Intelligent safety inspection method and system for new energy station

Abstract

The invention relates to the technical field of new energy station intelligent inspection, in particular to a new energy station intelligent safety inspection method and system, and the method comprises the steps: judging whether an inspection condition is satisfied, and starting an unmanned plane inspection task if the inspection condition is satisfied; generating a dynamic inspection path; performing intelligent safety inspection on the new energy station based on the dynamic inspection path, and collecting personnel operation image information of a target area in real time; the personnel operation image information is transmitted to the cloud server through the hangar center; and the cloud server identifies unsafe behaviors according to the personnel operation image information, marks key information of the hidden danger picture, determines the operation personnel with nonstandard behaviors and information thereof according to the key information, and outputs a potential safety hazard prompt signal. According to the invention, unmanned aerial vehicle inspection full coverage, least time and high unmanned aerial vehicle safety inspection efficiency are realized through dynamic path planning, hidden danger identification reminding is carried out, illegal behaviors are corrected in time, the station safety supervision efficiency and the production safety level are improved, and energy safety and green low-carbon development are guaranteed.

Description

Technical Field

[0001] This invention relates to the technical field of safety monitoring of new energy power stations, and more specifically, to an intelligent safety inspection method and system for new energy power stations. Background Technology

[0002] There are numerous new energy power plants, such as photovoltaic and wind power plants, which are widely distributed. Taking a large power generation group as an example, there are nearly a thousand new energy power plants, distributed in various regions. At each individual power plant, there are hundreds of construction and production workers, distributed in an operating area of ​​several square kilometers, including substations, wind turbines, photovoltaic areas, and power collection lines. They carry out various high-risk operations, such as high-altitude work, hoisting, and electrical work, resulting in high safety risks in new energy production and great difficulty in safety supervision.

[0003] Traditional safety production supervision adopts a combination of on-site supervision by safety supervisors and fixed-point monitoring by fixed cameras. However, this approach has problems such as high manpower input, incomplete monitoring coverage, and weak supervision timeliness. It also has blind spots in supervision of unsafe behaviors of personnel, abnormal equipment status, and site environmental risks. Risk identification is not intelligent enough, and hazard control is lagging behind.

[0004] To address these issues, the commonly used method is drone inspection. However, existing drone inspection methods often employ pre-set fixed flight routes. Safety supervision of new energy power stations primarily focuses on managing personnel violations. Due to the large construction area of ​​new energy power stations (several square kilometers scattered across different locations) and the dispersed nature of personnel operations, if drones use fixed flight routes for inspection, they often fail to capture images of workers for most of the time, resulting in low inspection efficiency and high drone energy consumption. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide an intelligent safety inspection method and system for new energy power stations, addressing the problems existing in the prior art.

[0006] The technical solution adopted by this invention to solve its technical problem is: to construct an intelligent safety inspection method for new energy power stations, including the following steps: Determine if the drone meets the inspection conditions. If not, do not start the drone inspection task. If it does, start the drone inspection task. After initiating the drone inspection mission, the inspection path is dynamically planned and generated. Intelligent safety inspections of new energy power stations are carried out based on the dynamic inspection path, and personnel operation image information in the target area is collected in real time during the inspection process. The personnel operation image information is transmitted back to the hangar center, and then transmitted to the cloud server through the hangar center. The cloud server identifies safety hazards in the personnel work image information, and when unsafe behavior is identified, determines the hazard image and marks the key information of the hazard image; The cloud server determines the personnel involved in the unsafe act and their personnel information based on the key information. The cloud server outputs a safety hazard warning signal based on the operator and their personnel information.

[0007] In the intelligent safety inspection method for new energy power stations described in this invention, the inspection conditions include: meteorological conditions and unmanned aerial vehicle (UAV) equipment conditions; The determination of whether a drone meets the inspection criteria includes: Determine and obtain the current time information; Determine whether the area is within the inspection interval based on the current time information; If not, then the inspection conditions are not met; If so, obtain the current weather information and drone equipment information; Determine whether the meteorological conditions are met based on the current meteorological information, and determine whether the drone equipment conditions are met based on the drone equipment information; If the meteorological conditions and the UAV equipment conditions are met, then the inspection conditions are determined to be met; otherwise, the inspection conditions are determined not to be met.

