Fuse lead anti-swing rod for distribution network uninterruptible operation and safety analysis method
By designing a modular lead wire fixing structure and combining multi-dimensional data acquisition with a deep learning-based safety analysis method, the safety risk problem of Link lead wire anti-sway rod was solved, achieving rapid fixing and safety early warning, and reducing operational risks.
Patent Information
- Application Number
- CN202511479754.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-16
- Publication Date
- 2026-01-30
AI Technical Summary
Existing Link lead anti-sway rods have safety risks such as mechanical performance degradation, stress concentration areas, and excessive swaying during use, leading to safety hazards such as electric shock and detachment.
A fuse lead anti-sway rod for live-line work in power distribution networks was designed, including an aluminum alloy crossarm clip, an internal transmission rod clip, a concealed internal transmission rod, a fully insulated, lightweight, detachable and adjustable clip, an adjustable double fork hook, and a modular lead fixing rod. By combining multi-dimensional data acquisition, deep reinforcement learning, and digital twin technology, a risk prediction model was constructed to achieve safety analysis.
It achieves rapid and stable fixing of leads and adaptability to multiple environments. By using predictive models to identify safety risks in advance, it reduces accidents caused by human error and improves safety during use.
Smart Images
Figure CN121440412A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to a fuse lead anti-sway rod for live-line work in power distribution networks and a safety analysis method, belonging to the field of Link lead anti-sway rods. Background Technology
[0002] Link anti-sway bars, also known as lead wire support bars or insulating brackets, are key safety tools in live-line electrical work, primarily used to prevent short-circuit accidents caused by lead wire swaying during operation. Their core applications include: fixing lead wires when disconnecting or connecting unloaded lines; stabilizing conductors during the installation or maintenance of coupling capacitors, surge arresters, wave traps, and other equipment leads; and providing temporary support jumpers in high-voltage distribution lines to prevent conductor swaying caused by wind or operation. However, the use of link anti-sway bars can easily lead to certain safety risks, such as mechanical performance degradation, stress concentration areas, and excessive swaying. For example, mechanical performance degradation (e.g., insulation performance) can lead to electric shock; stress concentration areas can cause the link to detach; and excessive swaying can result in various safety hazards. Summary of the Invention
[0003] Based on the problems described in the background, the problem to be solved by the present invention is to provide an anti-sway rod for fuse leads used in power distribution network uninterrupted operation and a safety analysis method, so as to solve the problems mentioned above.
[0004] To achieve the above objectives, the present invention provides the following technical solution: a fuse lead anti-sway rod for uninterrupted power distribution network operation, comprising an aluminum alloy crossarm clip, an inner transmission rod clip, a concealed inner transmission rod, a fully insulated lightweight detachable and adjustable clip, an adjustable double hook, a modular lead fixing rod, and a Y-shaped fixing seat. The concealed inner transmission rod has an inner transmission rod clip at one end, and an aluminum alloy crossarm clip is fixed to one end of the inner transmission rod clip. A Y-shaped fixing seat is installed at the other end of the concealed inner transmission rod. An adjustable double hook is provided on the Y-shaped fixing seat, and a modular lead fixing rod is installed on the adjustable double hook. Fully insulated lightweight detachable and adjustable clips are installed on both sides of the modular lead fixing rod.
[0005] Preferably, detachable nylon plugs are also installed at both ends of the modular lead wire fixing rod.
[0006] This invention also provides a safety analysis method for anti-sway rods of fuse leads used in live-line work on power distribution networks, comprising the following steps:
[0007] (1) A multi-dimensional data acquisition system is configured on the anti-sway rod of the fuse lead for live-line work in the power distribution network, and real-time environmental monitoring data is obtained through the multi-dimensional data acquisition system;
[0008] (2) Construct a multi-scale model based on the real-time environmental monitoring data;
[0009] (3) Construct a risk prediction model based on deep reinforcement learning, train the risk prediction model using the multi-scale model, and predict the safety risk of the anti-sway rod of the fuse lead for live-line work in the distribution network.
