CN116560219B - Self-adaptive monitoring control method and system based on transmission tower wind speed joint analysis - Google Patents
Self-adaptive monitoring control method and system based on transmission tower wind speed joint analysis Download PDFInfo
- Publication number
- CN116560219B CN116560219B CN202310852734.1A CN202310852734A CN116560219B CN 116560219 B CN116560219 B CN 116560219B CN 202310852734 A CN202310852734 A CN 202310852734A CN 116560219 B CN116560219 B CN 116560219B
- Authority
- CN
- China
- Prior art keywords
- wind speed
- monitoring
- transmission
- transmission tower
- tower
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 230000005540 biological transmission Effects 0.000 title claims abstract description 194
- 238000012544 monitoring process Methods 0.000 title claims abstract description 125
- 238000000034 method Methods 0.000 title claims abstract description 45
- 238000013461 design Methods 0.000 claims abstract description 25
- 230000003044 adaptive effect Effects 0.000 claims description 13
- 230000008569 process Effects 0.000 claims description 13
- 230000008859 change Effects 0.000 claims description 12
- 238000012937 correction Methods 0.000 claims description 10
- 238000012545 processing Methods 0.000 claims description 4
- 238000005265 energy consumption Methods 0.000 description 3
- 230000002035 prolonged effect Effects 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 239000004576 sand Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/0205—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system
- G05B13/024—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system in which a parameter or coefficient is automatically adjusted to optimise the performance
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Computation (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Wind Motors (AREA)
Abstract
The application discloses a self-adaptive monitoring control method and a system based on transmission tower wind speed joint analysis, which relate to the technical field of transmission tower monitoring and have the technical scheme that: collecting a plurality of monitoring wind speed values of a transmission tower in a monitoring period in a target area to obtain a local wind speed sequence; carrying out global joint analysis according to the local wind speed sequences of all the transmission towers, and predicting to obtain a final wind speed predicted value of each transmission tower at the next moment; comparing the final wind speed predicted value with a wind speed design value of a corresponding transmission tower, and generating a monitoring control command for the transmission tower corresponding to the final wind speed predicted value exceeding the wind speed design value; responding to the monitoring control command and then controlling a monitoring component in the corresponding transmission tower to start; and acquiring monitoring values of the transmission tower in real time through the started monitoring assembly, and transmitting all the acquired monitoring values to the cloud platform for storage. The application realizes the self-adaptive accurate control of the sensors in each transmission tower.
Description
Technical Field
The application relates to the technical field of transmission tower monitoring, in particular to a self-adaptive monitoring control method and system based on transmission tower wind speed joint analysis.
Background
The transmission tower is higher due to the position of carrying the transmission line, and under severe natural environments such as typhoons, sand storm, storm and the like, the upper end of the transmission tower easily shakes by a large margin, and the transmission towers at the two ends of the transmission line are extremely easy to cause the transmission line to break in a large margin shaking process, and simultaneously the transmission towers are also easy to incline and deform. Therefore, the power transmission tower state monitoring is beneficial to timely unfolding and maintaining and timely emergency treatment for guaranteeing the safe operation of the power transmission tower.
In the prior art, the state monitoring of the transmission towers is realized by arranging various sensors on the transmission towers for real-time data acquisition, and for the whole power system or a certain designated area, the distribution number of the transmission towers is large, and each transmission tower is generally provided with a plurality of sensors, so that the number of the sensors in the coverage area of the power system in a certain range is large as a whole. The traditional transmission tower state monitoring operation is to start other sensors to monitor when a certain state reaches a design value or a threshold value, for example, when the wind speed value of the transmission tower reaches the design value, the sensors such as a vibration sensor, an inclination sensor, a pressure sensor and the like can be started to realize the transmission tower state monitoring. However, whether or not each sensor is activated in time in this manner depends on the magnitude of the design value or threshold; if the design value or the threshold value is smaller, the sensor of part of the transmission towers is easy to start by mistake; if the design value or the threshold value is larger, various monitoring values between the design value or the threshold value are easily lost; moreover, various design values or threshold values corresponding to the transmission towers at different positions are different, so that accurate starting of various sensors in the transmission towers is difficult to realize.
