Power transmission network security management system

Abstract

The invention relates to a power transmission network security management system, and the system comprises a final-stage conversion mechanism which is used for successively executing Wiener filtering processing and median filtering processing on a secondary conversion picture; and the model application device is used for intelligently identifying whether the field spacing distance between the grounding piece and the operation electrician is smaller than or equal to the safe spacing distance or not by adopting an AI identification model. The power transmission network security management system is intelligent in design and simple to operate and control. The image content capturing action can be executed on the replacement scene for replacing the strain insulator string so as to obtain and output the corresponding replacement scene picture, and the AI identification model is adopted to intelligently identify whether the field spacing distance between the grounding piece and the operation electrician is smaller than or equal to the safe spacing distance based on various visual information in the replacement scene picture; therefore, when a strain insulator string is replaced in a power transmission network, a reliable and safe distance between an operation electrician and a grounding body is maintained.

Description

Technical Field

[0001] This invention relates to the field of power transmission networks, and more specifically, to a power transmission network security management system. Background Technology

[0002] Electric shocks caused by electrostatic induction mainly correspond to two situations. First, when electricians wearing insulated shoes are near the windows of power poles, the induced charge on their bodies is relatively high due to their proximity to live conductors; for example, touching the tower will cause a stinging sensation. Second, when ground workers touch suspended hardware or metal parts of de-energized equipment in a strong electric field, they will experience electric shocks due to electrostatic induction. Therefore, during live-line work on high-voltage transmission lines, electricians should wear full protective clothing or electrostatic protective suits and ensure all connections are correct to prevent electric shocks caused by electrostatic induction.

[0003] Meanwhile, on operating transmission lines, electricians must not wear insulated shoes when climbing towers, especially when wearing shielding suits or electrostatic protective clothing. If an electrician on the tower needs to touch a long metal object on the transmission rope, grounding must be ensured, and the actual distance between the grounding device and the electrician must be less than or equal to the safe distance to guarantee the electrician's safety. However, due to the complexity of the transmission line environment and the difficulty of on-site measurement, the existing technology lacks a mechanism to accurately and non-contactly verify whether the actual distance between the grounding device and the electrician is less than or equal to the safe distance, making it difficult to reliably guarantee the on-site safety of electricians. Summary of the Invention

[0004] To address the aforementioned technical problems in the prior art, this invention provides a power transmission network security management system capable of capturing image content during the replacement of tension insulator strings to obtain and output corresponding replacement scene images. Crucially, the system sequentially performs nonlinear transformation processing using logarithmic transformation, white balance processing using dynamic thresholds, Wiener filtering, and median filtering on the replacement scene images to obtain and output a final-stage conversion image with superior image quality. This provides more reliable foundational information for subsequent intelligent identification. Furthermore, the system acquires the curvature values ​​of the geometric curves corresponding to the sub-images occupied by the grounding component and the sub-images occupied by the operating electrician in the received final-stage conversion image. Based on the final-stage conversion... The signal-to-noise ratio of the image, the number of noise types in the final-stage conversion image, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final-stage conversion image, the vertical resolution of the final-stage conversion image, and the curvature values ​​corresponding to the operating electrician are all analyzed using an AI recognition model to intelligently determine whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance. The AI ​​recognition model is a radial basis function neural network that has undergone multiple training iterations. The number of training iterations is positively correlated with both the horizontal and vertical resolution of the final-stage conversion image, thereby enabling intelligent judgment on whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance. This ensures a reliable and safe distance between the operating electrician and the grounding body when replacing tension insulator strings in the transmission network.