[0010] (4) Generate relevant early warning information based on the safety risks of the anti-sway rod of the fuse lead of the power distribution network without power interruption operation, and display it in a preset manner.
[0011] Preferably, step (1) includes the following steps:
[0012] (1.1) Set up a physical sensing layer. In the physical sensing layer, deploy fiber Bragg grating sensors on the anti-sway rod of the fuse lead for live-line work in the distribution network. The fiber Bragg grating sensors collect strain distribution, temperature field data, vibration spectrum data and humidity data in real time.
[0013] (1.2) Connect to an environmental monitoring terminal and acquire wind speed data, precipitation data, and pollution level data from the environmental monitoring terminal;
[0014] (1.3) Based on the strain distribution, temperature field data, vibration spectrum data, humidity data, wind speed data, precipitation data and pollution level data, real-time environmental monitoring data are constructed to form a multi-dimensional data acquisition system.
[0015] Preferably, step (2) includes the following steps:
[0016] (2.1) Based on the real-time environmental monitoring data, obtain the pollution level data, humidity data and temperature data to form the first interference data, obtain the material type of the anti-sway bar, and collect the mechanical performance characteristic data of the current anti-sway bar material type under the first interference data;
[0017] (2.2) Collect the mechanical performance degradation characteristics of the current anti-sway bar material type under the first interference data within a preset time. Simulate the mechanical performance degradation characteristics of the current anti-sway bar material type under the first interference data within a preset time using digital twin technology to form a micro model.
[0018] (2.3) Based on the real-time environmental monitoring data, obtain strain distribution and vibration spectrum data, and simulate the stress concentration area of the anti-sway rod of the fuse lead in the power distribution network during the locking process using digital twin technology to form a component model;
[0019] (2.4) Obtain wind speed data, simulate the dynamic behavior of the anti-sway rod of the fuse lead of the power distribution network under the current wind speed data conditions, construct a system model, and construct a multi-scale model based on the micro model, component model and system model.
[0020] Preferably, step (3) includes the following steps:
[0021] (3.1) Construct a risk prediction model based on deep reinforcement learning, set risk evaluation indicators, calculate the deviation value between each model feature in the multi-scale model and the risk evaluation indicators, determine the risk level based on the deviation value, and use the multi-scale model as the model input.
[0022] (3.2) The risk level is used as the model output. The multi-scale model is input into the risk prediction model for training. The contribution value of the model features to the risk prediction model in predicting the risk level is calculated, and the contribution feature threshold is set.
[0023] (3.3) Introduce a multi-head attention mechanism, input model features whose contribution value is greater than the contribution feature threshold into the multi-head attention mechanism for processing, and focus attention on model features whose contribution value is greater than the contribution feature threshold;
[0024] (3.4) Update the state of the hidden layer and continue to use federated learning technology to aggregate data from multiple regions to update parameters while ensuring privacy.
[0025] Preferably, step (3) further includes the following steps:
[0026] (3.5) Obtain multi-dimensional data information of the anti-sway rod of the fuse lead wire for live-line work in distribution network, and input the multi-dimensional data information of the anti-sway rod of the fuse lead wire for live-line work in distribution network into the risk prediction model for prediction;
[0027] (3.6) By prediction, obtain the mechanical performance degradation risk level, stress concentration area risk level, and swing over-limit risk level of the anti-sway rod of the fuse lead for live-line work in distribution network, and generate the safety risk of the anti-sway rod of the fuse lead for live-line work in distribution network.
[0028] Preferably, step (4) further includes the following steps:
[0029] (4.1) Set risk level evaluation indicators to determine whether the safety risk of the anti-sway rod of the fuse lead of the power distribution network live-line operation is greater than the risk level evaluation indicators;
[0030] (4.2) When the safety risk of the anti-sway rod of the fuse lead of the power distribution network during live-line work is greater than the risk level evaluation index, relevant early warning information is generated.
