Power transmission line object detection alarm system using state analysis
By using intelligent analysis of visual data based on contrast-preserving images and employing a BP neural network model, the problem of high-precision detection of white pollution on power transmission lines was solved, enabling intelligent detection and alarm of white pollution and improving the safety and stability of the power system.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NANJING FANGETING ELECTRIC POWER TECH CO LTD
- Filing Date
- 2024-01-10
- Publication Date
- 2026-04-17
AI Technical Summary
The lack of high-precision detection and alarm schemes for icing and litter detection on transmission lines in existing technologies threatens the safe and stable operation of the power system and the reliability of power supply.
The system employs intelligent visual data analysis based on contrast-preserving images, utilizing a BP neural network model, combined with state analysis devices, environmental monitoring devices, smoothing spatial filtering equipment, bilateral filtering equipment, and data analysis mechanisms to achieve intelligent detection and alarm for white pollution.
It achieves high-precision detection and alarm for white pollution, reduces system power consumption, and can promptly send alarm signals to a remote management server for fault location and judgment.
Smart Images
Figure HDA0004657645980000011 
Figure HDA0004657645980000012 
Figure HDA0004657645980000021
Abstract
Description
Technical Field
[0001] This invention relates to the field of power transmission line detection and alarm, and more particularly to a power transmission line object detection and alarm system that utilizes state analysis. Background Technology
[0002] Transmission lines operate in complex external environments, requiring various targeted monitoring measures to ensure transmission safety. For example, icing detection and early warning are crucial. In cold, rainy, or snowy weather, high humidity causes large amounts of water vapor to condense on the conductor surface, leading to icing and potential freezing disasters in the power system. Icing can cause tension imbalances on both sides of the pole, resulting in conductor breakage and impact loads that can cause pole collapse. Iced wires contract in cold temperatures, and wind-induced vibrations can sometimes cause them to break under the weight. Even prolonged galloping can cause fatigue damage to conductors, towers, insulators, and hardware due to unbalanced impacts. Pole collapse, wire breakage, and power outages caused by icing and galloping can severely damage power transmission lines and threaten the safe and stable operation of the power grid and the reliability of the power supply system.
[0003] In addition, power transmission lines also require detection and early warning systems for litter, such as garbage bags, which can easily cause phase-to-phase or phase-to-ground short circuits when entangled in power lines. Therefore, it is necessary to detect and alarm on the presence of litter on power transmission lines. However, there is currently no corresponding high-precision detection and alarm solution in the existing technology. Summary of the Invention
[0004] This invention provides a transmission line object detection alarm system utilizing state analysis. Based on targeted visual data processing, it employs a specially designed artificial intelligence model to intelligently analyze various visual data from contrast-preserved images to identify white pollution presence markers. These white pollution presence markers indicate the presence of white pollution in the contrast-preserved image. The number of times the model learns is positively correlated with the number of pixels in the contrast-preserved image. When the white pollution presence markers intelligently analyzed by the artificial intelligence model indicate the presence of white pollution in the contrast-preserved image, a white pollution alarm signal is wirelessly transmitted to a remote management server, thereby completing the fault location and judgment at the accident site and solving technical problems in related fields.
[0005] Specifically, according to the present invention, the system includes:
[0006] A status analysis device, connected to a target transmission line, is used to issue a monitoring request signal when a phase-to-phase short circuit or a phase-to-ground short circuit is detected in the target transmission line, and to issue a stop monitoring signal when no phase-to-phase short circuit or a phase-to-ground short circuit is detected in the target transmission line.
[0007] An environmental monitoring device, connected to the state analysis device, is used to perform a visual monitoring operation on the power transmission environment of the target power transmission line when the monitoring request signal is received, so as to obtain and output the corresponding visual monitoring image.
[0008] A smoothing spatial filtering device, connected to the environmental monitoring device, is used to perform smoothing spatial filtering processing on the received visual monitoring image to obtain and output the corresponding smoothing spatial filtering image.
[0009] A bilateral filtering device, connected to the smoothing spatial filtering device, is used to perform bilateral filtering processing on the received smoothing spatial filtering image to obtain and output the corresponding bilateral filtering image;
[0010] A contrast-preserving device, connected to the bilateral filtering device, is used to perform processing on the received bilaterally filtered image to preserve the boundary between two parts of the image with obvious color or brightness contrast, so as to obtain and output the corresponding contrast-preserving image.