Therefore, how to research and design a self-adaptive monitoring control method and a system based on transmission tower wind speed joint analysis, which can overcome the defects, is a problem which needs to be solved at present.
Disclosure of Invention
In order to solve the defects in the prior art, the application aims to provide the self-adaptive monitoring control method and the system based on the wind speed joint analysis of the transmission towers, the wind speed values of the transmission towers are subjected to joint prediction analysis to obtain the different wind speed prediction conditions of the transmission towers, and the wind speed design values of the different transmission towers are combined to realize the self-adaptive accurate control of the sensors in the transmission towers, so that the operation energy consumption of the sensors in the state monitoring process of the transmission towers is reduced, the collected monitoring values can be higher in effective ratio, and the service life of the sensors is prolonged.
The technical aim of the application is realized by the following technical scheme:
in a first aspect, an adaptive monitoring control method based on transmission tower wind speed joint analysis is provided, including the following steps:
collecting a plurality of monitoring wind speed values of a transmission tower in a monitoring period in a target area to obtain a local wind speed sequence corresponding to the transmission tower one by one;
carrying out global joint analysis according to the local wind speed sequences of all the transmission towers, and predicting to obtain a final wind speed predicted value of each transmission tower at the next moment;
comparing the final wind speed predicted value with a wind speed design value of a corresponding transmission tower, and generating a monitoring control command for the transmission tower corresponding to the final wind speed predicted value exceeding the wind speed design value;
responding to the monitoring control command and then controlling a monitoring component in the corresponding transmission tower to start;
collecting monitoring values of the transmission tower in real time through the started monitoring assembly, and transmitting all the collected monitoring values to the cloud platform for storage;
the analysis process of the final wind speed predicted value specifically comprises the following steps:
analyzing the monitoring wind speed average value at the same moment in all local wind speed sequences to obtain a global wind speed sequence corresponding to the target area in the monitoring period;
analyzing a global wind speed predicted value of the global wind speed sequence at the next moment by adopting a curve fitting method;
the ratio of the wind speed values of the local wind speed sequence and the global wind speed sequence at the same moment is used as a relative factor for representing the relative change of the wind speed of the corresponding transmission tower at the corresponding moment, and a relative factor sequence of the transmission tower in a monitoring period is obtained;
analyzing relative predictors of the relative factor sequences at the next moment by adopting a curve fitting method, and determining relative parameters of the target area representing relative change of wind speed at the next moment by combining the relative predictors of all transmission towers;
correcting the global wind speed predicted value according to the relative parameters to obtain a global wind speed corrected value;
and solving according to the global wind speed correction value and the relative predictive factors of the transmission towers to obtain the final wind speed predictive values of the different transmission towers in the target area.
Further, the expression of the global wind speed sequence is specifically:
；
wherein ,representing the>Monitoring the wind speed average value corresponding to the moment; />Representing the number of transmission towers in the target area; />Indicate->The local wind speed sequence of the transmission towers is +.>Monitoring wind speed value corresponding to moment; />Representing the monitoring period.
Further, the expression of the global wind speed sequence is specifically:
；
wherein ,representing the>Monitoring the wind speed average value corresponding to the moment; />Representing the number of transmission towers in the target area; />Indicate->The local wind speed sequence of the transmission towers is +.>Monitoring wind speed value corresponding to moment; />Representing a monitoring period; />Indicate->The weight coefficient of each transmission tower is formed by +.>The distribution density of the transmission towers in the region where the transmission towers are located is determined, and the smaller the density is, the larger the weight coefficient is.