[0031] Preferably, a safety analysis system for an anti-sway rod for a fuse lead wire used in live-line work of a power distribution network is characterized by comprising a memory and a processor. The memory includes a safety analysis method program for the anti-sway rod for a fuse lead wire used in live-line work of a power distribution network. When the processor executes the safety analysis method program for the anti-sway rod for a fuse lead wire used in live-line work of a power distribution network, it implements the steps of the safety analysis method for the anti-sway rod for a fuse lead wire used in live-line work of a power distribution network as described in any one of claims 3-8.
[0032] Preferably, a computer-readable storage medium is characterized in that it includes a safety analysis method program for anti-sway rods of fuse leads used in live-line work of power distribution networks, wherein when the safety analysis method program for anti-sway rods of fuse leads used in live-line work of power distribution networks is executed by a processor, it implements the steps of the safety analysis method for anti-sway rods of fuse leads used in live-line work of power distribution networks as described in any one of claims 3-8.
[0033] The beneficial effects of this invention are: this invention enables modular fixing of the lead wire, and the Y-shaped fixing base combined with the double fork hook enables quick installation of the modular lead wire. Moreover, the hidden internal transmission design of the main fixing rod can quickly and stably fix the main structure. The fixing position of the modular lead wire fixing rod can be adjusted over a wide range to meet various working environments. The fully insulated, lightweight, adjustable integrated buckle design allows the lead wire to be well fixed in any position even when it is covered. Attached Figure Description
[0034] Figure 1 A schematic diagram of the overall structure of the anti-sway rod for fuse leads used in live-line work of power distribution networks;
[0035] Figure 2 System block diagram of a safety analysis system for anti-sway rods with fuse leads used in live-line work of power distribution networks;
[0036] Figure 3 A partial structural diagram of the anti-sway rod for fuse leads used in live-line work on power distribution networks;
[0037] Figure 4 A side view of the anti-sway rod for fuse leads used in live-line power distribution work.
[0038] In the diagram: 1 is an aluminum alloy crossarm clip; 2 is an internal drive rod clip; 3 is a concealed internal drive rod; 4 is a fully insulated, lightweight, detachable, and adjustable clip; 5 is an adjustable double fork hook; 6 is a modular lead wire fixing rod; 7 is a Y-shaped fixing seat; and 8 is a detachable nylon plug. Detailed Implementation
[0039] The embodiments of the present invention will be further described below with reference to the accompanying drawings:
[0040] Example 1
[0041] like Figure 1 , 3 As shown in Figure 4, the present invention provides a fuse lead anti-sway rod for uninterrupted power distribution network operation, comprising an aluminum alloy crossarm clip 1, an inner transmission rod clip 2, a concealed inner transmission rod 3, a fully insulated lightweight detachable and adjustable clip 4, an adjustable double hook 5, a modular lead fixing rod 6, and a Y-shaped fixing seat 7. The concealed inner transmission rod 3 has an inner transmission rod clip 2 at one end, and an aluminum alloy crossarm clip 1 is fixed at one end of the inner transmission rod clip 2. The concealed inner transmission rod 3 has a Y-shaped fixing seat 7 installed at the other end, and an adjustable double hook 5 is provided on the Y-shaped fixing seat 7. The modular lead fixing rod 6 is installed on the adjustable double hook 5, and the fully insulated lightweight detachable and adjustable clip 4 is installed on both sides of the modular lead fixing rod 6.
[0042] It should be noted that the concealed internal transmission rod 3 and the modular lead wire fixing rod 6 are separable.
[0043] The modular lead wire fixing rod 6 is also equipped with detachable nylon plugs 8 at both ends.
[0044] It should be noted that the fuse lead anti-sway rod for live-line work in this power distribution network is suitable for various crossarm operations.
[0045] It should be noted that the anti-sway rod for the lead wire can achieve modular fixation of the lead wire. The Y-shaped fixing base with double fork hooks can achieve quick installation of the modular lead wire. Moreover, the hidden internal transmission design of the main fixing rod can quickly and stably fix the main structure. The fixing position of the modular lead wire fixing rod can be adjusted over a wide range to meet various working environments. The fully insulated, lightweight, adjustable integrated buckle design allows the lead wire to be well fixed in any position even when it is covered.
