thermal station operation monitoring system, such as the patent with the publication number CN108388210A, the sensor generally communicates directly with the base station (i.e. the primary data processor in the patent) in the process of data transmission, which makes In the existing thermal station operation monitoring system, the monitoring range covered by a single base station is not large enough, and multiple base stations need to be installed, resulting in increased monitoring costs.

Contents of the invention

The purpose of the present invention is to disclose a thermal station operation monitoring system based on Internet of Things technology, to solve the problem that in the existing thermal station operation monitoring system, the monitoring range covered by a single base station is not large enough, and multiple base stations need to be set up, resulting in increased monitoring costs The problem.

In order to achieve the above object, the present invention adopts following technical scheme:

A thermal station operation monitoring system based on Internet of Things technology, including wireless sensor nodes, base stations and monitoring centers;

The base station is used to periodically partition the monitoring range of the wireless sensor nodes, obtain the partition results, and cluster the wireless sensor nodes according to the partition results, obtain the clustering results, and send the clustering results to the wireless sensor nodes;

Wireless sensor nodes are used to form a transmission network according to the clustering results;

The wireless sensor nodes are used to obtain the status data of the thermal station, and send the status data to the base station through the transmission network;

The base station is also used to send status data to the monitoring center.

Optionally, the periodically partitioning the monitoring range of the wireless sensor node includes:

The monitoring range of wireless sensor nodes is partitioned according to the attribute information of wireless sensor nodes.

Optionally, the attribute information includes remaining energy and communication radius.

Optionally, the partitioning of the monitoring range of the wireless sensor nodes according to the attribute information of the wireless sensor nodes includes:

Get the number N of adaptive partitions;

Taking N as the number of classifications, the classification algorithm is used to calculate the wireless sensor nodes, and the classification results are obtained, and the wireless sensor nodes belonging to the same classification are divided into the same area.

Optionally, the wireless sensor nodes are calculated by using a classification algorithm to obtain a classification result, including:

S1, randomly select N wireless sensor nodes as classification centers;

S2, calculate the distance between other wireless sensor nodes and each classification center except as the classification center;

S3, obtaining the minimum distance corresponding to each wireless sensor node;

S4, dividing the wireless sensor nodes into the classification of the classification center corresponding to the smallest distance;

S5, respectively calculate the average classification coordinates of the wireless sensor nodes in each classification, and use the wireless sensor node closest to the average classification coordinates as a new classification center;

S6, judging whether the distance between the new classification center obtained in S5 and the classification center in S2 is less than the set distance threshold, if yes, then output the classification obtained in S4, if not, then enter S2.

Optionally, the S2 includes:

For wireless sensor node A, the calculation function of the distance between wireless sensor node A and the nth classification center is:

Among them, dist(A,n) represents the distance between the wireless sensor node A and the nth classification center; x _A and y _A represent the abscissa and ordinate of the wireless sensor node A respectively, and x _n and y _n represent the The abscissa and ordinate of n classification centers; n∈[1,N].

Optionally, the S5 includes:

For the nth category, the calculation function of the average category coordinates is:

Among them, x _ave,n represents the abscissa of the average category coordinates, y _ave,n represents the ordinate of the average category coordinates, set _n represents the set of all wireless sensor nodes in the nth category, x _i and y _i respectively represent the set The abscissa and ordinate of the wireless sensor node i in _n ; numset _n represents the number of wireless sensor nodes in the nth category, n∈[1,N].

Optionally, the S6 includes:

Store the new classification center obtained in S5 into the collection set _S5 , and store the classification center in S2 into the collection set _S2 ;

For the classification center clsf _S5 in the set _S5 , obtain the classification center clsf _S3 closest to clsf _S5 in the set _S2 , and form a matching pair with clsf _S5 and clsf _S3 ;

If the distance between each matching pair is less than the set distance threshold, then output the classification obtained in S4, otherwise, go to S2.

In the thermal station detection system of the present invention, in the process of using wireless sensor nodes and base stations to monitor the thermal station, the wireless sensor nodes are formed into a transmission network through the base station to transmit various state data in the thermal station, thereby greatly expanding The monitoring range that a single base station can cover can effectively save the monitoring cost.

Description of drawings

The present invention is further described by using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. For those of ordinary skill in the art, without paying creative work, other embodiments can also be obtained according to the following accompanying drawings Attached picture.

Fig. 1 is a diagram of an embodiment of a heating station operation monitoring system based on the Internet of Things technology according to the present invention.

FIG. 2 is a diagram of an embodiment of the present invention using a classification algorithm to calculate wireless sensor nodes and obtain classification results.

Detailed ways

Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

An embodiment as shown in Figure 1, the present invention provides a thermal station operation monitoring system based on Internet of Things technology, including wireless sensor nodes, base stations and monitoring centers;

The base station is used to periodically partition the monitoring range of the wireless sensor nodes, obtain the partition results, and cluster the wireless sensor nodes according to the partition results, obtain the clustering results, and send the clustering results to the wireless sensor nodes;

Wireless sensor nodes are used to form a transmission network according to the clustering results;

The wireless sensor nodes are used to obtain the status data of the thermal station, and send the status data to the base station through the transmission network;

The base station is also used to send status data to the monitoring center.

As a prior art patent with the publication number CN108388210A, in the process of transmitting the collected information obtained by the sensor, each sensor needs to be connected to the primary data processor through the Internet of Things communication module. Obviously, such a connection method will limit a single primary data processor. If the detection range covered by the data processor needs to be improved, it can only be achieved by means of wired communication or increasing the transmission power of the communication module of the Internet of Things. However, setting up a large number of communication lines will bring great pressure to later maintenance, and the price of communication cables is not cheap, and if the transmission power of the IoT communication module is increased, the probability of communication conflicts will be greatly increased. The communication delay between the sensor and the primary data processor is greatly increased, and the probability of data packet loss will also increase, which is not conducive to effective monitoring of the thermal power station.

In the thermal station detection system of the present invention, in the process of using wireless sensor nodes and base stations to monitor the thermal station, the wireless sensor nodes are formed into a transmission network through the base station to transmit various state data in the thermal station, thereby greatly expanding The monitoring range that a single base station can cover can effectively save the monitoring cost.

Optionally, the wireless sensor node may include a wireless noise sensor, a wireless vibration sensor, a wireless temperature and humidity sensor, a wireless smoke sensor, and the like.

Optionally, the status data may include one or more of operating noise, vibration frequency, temperature, humidity of the equipment in the thermal power station, and smoke content in the operating environment of the thermal power station.

Optionally, the periodically partitioning the monitoring range of the wireless sensor node includes:

The monitoring range of wireless sensor nodes is partitioned according to the attribute information of wireless sensor nodes.

The base station partitions the monitoring range of the wireless sensor nodes through a fixed period. After partitioning, you can re-cluster according to the partition results.

Optionally, the attribute information includes remaining energy and communication radius.

Optionally, the partitioning of the monitoring range of the wireless sensor nodes according to the attribute information of the wireless sensor nodes includes:

Get the number N of adaptive partitions;

Taking N as the number of classifications, the classification algorithm is used to calculate the wireless sensor nodes, and the classification results are obtained, and the wireless sensor nodes belonging to the same classification are divided into the same area.

The partition result is the number of wireless sensor nodes contained in each area.

In the present invention, the number of partitions is adaptive and associated with the current state of the wireless sensor node, thereby obtaining a more reasonable number of partitions.

Optionally, obtain the number N of adaptive partitions, including:

Calculate the number of adaptive partitions using the following function:

Among them, N represents the number of adaptive partitions, bsnum represents the benchmark value of the partition number, wsnset represents the set of wireless sensor nodes, nwsnset represents the total number of wireless sensor nodes contained in wsnset, enrlft _k represents the remaining energy of wireless sensor node k, enrfc represents Remaining energy contrast value, currad _k represents the communication radius of wireless sensor node k, curradst represents the average communication radius contrast value, λ ₁ , λ ₂ represent weight parameters.

In the present invention, the number of adaptive partitions is related to the residual energy and communication radius of wireless sensor nodes, the greater the difference in residual energy between wireless sensor nodes, the smaller the average communication radius of wireless sensor nodes, and the smaller the number of adaptive partitions More, the smaller the difference of residual energy between wireless sensor nodes, the larger the average communication radius of wireless sensor nodes, and the smaller the number of adaptive partitions. The greater the difference in the remaining energy, the more unbalanced the energy distribution, some wireless sensor nodes have more remaining energy, and some wireless sensor nodes have too little remaining energy, which will affect the average monitoring time of wireless sensor nodes. Therefore, the present invention increases The number of partitions is used to balance the energy distribution. When the average communication radius is larger, it reflects the communication capability of wireless sensor nodes from another aspect. The larger the communication capability, the communication can be carried out with greater communication power. To comprehensively calculate the number of adaptive partitions, which improves the rationality of the obtained number of partitions.

Optionally, as shown in Figure 2, the wireless sensor nodes are calculated using a classification algorithm to obtain a classification result, including:

S1, randomly select N wireless sensor nodes as classification centers;

S2, calculate the distance between other wireless sensor nodes and each classification center except as the classification center;

S3, obtaining the minimum distance corresponding to each wireless sensor node;

S4, dividing the wireless sensor nodes into the classification of the classification center corresponding to the smallest distance;

S5, respectively calculate the average classification coordinates of the wireless sensor nodes in each classification, and use the wireless sensor node closest to the average classification coordinates as a new classification center;

S6, judging whether the distance between the new classification center obtained in S5 and the classification center in S2 is less than the set distance threshold, if yes, then output the classification obtained in S4, if not, then enter S2.

In the present invention, the method of cyclic calculation is used to classify. When the result of the classification varies very little, that is, whether the distance in S6 is less than the set distance threshold, the classification is stopped and the result of the classification is output, otherwise , then continue to calculate cyclically according to the newly selected classification center. By setting the distance threshold, the present invention does not need to wait until the wireless sensor nodes used as the classification center obtained by the two calculations are completely consistent before outputting the classification result. Because in the present invention, the classification is carried out based on sparsely distributed wireless sensor nodes, the center of classification is not necessarily just on the wireless sensor nodes, therefore, if the output classification results are selected to be completely consistent, it may fall into a local cycle, Can not get the result, therefore, the setting of the present invention can guarantee to obtain the classification result smoothly.

Optionally, the S2 includes:

For wireless sensor node A, the calculation function of the distance between wireless sensor node A and the nth classification center is:

Among them, dist(A,n) represents the distance between the wireless sensor node A and the nth classification center; x _A and y _A represent the abscissa and ordinate of the wireless sensor node A respectively, and x _n and y _n represent the The abscissa and ordinate of n classification centers; n∈[1,N].

Optionally, the S5 includes:

For the nth category, the calculation function of the average category coordinates is:

Among them, x _ave,n represents the abscissa of the average category coordinates, y _ave,n represents the ordinate of the average category coordinates, set _n represents the set of all wireless sensor nodes in the nth category, x _i and y _i respectively represent the set The abscissa and ordinate of the wireless sensor node i in _n ; numset _n represents the number of wireless sensor nodes in the nth category, n∈[1,N].

Optionally, the S6 includes:

Store the new classification center obtained in S5 into the collection set _S5 , and store the classification center in S2 into the collection set _S2 ;

For the classification center clsf _S5 in the set _S5 , obtain the classification center clsf _S3 closest to clsf _S5 in the set _S2 , and form a matching pair with clsf _S5 and clsf _S3 ;

If the distance between each matching pair is less than the set distance threshold, then output the classification obtained in S4, otherwise, go to S2.

In the present invention, classification is completed only when each matching pair meets the requirements.

Optionally, the wireless sensor nodes are clustered according to the partition results to obtain the cluster results, including:

For a partition, use the following function to update the communication radius of the wireless sensor nodes in the partition:

Among them, currad _partition represents the updated communication radius of the wireless sensor nodes in the partition, bascur represents the set reference communication radius, wsnnum _{par titition} represents the number of wireless sensor nodes in the partition, area _{par tition} represents the wireless sensor nodes in the partition The size of the monitoring range of the sensor node, densta represents the set distribution density reference value, aveenr represents the average value of the remaining energy of the wireless sensor nodes in the partition, and fulenr represents the average value of the initial energy of the wireless sensor nodes;

Calculate the number of cluster head nodes according to the updated communication radius:

Among them, numclst _partition represents the number of cluster head nodes in the partition, Φ represents the adjustment coefficient, Φ>1.1;

Use the HEED algorithm to calculate the initial probability of each wireless sensor node in the partition becoming a cluster head, and use the first numclst _partition wireless sensor nodes with the largest initial probability as the cluster head node in the partition, and use the rest of the wireless sensor nodes in the partition as members Nodes are added to the cluster where the cluster head node is located according to the principle of the smallest distance;

The number of the cluster head node, the number of member nodes and the updated communication radius of each cluster are taken as the clustering result.

In the present invention, after each clustering, the communication radius of the member nodes will be recalculated, so as to achieve the purpose of prolonging the average monitoring time of the wireless sensor nodes. In densely distributed places, the communication radius of wireless sensor nodes will be set smaller, and within a specified range, the smaller the average value of the remaining energy of wireless sensor nodes, the smaller the communication radius will be set. The calculation of the number of cluster head nodes is calculated by the updated communication radius. The smaller the updated communication radius and the larger the monitoring range, the greater the number of cluster head nodes, so that the cluster head The number of nodes changes adaptively with the updated communication radius.

Optionally, a transmission network is formed according to the clustering results, including:

After the wireless sensor node receives the clustering result, it determines whether it belongs to the cluster head node or a member node according to its own number, and then the member node communicates with the cluster head node or member node according to the transmission power corresponding to the updated communication radius contained in the clustering result. The cluster head node communicates, and the cluster head node is not limited by the updated communication radius. The cluster head node communicates with the base station to form a hierarchical transmission network.

The communication between the cluster head node and the base station can be carried out in a single-hop or multi-hop manner. The single hop communicates directly with the base station, and the hop communicates with the base station through the relay of other cluster head nodes.

Optionally, the status data is sent to the base station through the transmission network, including:

After the member nodes obtain the state data, they send the state data to the corresponding cluster head node, and then the cluster head node forwards the state data to the base station.

Optionally, the monitoring center includes a storage module and a monitoring module;

The storage module is used to store the state data sent by the base station;

The monitoring module is used to judge whether the status data exceeds the set size range, and if it exceeds, an alarm will be sent to the staff of the monitoring center.

The present invention has been exemplarily described above, and it is obvious that the specific implementation of the present invention is not limited by the above methods.

As long as the various improvements made by adopting the method concept and technical scheme of the present invention, or directly applied to other occasions without improvement, are all within the protection scope of the present invention.

Claims (8)

1. A heating station operation monitoring system based on the Internet of Things technology, characterized in that it includes a wireless sensor node, a base station and a monitoring center; The base station is used to periodically partition the monitoring range of the wireless sensor nodes, obtain the partition results, and cluster the wireless sensor nodes according to the partition results, obtain the clustering results, and send the clustering results to the wireless sensor nodes; Wireless sensor nodes are used to form a transmission network according to the clustering results; The wireless sensor nodes are used to obtain the status data of the thermal station, and send the status data to the base station through the transmission network; The base station is also used to send status data to the monitoring center. 2. A kind of heating station operation monitoring system based on Internet of Things technology according to claim 1, is characterized in that, described periodical is carried out partition to the monitoring scope of wireless sensor node, comprises: The monitoring range of wireless sensor nodes is partitioned according to the attribute information of wireless sensor nodes. 3. A thermal station operation monitoring system based on the Internet of Things technology according to claim 2, wherein the attribute information includes remaining energy and communication radius. 4. A kind of thermal substation operation monitoring system based on Internet of Things technology according to claim 3, is characterized in that, described according to the attribute information of wireless sensor node, the monitoring range of wireless sensor node is partitioned, comprising: Get the number N of adaptive partitions; Taking N as the number of classifications, the classification algorithm is used to calculate the wireless sensor nodes, and the classification results are obtained, and the wireless sensor nodes belonging to the same classification are divided into the same area. 5. A kind of heating station operation monitoring system based on Internet of Things technology according to claim 4, is characterized in that, described adopting classification algorithm to calculate wireless sensor node, obtain classification result, comprise: S1, randomly select N wireless sensor nodes as classification centers; S2, calculate the distance between other wireless sensor nodes and each classification center except as the classification center; S3, obtaining the minimum distance corresponding to each wireless sensor node; S4, dividing the wireless sensor nodes into the classification of the classification center corresponding to the smallest distance; S5, respectively calculate the average classification coordinates of the wireless sensor nodes in each classification, and use the wireless sensor node closest to the average classification coordinates as a new classification center; S6, judging whether the distance between the new classification center obtained in S5 and the classification center in S2 is less than the set distance threshold, if yes, then output the classification obtained in S4, if not, then enter S2. 6. A thermal station operation monitoring system based on the Internet of Things technology according to claim 5, wherein said S2 includes: For wireless sensor node A, the calculation function of the distance between wireless sensor node A and the nth classification center is:

Among them, dist(A,n) represents the distance between the wireless sensor node A and the nth classification center; x _A and y _A represent the abscissa and ordinate of the wireless sensor node A respectively, and x _n and y _n represent the The abscissa and ordinate of n classification centers; n∈[1,N]. 7. A thermal station operation monitoring system based on Internet of Things technology according to claim 5, characterized in that, said S5 includes: For the nth category, the calculation function of the average category coordinates is:

Among them, x _ave,n represents the abscissa of the average category coordinates, y _ave,n represents the ordinate of the average category coordinates, set _n represents the set of all wireless sensor nodes in the nth category, x _i and y _i respectively represent the set The abscissa and ordinate of the wireless sensor node i in _n ; numset _n represents the number of wireless sensor nodes in the nth category, n∈[1,N]. 8. A thermal station operation monitoring system based on the Internet of Things technology according to claim 5, wherein said S6 includes: Store the new classification center obtained in S5 into the collection set _S5 , and store the classification center in S2 into the collection set _S2 ; For the classification center clsf _S5 in the set _S5 , obtain the classification center clsf _S3 closest to clsf _S5 in the set _S2 , and form a matching pair with clsf _S5 and clsf _S3 ; If the distance between each matching pair is less than the set distance threshold, then output the classification obtained in S4, otherwise, go to S2.

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