[0011] The data analysis mechanism includes a model training unit, a model application unit, and a parameter configuration unit. The parameter configuration unit is connected to both the model training unit and the model application unit, and is used to configure the parameters of the model training unit and the model application unit. The model training unit is used to perform multiple learning operations on the BP neural network to obtain a BP neural network that has completed multiple learning operations and outputs it as an artificial intelligence model. The model application unit is connected to the model training unit and is used to intelligently analyze the presence of white pollution markers based on the number of pixels in the contrast-preserved image, the sharpness and signal-to-noise ratio of the contrast-preserved image, and the color component values of each pixel in the contrast-preserved image using an artificial intelligence model. The white pollution presence markers are used to indicate whether white pollution exists in the contrast-preserved image.
[0012] A wireless alarm mechanism, connected to the data analysis mechanism, is used to wirelessly send a white pollution alarm signal to a remote management server when the white pollution presence marker, which is intelligently analyzed using an artificial intelligence model, indicates the presence of white pollution in the contrast-preserving image.
[0013] The model training unit is used to perform multiple learning operations on the BP neural network to obtain a BP neural network that has completed multiple learning operations and outputs it as an artificial intelligence model. The number of learning operations is positively correlated with the number of pixels in the contrast-preserving image.
[0014] The transmission line object detection alarm system of the present invention, which utilizes state analysis, is intelligently designed and has a certain degree of specificity. Attached Figure Description
[0015] The embodiments of the present invention will now be described with reference to the accompanying drawings, wherein:
[0016] Figure 1 This is a structural block diagram of a transmission line object detection and alarm system utilizing state analysis, according to Embodiment 1 of the present invention.
[0017] Figure 2 This is a structural block diagram of a transmission line object detection and alarm system utilizing state analysis, as shown in Embodiment 2 of the present invention.
[0018] Figure 3 This is a structural block diagram of a transmission line object detection and alarm system utilizing state analysis, as shown in Embodiment 3 of the present invention. Detailed Implementation
[0019] The embodiments of the transmission line object detection and alarm system of the present invention, which utilizes state analysis, will now be described in detail with reference to the accompanying drawings.
[0020] Example 1
[0021] Figure 1 The above is a structural block diagram of a transmission line object detection and alarm system utilizing state analysis according to Embodiment 1 of the present invention. The system includes:
[0022] A status analysis device, connected to a target transmission line, is used to issue a monitoring request signal when a phase-to-phase short circuit or a phase-to-ground short circuit is detected in the target transmission line, and to issue a stop monitoring signal when no phase-to-phase short circuit or a phase-to-ground short circuit is detected in the target transmission line.
[0023] For example, a status analysis device, connected to a target transmission line, is used to issue a monitoring request signal when a phase-to-phase short circuit or a line-to-ground short circuit is detected in the target transmission line, and to issue a stop monitoring signal when no phase-to-phase short circuit or line-to-ground short circuit is detected in the target transmission line. The status analysis device has a built-in short-circuit analysis unit for analyzing whether a phase-to-phase short circuit or a line-to-ground short circuit has occurred in the target transmission line.
[0024] An environmental monitoring device, connected to the state analysis device, is used to perform a visual monitoring operation on the power transmission environment of the target power transmission line when the monitoring request signal is received, so as to obtain and output the corresponding visual monitoring image.
[0025] A smoothing spatial filtering device, connected to the environmental monitoring device, is used to perform smoothing spatial filtering processing on the received visual monitoring image to obtain and output the corresponding smoothing spatial filtering image.
[0026] A bilateral filtering device, connected to the smoothing spatial filtering device, is used to perform bilateral filtering processing on the received smoothing spatial filtering image to obtain and output the corresponding bilateral filtering image;
[0027] A contrast-preserving device, connected to the bilateral filtering device, is used to perform processing on the received bilaterally filtered image to preserve the boundary between two parts of the image with obvious color or brightness contrast, so as to obtain and output the corresponding contrast-preserving image.