Further, the determining process of the distribution density specifically includes:
selecting a transmission tower as a central tower;
acquiring the number of areas of the transmission towers in the area with the center tower as the center and within a fixed radius range;
the distribution density of the center towers is determined by the ratio of the number of areas of the transmission towers to the area of the corresponding area.
Further, the determining process of the distribution density may further be:
selecting a transmission tower as a central tower;
selecting M transmission towers with the minimum distance from the central tower from the target area, and calculating the tower distance between the selected transmission towers and the central tower;
and determining the distribution density of the central tower according to the sum of the tower distances corresponding to M, wherein the distribution density and the sum of the tower distances are inversely related.
Further, the calculation formula of the relative parameter specifically includes:
；
wherein ,indicating the target area at the next moment +.>Is a relative parameter of (2); />Representing the number of transmission towers in the target area; />Indicate->And the relative prediction factors corresponding to the relative factor sequences of the transmission towers.
Further, the calculation formula of the global wind speed correction value specifically includes:
；
wherein ,representing a global wind speed correction value; />Indicating the target area at the next moment +.>Is a relative parameter of (2); />Representing the global wind speed sequence at the next moment +.>Is provided.
Further, the monitored values include one or more of vibration signal, inclination, temperature value, humidity value, voltage value, altitude value, and pressure value.
In a second aspect, an adaptive monitoring control system based on transmission tower wind speed joint analysis is provided, where the system is configured to implement the adaptive monitoring control method based on transmission tower wind speed joint analysis according to the first aspect, and the adaptive monitoring control method includes:
the wind speed acquisition module is used for acquiring a plurality of monitoring wind speed values of the transmission towers in the target area in a monitoring period to obtain local wind speed sequences corresponding to the transmission towers one by one;
the cloud server is used for carrying out overall joint analysis according to the local wind speed sequences of all the transmission towers, and predicting to obtain the final wind speed predicted value of each transmission tower at the next moment;
the logic processing module is used for comparing the final wind speed predicted value with a wind speed design value of a corresponding transmission tower and generating a monitoring control command for the transmission tower corresponding to the fact that the final wind speed predicted value exceeds the wind speed design value;
the controller module is used for responding to the monitoring control command and then controlling the monitoring assembly in the corresponding transmission tower to start;
and the real-time monitoring module is used for collecting monitoring values of the transmission tower in real time through the started monitoring assembly and transmitting all the collected monitoring values to the cloud platform for storage.
Compared with the prior art, the application has the following beneficial effects:
1. according to the self-adaptive monitoring control method based on the transmission tower wind speed joint analysis, the wind speed values of the transmission towers are subjected to joint prediction analysis to obtain the differential wind speed prediction conditions of the transmission towers, and the wind speed design values of the different transmission towers are combined to realize the self-adaptive accurate control of the sensors in the transmission towers, so that the running energy consumption of the sensors in the transmission tower state monitoring process is reduced, the collected monitoring values are higher in effective ratio, and the service life of the sensors is prolonged;
2. according to the method, the global wind speed conditions of the target area are predicted and analyzed, the local wind speed conditions of all the transmission towers are predicted and analyzed, and finally, the predicted global wind speed conditions are corrected by combining the local wind speed conditions of all the transmission towers, so that the differential prediction of different transmission towers in the whole wind field change process is realized under the condition that the wind speed prediction accuracy of the target area is ensured, and meanwhile, the wind speed prediction difficulty of the transmission towers is reduced;
3. according to the wind speed prediction method, the ratio of the wind speed values of the local wind speed sequence to the wind speed values of the global wind speed sequence at the same moment is used as the relative factor of the relative change of the wind speed of the corresponding transmission tower at the corresponding moment, and the prediction of the local wind speed condition is realized according to the relative factor, so that the condition that curve fitting prediction cannot be performed due to the fact that the wind speed difference at different positions changes along with the change of the whole wind field can be reduced, and the reliability of predicting and analyzing the local wind speed condition is enhanced;
4. in the calculation process of the monitored wind speed average value in the global wind speed sequence, the distribution sparseness condition of each transmission tower in the target area is considered, the influence of the local area wind speed change of no transmission tower on the calculation of the monitored wind speed average value is weakened, and the accuracy of the monitored wind speed average value is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of embodiments of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the principles of the application. In the drawings:
FIG. 1 is a flow chart in embodiment 1 of the present application;
fig. 2 is a system block diagram in embodiment 2 of the present application.