[0005] According to the present invention, a power transmission network security management system is provided, the system comprising: The operation detection mechanism is used to detect whether the current transmission network is in the process of replacing tension insulator strings. If the current transmission network is in the process of replacing tension insulator strings, a replacement detection signal is issued; otherwise, a replacement not detected signal is issued. The overhead camera capture mechanism is located below the current power transmission network and connected to the operation detection mechanism. When the replacement detection signal is received, it uses an overhead camera perspective to capture the image content of the replacement scene of the tension insulator string replacement, so as to obtain and output the corresponding replacement scene image. The primary conversion mechanism, connected to the overhead capture mechanism, is used to perform nonlinear transformation processing using logarithmic transformation on the received scene change images to obtain and output the corresponding primary conversion images. The secondary conversion mechanism is connected to the primary conversion mechanism and is used to perform white balance processing using dynamic threshold on the received primary conversion image to obtain and output the corresponding secondary conversion image. The final-stage conversion mechanism, connected to the secondary conversion mechanism, is used to perform Wiener filtering and median filtering on the received secondary conversion image in sequence to obtain and output the corresponding final-stage conversion image; The model application device, connected to the final stage conversion mechanism, is used to acquire the curvature values ​​of the geometric curves corresponding to the sub-screen occupied by the grounding component in the received final stage conversion screen, and to acquire the curvature values ​​of the geometric curves corresponding to the sub-screen occupied by the operating electrician in the received final stage conversion screen. Based on the signal-to-noise ratio of the final stage conversion screen, the number of noise types in the final stage conversion screen, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final stage conversion screen, the vertical resolution of the final stage conversion screen, and the curvature values ​​corresponding to the operating electrician, an AI recognition model is used to intelligently identify whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance. The AI ​​recognition model is a radial basis function neural network after each training iteration. The number of training iterations is positively correlated with the horizontal resolution of the final stage conversion screen and also positively correlated with the vertical resolution of the final stage conversion screen. The AI ​​identification model intelligently identifies whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance based on the signal-to-noise ratio of the final-stage conversion image, the number of noise types in the final-stage conversion image, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final-stage conversion image, the vertical resolution of the final-stage conversion image, and the curvature values ​​corresponding to the operating electrician. This includes the AI ​​identification model outputting a status identification label indicating whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance. The AI ​​identification model outputs status identification labels indicating whether the actual distance between the grounding device and the operating electrician is less than or equal to the safe distance. These labels include status identification labels with different values ​​to indicate whether the actual distance between the grounding device and the operating electrician is less than or equal to the safe distance.

[0006] Therefore, the present invention has at least the following three beneficial technical effects: First, image content capture is performed on the replacement scene of the tension insulator string to obtain and output the corresponding replacement scene image. Crucially, the replacement scene image is processed sequentially using nonlinear transformation with logarithmic transformation, white balance processing with dynamic threshold, Wiener filtering, and median filtering to obtain and output a final-stage transformation image with better image quality, providing more reliable basic information for subsequent intelligent identification. Secondly: obtain the curvature values ​​of each geometric curve corresponding to the sub-screen occupied by the grounding component in the received final stage conversion screen, and obtain the curvature values ​​of each geometric curve corresponding to the sub-screen occupied by the operating electrician in the received final stage conversion screen. Furthermore, based on the signal-to-noise ratio of the final-stage conversion image, the number of noise types in the final-stage conversion image, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final-stage conversion image, the vertical resolution of the final-stage conversion image, and the curvature values ​​corresponding to the operating electrician, an AI recognition model is used to intelligently identify whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance. The AI ​​recognition model is a radial basis function neural network after each training iteration. The number of training iterations is positively correlated with both the horizontal and vertical resolution of the final-stage conversion image, thereby completing the intelligent judgment of whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance, so as to maintain a reliable safe distance between the operating electrician and the grounding body when replacing tension insulator strings in the transmission network.

[0007] The power transmission network security management system of this invention is intelligently designed and easy to operate. It can capture image content during the replacement of tension insulator strings, obtain and output corresponding replacement scene images, and intelligently identify whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance based on various visual information in the replacement scene images using an AI recognition model. This ensures a reliable and safe distance between the operating electrician and the grounding body during the replacement of tension insulator strings in the power transmission network. Detailed Implementation

[0008] The implementation scheme of the power transmission network security management system of the present invention will be described in detail below.

