A transformer operation and maintenance system based on the Internet of Things

Abstract

The present invention belongs to the field of transformer monitoring, and discloses a transformer operation and maintenance system based on the Internet of Things, including multiple wireless sensor nodes, an Internet of Things gateway, a cloud server and an operation and maintenance monitoring terminal; the wireless sensor node is used to collect real-time data of the environment, and is used to send the real-time data to the Internet of Things gateway when the real-time data is less than a preset threshold; the Internet of Things gateway is used to judge the correctness of the real-time data using preset rules, and remotely send the correct real-time data to the cloud server; the cloud server is used to judge whether the real-time data triggers an operation and maintenance monitoring event, and if so, sends an operation and maintenance message to the operation and maintenance monitoring terminal; the operation and maintenance monitoring terminal is used to provide operation and maintenance prompts based on the operation and maintenance information. The present invention can effectively detect the real-time data obtained when the wireless sensor node is subjected to sudden interference, which is less than the preset threshold, but is actually larger than the preset erroneous real-time data.

Description

Technical Field

[0001] The present invention relates to the field of transformer monitoring, and in particular to a transformer operation and maintenance system based on the Internet of Things. Background Art

[0002] In a large substation, there are usually a large number of transformers. In order to ensure the safe operation of the transformer, it is usually necessary to remotely monitor the environment where the transformer is located. Since the transformers are distributed relatively scattered in the substation, in order to avoid setting up too many lines to obtain data about the environment where the transformer is located, there is a solution in the prior art that uses wireless sensor nodes to collect real-time data of the environment. This solution disperses the wireless sensor nodes around the transformer and transmits real-time data by forming a wireless sensor network, so that the data about the environment where the transformer is located can be obtained without laying dedicated lines, and the collection location can be adjusted more flexibly.

[0003] However, the acquisition scheme in the prior art has such a disadvantage that in order to ensure the accuracy of the obtained real-time data of the environment, the real-time data obtained will be judged by a set threshold when it is wirelessly transmitted to the node for collection. When the real-time data is greater than the threshold, it will be judged as wrong data and discarded. If the threshold is set too small, it is easy to judge the correct data as wrong data, and if the threshold is set too large, it is difficult to filter the real-time data that is smaller than the threshold but is actually wrong and too large due to sudden interference. In this way, when the transformer is remotely operated and maintained, the environmental conditions of the transformer will be misjudged. Summary of the invention

[0004] The purpose of the present invention is to disclose a transformer operation and maintenance system based on the Internet of Things, so as to solve the problem of how to improve the accuracy of the obtained real-time data about the environment during the remote operation and maintenance of the transformer.

[0005] In order to achieve the above object, the present invention provides the following technical solutions:

[0006] The present invention provides a transformer operation and maintenance system based on the Internet of Things, comprising a plurality of wireless sensor nodes, an Internet of Things gateway, a cloud server and an operation and maintenance monitoring terminal;

[0007] Multiple wireless sensor nodes are dispersed around the transformer to collect real-time data of the environment and to detect when the real-time data is less than a preset threshold. When the real-time data is sent to the IoT gateway;

[0008] The IoT gateway is used to judge the correctness of real-time data using preset rules and send the correct real-time data remotely to the cloud server;

[0009] The cloud server is used to determine whether the real-time data triggers an operation and maintenance monitoring event. If so, it sends an operation and maintenance message to the operation and maintenance monitoring terminal;

[0010] The operation and maintenance monitoring terminal is used to provide operation and maintenance prompts based on operation and maintenance information;

[0011] The correctness of real-time data is judged by using preset rules, including:

[0012] The real-time data obtained by wireless sensor node b at collection time k is expressed as ;

[0013] Calculate the adaptive judgment distance ;

[0014] The distance between it and b is less than The set of wireless sensor nodes is represented as ;

[0015] Calculate the deviation ratio:

[0016] devfac = s b , k − [ λ × ∑ i ∈ U b madist − dist i , b ∑ i ∈ U b madist − dist i , b × s i , k + ( 1 − λ ) × ∑ i ∈ U b madif − | s b , k − s i , k | ∑ i ∈ U b madif − | s b , k − s i , k | × s i , k ] λ × ∑ i ∈ U b madist − dist i , b ∑ i ∈ U b madist − dist i , b × s i , k + ( 1 − λ ) × ∑ i ∈ U b madif − | s b , k − s i , k | ∑ i ∈ U b madif − | s b , k − s i , k | × s i , k

[0017] Indicates deviation from proportion, express The maximum distance between the wireless sensor node in and b, express The distance between wireless sensor nodes i and b in It means that i gets the same value as k at the acquisition time. The same type of real-time data, express The wireless sensor nodes in the The same type of real-time data as The maximum absolute value of the difference between represents the deviation judgment coefficient, ;

[0018] If the deviation ratio is greater than the set deviation ratio threshold , then it means It is wrong real-time data.