Detailed Description
For the purpose of making apparent the objects, technical solutions and advantages of the present application, the present application will be further described in detail with reference to the following examples and the accompanying drawings, wherein the exemplary embodiments of the present application and the descriptions thereof are for illustrating the present application only and are not to be construed as limiting the present application.
Example 1: the self-adaptive monitoring control method based on the transmission tower wind speed joint analysis, as shown in fig. 1, comprises the following steps:
step S1: collecting a plurality of monitoring wind speed values of a transmission tower in a monitoring period in a target area to obtain a local wind speed sequence corresponding to the transmission tower one by one;
step S2: carrying out global joint analysis according to the local wind speed sequences of all the transmission towers, and predicting to obtain a final wind speed predicted value of each transmission tower at the next moment;
step S3: comparing the final wind speed predicted value with a wind speed design value of a corresponding transmission tower, and generating a monitoring control command for the transmission tower corresponding to the final wind speed predicted value exceeding the wind speed design value;
step S4: responding to the monitoring control command and then controlling a monitoring component in the corresponding transmission tower to start;
step S5: and acquiring monitoring values of the transmission tower in real time through the started monitoring assembly, and transmitting all the acquired monitoring values to the cloud platform for storage.
In this embodiment, the wind speed value is not considered in the direction, and may be collected by a wind speed sensor, or may be collected by other sensors or instruments, and is generally installed at the top or middle of the transmission tower.
In addition, because the wind speed value does not have too much change in a short time, the data is collected in an interval sampling mode, and each transmission tower is kept to synchronously collect.
In this embodiment, the analysis process of the final wind speed predicted value specifically includes: analyzing the monitoring wind speed average value at the same moment in all local wind speed sequences to obtain a global wind speed sequence corresponding to the target area in the monitoring period; analyzing a global wind speed predicted value of the global wind speed sequence at the next moment by adopting a curve fitting method; the ratio of the wind speed values of the local wind speed sequence and the global wind speed sequence at the same moment is used as a relative factor for representing the relative change of the wind speed of the corresponding transmission tower at the corresponding moment, and a relative factor sequence of the transmission tower in a monitoring period is obtained; analyzing relative predictors of the relative factor sequences at the next moment by adopting a curve fitting method, and determining relative parameters of the target area representing relative change of wind speed at the next moment by combining the relative predictors of all transmission towers; correcting the global wind speed predicted value according to the relative parameters to obtain a global wind speed corrected value; and solving according to the global wind speed correction value and the relative predictive factors of the transmission towers to obtain the final wind speed predictive values of the different transmission towers in the target area.
As an alternative embodiment, the expression of the global wind speed sequence is specifically:
；
wherein ,representing the>Monitoring the wind speed average value corresponding to the moment; />Representing the number of transmission towers in the target area; />Indicate->The local wind speed sequence of the transmission towers is +.>Monitoring wind speed value corresponding to moment; />Representing the monitoring period.
Because the transmission tower data of partial areas in the target area are less, when the wind speed values of the areas are larger or smaller, the monitoring wind speed average value directly adopting average value calculation is difficult to accurately reflect the global wind speed.
To this end, as another alternative embodiment, the expression of the global wind speed sequence is specifically:
；
wherein ,representing the>Monitoring the wind speed average value corresponding to the moment; />Representing the number of transmission towers in the target area; />Indicate->The local wind speed sequence of the transmission towers is +.>Monitoring wind speed value corresponding to moment; />Representing a monitoring period; />Indicate->The weight coefficient of each transmission tower is formed by +.>The distribution density of the transmission towers in the region where the transmission towers are located is determined, and the smaller the density is, the larger the weight coefficient is.