[0046] This invention also provides a safety analysis method for anti-sway rods of fuse leads used in live-line work on power distribution networks, comprising the following steps:
[0047] (1) A multi-dimensional data acquisition system is configured on the anti-sway rod of the fuse lead for live-line work in the power distribution network, and real-time environmental monitoring data is obtained through the multi-dimensional data acquisition system;
[0048] (2) Construct a multi-scale model based on the real-time environmental monitoring data;
[0049] (3) Construct a risk prediction model based on deep reinforcement learning, train the risk prediction model using the multi-scale model, and predict the safety risk of the anti-sway rod of the fuse lead for live-line work in the distribution network.
[0050] (4) Generate relevant early warning information based on the safety risks of the anti-sway rod of the fuse lead of the power distribution network without power interruption operation, and display it in a preset manner.
[0051] It should be noted that by combining a multi-dimensional data acquisition system to assess the safety of the anti-sway rod of the fuse lead for live-line work in power distribution networks, safety during use can be guaranteed.
[0052] Step (1) includes the following steps:
[0053] (1.1) Set up a physical sensing layer. In the physical sensing layer, deploy fiber Bragg grating sensors on the anti-sway rod of the fuse lead for live-line work in the distribution network. The fiber Bragg grating sensors collect strain distribution, temperature field data, vibration spectrum data and humidity data in real time.
[0054] (1.2) Connect to an environmental monitoring terminal and acquire wind speed data, precipitation data, and pollution level data from the environmental monitoring terminal;
[0055] (1.3) Based on the strain distribution, temperature field data, vibration spectrum data, humidity data, wind speed data, precipitation data and pollution level data, real-time environmental monitoring data are constructed to form a multi-dimensional data acquisition system.
[0056] It should be noted that this method can be used to construct a multi-dimensional data acquisition system to obtain real-time environmental monitoring data.
[0057] Step (2) includes the following steps:
[0058] (2.1) Based on the real-time environmental monitoring data, obtain the pollution level data, humidity data and temperature data to form the first interference data, obtain the material type of the anti-sway bar, and collect the mechanical performance characteristic data of the current anti-sway bar material type under the first interference data;
[0059] (2.2) Collect the mechanical performance degradation characteristics of the current anti-sway bar material type under the first interference data within a preset time. Simulate the mechanical performance degradation characteristics of the current anti-sway bar material type under the first interference data within a preset time using digital twin technology to form a micro model.
[0060] It should be noted that the degradation of the mechanical performance characteristics (such as insulation and hardness) of the anti-sway bar varies under different levels of contamination, humidity, material type, and temperature. By using digital twin technology to simulate the degradation characteristics of the mechanical performance of the current anti-sway bar under the first interference data within a preset time, a microscopic model is formed, which more intuitively represents the mechanical performance. For example, it can be used to observe the risk of insulation failure and the risk of electric shock under ultra-high voltage.
[0061] (2.3) Based on the real-time environmental monitoring data, obtain strain distribution and vibration spectrum data, and simulate the stress concentration area of the anti-sway rod of the fuse lead in the power distribution network during the locking process using digital twin technology to form a component model;
[0062] It should be noted that by using digital twin technology to simulate the stress concentration area of the anti-sway rod of the fuse lead wire in the live-line work of the distribution network during the locking process, the crack phenomenon of the anti-sway rod of the fuse lead wire in the live-line work of the distribution network can be observed, so as to avoid this situation from occurring during use.
[0063] (2.4) Obtain wind speed data, simulate the dynamic behavior of the anti-sway rod of the fuse lead of the power distribution network under the current wind speed data conditions, construct a system model, and construct a multi-scale model based on the micro model, component model and system model.
[0064] It should be noted that the simulation is performed on the dynamic behavior of the anti-sway rod of the fuse lead for live-line work in the distribution network under the current wind speed data, so as to simulate the swaying dynamic behavior under the current wind speed data and then analyze the risk behavior.