[0009] Implementation Plan The power transmission network security management system according to an embodiment of the present invention includes: The operation detection mechanism is used to detect whether the current transmission network is in the process of replacing tension insulator strings. If the current transmission network is in the process of replacing tension insulator strings, a replacement detection signal is issued; otherwise, a replacement not detected signal is issued. The overhead camera capture mechanism is located below the current power transmission network and connected to the operation detection mechanism. When the replacement detection signal is received, it uses an overhead camera perspective to capture the image content of the replacement scene of the tension insulator string replacement, so as to obtain and output the corresponding replacement scene image. Specifically, the overhead camera capture mechanism is located below the current power transmission network and connected to the operation detection mechanism. When the replacement detection signal is received, it performs image content capture on the replacement scene of the tension insulator string from an overhead perspective to obtain and output the corresponding replacement scene image. The overhead camera capture mechanism includes an overhead camera lens and an image sensing component. The primary conversion mechanism, connected to the overhead capture mechanism, is used to perform nonlinear transformation processing using logarithmic transformation on the received scene change images to obtain and output the corresponding primary conversion images. The secondary conversion mechanism is connected to the primary conversion mechanism and is used to perform white balance processing using dynamic threshold on the received primary conversion image to obtain and output the corresponding secondary conversion image. The final-stage conversion mechanism, connected to the secondary conversion mechanism, is used to perform Wiener filtering and median filtering on the received secondary conversion image in sequence to obtain and output the corresponding final-stage conversion image; The model application device, connected to the final stage conversion mechanism, is used to acquire the curvature values ​​of the geometric curves corresponding to the sub-screen occupied by the grounding component in the received final stage conversion screen, and to acquire the curvature values ​​of the geometric curves corresponding to the sub-screen occupied by the operating electrician in the received final stage conversion screen. Based on the signal-to-noise ratio of the final stage conversion screen, the number of noise types in the final stage conversion screen, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final stage conversion screen, the vertical resolution of the final stage conversion screen, and the curvature values ​​corresponding to the operating electrician, an AI recognition model is used to intelligently identify whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance. The AI ​​recognition model is a radial basis function neural network after each training iteration. The number of training iterations is positively correlated with the horizontal resolution of the final stage conversion screen and also positively correlated with the vertical resolution of the final stage conversion screen. The AI ​​identification model intelligently identifies whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance based on the signal-to-noise ratio of the final-stage conversion image, the number of noise types in the final-stage conversion image, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final-stage conversion image, the vertical resolution of the final-stage conversion image, and the curvature values ​​corresponding to the operating electrician. This includes the AI ​​identification model outputting a status identification label indicating whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance. The AI ​​identification model outputs status identification labels indicating whether the actual distance between the grounding device and the operating electrician is less than or equal to the safe distance, including: using status identification labels with different values ​​to indicate whether the actual distance between the grounding device and the operating electrician is less than or equal to the safe distance. The AI ​​identification model outputs a status identification label indicating whether the actual distance between the grounding device and the operating electrician is less than or equal to the safe distance, which further includes: the status identification label is represented in binary numerical form; The process of using an AI recognition model to intelligently identify whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance, based on the signal-to-noise ratio of the final-stage conversion image, the number of noise types in the final-stage conversion image, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final-stage conversion image, the vertical resolution of the final-stage conversion image, and the curvature values ​​corresponding to the operating electrician, also includes: converting the signal-to-noise ratio of the final-stage conversion image, the number of noise types in the final-stage conversion image, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final-stage conversion image, the vertical resolution of the final-stage conversion image, and the curvature values ​​corresponding to the operating electrician into binary values ​​and then inputting them in parallel into the AI ​​recognition model. Furthermore, the overhead camera capture mechanism is also used to temporarily suspend the image content capture action of replacing the tension insulator string from an overhead perspective when the replacement undetected signal is received; The internal control instructions for the step of intelligently identifying whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance based on the signal-to-noise ratio of the final-stage conversion image, the number of noise types in the final-stage conversion image, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final-stage conversion image, the vertical resolution of the final-stage conversion image, and the curvature values ​​corresponding to the operating electrician are based on the AI ​​recognition model are transmitted by the instruction control channel. The internal control command for the step of intelligently identifying whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance based on the signal-to-noise ratio of the final-stage conversion image, the number of noise types in the final-stage conversion image, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final-stage conversion image, the vertical resolution of the final-stage conversion image, and the curvature values ​​corresponding to the operating electrician using an AI recognition model is transmitted by the command control channel. The command control channel is operated and maintained by the SOC chip. The internal control instructions for the step of intelligently identifying whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance based on the signal-to-noise ratio of the final-stage conversion image, the number of noise types in the final-stage conversion image, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final-stage conversion image, the vertical resolution of the final-stage conversion image, and the curvature values ​​corresponding to the operating electrician using an AI recognition model are transmitted by the instruction control channel. The instruction control channel is operated and maintained by an ASIC chip. In addition, the intermediate data of the step of intelligently identifying whether the actual distance between the grounding device and the operating electrician is less than or equal to the safe distance based on the signal-to-noise ratio of the final conversion image, the number of noise types in the final conversion image, the curvature values ​​corresponding to the grounding device, the horizontal resolution of the final conversion image, the vertical resolution of the final conversion image, and the curvature values ​​corresponding to the operating electrician using an AI recognition model is transmitted to the network transmission interface. The intermediate data in the step of intelligently identifying whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance using an AI recognition model based on the signal-to-noise ratio of the final-stage conversion image, the number of noise types in the final-stage conversion image, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final-stage conversion image, the vertical resolution of the final-stage conversion image, and the curvature values ​​corresponding to the operating electrician is transmitted to the network transmission interface. This includes the network transmission interface performing network data transmission and reception based on a time-division duplex communication mechanism. The intermediate data in the step of intelligently identifying whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance using an AI recognition model based on the signal-to-noise ratio of the final-stage conversion image, the number of noise types in the final-stage conversion image, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final-stage conversion image, the vertical resolution of the final-stage conversion image, and the curvature values ​​corresponding to the operating electrician is transmitted to the network transmission interface. This includes the network transmission interface performing network data transmission and reception based on a frequency division duplex communication mechanism. The intermediate data of the step of intelligently identifying whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance using an AI recognition model based on the signal-to-noise ratio of the final-stage conversion image, the number of noise types in the final-stage conversion image, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final-stage conversion image, the vertical resolution of the final-stage conversion image, and the curvature values ​​corresponding to the operating electrician is transmitted to the network transmission interface. The network transmission interface performs network data transmission and reception based on the WIFI communication mechanism.

[0010] In addition, in the aforementioned power transmission network security management system, the AI ​​recognition model is used to intelligently identify whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance, based on the signal-to-noise ratio of the final-stage conversion image, the number of noise types in the final-stage conversion image, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final-stage conversion image, the vertical resolution of the final-stage conversion image, and the curvature values ​​corresponding to the operating electrician. This also includes: using numerical simulation to simulate and test the data processing process of intelligently identifying whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance, based on the signal-to-noise ratio of the final-stage conversion image, the number of noise types in the final-stage conversion image, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final-stage conversion image, the vertical resolution of the final-stage conversion image, and the curvature values ​​corresponding to the operating electrician.

[0011] While only exemplary embodiments of the invention have been described in detail above, those skilled in the art will immediately understand that many variations can be made in these exemplary embodiments without substantially departing from the novel principles and advantages of the invention. Accordingly, all such variations are to be included within the scope of the invention as defined in the following claims. In the claims, the means and function clauses are intended to include the structures described herein as implementing the stated functions, and include not only structural equivalents but also equivalent structures.

Claims

1. A power transmission network security management system, characterized in that, The system includes: The operation detection mechanism is used to detect whether the current transmission network is in the process of replacing tension insulator strings. If the current transmission network is in the process of replacing tension insulator strings, a replacement detection signal is issued; otherwise, a replacement not detected signal is issued. The overhead camera capture mechanism is located below the current power transmission network and connected to the operation detection mechanism. When the replacement detection signal is received, it uses an overhead camera perspective to capture the image content of the replacement scene of the tension insulator string replacement, so as to obtain and output the corresponding replacement scene image. The primary conversion mechanism, connected to the overhead capture mechanism, is used to perform nonlinear transformation processing using logarithmic transformation on the received scene change image to obtain and output the corresponding primary conversion image. The secondary conversion mechanism is connected to the primary conversion mechanism and is used to perform white balance processing using dynamic threshold on the received primary conversion image to obtain and output the corresponding secondary conversion image. The final-stage conversion mechanism, connected to the secondary conversion mechanism, is used to perform Wiener filtering and median filtering on the received secondary conversion image in sequence to obtain and output the corresponding final-stage conversion image; The model application device, connected to the final-stage conversion mechanism, is used to acquire the curvature values ​​of the geometric curves corresponding to the sub-screen occupied by the grounding component in the received final-stage conversion screen, and to acquire the curvature values ​​of the geometric curves corresponding to the sub-screen occupied by the operating electrician in the received final-stage conversion screen. Based on the signal-to-noise ratio of the final-stage conversion screen, the number of noise types in the final-stage conversion screen, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final-stage conversion screen, the vertical resolution of the final-stage conversion screen, and the curvature values ​​corresponding to the operating electrician, an AI recognition model is used to intelligently identify whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance. The AI ​​recognition model is a radial basis function neural network after each training iteration. The number of training iterations is positively correlated with both the horizontal and vertical resolutions of the final-stage conversion screen. The AI ​​recognition model output uses different numerical state recognition labels to indicate whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance.

2. The power transmission network security management system as described in claim 1, characterized in that: The AI ​​identification model outputs a status identification label indicating whether the actual distance between the grounding device and the operating electrician is less than or equal to the safe distance. The status identification label is in the form of a binary numerical value. The process of using an AI recognition model to intelligently identify whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance, based on the signal-to-noise ratio of the final-stage conversion image, the number of noise types in the final-stage conversion image, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final-stage conversion image, the vertical resolution of the final-stage conversion image, and the curvature values ​​corresponding to the operating electrician, also includes: converting the signal-to-noise ratio of the final-stage conversion image, the number of noise types in the final-stage conversion image, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final-stage conversion image, the vertical resolution of the final-stage conversion image, and the curvature values ​​corresponding to the operating electrician into binary values ​​and then inputting them in parallel into the AI ​​recognition model. The overhead camera capture mechanism is also used to temporarily suspend the image content capture action of replacing the tension insulator string from an overhead perspective when the undetected replacement signal is received.

3. The power transmission network security management system as described in claim 2, characterized in that: The internal control commands for the step of intelligently identifying whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance is based on the signal-to-noise ratio of the final stage conversion image, the number of noise types in the final stage conversion image, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final stage conversion image, the vertical resolution of the final stage conversion image, and the curvature values ​​corresponding to the operating electrician using an AI recognition model are transmitted through the command control channel.

4. The power transmission network security management system as described in claim 3, characterized in that: The internal control instructions for the step of intelligently identifying whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance based on the signal-to-noise ratio of the final stage conversion image, the number of noise types in the final stage conversion image, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final stage conversion image, the vertical resolution of the final stage conversion image, and the curvature values ​​corresponding to the operating electrician using an AI recognition model are transmitted by the instruction control channel. The instruction control channel is operated and maintained by the SOC chip.

5. The power transmission network security management system as described in claim 3, characterized in that: The internal control instructions for the step of intelligently identifying whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance based on the signal-to-noise ratio of the final stage conversion image, the number of noise types in the final stage conversion image, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final stage conversion image, the vertical resolution of the final stage conversion image, and the curvature values ​​corresponding to the operating electrician using an AI recognition model are transmitted by the instruction control channel. The instruction control channel is operated and maintained by an ASIC chip.

6. The power transmission network security management system as described in claim 2, characterized in that: The intermediate data of the step of intelligently identifying whether the actual distance between the grounding device and the operating electrician is less than or equal to the safe distance is transmitted to the network transmission interface based on the signal-to-noise ratio of the final stage conversion image, the number of noise types in the final stage conversion image, the curvature values ​​corresponding to the grounding device, the horizontal resolution of the final stage conversion image, the vertical resolution of the final stage conversion image, and the curvature values ​​corresponding to the operating electrician using an AI recognition model.

7. The power transmission network security management system as described in claim 6, characterized in that: The intermediate data of the step of intelligently identifying whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance using an AI recognition model based on the signal-to-noise ratio of the final-stage conversion image, the number of noise types in the final-stage conversion image, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final-stage conversion image, the vertical resolution of the final-stage conversion image, and the curvature values ​​corresponding to the operating electrician is transmitted to the network transmission interface. This includes the network transmission interface performing network data transmission and reception based on a time-division duplex communication mechanism.

8. The power transmission network security management system as described in claim 6, characterized in that: The intermediate data of the step of intelligently identifying whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance using an AI recognition model based on the signal-to-noise ratio of the final-stage conversion image, the number of noise types in the final-stage conversion image, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final-stage conversion image, the vertical resolution of the final-stage conversion image, and the curvature values ​​corresponding to the operating electrician is transmitted to the network transmission interface. This includes the network transmission interface performing network data transmission and reception based on a frequency division duplex communication mechanism.

9. The power transmission network security management system as described in claim 6, characterized in that: The intermediate data of the step of intelligently identifying whether the actual distance between the grounding component and the operating electrician is less than or equal to the safe distance using an AI recognition model based on the signal-to-noise ratio of the final-stage conversion image, the number of noise types in the final-stage conversion image, the curvature values ​​corresponding to the grounding component, the horizontal resolution of the final-stage conversion image, the vertical resolution of the final-stage conversion image, and the curvature values ​​corresponding to the operating electrician is transmitted to the network transmission interface. This includes the network transmission interface performing network data transmission and reception based on the WIFI communication mechanism.