The determining process of the density may be: selecting a transmission tower as a central tower; acquiring the number of areas of the transmission towers in the area with the center tower as the center and within a fixed radius range; the distribution density of the center towers is determined by the ratio of the number of areas of the transmission towers to the area of the corresponding area.
In addition, the determination process of the distribution density may be: selecting a transmission tower as a central tower; selecting M transmission towers with the minimum distance from the central tower from the target area, and calculating the tower distance between the selected transmission towers and the central tower; and determining the distribution density of the central tower according to the sum of the tower distances corresponding to M, wherein the distribution density and the sum of the tower distances are inversely related. When M transmission towers are selected, all transmission towers in the target area need to be sorted according to the distance between the transmission towers and the central tower, and then the first M transmission towers with the smallest distance are selected from the sorting results.
In the calculation process of the monitored wind speed average value in the global wind speed sequence, the distribution sparseness condition of each transmission tower in the target area is considered, the influence of the local area wind speed change of no transmission tower on the calculation of the monitored wind speed average value is weakened, and the accuracy of the monitored wind speed average value is improved.
It should be noted that, the curve fitting method in this embodiment may be a common least square method, or may be another curve trend prediction method, which is not limited herein.
The relative factors were calculated as follows: if the wind speed value at the time t in the local wind speed sequence corresponding to the transmission tower k is a, and the wind speed value at the time t in the global wind speed sequence is b, the relative factor of the transmission tower at the time t is a/b.
In this embodiment, the calculation formula of the relative parameter is specifically:
；
wherein ,indicating the target area at the next moment +.>Is a relative parameter of (2); />Representing the number of transmission towers in the target area; />Indicate->And the relative prediction factors corresponding to the relative factor sequences of the transmission towers.
The calculation formula of the global wind speed correction value is specifically as follows:
；
wherein ,representing a global wind speed correction value; />Indicating the target area at the next moment +.>Is a relative parameter of (2); />Representing the global wind speed sequence at the next moment +.>Is provided.
For example, the final wind speed prediction value of the transmission tower k can be obtained by multiplying the global wind speed correction value by the relative prediction factor of the transmission tower k.
In this embodiment, the monitored values include, but are not limited to, vibration signals, inclinations, temperature values, humidity values, voltage values, altitude values, and pressure values.
Example 2: the system is used for realizing the self-adaptive monitoring control method based on the transmission tower wind speed joint analysis, which is described in the embodiment 1, and comprises a wind speed acquisition module, a cloud server, a logic processing module, a controller module and a real-time monitoring module, as shown in fig. 2.
The wind speed acquisition module is used for acquiring a plurality of monitoring wind speed values of the transmission towers in the monitoring period in the target area to obtain local wind speed sequences corresponding to the transmission towers one by one; the cloud server is used for carrying out overall joint analysis according to the local wind speed sequences of all the transmission towers, and predicting to obtain the final wind speed predicted value of each transmission tower at the next moment; the logic processing module is used for comparing the final wind speed predicted value with a wind speed design value of a corresponding transmission tower and generating a monitoring control command for the transmission tower corresponding to the fact that the final wind speed predicted value exceeds the wind speed design value; the controller module is used for responding to the monitoring control command and then controlling the monitoring assembly in the corresponding transmission tower to start; and the real-time monitoring module is used for collecting monitoring values of the transmission tower in real time through the started monitoring assembly and transmitting all the collected monitoring values to the cloud platform for storage.