[0008] In the intelligent safety inspection method for new energy power stations described in this invention, the dynamic planning of inspection paths and generation of dynamic inspection paths includes: Obtain the construction drawings of the aforementioned new energy power station; The construction area is divided according to the construction drawings of the new energy power station, multiple inspection areas are obtained, and the center point coordinate information of the multiple inspection areas is extracted. Obtain the number of workers operating in the multiple inspection areas; The dynamic inspection path is obtained by dynamically planning the path based on the number of workers in the multiple inspection areas.

[0009] In the intelligent safety inspection method for new energy power stations described in this invention, obtaining the number of operators in the plurality of inspection areas includes: Obtain the location information of the workers in the multiple inspection areas; The number of workers in the multiple inspection areas is obtained by counting the number of workers in the multiple inspection areas based on the location information of the workers.

[0010] In the intelligent safety inspection method for new energy power stations described in this invention, the dynamic inspection path includes: a primary inspection path; The step of dynamically planning the path based on the number of workers in the multiple inspection areas to obtain the dynamic inspection path includes: The multiple inspection areas are sorted from highest to lowest according to the number of operators to obtain a primary inspection path; After obtaining the primary inspection path, the UAV performs inspections based on the primary inspection path and the center point coordinates of the multiple inspection areas.

[0011] In the intelligent safety inspection method for new energy power stations described in this invention, the dynamic inspection path further includes: a secondary inspection path; The step of dynamically planning the path based on the number of workers in the multiple inspection areas to obtain the dynamic inspection path includes: When the drone reaches the center of the target area, it acquires the location information of all personnel operating within the target area. The distance to each worker is calculated based on the location information of all workers within the target area; the distance to each worker is the distance between each worker and the center point of the target area. Based on the distance of each operator, a path is planned for the target area to obtain the secondary inspection path.

[0012] In the intelligent safety inspection method for new energy power stations described in this invention, the method further includes: Determine whether the conditions for returning to base are met; If the return conditions are met, then return to the hangar center.

[0013] In the intelligent safety inspection method for new energy power stations described in this invention, the return conditions include: completing the inspection of all inspection areas or the drone's battery level reaching the warning value; If the return condition is the completion of inspection of all inspection areas, then the inspection task of the UAV has been completed. If the return condition is that the drone's battery level reaches the warning value, then after the drone returns to the hangar center, it will be charged, and after the drone is charged to the set battery level, the inspection mission will be restarted.

[0014] In the intelligent safety inspection method for new energy power stations described in this invention, the step of restarting the inspection task includes: Based on the dynamic inspection path, the drone excludes areas that have already been inspected that day, replans the remaining inspection areas, and conducts inspections according to the replanned path until all inspection areas are completed before returning to base.

[0015] This invention also provides an intelligent safety inspection system for new energy power stations, comprising: a drone, a hangar center, and a cloud server; The drone is used to: determine whether the inspection conditions are met; if not, the drone inspection task will not be started; if the conditions are met, the drone inspection task will be started. After initiating the drone inspection mission, the inspection path is dynamically planned and generated. Intelligent safety inspections of new energy power stations are carried out based on the dynamic inspection path, and personnel operation image information in the target area is collected in real time during the inspection process. The personnel operation image information is transmitted back to the hangar center; The hangar center is used to transmit the personnel operation image information to the cloud server; The cloud server is used for: The system identifies safety hazards in the personnel work image information, determines hazard images when unsafe behaviors are identified, and marks key information of the hazard images. Based on the aforementioned key information, identify the workers involved in the unsafe acts and their personnel information; Based on the information of the operators and their personnel, a safety hazard warning signal is output.

[0016] The intelligent safety inspection method and system for new energy power stations implemented in this invention have the following beneficial effects: It includes: determining whether inspection conditions are met; if so, initiating a drone inspection task; generating a dynamic inspection path; conducting intelligent safety inspections of the new energy power station based on the dynamic inspection path, and collecting real-time personnel operation image information in the target area; transmitting the personnel operation image information to a cloud server through a hangar center; the cloud server identifying unsafe behaviors in the personnel operation image information and marking key information of the hazard images, determining the personnel and their information based on the key information, and outputting a safety hazard warning signal. This invention achieves full coverage of drone inspections through real-time dynamic path planning with minimal time consumption, improving the efficiency of drone safety inspections. Simultaneously, it identifies and reminds users of existing hazards, promptly corrects personnel violations, significantly improves the safety supervision efficiency and production safety level of new energy power stations, and ensures energy security and green low-carbon development. Attached Figure Description

[0017] The present invention will be further described below with reference to the accompanying drawings and embodiments. In the accompanying drawings: Figure 1 This is a flowchart illustrating the intelligent safety inspection method for new energy power stations provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the path for unmanned aerial vehicle (UAV) safety inspection provided in an embodiment of the present invention; Figure 3 This is an architecture diagram of the intelligent safety inspection system for new energy power stations provided in an embodiment of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] To address the problems in safety supervision and inspection of new energy power plants such as photovoltaic and wind power plants, this invention provides an intelligent safety inspection method for new energy power plants. This method is based on dynamic path planning for inspection, and can dynamically plan the inspection path of drones according to the location of operators, identify hidden dangers in real time, and carry out timely control.

[0020] refer to Figure 1 The intelligent safety inspection method for new energy power stations provided by this invention includes the following steps: Step S10: Determine whether the drone meets the inspection conditions. If it does not meet the conditions, do not start the drone inspection task. If it does meet the conditions, start the drone inspection task.

[0021] Optionally, in this embodiment of the invention, the inspection conditions include: meteorological conditions and drone equipment conditions. Meteorological conditions include, but are not limited to, local wind speed and rainfall. Drone equipment conditions include, for example, the drone's battery level.

[0022] Preferably, determining whether a drone meets the inspection conditions includes: obtaining the current time information; determining whether it is within the inspection interval based on the current time information; if not, the inspection conditions are not met; if so, obtaining the current meteorological information and drone equipment information; determining whether the meteorological conditions are met based on the current meteorological information and whether the drone equipment conditions are met based on the drone equipment information; if both the meteorological conditions and the drone equipment conditions are met, the inspection conditions are determined to be met; otherwise, the inspection conditions are determined to be not met.

[0023] Specifically, the time interval T for drone inspections can be preset, for example, 9:00 AM to 12:00 PM and 2:00 PM to 4:00 PM. The time interval can be adjusted based on local sunlight conditions. Before initiating the drone inspection condition judgment, it is first confirmed whether the current time is within the preset time interval T. If it is not within the time interval T, the inspection condition judgment will not be initiated; otherwise, it will be initiated. The inspection condition judgment involves determining whether both weather conditions and drone equipment conditions are met. If not, the drone inspection task will not be initiated; if they are met, the drone inspection task will be initiated.

[0024] Step S20: After starting the UAV inspection mission, dynamically plan the inspection path and generate the dynamic inspection path.

[0025] Optionally, in this embodiment of the invention, dynamically planning and generating a dynamic inspection path includes: obtaining construction drawings of the new energy power station; dividing the construction area according to the construction drawings of the new energy power station to obtain multiple inspection areas and extracting the center point coordinate information of the multiple inspection areas; obtaining the number of workers in the multiple inspection areas; and dynamically planning the path according to the number of workers in the multiple inspection areas to obtain a dynamic inspection path.

[0026] Preferably, obtaining the number of workers in multiple inspection areas includes: obtaining the location information of workers in multiple inspection areas; and performing a headcount based on the location information of workers in multiple inspection areas to obtain the total number of workers in multiple inspection areas. Preferably, the location information of the workers in this invention can be obtained based on the location of their mobile phones or wristbands.

[0027] Optionally, in this embodiment of the invention, the dynamic inspection path includes: a primary inspection path; dynamically planning the path based on the number of workers in multiple inspection areas to obtain the dynamic inspection path includes: sorting the multiple inspection areas from highest to lowest according to the number of workers to obtain the primary inspection path; after obtaining the primary inspection path, the UAV performs inspection based on the primary inspection path and the center point coordinate information of the multiple inspection areas. Further, in this embodiment of the invention, the dynamic inspection path also includes: a secondary inspection path. Specifically, dynamically planning the path based on the number of workers in multiple inspection areas to obtain the dynamic inspection path includes: when the UAV reaches the airspace above the center point of the target area, acquiring the positioning information of all workers in the target area; calculating the distance of each worker based on the positioning information of all workers in the target area; the distance of each worker is the distance between each worker and the center point of the target area; and planning the path for the target area based on the distance of each worker to obtain the secondary inspection path.

[0028] After initiating a drone inspection mission, the drone first needs to dynamically plan and generate an inspection path, and then perform the inspection according to the generated path. The details are as follows: First, divide the inspection area. Taking a photovoltaic power station as an example, the construction area of ​​a photovoltaic power station under construction generally includes: one step-up substation, multiple photovoltaic areas, and multiple collection lines, with a total construction area of ​​n (n≥2, an integer), R i Let i represent the i-th region, where i = 1, 2, ..., n. Based on the construction drawings of the photovoltaic power station, the boundaries of each construction area are delineated on the map of the safety supervision and inspection system, resulting in multiple inspection areas. The coordinate information of the center point of each inspection area (Ri) is then extracted. 1_c R 2_c R n_cThe center point coordinates of a single inspection area include two horizontal directions and one vertical direction (R). i_cx R i_cy R i_cz ).

[0029] Secondly, after dividing the inspection areas, inspection routes are determined. Preferably, in this embodiment of the invention, the safety inspection strategy for drones can be summarized as: "Fly where there are many people (Level 1 inspection task)," and "Fly where there are people" (Level 2 inspection task). Therefore, route planning can be performed based on this safety inspection strategy. Specifically, among the various inspection areas (also known as work areas), the inspection areas are sorted according to the number of people in each area (the number of people in each area is N1, N2, ..., N). n , where N i (R represents the number of people in the i-th region), and prioritizes the region with the most people flying (defined as R). k (where k is the symbol for the area with the most people), followed by the area with the second most flying personnel, and so on. This inspection path is the first-level inspection path. When the drone reaches the center point of an inspection area (i.e., the target area referred to in this invention), a second-level inspection task is initiated. Within this inspection area, an inspection path is determined based on the distance between the operators and the drone. This is the second-level inspection path. The specific process is as follows: Figure 2 As shown.

[0030] Specifically, such as Figure 2 As shown, the system uses location information from the mobile phones or wristbands worn by the operators to count the number of workers in each inspection area of ​​the new energy power station. Then, based on the number of workers in each inspection area, the areas are sorted in descending order to obtain the primary inspection path. When the inspection task starts on a given day, the area with the most workers is inspected first. Provided the drone's battery power allows, inspections are carried out sequentially according to the number of workers in each area, achieving "flying where there are the most people."

[0031] like Figure 2 As shown, when the drone reaches the center point of a certain inspection area on the primary inspection path, the secondary inspection path planning is initiated. Specifically, the positioning coordinates (R) of all personnel within the inspection area are extracted in real time using the positioning information from the mobile phones or wristbands worn by the operators. i_Pj_x R i_Pj_y R i_Pj_z The distance between the operator and the center point of the inspection area (i.e., the location of the drone) is calculated to obtain the operator's distance. The operator's distance is calculated using the following formula: ; After calculating the distances between all personnel and the center point within the inspection area using the above formula, the calculated distances are sorted to determine the personnel closest to them. The drone then flies from the center of the inspection area to the nearest personnel (e.g., ...). Figure 2 The drone then performs aerial inspections over the worker (Pk). After reaching the worker's location, the distance between that worker and the remaining workers is recalculated, and the calculated distances are then sorted to determine the worker closest to that worker (e.g., Pk). Figure 2 The drone flies to the nearest worker (i.e., worker Pi) within the inspection area (i.e., worker Pk) to conduct an inspection. This process is repeated for all workers within the inspection area, achieving "flying wherever there are people."

[0032] Step S30: Conduct intelligent safety inspections of new energy power stations based on dynamic inspection paths, and collect real-time image information of personnel working in the target area during the inspection process.

[0033] In this embodiment of the invention, when the drone is conducting intelligent safety inspections, it can acquire images through an image acquisition module (installed on the drone) to realize real-time acquisition of personnel operation image information in the target area during the inspection process.

[0034] Step S40: The personnel operation image information is sent back to the hangar center, and then transmitted to the cloud server through the hangar center.

[0035] Optionally, in this embodiment of the invention, the hangar center can transmit images of personnel working to the cloud server in real time via a wireless router or wired network.

[0036] Step S50: The cloud server identifies safety hazards in the personnel operation image information, and when unsafe behavior is identified, it determines the hazard image and marks the key information of the hazard image.

[0037] In this embodiment of the invention, a personnel behavior visual recognition algorithm is deployed on the cloud server. This algorithm intelligently identifies potential hazards in real-time video transmitted from the site, thereby identifying unsafe behaviors of workers. Examples include workers not wearing or using safety belts properly while working at heights, and workers handling electrical work not wearing appropriate personal protective equipment. Once an unsafe behavior is identified, the image is defined as a hazard image. By comparing the coordinates of the drone inspection with the coordinates of the inspection area, key information such as the inspection area and time is marked on the identified hazard image.

[0038] Step S60: The cloud server determines the personnel involved in the unsafe act and their information based on key information. This personnel information includes: the name of the work unit, the individual's name, and their position.

[0039] In this embodiment of the invention, by intelligently identifying the hazard images, the work unit and personnel in the inspection area are found based on key information such as the inspection area and time, thereby determining their work unit name, personal name, position, etc.

[0040] Step S70: The cloud server outputs a safety hazard warning signal based on the operator and their personnel information.

[0041] Optionally, in this embodiment of the invention, the cloud server can use safety hazard warning signals such as SMS reminders and drone announcements to promptly remind and correct unsafe behaviors of operators, thereby efficiently managing safety hazards at new energy power plants and effectively preventing safety accidents.

[0042] Furthermore, the intelligent safety inspection method for new energy power stations also includes: determining whether the return-to-base conditions are met; if the return-to-base conditions are met, the drone returns to the hangar center. The return-to-base conditions include: completing the inspection of all inspection areas or the drone's battery level reaching a warning threshold; if the return-to-base condition is completing the inspection of all inspection areas, the drone's inspection task is complete; if the return-to-base condition is the drone's battery level reaching the warning threshold, the drone is charged after returning to the hangar center, and the inspection task is restarted after the drone is charged to a set battery level (e.g., 80%). Optionally, in this embodiment of the invention, restarting the inspection task includes: the drone, based on a dynamic inspection path, excluding areas already inspected that day, replanning the remaining inspection areas, and inspecting according to the replanned path until all inspection areas are completed before returning to base.

[0043] Specifically, the drone will automatically return to base when it has completed all inspection areas or when its battery level reaches the warning threshold. If the drone automatically returns to base due to insufficient battery (i.e., low battery), and after recharging to 80%, it will continue to inspect the remaining areas, excluding those already inspected that day, by reordering the personnel and conducting inspections in sequence, until all remaining inspection areas have been inspected, which is considered the end of one round of inspection.

[0044] refer to Figure 3 The present invention also provides an intelligent safety inspection system for new energy power stations.

[0045] like Figure 3As shown, the intelligent safety inspection system for new energy power stations includes: drones, a hangar center, and a cloud server. The drones communicate wirelessly with the hangar center, and the hangar center communicates with the cloud server via a wireless router or wired network. This intelligent safety inspection system for new energy power stations can support multiple power stations (#1, #2, #3, ..., #N) and multiple drones (#1 drone, #2 drone, #3 drone, ..., #N drone), with one drone configured for each new energy power station. Correspondingly, as... Figure 3 As shown, the hangar center has multiple hangars (Hanger #1, Hanger #2, Hanger #3, ..., Hanger #N), with one hangar corresponding to one drone.

[0046] The drones are used for: determining whether inspection conditions are met; if not, the drone inspection task is not initiated; if met, the drone inspection task is initiated; after initiating the drone inspection task, the inspection path is dynamically planned and generated; intelligent safety inspections of the new energy power stations are conducted based on the dynamic inspection path, and personnel operation image information in the target area is collected in real time during the inspection; the personnel operation image information is transmitted back to the hangar center. The hangar center is used to transmit the personnel operation image information to the cloud server. The cloud server is used for: identifying safety hazards in the personnel operation image information, determining hazard images when unsafe behaviors are identified, and marking key information in the hazard images; determining the personnel involved in the unsafe behavior and their information based on the key information; and outputting safety hazard warning signals based on the personnel and their information.

[0047] Specifically, the specific operational procedures between the various units in the intelligent safety inspection system for new energy power stations can be found in the aforementioned intelligent safety inspection method for new energy power stations, and will not be repeated here.

[0048] This invention addresses the challenges of safety supervision at photovoltaic and wind power plants, which involve numerous workers, dispersed work areas, and diverse high-risk operations. It employs intelligent safety inspection technology using drones with real-time dynamic path planning. The technology utilizes location information from workers' mobile phones or wristbands to count the number of people and their locations in each work area of ​​the power plant. Based on the number of workers in each area, the drone plans a primary inspection path, prioritizing areas with the most workers. Once the drone reaches the center of the work area, a secondary inspection path is dynamically planned based on the distance of workers to the drone, ensuring that all workers in the area are inspected simultaneously using the optimal drone path. Through this two-stage dynamic optimization of inspection paths, drone inspections cover all workers in the shortest possible time, significantly improving the efficiency of drone-based safety inspections.

[0049] Meanwhile, a visual recognition algorithm for unsafe human behavior is deployed in the cloud to intelligently identify the video transmitted back by drones in real time. Violations can be corrected in a timely manner through SMS reminders and drone announcements. This can not only directly prevent accidents from happening and avoid irreparable losses such as casualties, but also prevent equipment damage, ensure power generation efficiency, and significantly improve the safety supervision efficiency and production safety level of new energy power plants, further ensuring energy security and green and low-carbon development.

[0050] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0051] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0052] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0053] The above embodiments are only for illustrating the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the content of the present invention and implement it accordingly. They do not limit the scope of protection of the present invention. All equivalent changes and modifications made within the scope of the claims of the present invention should fall within the scope of the claims of the present invention.

Claims

1. A method for intelligent safety inspection of new energy power stations, characterized in that, Includes the following steps: Determine if the drone meets the inspection conditions. If not, do not start the drone inspection task. If it does, start the drone inspection task. After initiating the drone inspection mission, the inspection path is dynamically planned and generated. Intelligent safety inspections of new energy power stations are carried out based on the dynamic inspection path, and personnel operation image information in the target area is collected in real time during the inspection process. The personnel operation image information is transmitted back to the hangar center, and then transmitted to the cloud server through the hangar center. The cloud server identifies safety hazards in the personnel work image information, and when unsafe behavior is identified, determines the hazard image and marks the key information of the hazard image; The cloud server determines the personnel involved in the unsafe act and their personnel information based on the key information. The cloud server outputs a safety hazard warning signal based on the operator and their personnel information.

2. The intelligent safety inspection method for new energy power stations according to claim 1, characterized in that, The inspection conditions include: weather conditions and drone equipment conditions; The determination of whether a drone meets the inspection criteria includes: Determine and obtain the current time information; Determine whether the area is within the inspection interval based on the current time information; If not, then the inspection conditions are not met; If so, obtain the current weather information and drone equipment information; Determine whether the meteorological conditions are met based on the current meteorological information, and determine whether the drone equipment conditions are met based on the drone equipment information; If the meteorological conditions and the UAV equipment conditions are met, then the inspection conditions are determined to be met; otherwise, the inspection conditions are determined not to be met.

3. The intelligent safety inspection method for new energy power stations according to claim 1, characterized in that, The dynamic planning and generation of inspection paths includes: Obtain the construction drawings of the aforementioned new energy power station; The construction area is divided according to the construction drawings of the new energy power station, multiple inspection areas are obtained, and the center point coordinate information of the multiple inspection areas is extracted. Obtain the number of workers operating in the multiple inspection areas; The dynamic inspection path is obtained by dynamically planning the path based on the number of workers in the multiple inspection areas.

4. The intelligent safety inspection method for new energy power stations according to claim 3, characterized in that, The number of personnel acquiring the multiple inspection areas includes: Obtain the location information of the workers in the multiple inspection areas; The number of workers in the multiple inspection areas is obtained by counting the number of workers in the multiple inspection areas based on the location information of the workers.

5. The intelligent safety inspection method for new energy power stations according to claim 3, characterized in that, The dynamic inspection path includes: a primary inspection path; The step of dynamically planning the path based on the number of workers in the multiple inspection areas to obtain the dynamic inspection path includes: The multiple inspection areas are sorted from highest to lowest according to the number of operators to obtain a primary inspection path; After obtaining the primary inspection path, the UAV performs inspections based on the primary inspection path and the center point coordinates of the multiple inspection areas.

6. The intelligent safety inspection method for new energy power stations according to claim 5, characterized in that, The dynamic inspection path also includes: a secondary inspection path; The step of dynamically planning the path based on the number of workers in the multiple inspection areas to obtain the dynamic inspection path includes: When the drone reaches the center of the target area, it acquires the location information of all personnel operating within the target area. The distance to each worker is calculated based on the location information of all workers within the target area; the distance to each worker is the distance between each worker and the center point of the target area. Based on the distance of each operator, a path is planned for the target area to obtain the secondary inspection path.

7. The intelligent safety inspection method for new energy power stations according to any one of claims 1-6, characterized in that, The method further includes: Determine whether the conditions for returning to base are met; If the return conditions are met, then return to the hangar center.

8. The intelligent safety inspection method for new energy power stations according to claim 7, characterized in that, The conditions for returning to base include: completing the inspection of all inspection areas or the drone's battery level reaching the warning value; If the return condition is the completion of inspection of all inspection areas, then the inspection task of the UAV has been completed. If the return condition is that the drone's battery level reaches the warning value, then after the drone returns to the hangar center, it will be charged, and after the drone is charged to the set battery level, the inspection mission will be restarted.

9. The intelligent safety inspection method for new energy power stations according to claim 8, characterized in that, The restart of the inspection task includes: Based on the dynamic inspection path, the drone excludes areas that have already been inspected that day, replans the remaining inspection areas, and conducts inspections according to the replanned path until all inspection areas are completed before returning to base.

10. A smart safety inspection system for new energy power stations, characterized in that, include: Drones, hangar centers, and cloud servers; The drone is used to: determine whether the inspection conditions are met; if not, the drone inspection task will not be started; if the conditions are met, the drone inspection task will be started. After initiating the drone inspection mission, the inspection path is dynamically planned and generated. Intelligent safety inspections of new energy power stations are carried out based on the dynamic inspection path, and personnel operation image information in the target area is collected in real time during the inspection process. The personnel operation image information is transmitted back to the hangar center; The hangar center is used to transmit the personnel operation image information to the cloud server; The cloud server is used for: The system identifies safety hazards in the personnel work image information, determines hazard images when unsafe behaviors are identified, and marks key information of the hazard images. Based on the aforementioned key information, identify the workers involved in the unsafe acts and their personnel information; Based on the information of the operators and their personnel, a safety hazard warning signal is output.

Images