[0028] The data analysis mechanism includes a model training unit, a model application unit, and a parameter configuration unit. The parameter configuration unit is connected to both the model training unit and the model application unit, and is used to configure the parameters of the model training unit and the model application unit. The model training unit is used to perform multiple learning operations on the BP neural network to obtain a BP neural network that has completed multiple learning operations and outputs it as an artificial intelligence model. The model application unit is connected to the model training unit and is used to intelligently analyze the presence of white pollution markers based on the number of pixels in the contrast-preserved image, the sharpness and signal-to-noise ratio of the contrast-preserved image, and the color component values of each pixel in the contrast-preserved image using an artificial intelligence model. The white pollution presence markers are used to indicate whether white pollution exists in the contrast-preserved image.
[0029] A wireless alarm mechanism, connected to the data analysis mechanism, is used to wirelessly send a white pollution alarm signal to a remote management server when the white pollution presence marker, which is intelligently analyzed using an artificial intelligence model, indicates the presence of white pollution in the contrast-preserving image.
[0030] The model training unit is used to perform multiple learning operations on the BP neural network to obtain a BP neural network that has completed multiple learning operations and outputs it as an artificial intelligence model, including: the number of learning operations is positively correlated with the number of pixels in the contrast-preserving image;
[0031] The environmental monitoring device is also used to temporarily suspend the visual monitoring operation on the power transmission environment of the target power transmission line when it receives the stop monitoring signal.
[0032] The wireless alarm mechanism is also used to temporarily suspend the wireless transmission of the white pollution alarm signal to the remote management server when the white pollution presence marker, which is intelligently analyzed using an artificial intelligence model, indicates that there is no white pollution in the contrast-preserving image.
[0033] Example 2
[0034] Figure 2 This is a structural block diagram of a transmission line object detection and alarm system utilizing state analysis, as shown in Embodiment 2 of the present invention.
[0035] Compared to Figure 1 , Figure 2 The transmission line object detection alarm system utilizing state analysis may also include:
[0036] A height sensor is connected to the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data analysis mechanism, respectively, and is used to measure the current real-time height values of each of the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data analysis mechanism.
[0037] The height sensor is connected to the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data analysis mechanism, respectively, and is used to measure the current real-time height values of each of the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data analysis mechanism. The height sensor includes multiple height measurement units, each connected to the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data analysis mechanism, to respectively measure the current real-time height values of each of the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data analysis mechanism.
[0038] The height sensor includes multiple height measurement units, which are respectively connected to the smoothing spatial filtering device, the bilateral filtering device, the contrast retention device, and the data analysis mechanism to separately measure the current real-time height values of each of the smoothing spatial filtering device, the bilateral filtering device, the contrast retention device, and the data analysis mechanism. The multiple height measurement units are multiple height sensors, respectively connected to the smoothing spatial filtering device, the bilateral filtering device, the contrast retention device, and the data analysis mechanism to separately measure the current real-time height values of each of the smoothing spatial filtering device, the bilateral filtering device, the contrast retention device, and the data analysis mechanism.
[0039] The plurality of height measurement units are plurality of height sensors, which are respectively connected to the smoothing spatial filtering device, the bilateral filtering device, the contrast retention device and the data parsing mechanism to complete the separate measurement of the current real-time height values of the smoothing spatial filtering device, the bilateral filtering device, the contrast retention device and the data parsing mechanism, including: the plurality of height sensors have the same structure;
[0040] The plurality of height measurement units are plurality of height sensors, which are respectively connected to the smoothing spatial filtering device, the bilateral filtering device, the contrast retention device and the data parsing mechanism to complete the separate measurement of the current real-time height values of the smoothing spatial filtering device, the bilateral filtering device, the contrast retention device and the data parsing mechanism. The plurality of height sensors have the same upper limit value and lower limit value for height measurement.
[0041] Example 3
[0042] Figure 3 This is a structural block diagram of a transmission line object detection and alarm system utilizing state analysis, as shown in Embodiment 3 of the present invention.
[0043] Compared to Figure 1 , Figure 3 The transmission line object detection alarm system utilizing state analysis may also include:
[0044] The playback processing device is connected to multiple height sensors of the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data analysis mechanism, respectively, for synchronously playing the current real-time height values of the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data analysis mechanism.
[0045] The playback processing device is connected to multiple height sensors of the smoothing spatial filtering device, the bilateral filtering device, the contrast retention device, and the data parsing mechanism, respectively, and is used to synchronously play the current real-time height values of the smoothing spatial filtering device, the bilateral filtering device, the contrast retention device, and the data parsing mechanism, including: the playback processing device is a character display device;
[0046] The playback processing device is connected to multiple height sensors of the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data analysis mechanism, respectively, and is used to synchronously play the current real-time height values of the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data analysis mechanism, including: the playback processing device is a voice playback device.
[0047] In addition, in the transmission line object detection alarm system utilizing state analysis, the model training unit is used to perform multiple learning operations on the BP neural network to obtain a BP neural network that has completed multiple learning operations and outputs it as an artificial intelligence model. The model application unit is connected to the model training unit and is used to intelligently analyze the presence of white pollution markers based on the number of pixels in the contrast-preserved image, the sharpness and signal-to-noise ratio of the contrast-preserved image, and the color component values of each pixel in the contrast-preserved image using an artificial intelligence model. The presence of white pollution markers is used to indicate whether white pollution exists in the contrast-preserved image. This includes simulation and testing using the MATLAB toolbox to perform multiple learning operations on the BP neural network to obtain a BP neural network that has completed multiple learning operations and outputs it as an artificial intelligence model.
[0048] Therefore, the specific technical effects embodied by this invention are as follows:
[0049] First, a specially designed artificial intelligence model is used to intelligently analyze the white pollution presence markers based on various visual data of the contrast-preserved image. The white pollution presence markers are used to indicate whether white pollution exists in the contrast-preserved image. The number of times the model learns is positively correlated with the number of pixels in the contrast-preserved image.
[0050] Secondly: When the white pollution presence marker, which is identified by the artificial intelligence model, indicates the presence of white pollution in the contrast-preserving image, the white pollution alarm signal is wirelessly sent to the remote management server, thereby completing the fault location and judgment at the accident site;
[0051] Furthermore, the system only sends an intelligent analysis to determine whether white pollution exists on the target transmission line when a phase-to-phase short circuit or a phase-to-ground short circuit occurs on the target transmission line, thereby effectively reducing the power consumption of the entire system.
[0052] Although the invention has been specifically shown and described with reference to preferred embodiments thereof, those skilled in the art will understand that various changes in form and detail may be made without departing from the spirit and scope of the invention as set forth in the appended claims. Furthermore, while elements of the invention are described or claimed in the singular, the plural forms are also covered unless expressly stated to be limited to the singular.
Claims
1. A transmission line object detection and alarm system utilizing state analysis, characterized in that, The system includes: A status analysis device, connected to a target transmission line, is used to issue a monitoring request signal when a phase-to-phase short circuit or a phase-to-ground short circuit is detected in the target transmission line, and to issue a stop monitoring signal when no phase-to-phase short circuit or a phase-to-ground short circuit is detected in the target transmission line. An environmental monitoring device, connected to the state analysis device, is used to perform a visual monitoring operation on the power transmission environment of the target power transmission line when the monitoring request signal is received, so as to obtain and output the corresponding visual monitoring image. A smoothing spatial filtering device, connected to the environmental monitoring device, is used to perform smoothing spatial filtering processing on the received visual monitoring image to obtain and output the corresponding smoothing spatial filtering image. A bilateral filtering device, connected to the smoothing spatial filtering device, is used to perform bilateral filtering processing on the received smoothing spatial filtering image to obtain and output the corresponding bilateral filtering image; A contrast-preserving device, connected to the bilateral filtering device, is used to perform processing on the received bilaterally filtered image to preserve the boundary between two parts of the image with obvious color or brightness contrast, so as to obtain and output the corresponding contrast-preserving image. The data analysis mechanism includes a model training unit, a model application unit, and a parameter configuration unit. The parameter configuration unit is connected to both the model training unit and the model application unit, and is used to configure the parameters of the model training unit and the model application unit. The model training unit is used to perform multiple learning operations on the BP neural network to obtain a BP neural network that has completed multiple learning operations and outputs it as an artificial intelligence model. The model application unit is connected to the model training unit and is used to intelligently analyze the presence of white pollution markers based on the number of pixels in the contrast-preserved image, the sharpness and signal-to-noise ratio of the contrast-preserved image, and the color component values of each pixel in the contrast-preserved image using an artificial intelligence model. The white pollution presence markers are used to indicate whether white pollution exists in the contrast-preserved image. A wireless alarm mechanism, connected to the data analysis mechanism, is used to wirelessly send a white pollution alarm signal to a remote management server when the white pollution presence marker, which is intelligently analyzed using an artificial intelligence model, indicates the presence of white pollution in the contrast-preserving image. The model training unit is used to perform multiple learning operations on the BP neural network to obtain a BP neural network that has completed multiple learning operations and outputs it as an artificial intelligence model. The number of learning operations is positively correlated with the number of pixels in the contrast-preserving image.
2. The object detection alarm system utilizing state analysis as described in claim 1, characterized in that: The environmental monitoring device is also used to temporarily suspend the visual monitoring operation on the power transmission environment of the target power transmission line when it receives the stop monitoring signal; The wireless alarm mechanism is also used to temporarily suspend the wireless transmission of the white pollution alarm signal to the remote management server when the white pollution presence marker, which is intelligently analyzed using an artificial intelligence model, indicates that there is no white pollution in the contrast-preserving image.
3. The object detection alarm system utilizing state analysis as described in claim 2, characterized in that, The system also includes: A height sensor is connected to the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data analysis mechanism, respectively, and is used to measure the current real-time height values of each of the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data analysis mechanism. The height sensor is connected to the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data analysis mechanism, respectively, and is used to measure the current real-time height values of each of the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data analysis mechanism. The height sensor includes multiple height measurement units, each connected to the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data analysis mechanism, to separately measure the current real-time height values of each of the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data analysis mechanism.
4. The object detection alarm system utilizing state analysis as described in claim 3, characterized in that: The height sensor includes multiple height measurement units, which are respectively connected to the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data analysis mechanism to separately measure the current real-time height values of each of the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data analysis mechanism. The multiple height measurement units are multiple height sensors, respectively connected to the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data analysis mechanism to separately measure the current real-time height values of each of the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data analysis mechanism.
5. The object detection alarm system utilizing state analysis as described in claim 4, characterized in that: The plurality of height measurement units are plurality of height sensors, which are respectively connected to the smoothing spatial filtering device, the bilateral filtering device, the contrast retention device and the data analysis mechanism to complete the separate measurement of the current real-time height values of the smoothing spatial filtering device, the bilateral filtering device, the contrast retention device and the data analysis mechanism, including: the plurality of height sensors have the same structure.
6. The object detection alarm system utilizing state analysis as described in claim 5, characterized in that: The plurality of height measurement units are plurality of height sensors, which are respectively connected to the smoothing spatial filtering device, the bilateral filtering device, the contrast retention device and the data parsing mechanism to complete the separate measurement of the current real-time height values of the smoothing spatial filtering device, the bilateral filtering device, the contrast retention device and the data parsing mechanism. The plurality of height sensors have the same upper limit value and lower limit value for height measurement.
7. The object detection alarm system utilizing state analysis as described in any one of claims 3-6, characterized in that, The system also includes: The playback processing device is connected to multiple height sensors of the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data analysis mechanism, respectively, for synchronously playing the current real-time height values of each of the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data analysis mechanism.
8. The object detection alarm system utilizing state analysis as described in claim 7, characterized in that: The playback processing device is connected to multiple height sensors of the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data parsing mechanism, respectively, and is used to synchronously play the current real-time height values of the smoothing spatial filter, the bilateral filter, the contrast retention device, and the data parsing mechanism, including: the playback processing device is a character display device.
9. The object detection alarm system utilizing state analysis as described in claim 7, characterized in that: The playback processing device is connected to multiple height sensors of the smoothing spatial filter, the bilateral filter, the contrast preservation device, and the data analysis mechanism, respectively, and is used to synchronously play the current real-time height values of the smoothing spatial filter, the bilateral filter, the contrast preservation device, and the data analysis mechanism, including: the playback processing device is a voice playback device.