Working principle: according to the application, the wind speed values of the transmission towers are subjected to joint prediction analysis to obtain the differential wind speed prediction conditions of the transmission towers, and the wind speed design values of different transmission towers are combined to realize the self-adaptive accurate control of the sensors in the transmission towers, so that the running energy consumption of the sensors in the state monitoring process of the transmission towers is reduced, the collected monitoring values can be higher in effective ratio, and the service life of the sensors is prolonged.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the application, and is not meant to limit the scope of the application, but to limit the application to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the application are intended to be included within the scope of the application.
Claims (9)
1. The self-adaptive monitoring control method based on the transmission tower wind speed joint analysis is characterized by comprising the following steps of:
collecting a plurality of monitoring wind speed values of a transmission tower in a monitoring period in a target area to obtain a local wind speed sequence corresponding to the transmission tower one by one;
carrying out global joint analysis according to the local wind speed sequences of all the transmission towers, and predicting to obtain a final wind speed predicted value of each transmission tower at the next moment;
comparing the final wind speed predicted value with a wind speed design value of a corresponding transmission tower, and generating a monitoring control command for the transmission tower corresponding to the final wind speed predicted value exceeding the wind speed design value;
responding to the monitoring control command and then controlling a monitoring component in the corresponding transmission tower to start;
collecting monitoring values of the transmission tower in real time through the started monitoring assembly, and transmitting all the collected monitoring values to the cloud platform for storage;
the analysis process of the final wind speed predicted value specifically comprises the following steps:
analyzing the monitoring wind speed average value at the same moment in all local wind speed sequences to obtain a global wind speed sequence corresponding to the target area in the monitoring period;
analyzing a global wind speed predicted value of the global wind speed sequence at the next moment by adopting a curve fitting method;
the ratio of the wind speed values of the local wind speed sequence and the global wind speed sequence at the same moment is used as a relative factor for representing the relative change of the wind speed of the corresponding transmission tower at the corresponding moment, and a relative factor sequence of the transmission tower in a monitoring period is obtained;
analyzing relative predictors of the relative factor sequences at the next moment by adopting a curve fitting method, and determining relative parameters of the target area representing relative change of wind speed at the next moment by combining the relative predictors of all transmission towers;
correcting the global wind speed predicted value according to the relative parameters to obtain a global wind speed corrected value;
and solving according to the global wind speed correction value and the relative predictive factors of the transmission towers to obtain the final wind speed predictive values of the different transmission towers in the target area.
2. The adaptive monitoring control method based on transmission tower wind speed joint analysis according to claim 1, wherein the expression of the global wind speed sequence is specifically:
；
wherein ,representing the>Monitoring the wind speed average value corresponding to the moment; />Representing the number of transmission towers in the target area; />Indicate->The local wind speed sequence of the transmission towers is +.>Monitoring wind speed value corresponding to moment; />Representing the monitoring period.
3. The adaptive monitoring control method based on transmission tower wind speed joint analysis according to claim 1, wherein the expression of the global wind speed sequence is specifically:
；
wherein ,representing the>Monitoring the wind speed average value corresponding to the moment; />Representing the number of transmission towers in the target area; />Indicate->The local wind speed sequence of the transmission towers is +.>Monitoring wind speed value corresponding to moment; />Representing a monitoring period; />Indicate->The weight coefficient of each transmission tower is formed by +.>The distribution density of the transmission towers in the region where the transmission towers are located is determined, and the smaller the density is, the larger the weight coefficient is.
4. The adaptive monitoring control method based on transmission tower wind speed joint analysis according to claim 3, wherein the determining process of the distribution density specifically comprises the following steps:
selecting a transmission tower as a central tower;
acquiring the number of areas of the transmission towers in the area with the center tower as the center and within a fixed radius range;
the distribution density of the center towers is determined by the ratio of the number of areas of the transmission towers to the area of the corresponding area.
5. The adaptive monitoring control method based on transmission tower wind speed joint analysis according to claim 3, wherein the determining process of the distribution density specifically comprises the following steps:
selecting a transmission tower as a central tower;
selecting M transmission towers with the minimum distance from the central tower from the target area, and calculating the tower distance between the selected transmission towers and the central tower;
and determining the distribution density of the central tower according to the sum of the tower distances corresponding to M, wherein the distribution density and the sum of the tower distances are inversely related.