[0065] Step (3) includes the following steps:
[0066] (3.1) Construct a risk prediction model based on deep reinforcement learning, set risk evaluation indicators, calculate the deviation value between each model feature in the multi-scale model and the risk evaluation indicators, determine the risk level based on the deviation value, and use the multi-scale model as the model input.
[0067] (3.2) The risk level is used as the model output. The multi-scale model is input into the risk prediction model for training. The contribution value of the model features to the risk prediction model in predicting the risk level is calculated, and the contribution feature threshold is set.
[0068] (3.3) Introduce a multi-head attention mechanism, input model features whose contribution value is greater than the contribution feature threshold into the multi-head attention mechanism for processing, and focus attention on model features whose contribution value is greater than the contribution feature threshold;
[0069] (3.4) Update the state of the hidden layer and continue to use federated learning technology to aggregate data from multiple regions to update parameters while ensuring privacy.
[0070] This ensures the privacy of the data.
[0071] It should be noted that different deviation values can be set as different risk levels. For example, a deviation value of 0-5 indicates no risk, 5-20 indicates low risk, 20-50 indicates medium risk, 50-100 indicates high risk, and above 100 indicates extremely high risk. In this process, a multi-head attention mechanism is introduced. Model features with contribution values greater than the contribution feature threshold are input into the multi-head attention mechanism for processing. Attention is focused on model features with contribution values greater than the contribution feature threshold when predicting each type of risk (such as crack risk and insulation risk). This avoids the influence of multi-scale data on the prediction of different risk situations and improves the prediction accuracy of risk situations.
[0072] Step (3) further includes the following steps:
[0073] (3.5) Obtain multi-dimensional data information of the anti-sway rod of the fuse lead wire for live-line work in distribution network, and input the multi-dimensional data information of the anti-sway rod of the fuse lead wire for live-line work in distribution network into the risk prediction model for prediction;
[0074] (3.6) By prediction, obtain the mechanical performance degradation risk level, stress concentration area risk level, and swing over-limit risk level of the anti-sway rod of the fuse lead for live-line work in distribution network, and generate the safety risk of the anti-sway rod of the fuse lead for live-line work in distribution network.
[0075] Step (4) further includes the following steps:
[0076] (4.1) Set risk level evaluation indicators to determine whether the safety risk of the anti-sway rod of the fuse lead of the power distribution network live-line operation is greater than the risk level evaluation indicators;
[0077] (4.2) When the safety risk of the anti-sway rod of the fuse lead of the power distribution network during live-line work is greater than the risk level evaluation index, relevant early warning information is generated.
[0078] It should be noted that this solution breaks through the traditional passive protection model, enabling proactive prediction and intervention of security risks. Through continuous interaction between the digital twin and the actual equipment, it forms a self-optimizing security decision-making capability, significantly reducing accidents caused by human error.
[0079] This method also includes integrating a miniature lidar, a binocular vision module, and an environmental sensor at the top of the anti-sway bar to acquire real-time work environment data and to construct a three-dimensional point cloud map of the work environment in real time based on the real-time work environment data.
[0080] Based on the three-dimensional point cloud map of the working environment, the position of the lead wire and surrounding obstacles are identified. Based on the principle of computational fluid dynamics and combined with wind speed data, the swing trajectory information of the lead wire within a preset time value is predicted.
[0081] A swing trajectory amplitude range threshold is set based on the position of the lead wire and the position of surrounding obstacles. The swing trajectory amplitude range value is obtained based on the swing trajectory information of the lead wire within a preset time value, and it is determined whether the swing trajectory amplitude range value is greater than the swing trajectory amplitude range threshold.
[0082] When the swing trajectory amplitude range threshold is greater than the swing trajectory amplitude range threshold, an early warning is issued for the current working position and transmitted in a preset manner (such as display on a mobile terminal or display on the anti-swing pole).
[0083] It should be noted that during operation, the system continuously compares the deviation between the physical entity and the digital model. When an anomaly is detected, an early warning is issued to improve safety during use.
[0084] like Figure 2 As shown, the present invention also provides a safety analysis system 4 for anti-sway rods of fuse leads used in live-line work of power distribution networks. The system is characterized by including a memory 41 and a processor 42. The memory 41 includes a safety analysis method program for anti-sway rods of fuse leads used in live-line work of power distribution networks. When the processor 42 executes the safety analysis method program for anti-sway rods of fuse leads used in live-line work of power distribution networks, it implements the steps of the safety analysis method for anti-sway rods of fuse leads used in live-line work of power distribution networks as described in any one of claims 3-8.
[0085] The present invention also provides a computer-readable storage medium, characterized in that it includes a safety analysis method program for an anti-sway rod for a fuse lead wire used in live-line work of a power distribution network, wherein when the safety analysis method program for an anti-sway rod for a fuse lead wire used in live-line work of a power distribution network is executed by a processor, it implements the steps of the safety analysis method for an anti-sway rod for a fuse lead wire used in live-line work of a power distribution network as described in any one of claims 3-8.
[0086] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.
[0087] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.
[0088] In addition, in the various embodiments of the present invention, each functional unit can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.
[0089] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0090] Alternatively, if the integrated units of this invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.
[0091] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.
Claims
1. A fuse lead anti-swinging rod for power distribution network operation without power interruption, characterized in that, The utility model relates to an aluminum alloy cross arm card (1), inner transmission rod buckle (2), hidden inner transmission rod (3), all insulation lightweight detachable adjustable buckle (4), adjustable double fork hook (5), modularization lead fixing rod (6) and Y type fixing base (7), one end of hidden inner transmission rod (3) is equipped with inner transmission rod buckle (2), one end of inner transmission rod buckle (2) is fixed with aluminum alloy cross arm card (1), the other end of hidden inner transmission rod (3) is installed with Y type fixing base (7), Y type fixing base (7) is equipped with adjustable double fork hook (5), adjustable double fork hook (5) is installed with modularization lead fixing rod (6), and all insulation lightweight detachable adjustable buckle (4) is installed on both sides of modularization lead fixing rod (6).
2. The anti-swinging rod for fuse lead of power distribution network operation without power interruption according to claim 1, characterized in that, Detachable nylon plug (8) is also installed on both ends of the modularization lead fixing rod (6).
3. A safety analysis method for a fuse lead anti-swing rod for power distribution network operation without power interruption, characterized by, The application is applied to the fuse lead anti-swing rod for distribution network non-power operation of any one of claims 1-2, comprising the following steps: (1) configuring a multi-dimensional data acquisition system on the fuse lead anti-swing rod for distribution network non-power operation, and obtaining real-time environmental monitoring data through the multi-dimensional data acquisition system; (2) constructing a multi-scale model according to the real-time environmental monitoring data; (3) constructing a risk prediction model based on deep reinforcement learning, training the risk prediction model using the multi-scale model, and predicting the safety risk of the fuse lead anti-swing rod for distribution network non-power operation; (4) generating relevant warning information according to the safety risk of the fuse lead anti-swing rod for distribution network non-power operation, and displaying according to a preset mode.
4. The safety analysis method of the anti-swinging rod of the fuse lead for the power distribution network operation without power interruption according to claim 3, characterized in that, The step (1) comprises the following steps: (1.1) setting a physical perception layer, deploying a fiber Bragg grating sensor on the fuse lead anti-swing rod in the physical perception layer, and collecting strain distribution, temperature field data, vibration spectrum data, and humidity data in real time through the fiber Bragg grating sensor; (1.2) connecting an environmental monitoring terminal, and obtaining wind speed data, precipitation data, and contamination degree data in the environmental monitoring terminal; (1.3) constructing real-time environmental monitoring data according to the strain distribution, temperature field data, vibration spectrum data, humidity data, wind speed data, precipitation data, and contamination degree data, and forming a multi-dimensional data acquisition system.
5. The safety analysis method of the anti-swinging fuse lead rod for distribution network non-power operation according to claim 3, characterized in that, The step (2) comprises the following steps: (2.1) obtaining contamination degree data, humidity data, and temperature data from the real-time environmental monitoring data to form first interference data, obtaining the material type of the anti-swing rod, and collecting the mechanical property characteristic data of the material type of the current anti-swing rod under the first interference data; (2.2) collecting the mechanical property degradation characteristic data of the material type of the current anti-swing rod under the first interference data within a preset time, simulating the mechanical property degradation characteristic data of the material type of the current anti-swing rod under the first interference data within the preset time through digital twinning technology, and forming a micro model; (2.3) Obtain strain distribution and vibration frequency spectrum data according to the real-time environmental monitoring data, simulate the stress concentration area of the fuse lead anti-swing rod for distribution network non-stop operation by digital twinning technology during locking, and form a component model; (2.4) Obtain wind speed data, simulate the dynamic behavior of the fuse lead anti-swing rod for distribution network non-stop operation under the current wind speed data condition, construct a system model, and construct a multi-scale model based on the micro model, the component model and the system model.
6. The safety analysis method of the anti-swinging fuse lead rod for distribution network non-power operation according to claim 3, characterized in that, The step (3) comprises the following steps: (3.1) Construct a risk prediction model based on deep reinforcement learning, set a risk evaluation index, calculate the deviation value of each model feature in the multi-scale model and the risk evaluation index, determine the risk level according to the deviation value, and input the multi-scale model as a model; (3.2) The risk level is taken as the model output, the multi-scale model is input into the risk prediction model for training, the contribution value of the model feature to the risk prediction model in predicting the risk level is calculated, and a contribution feature threshold is set; (3.3) Introduce a multi-head attention mechanism, input the model features with contribution values greater than the contribution feature threshold into the multi-head attention mechanism for processing, and focus attention on the model features with contribution values greater than the contribution feature threshold; (3.4) Update the state of the hidden layer, and continuously use the federated learning technology to aggregate multi-region data to update parameters under the premise of ensuring privacy.
7. The safety analysis method of the anti-swinging fuse lead rod for distribution network non-power operation according to claim 6, characterized in that, The step (3) further comprises the following steps: (3.5) Obtain multi-dimensional data information of the fuse lead anti-swing rod for distribution network non-stop operation, and input the multi-dimensional data information of the fuse lead anti-swing rod for distribution network non-stop operation into the risk prediction model for prediction; (3.6) Through prediction, obtain the mechanical property degradation risk level, stress concentration area risk level and swing overrun risk level of the fuse lead anti-swing rod for distribution network non-stop operation, and generate the safety risk of the fuse lead anti-swing rod for distribution network non-stop operation.
8. The safety analysis method of the anti-swinging fuse lead rod for distribution network non-power operation according to claim 3, characterized in that, The step (4) further comprises the following steps: (4.1) Set a risk level evaluation index, and judge whether the safety risk of the fuse lead anti-swing rod for distribution network non-stop operation is greater than the risk level evaluation index; (4.2) When the safety risk of the fuse lead anti-swing rod for distribution network non-stop operation is greater than the risk level evaluation index, generate relevant early warning information.
9. The safety analysis method of the anti-swinging fuse lead rod for distribution network non-power operation according to claim 3, characterized in that, Further comprising a safety analysis system for a fuse lead anti-swing rod for distribution network non-stop operation, comprising a memory and a processor, the memory comprising a safety analysis method program for a fuse lead anti-swing rod for distribution network non-stop operation, and the safety analysis method program for a fuse lead anti-swing rod for distribution network non-stop operation being executed by the processor to realize the steps of the safety analysis method for a fuse lead anti-swing rod for distribution network non-stop operation according to any one of claims 3-8.
10. A computer-readable storage medium, characterized in that, The safety analysis method program of the fuse lead anti-swing rod for distribution network non-power-off operation, when executed by the processor, realizes the steps of the safety analysis method of the fuse lead anti-swing rod for distribution network non-power-off operation as claimed in any one of claims 3-8.