[0019] Preferably, the real-time data includes temperature, humidity and concentration of corrosive gases.

[0020] Preferably, the corrosive gas includes sulfur dioxide, hydrogen sulfide and ammonia.

[0021] Preferably, the IoT gateway is also used to control the state of the wireless sensor node based on a set control cycle;

[0022] In each control cycle, the state of the wireless sensor node is working state or sleeping state.

[0023] Preferably, controlling the state of the wireless sensor node based on a set control period includes:

[0024] A calculation cycle is set between two adjacent control cycles;

[0025] After the current control cycle ends, it enters the calculation cycle. In the calculation cycle, the IoT gateway determines the state of each wireless sensor node in the next control cycle, and then sends the state to the corresponding wireless sensor node;

[0026] When the calculation cycle is completed, it enters the next control cycle.

[0027] Preferably, respectively determining the state of each wireless sensor node in the next control cycle includes:

[0028] S1, obtain the set of wireless sensor nodes that were in sleep state in the previous control cycle ;

[0029] S2, respectively calculated The working coefficient of each wireless sensor node in;

[0030] S3, store the wireless sensor node with the largest working coefficient into the set , and move the wireless sensor node with the largest working coefficient from delete;

[0031] S4, Judgment Is the coverage ratio of the wireless sensor nodes in greater than the set coverage ratio threshold? If so, The wireless sensor nodes in are regarded as the wireless sensor nodes in working state in the next control cycle. If not, enter S2.

[0032] Preferably, the calculation formula of the working coefficient is:

[0033]

[0034] express The working coefficient of wireless sensor node j in is, Indicates the remaining power of j, Indicates the set power control value. represents j and The distance between the wireless sensor nodes k in represents j and The maximum distance between the wireless sensor nodes k in express The number of wireless sensor nodes in express The number of wireless sensor nodes that can communicate with j in a single hop; represents the number of wireless sensor nodes that can communicate with j in a single hop among all wireless sensor nodes, , , Respectively represent the set first coefficient, second coefficient and third coefficient.

[0035] Beneficial effects:

[0036] Compared with the prior art, in the process of remote operation and maintenance of transformers, in addition to judging whether the real-time data is correct when the wireless sensor node collects data, the present invention also judges the real-time data in the Internet of Things gateway, and uses the real-time data obtained by other wireless sensor nodes with the same collection time and the same type and whose distance from the wireless sensor node b is less than the adaptive distance as a reference to calculate the deviation ratio, so that when the value of the preset threshold of the wireless sensor node is too large, the real-time data obtained by the wireless sensor node when it is subjected to sudden interference, which is less than the preset threshold but is actually larger than the preset threshold, can be effectively detected. Thereby effectively ensuring the accuracy of the obtained real-time data. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0038] Figure 1 A schematic diagram of a transformer operation and maintenance system based on the Internet of Things of the present invention. DETAILED DESCRIPTION

[0039] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope parameters of the protection of the present invention.

[0040] like Figure 1 In one embodiment shown, the present invention provides a transformer operation and maintenance system based on the Internet of Things, including multiple wireless sensor nodes, an Internet of Things gateway, a cloud server and an operation and maintenance monitoring terminal;

[0041] Multiple wireless sensor nodes are dispersed around the transformer to collect real-time data of the environment and to detect when the real-time data is less than a preset threshold. When the real-time data is sent to the IoT gateway;

[0042] The IoT gateway is used to judge the correctness of real-time data using preset rules and send the correct real-time data remotely to the cloud server;

[0043] The cloud server is used to determine whether the real-time data triggers an operation and maintenance monitoring event. If so, it sends an operation and maintenance message to the operation and maintenance monitoring terminal;

[0044] The operation and maintenance monitoring terminal is used to provide operation and maintenance prompts based on operation and maintenance information;

[0045] The correctness of real-time data is judged by using preset rules, including:

[0046] The real-time data obtained by wireless sensor node b at collection time k is expressed as ;

[0047] Calculate the adaptive judgment distance ;

[0048] The distance between it and b is less than The set of wireless sensor nodes is represented as ;

[0049] Calculate the deviation ratio:

[0050] devfac = s b , k − [ λ × ∑ i ∈ U b madist − dist i , b ∑ i ∈ U b madist − dist i , b × s i , k + ( 1 − λ ) × ∑ i ∈ U b madif − | s b , k − s i , k | ∑ i ∈ U b madif − | s b , k − s i , k | × s i , k ] λ × ∑ i ∈ U b madist − dist i , b ∑ i ∈ U b madist − dist i , b × s i , k + ( 1 − λ ) × ∑ i ∈ U b madif − | s b , k − s i , k | ∑ i ∈ U b madif − | s b , k − s i , k | × s i , k

[0051] Indicates deviation from proportion, express The maximum distance between the wireless sensor node in and b, express The distance between wireless sensor nodes i and b in It means that i gets the same value as k at the acquisition time. The same type of real-time data, express The wireless sensor nodes in the The same type of real-time data as The maximum absolute value of the difference between represents the deviation judgment coefficient, ;

[0052] If the deviation ratio is greater than the set deviation ratio threshold , then it means It is wrong real-time data.

[0053] In the above operation and maintenance process, in addition to judging whether the real-time data is correct when the wireless sensor node collects, the real-time data is also judged in the Internet of Things gateway, and the deviation ratio is calculated by using the real-time data obtained by other wireless sensor nodes with the same collection time and the same type and whose distance from the wireless sensor node b is less than the adaptive distance as a reference, so that when the value of the preset threshold of the wireless sensor node is too large, the real-time data obtained by the wireless sensor node when it is subjected to sudden interference is less than the preset threshold, but is actually larger than the preset threshold. In this way, the accuracy of the obtained real-time data is effectively guaranteed.

[0054] When judging whether the real-time data is correct based on the real-time data obtained by other wireless sensor nodes as a reference, the present invention does not directly set a fixed numerical threshold, but sets a proportional threshold. The advantage of setting a proportional threshold is that the proportional threshold can be applied to the judgment process of different types of real-time data, avoiding the need to set too many numerical thresholds for the Internet of Things gateway, making the implementation of the present invention easier. When calculating the deviation ratio, it is mainly to and The comprehensive weighted value of the real-time data obtained by the wireless sensor nodes in the When the value of is larger than the comprehensive weighted value, it means The greater the probability of being erroneous real-time data, the more erroneous real-time data caused by sudden interference can be identified.

[0055] In the process of calculating the comprehensive weighted value, when the distance between i and b is smaller, the weight of the real-time data obtained by i is larger, and the reference degree of the real-time data obtained by i is higher; when the gap between the real-time data obtained by i and the real-time data obtained by b is smaller, the weight of the real-time data obtained by i is larger, and the reference degree of the real-time data obtained by i is higher. After obtaining the weighted value of a single direction from two aspects of the distance and the difference in numerical value, the present invention obtains the final weighted result based on the deviation judgment coefficient. Since more weighted factors are taken into account, the weighted result of the present invention is more accurate compared with the weighted method considering a single factor.

[0056] Preferably, the surrounding of the transformer refers to a square area of ​​a preset size centered on the transformer, and the transformer is located at the center of the square area.

[0057] For example, a square area with a preset side length of 10 meters.

[0058] Preferably, the deviation determination coefficient is 0.6.

[0059] Preferably, determining whether the real-time data triggers an operation and maintenance monitoring event includes:

[0060] If the real-time data exceeds the corresponding alarm threshold, it means that the real-time data triggers an operation and maintenance monitoring event.

[0061] Preferably, sending the operation and maintenance message to the operation and maintenance monitoring terminal includes:

[0062] Obtain the code of the transformer corresponding to the real-time data that triggers the operation and maintenance monitoring event;

[0063] The real-time data encoding and triggering the operation and maintenance monitoring event is filled into the corresponding position in the preset operation and maintenance message template, a new operation and maintenance message is generated, and the new operation and maintenance message is sent to the operation and maintenance monitoring terminal.

[0064] Preferably, providing operation and maintenance prompts based on the operation and maintenance information includes:

[0065] While displaying operation and maintenance information to personnel responsible for transformer operation and maintenance, a pre-set prompt audio is played.

[0066] Preferably, the calculation formula for the adaptive judgment distance is:

[0067]

[0068] Indicates that b gets In real-time data of the same type, the collection time is in the time interval [ k − T , k ] A collection of real-time data, T represents the set duration, express The number of real-time data in, v represents Real-time data in express The maximum value of real-time data in Indicates that b gets In real-time data of the same type, the collection time and The real-time data closest to the collection time, R represents the farthest communication distance of the wireless sensor node, Indicates the set data fluctuation weight, Represents the data trend weight.

[0069] The judgment distance of the present invention is not fixed, but can be changed with the The degree of difference in the data and and The advantage of the judgment distance obtained in this way is that when the data difference is greater and the real-time data shows an expanding trend, a larger adaptive judgment distance can be used, so that More wireless sensor nodes are included, and when calculating the deviation ratio, the calculation can be performed based on more reference data, so that the obtained result has a stronger reference, thereby obtaining a more accurate correctness judgment result.

[0070] Preferably, the data fluctuation weight is 0.7 and the data trend weight is 0.3.

[0071] Preferably, the set duration is 1 hour.

[0072] Preferably, the real-time data includes temperature, humidity and concentration of corrosive gases.

[0073] When the ambient temperature of the transformer is too high, the humidity is too high, or there is a high concentration of corrosive gas, it will affect the safe operation of the transformer. Therefore, by obtaining these real-time data, the personnel responsible for operation and maintenance can control the status of the transformer more promptly according to environmental abnormalities, thereby improving the safety of the transformer.

[0074] Preferably, the corrosive gas includes sulfur dioxide, hydrogen sulfide and ammonia.

[0075] Each type of real-time data has a corresponding preset threshold value. For example, when the real-time data is temperature, the preset threshold value is 60 degrees Celsius.

[0076] Preferably, the IoT gateway is also used to control the state of the wireless sensor node based on a set control cycle;

[0077] In each control cycle, the state of the wireless sensor node is working state or sleeping state.

[0078] In order to ensure coverage, wireless sensor nodes are generally redundant. Therefore, in each control cycle, the present invention only uses part of the wireless sensor nodes to obtain real-time data, thereby increasing the cycle of replacing batteries for the wireless sensor nodes and reducing the cost of operating and maintaining the transformer of the present invention.

[0079] Preferably, before the first control cycle starts, the IoT gateway performs the following calculations:

[0080] Obtain the union of the communication coverage areas of all wireless sensor nodes in the map to obtain area H;

[0081] The area H is divided into multiple local areas of the same area, and the area of ​​each local area is smaller than the communication coverage range of the wireless sensor node;

[0082] In each local area, a wireless sensor node is randomly selected as the node in working state in the first control cycle, and the remaining wireless sensor nodes are in dormant state in the first control cycle.

[0083] Preferably, controlling the state of the wireless sensor node based on a set control period includes:

[0084] A calculation cycle is set between two adjacent control cycles;

[0085] After the current control cycle ends, it enters the calculation cycle. In the calculation cycle, the IoT gateway determines the state of each wireless sensor node in the next control cycle, and then sends the state to the corresponding wireless sensor node;

[0086] When the calculation cycle is completed, it enters the next control cycle.

[0087] Preferably, respectively determining the state of each wireless sensor node in the next control cycle includes:

[0088] S1, obtain the set of wireless sensor nodes that were in sleep state in the previous control cycle ;

[0089] S2, respectively calculated The working coefficient of each wireless sensor node in;

[0090] S3, store the wireless sensor node with the largest working coefficient into the set , and move the wireless sensor node with the largest working coefficient from delete;

[0091] S4, Judgment Is the coverage ratio of the wireless sensor nodes in greater than the set coverage ratio threshold? If so, The wireless sensor nodes in are regarded as the wireless sensor nodes in working state in the next control cycle. If not, enter S2.

[0092] In the process of judging the state, the present invention does not directly use all the dormant wireless sensor nodes in the previous control cycle as the wireless sensor nodes in the working state in the next control cycle, but continuously selects the dormant wireless sensor nodes from the previous control cycle. The wireless sensor nodes in working state in the next control cycle are obtained, and when the coverage ratio meets the requirements, the acquisition is stopped. This acquisition method can use as few wireless sensor nodes as possible to achieve basic full coverage. It is conducive to further saving the power of wireless sensor nodes.

[0093] Preferably, The calculation process of the coverage ratio of the wireless sensor nodes in includes:

[0094] Get in map The union of the communication coverage areas of the wireless sensor nodes in is represented by the area of ​​the union as SN;

[0095] Calculate coverage ratio :

[0096]

[0097] It represents the area of ​​the union of the communication coverage of all wireless sensor nodes.

[0098] Preferably, the coverage ratio threshold is set to 0.95.

[0099] Preferably, the calculation formula of the working coefficient is:

[0100]

[0101] express The working coefficient of wireless sensor node j in is, Indicates the remaining power of j, Indicates the set power control value. represents j and The distance between the wireless sensor nodes k in represents j and The maximum distance between the wireless sensor nodes k in express The number of wireless sensor nodes in express The number of wireless sensor nodes that can communicate with j in a single hop; represents the number of wireless sensor nodes that can communicate with j in a single hop among all wireless sensor nodes, , , Respectively represent the first coefficient, second coefficient, and third coefficient that are set.

[0102] When j has more power left, and The farther the distance between the wireless sensor nodes k in the equation is, the more wireless sensor nodes that communicate with j in a single hop, and the larger the working coefficient is. The farther the distance between the wireless sensor nodes is, the better the final set The number of wireless sensor nodes is smaller, and the power of different wireless sensor nodes can be better evenly consumed while ensuring the coverage range.

[0103] Preferably, the first coefficient is 0.3, the second coefficient is 0.3, and the third coefficient is 0.4.

[0104] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0105] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0106] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0107] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope parameters of the technical solutions of the embodiments of the present invention.

Claims

1. A transformer operation and maintenance system based on the Internet of Things, characterized in that: Includes multiple wireless sensor nodes, IoT gateways, cloud servers, and operation and maintenance monitoring terminals; Multiple wireless sensor nodes are dispersed around the transformer to collect real-time data of the environment and to detect when the real-time data is less than a preset threshold. When the real-time data is sent to the IoT gateway; The IoT gateway is used to judge the correctness of real-time data using preset rules and send the correct real-time data remotely to the cloud server; The cloud server is used to determine whether the real-time data triggers an operation and maintenance monitoring event. If so, it sends an operation and maintenance message to the operation and maintenance monitoring terminal; The operation and maintenance monitoring terminal is used to provide operation and maintenance prompts based on operation and maintenance information; The correctness of real-time data is judged by using preset rules, including: The real-time data obtained by wireless sensor node b at collection time k is expressed as ; Calculate the adaptive judgment distance ; The distance between it and b is less than The set of wireless sensor nodes is represented as ; Calculate the deviation ratio: ; Indicates deviation from proportion, express The maximum distance between the wireless sensor node in and b, express The distance between wireless sensor nodes i and b in It means that i gets the same value as k at the acquisition time. The same type of real-time data, express The wireless sensor nodes in the The same type of real-time data as The maximum absolute value of the difference between represents the deviation judgment coefficient, ; If the deviation ratio is greater than the set deviation ratio threshold , then it means It is wrong real-time data.

2. The transformer operation and maintenance system based on the Internet of Things according to claim 1 is characterized in that: Real-time data includes temperature, humidity and concentration of corrosive gases.

3. The transformer operation and maintenance system based on the Internet of Things according to claim 2 is characterized in that: Corrosive gases include sulfur dioxide, hydrogen sulfide and ammonia.

4. The transformer operation and maintenance system based on the Internet of Things according to claim 1 is characterized in that: The IoT gateway is also used to control the status of wireless sensor nodes based on a set control cycle; In each control cycle, the state of the wireless sensor node is working state or sleeping state.

5. The transformer operation and maintenance system based on the Internet of Things according to claim 1 is characterized in that: The state of the wireless sensor node is controlled based on the set control cycle, including: A calculation cycle is set between two adjacent control cycles; After the current control cycle ends, it enters the calculation cycle. In the calculation cycle, the IoT gateway determines the state of each wireless sensor node in the next control cycle, and then sends the state to the corresponding wireless sensor node; When the calculation cycle is completed, it enters the next control cycle.

6. The transformer operation and maintenance system based on the Internet of Things according to claim 5 is characterized in that: The state of each wireless sensor node in the next control cycle is determined separately, including: S1, obtain the set of wireless sensor nodes that were in sleep state in the previous control cycle ; S2, respectively calculated The working coefficient of each wireless sensor node in; S3, store the wireless sensor node with the largest working coefficient into the set , and move the wireless sensor node with the largest working coefficient from delete; S4, Judgment Is the coverage ratio of the wireless sensor nodes in greater than the set coverage ratio threshold? If so, The wireless sensor nodes in are regarded as the wireless sensor nodes in working state in the next control cycle. If not, enter S2.

7. The transformer operation and maintenance system based on the Internet of Things according to claim 6 is characterized in that: The calculation formula of working coefficient is: ; express The working coefficient of wireless sensor node j in is, Indicates the remaining power of j, Indicates the set power control value. represents j and The distance between the wireless sensor nodes k in represents j and The maximum distance between the wireless sensor nodes k in express The number of wireless sensor nodes in express The number of wireless sensor nodes that can communicate with j in a single hop; represents the number of wireless sensor nodes that can communicate with j in a single hop among all wireless sensor nodes, , , Respectively represent the set first coefficient, second coefficient and third coefficient.

8. The transformer operation and maintenance system based on the Internet of Things according to claim 1 is characterized in that: The surrounding of the transformer refers to a square area of ​​a preset size centered on the transformer.

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