6. The adaptive monitoring control method based on transmission tower wind speed joint analysis according to claim 1, wherein the calculation formula of the relative parameters is specifically as follows:
；
wherein ,indicating the target area at the next moment +.>Is a relative parameter of (2); />Representing the number of transmission towers in the target area; />Indicate->And the relative prediction factors corresponding to the relative factor sequences of the transmission towers.
7. The adaptive monitoring control method based on transmission tower wind speed joint analysis according to claim 1, wherein the calculation formula of the global wind speed correction value is specifically as follows:
；
wherein ,representing a global wind speed correction value; />Indicating the target area at the next moment +.>Is a relative parameter of (2); />Representing the global wind speed sequence at the next moment +.>Is provided.
8. The transmission tower wind speed joint analysis-based adaptive monitoring control method according to claim 1, wherein the monitoring values include one or more of vibration signals, inclinations, temperature values, humidity values, voltage values, altitude values, and pressure values.
9. An adaptive monitoring control system based on transmission tower wind speed joint analysis, which is used for realizing the adaptive monitoring control method based on transmission tower wind speed joint analysis according to any one of claims 1-8, and is characterized by comprising the following steps:
the wind speed acquisition module is used for acquiring a plurality of monitoring wind speed values of the transmission towers in the target area in a monitoring period to obtain local wind speed sequences corresponding to the transmission towers one by one;
the cloud server is used for carrying out overall joint analysis according to the local wind speed sequences of all the transmission towers, and predicting to obtain the final wind speed predicted value of each transmission tower at the next moment;
the logic processing module is used for comparing the final wind speed predicted value with a wind speed design value of a corresponding transmission tower and generating a monitoring control command for the transmission tower corresponding to the fact that the final wind speed predicted value exceeds the wind speed design value;
the controller module is used for responding to the monitoring control command and then controlling the monitoring assembly in the corresponding transmission tower to start;
and the real-time monitoring module is used for collecting monitoring values of the transmission tower in real time through the started monitoring assembly and transmitting all the collected monitoring values to the cloud platform for storage.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310852734.1A CN116560219B (en) | 2023-07-12 | 2023-07-12 | Self-adaptive monitoring control method and system based on transmission tower wind speed joint analysis |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310852734.1A CN116560219B (en) | 2023-07-12 | 2023-07-12 | Self-adaptive monitoring control method and system based on transmission tower wind speed joint analysis |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116560219A CN116560219A (en) | 2023-08-08 |
| CN116560219B true CN116560219B (en) | 2023-09-08 |
Family
ID=87503978
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310852734.1A Active CN116560219B (en) | 2023-07-12 | 2023-07-12 | Self-adaptive monitoring control method and system based on transmission tower wind speed joint analysis |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116560219B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20150029160A (en) * | 2013-09-09 | 2015-03-18 | 한국전력공사 | Apparatus and method for realtime transmission capacity estimation using weather data and tgis data |
| CN105891537A (en) * | 2016-06-30 | 2016-08-24 | 广东电网有限责任公司电力科学研究院 | Wind speed monitoring method, device and system of pole towers of power transmission line |
| CN112507633A (en) * | 2020-12-03 | 2021-03-16 | 广东电网有限责任公司电力科学研究院 | Method and system for predicting and early warning wind speed of transmission tower |
| CN113191535A (en) * | 2021-04-14 | 2021-07-30 | 国网河南省电力公司电力科学研究院 | Design wind speed correction method in gale disaster early warning |
| CN114154812A (en) * | 2021-11-15 | 2022-03-08 | 广东电网有限责任公司 | Power transmission line wind speed monitoring method and device and storage medium |
| CN216206553U (en) * | 2021-07-13 | 2022-04-05 | 广西电网有限责任公司 | Transmission line shaft tower prevents typhoon on-line monitoring device based on 4G radio communication |
-
2023
- 2023-07-12 CN CN202310852734.1A patent/CN116560219B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20150029160A (en) * | 2013-09-09 | 2015-03-18 | 한국전력공사 | Apparatus and method for realtime transmission capacity estimation using weather data and tgis data |
| CN105891537A (en) * | 2016-06-30 | 2016-08-24 | 广东电网有限责任公司电力科学研究院 | Wind speed monitoring method, device and system of pole towers of power transmission line |
| CN112507633A (en) * | 2020-12-03 | 2021-03-16 | 广东电网有限责任公司电力科学研究院 | Method and system for predicting and early warning wind speed of transmission tower |
| CN113191535A (en) * | 2021-04-14 | 2021-07-30 | 国网河南省电力公司电力科学研究院 | Design wind speed correction method in gale disaster early warning |
| CN216206553U (en) * | 2021-07-13 | 2022-04-05 | 广西电网有限责任公司 | Transmission line shaft tower prevents typhoon on-line monitoring device based on 4G radio communication |
| CN114154812A (en) * | 2021-11-15 | 2022-03-08 | 广东电网有限责任公司 | Power transmission line wind speed monitoring method and device and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 基于风速时间周期特征的风电并网系统风险评估方法;付兵彬 等;《电力系统保护与控制》;第46卷(第19期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116560219A (en) | 2023-08-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105464912B (en) | A kind of method and apparatus of wind generator set blade icing detection | |
| CN115342814B (en) | Unmanned ship positioning method based on multi-sensor data fusion | |
| CN107869420B (en) | Method and system for controlling yaw of wind turbine farm | |
| CN113155196A (en) | Bridge operation real-time monitoring system based on AIoT and monitoring method thereof | |
| CN116560219B (en) | Self-adaptive monitoring control method and system based on transmission tower wind speed joint analysis | |
| US20220230023A1 (en) | Anomaly detection method, storage medium, and anomaly detection device | |
| CN113606099A (en) | Method and system for monitoring icing of blades of wind turbine generator | |
| CN117872328A (en) | Intelligent fault detection and wind measurement system for 3D laser wind measurement radar | |
| CN112305513A (en) | Sensor measurement parameter correction method and system | |
| CN115905997B (en) | Wind turbine generator meteorological disaster early warning method and system based on prediction deviation optimization | |
| CN111797545A (en) | Wind turbine generator yaw reduction coefficient calculation method based on measured data | |
| CN117708637A (en) | Wind turbine generator blade fault diagnosis method based on improved k-means clustering analysis | |
| CN117824588A (en) | Sampling optimization and early warning method for building safety monitoring inclination sensor | |
| CN113505345B (en) | Marine liquid level anomaly detection method and system and storage medium | |
| CN116306262A (en) | Galvanized steel corrosion prediction method based on ensemble learning algorithm | |
| CN114216440B (en) | Safety posture monitoring and early warning method and system for towering structure | |
| CN117093911A (en) | Bridge sliding support abrasion identification method based on longitudinal temperature-induced displacement amplitude monitoring of main beam | |
| CN115236772A (en) | Data quality control system and method for drifting observation instrument | |
| CN108825452B (en) | Method and device for determining blade icing of wind generating set | |
| CN117032016B (en) | Unmanned ship on-board sensor monitoring control method, system and equipment | |
| CN113138374B (en) | Laser radar wind field data reconstruction method and system | |
| CN118151676B (en) | Automatic cruising system and method for unmanned aerial vehicle remote sensing scene | |
| CN118425687B (en) | Power transmission cable fault monitoring method and system based on traveling wave characteristics | |
| CN118560298B (en) | Control method, device and system of electric balance car | |
| CN116564067B (en) | Highway state early warning system based on wisdom gathers materials technique |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |