Method, device, program product and equipment for predicting safety risks of offshore photovoltaics

Abstract

The present disclosure provides a kind of offshore photovoltaic safety risk prediction method, device, program product and equipment, it is related to information processing technical field.The method comprises: obtaining the position information of multiple construction areas of offshore photovoltaic construction site, according to the position information of each construction area Determine the distance between each construction area and sea area;According to the distance between each construction area and sea area, the operation type of each construction area, determine the risk coefficient of each construction area, and determine the alarm threshold according to the risk coefficient of each construction area;Obtain the monitoring information of each construction area, predict the safety risk value of each construction area according to the monitoring information;In response to the safety risk value of any construction area reaches the alarm threshold of this construction area, generate the alarm information for this construction area.The present disclosure can improve the safety of offshore photovoltaic project, reduce risk.

Description

Technical Field

[0001] This disclosure relates to the field of information processing technology, and in particular to a method for predicting safety risks of marine photovoltaic power generation, a device for predicting safety risks of marine photovoltaic power generation, a computer program product, and an electronic device. Background Technology

[0002] Offshore photovoltaic construction sites present complex environments and significant construction challenges, increasing the risk of safety hazards that could endanger personal safety and property. Current technologies typically issue alarms upon detecting anomalies, but this approach is reactive, unreliable, and fails to effectively guarantee project safety. Summary of the Invention

[0003] This disclosure provides a method for predicting safety risks of offshore photovoltaic projects, an apparatus for predicting safety risks of offshore photovoltaic projects, a computer program product, and electronic equipment, so as to improve the safety of offshore photovoltaic projects to at least a certain extent.

[0004] According to a first aspect of this disclosure, a method for predicting safety risks in offshore photovoltaic (PV) projects is provided. The method includes: acquiring location information of multiple construction areas at an offshore PV construction site; determining the distance between each construction area and the sea area based on the location information of each construction area; determining a risk coefficient for each construction area based on the distance between each construction area and the sea area and the operation type of each construction area; and determining an alarm threshold based on the risk coefficient of each construction area; acquiring monitoring information for each construction area; predicting a safety risk value for each construction area based on the monitoring information; and generating alarm information for any construction area when the safety risk value of any construction area reaches the alarm threshold for that construction area.

[0005] According to a second aspect of this disclosure, a safety risk prediction device for offshore photovoltaic (PV) projects is provided. The device includes: a location information processing module configured to acquire location information of multiple construction areas at an offshore PV construction site, and determine the distance between each construction area and the sea area based on the location information of each construction area; a risk coefficient processing module configured to determine a risk coefficient for each construction area based on the distance between each construction area and the sea area and the operation type of each construction area, and determine an alarm threshold based on the risk coefficient of each construction area; a safety monitoring module configured to acquire monitoring information for each construction area, and predict the safety risk value of each construction area based on the monitoring information; and an alarm processing module configured to generate alarm information for any construction area when the safety risk value of any construction area reaches the alarm threshold for that construction area.

[0006] According to a third aspect of this disclosure, a computer program product is provided, including a computer program that, when executed by a processor, implements the method of the first aspect described above and possible implementations thereof.

[0007] According to a fourth aspect of this disclosure, an electronic device is provided, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform the method of the first aspect and possible implementations thereof by executing the executable instructions.

[0008] The technical solution disclosed herein has the following beneficial effects:

[0009] This system acquires location information for multiple construction areas at an offshore photovoltaic (PV) construction site, determines the distance of each construction area from the sea based on its location, and determines the risk coefficient for each construction area based on its distance from the sea and the type of work performed there. An alarm threshold is then set based on this risk coefficient. Monitoring information for each construction area is acquired, and its safety risk value is predicted. When the safety risk value of any construction area reaches its alarm threshold, an alarm is generated for that area. This allows for the application of appropriate safety risk alarm intensity based on the location characteristics and work types of different construction areas, predicting safety risk values ​​based on monitoring information, and generating corresponding alarms when the safety risk value reaches the alarm threshold. This facilitates the timely detection of potential safety risks, enabling timely intervention to reduce or eliminate safety hazards and improve the safety of offshore PV projects. Attached Figure Description

[0010] Figure 1 A schematic diagram of a scenario architecture in this exemplary embodiment is shown.

[0011] Figure 2 A flowchart illustrating a safety risk prediction method for offshore photovoltaic systems in this exemplary embodiment is shown.

[0012] Figure 3 A flowchart illustrating the determination of a risk coefficient in this exemplary embodiment is shown.

[0013] Figure 4 A flowchart illustrating one method for determining a security risk value in this exemplary embodiment is shown.

[0014] Figure 5 A schematic diagram of a safety risk prediction device for marine photovoltaic systems is shown in this exemplary embodiment.

[0015] Figure 6 A schematic diagram of the structure of an electronic device in this exemplary embodiment is shown. Detailed Implementation

[0016] Exemplary embodiments of this disclosure will be described more fully below with reference to the accompanying drawings.

[0017] The accompanying drawings are schematic illustrations of this disclosure and are not necessarily drawn to scale. Some block diagrams shown in the drawings may be functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in hardware modules or integrated circuits, or in networks, processors, or microcontrollers. Implementations can be carried out in various forms and should not be construed as limited to the examples set forth herein. The features, structures, or characteristics described in this disclosure can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough description of embodiments of this disclosure. However, those skilled in the art will recognize that one or more specific details may be omitted when implementing the technical solutions of this disclosure, or other methods, components, apparatuses, steps, etc., may be used to replace one or more specific details.

[0018] Exemplary embodiments of this disclosure provide a method for predicting safety risks in offshore photovoltaic projects, aiming to reduce the risks of offshore photovoltaic projects and improve their safety.

[0019] Figure 1 The scenario architecture of this exemplary embodiment is illustrated. The scenario architecture 100 may include construction areas 1101, 1102, and 1103, and a project center 120. The construction site of an offshore photovoltaic project is relatively complex, involving offshore construction areas (e.g., construction area 1101), construction areas at the sea-land interface (e.g., construction area 1102), and onshore construction areas (e.g., construction area 1103). Furthermore, the types of work in different construction areas are usually different. This exemplary embodiment can manage each construction area 1101, 1102, and 1103 separately. The project center 120 is the central part of the entire scenario architecture 100, used for monitoring, safety risk prediction, alarm prompts, and other management of construction areas 1101, 1102, and 1103. The project center 120 may be located at a construction command center on land or on a floating platform, and may include one or more components such as a server, database, project center terminal, and monitoring screen. Wireless or wired communication links can be deployed between construction areas 1101, 1102, 1103 and project center 120 to enable data transmission. The method in this exemplary embodiment can be executed by project center 120.

[0020] In one implementation method, the safety risk prediction method for offshore photovoltaic systems can refer to... Figure 2 As shown, the procedure includes the following steps S210 to S240:

[0021] Step S210: Obtain the location information of multiple construction areas at the offshore photovoltaic construction site, and determine the distance between each construction area and the sea area based on the location information of each construction area.

[0022] Step S220: Determine the risk coefficient of each construction area based on the distance between each construction area and the sea area and the type of operation in each construction area, and determine the alarm threshold based on the risk coefficient of each construction area.

[0023] Step S230: Obtain monitoring information for each construction area and predict the safety risk value for each construction area based on the monitoring information;

[0024] Step S240: In response to the safety risk value of any construction area reaching the alarm threshold of that construction area, generate alarm information for that construction area.

[0025] based on Figure 2 This method involves acquiring location information of multiple construction areas at an offshore photovoltaic (PV) construction site, determining the distance between each construction area and the sea area based on its location information, determining the risk coefficient of each construction area based on its distance from the sea and the type of operation, and then determining an alarm threshold based on the risk coefficient. Monitoring information for each construction area is acquired, and the safety risk value of each construction area is predicted based on this information. In response to any construction area's safety risk value reaching its alarm threshold, an alarm message is generated for that construction area. Therefore, it is possible to adopt appropriate safety risk alarm intensity based on the location characteristics and operation type of different construction areas, predict safety risk values ​​based on monitoring information, and generate corresponding alarm messages when the safety risk value reaches the alarm threshold. This facilitates the timely detection of potential safety risks, enables the implementation of countermeasures to reduce or eliminate safety hazards, and improves the safety of offshore PV projects.

[0026] The following is about Figure 2 Each step is explained in detail.

[0027] refer to Figure 2 In step S210, the location information of multiple construction areas at the offshore photovoltaic construction site is obtained, and the distance between each construction area and the sea area is determined based on the location information of each construction area.

[0028] The distance between the construction area and the coastline, i.e., the distance between the construction area and the sea, can be determined based on the location information of the construction area. For example, the distance between a construction area located on land and the sea is a positive value; the distance between a construction area located at the boundary between land and water and the sea is a positive value or 0; and the distance between a construction area located at sea can be 0 or negative. In one implementation, the distance between a construction area located at sea and the sea can be the opposite of the water depth; for example, if a construction area is located in water with a depth of 10 meters, its distance from the sea can be -10 meters.

[0029] Continue to refer to Figure 2 In step S220, the risk coefficient of each construction area is determined based on the distance between each construction area and the sea area and the operation type of each construction area, and the alarm threshold is determined based on the risk coefficient of each construction area.

[0030] The risk coefficient indicates the degree to which risks are likely to occur in the construction area, while the alarm threshold is a threshold used to measure the safety risk value. When the safety risk value reaches the alarm threshold, it indicates that there is a high probability of risks occurring in the construction area or that there are serious safety hazards. Generally, the higher the risk coefficient and the lower the alarm threshold, the stricter the safety control measures to be taken for the construction area.

[0031] The distance between the construction area and the sea area can be negatively correlated with the risk coefficient; that is, the smaller the distance, the closer the construction area is to the sea area, and the higher the corresponding risk coefficient. Furthermore, the risk coefficient is also related to the type of work being done in the construction area. Different types of work have different risk levels; the higher the risk level, the higher the risk coefficient of the construction area. This exemplary implementation can determine the risk coefficient of each construction area by combining both the distance between the construction area and the sea area and the type of work being done in the construction area.

[0032] In one implementation, reference Figure 3 As shown, determining the risk coefficient for each construction area based on its distance from the sea and the type of work performed in each construction area may include the following steps S310 to S330:

[0033] Step S310: Set the highest risk coefficient when the distance between the construction area and the sea area is 0 and the operation type is the highest risk operation type;

[0034] Step S320: Set the first risk attenuation value corresponding to different distances, and set the second risk attenuation value corresponding to different work types;

[0035] Step S330: Based on the distance between each construction area and the sea area and the operation type of each construction area, determine the first risk attenuation value and the second risk attenuation value corresponding to each construction area, and attenuate based on the highest risk coefficient to obtain the risk coefficient of each construction area.

[0036] This can be understood as follows: if the distance between a construction area and the sea is 0, and the operation type in that construction area is the highest-risk operation type, this situation is called the highest-risk situation. Under the highest-risk situation, the construction area has the highest risk coefficient. The value of the highest-risk coefficient can be preset, based on experience or specific circumstances, such as setting it to 5. Furthermore, a first risk attenuation value can be set for different distances, representing the degree to which the risk coefficient decreases as the construction area moves further away from the sea. For example, the attenuation value can be set to 1 for every 50 meters or every 100 meters. A second risk attenuation value can also be set for different operation types, such as a attenuation value of 1 for each level of risk decrease. Thus, based on the distance between each construction area and the sea, and the operation type of each construction area, the first and second risk attenuation values ​​compared to the highest-risk situation can be determined. These attenuation values ​​are then applied to the highest-risk coefficient, resulting in the risk coefficient for each construction area. This allows for accurate assessment of the risk coefficient for each construction area.

[0037] In one implementation, the process of determining a first risk attenuation value and a second risk attenuation value for each construction area based on the distance between each construction area and the sea area, and the type of operation in each construction area, and then attenuating the risk based on the highest risk coefficient to obtain the risk coefficient for each construction area, may include the following steps:

[0038] Based on the distance between each construction area and the sea area, and the type of operation in each construction area, determine the first risk attenuation value and the second risk attenuation value for each construction area, and select the minimum value between them. Subtract the minimum value from the maximum risk coefficient to obtain the risk coefficient for each construction area.

[0039] For example, if a construction area is 300 meters from the sea, its first risk attenuation value is 3. The risk level of its work type is one level lower than the highest risk level, corresponding to a second risk attenuation value of 1. Taking the minimum value of 1, and subtracting the minimum value from the highest risk coefficient of 5, we get a risk coefficient of 4 for this construction area. It can be seen that by selecting the minimum of the first and second risk attenuation values ​​and subtracting it from the highest risk coefficient, we can obtain the risk coefficient for each construction area. This ensures that the construction area has a relatively high risk coefficient. In other words, considering both the distance between the construction area and the sea, and the type of work involved, we pay more attention to factors that are more likely to cause safety risks and tend to adopt stricter risk control measures to ensure safety.

[0040] Given a determined risk coefficient, the corresponding alarm threshold can be further determined. For example, a mapping relationship between the risk coefficient and the alarm threshold can be pre-defined; the two can be negatively correlated, such as a negative linear function relationship. Based on this mapping relationship, the alarm threshold corresponding to the risk coefficient of each construction area can be calculated, thus obtaining the alarm threshold for each construction area.

[0041] Continue to refer to Figure 2 In step S230, monitoring information for each construction area is obtained, and the safety risk value for each construction area is predicted based on the monitoring information.

[0042] For example, the safety risk value can be determined based on the degree to which the monitoring information deviates from the standard value or standard range; the greater the deviation, the higher the safety risk value.

[0043] In one implementation, monitoring information for each construction area is acquired, and the safety risk value for each construction area is predicted based on the monitoring information, including:

[0044] The monitoring cycle for each construction area is determined based on historical alarm information for that area.

[0045] Monitoring information for each construction area is obtained according to the monitoring cycle of each construction area, and the safety risk value of each construction area is predicted based on the monitoring information.

[0046] The monitoring cycle can be considered as the size of a time window. Monitoring information within each time window is analyzed to predict safety risk values. Historical alarm frequency can be calculated based on historical alarm information for each construction area. Construction areas with more frequent alarms should have shorter monitoring cycles. Conversely, construction areas with less frequent alarms should have longer monitoring cycles to reduce communication and data processing pressure.

[0047] For example, a pre-trained alarm analysis model (a machine learning model) can be used to analyze the historical alarm information of each construction area and output the monitoring cycle for each construction area.

[0048] In one implementation, reference Figure 4 As shown, the process of obtaining monitoring information for each construction area and predicting the safety risk value for each construction area based on the monitoring information may include the following steps S410 to S440:

[0049] Step S410: Obtain environmental monitoring information and operation monitoring information for each construction area;

[0050] Step S420: Determine the first safety risk value for each construction area based on environmental monitoring information;

[0051] Step S430: Determine the second safety risk value for each construction area based on the operation monitoring information;

[0052] Step S440: Determine the final safety risk value based on the first and second safety risk values ​​for each construction area.

[0053] Environmental monitoring information includes data on various environmental factors such as temperature, sunlight, surge, tides, and precipitation, reflecting environmental changes. Operational monitoring information involves monitoring indicators and parameters during the operational process, such as operation duration, the location and angle of a work object, and equipment parameters, reflecting the actual operational situation. Based on environmental monitoring information, a primary safety risk value is determined for each construction area, representing potential risks from the environment. A secondary safety risk value is determined for each construction area based on operational monitoring information, representing potential risks arising from the operational process. For example, improper work practices by construction personnel may cause some operational monitoring data to deviate from normal levels, thus determining the secondary safety risk value and indicating the existence of operational safety hazards.

[0054] In one implementation, a pre-trained first risk prediction model (a machine learning model) can be used to process environmental monitoring information, such as inputting environmental monitoring information into the first risk prediction model and outputting a first safety risk value.

[0055] In one implementation, a pre-trained second risk prediction model (a machine learning model) can be used to process the operation monitoring information, such as inputting the operation monitoring information into the second risk prediction model and outputting a second safety risk value.

[0056] Given a first risk prediction value and a second risk prediction value, the two can be combined to obtain the final safety risk value. For example, the two can be added together or their average value can be calculated to obtain the final safety risk value.

[0057] In one implementation, determining the final safety risk value based on the first and second safety risk values ​​for each construction area may include the following steps:

[0058] Based on the distance between each construction area and the sea area, the risk prediction weight for each construction area is determined;

[0059] The first and second safety risk values ​​of each construction area are weighted according to the risk prediction weight of each construction area to obtain the final safety risk value of each construction area.

[0060] The risk prediction weights are used to balance the environmental and operational risks in the final safety risk value. They can include a first weight corresponding to the first safety risk value and a second weight corresponding to the second safety risk value, with the sum of the first and second weights being 1. If the construction area is far from the sea, it indicates less environmental impact; in this case, the first weight can be appropriately reduced and the second weight increased, indicating a greater focus on operational risks. Conversely, if the construction area is close to the sea, it indicates greater environmental impact; in this case, the first weight can be appropriately increased and the second weight decreased, indicating increased focus on environmental risks. For example, the maximum value of the first weight can be set to 0.6 and the minimum value to 0.2 (i.e., the minimum value of the second weight is 0.4 and the maximum value is 0.8), and a decay relationship can be established between the distance between the construction area and the sea and the first weight. That is, as the distance increases, the first weight decreases; for example, for every 50 meters increase in distance, the first weight decreases by 0.1. Therefore, based on the distance between each construction area and the sea, the first and second weights for each construction area can be calculated, and the first and second safety risk values ​​can be weighted to obtain the final safety risk value for each construction area.

[0061] Continue to refer to Figure 2 In step S240, in response to the safety risk value of any construction area reaching the alarm threshold of that construction area, alarm information is generated for that construction area.

[0062] It should be understood that if only one security risk value (such as a first security risk value or a second security risk value) is predicted in step S230, then that security risk value is compared with an alarm threshold to determine whether to generate an alarm message. If multiple security risk values ​​(such as a first security risk value and a second security risk value) are predicted, then the final security risk value is calculated, and the final security risk value is compared with an alarm threshold to determine whether to generate an alarm message.

[0063] When the safety risk value of any construction area reaches the alarm threshold for that construction area, it indicates that there is a high safety risk in that construction area. An alarm message for that construction area can be generated and sent to relevant personnel in that construction area, such as to the mobile phones of construction workers, work computers and other terminal devices in the construction area, so as to serve as an early warning.

[0064] In one implementation, the security risk prediction method may further include the following steps:

[0065] In response to any construction area's safety risk value reaching the alarm threshold for that construction area, and generating alarm information for that construction area, risk warning information for other construction areas is also generated.

[0066] Among them, the alarm level of risk warning information is lower than that of alarm information. It is used to remind other construction areas to pay attention to and eliminate related safety hazards, so as to play a role in preventing problems before they occur.

[0067] Exemplary embodiments of this disclosure also provide a safety risk prediction device for marine photovoltaic systems, with reference to... Figure 5 As shown, the safety risk prediction device 500 may include the following program modules:

[0068] The location information processing module 510 is configured to acquire the location information of multiple construction areas at the offshore photovoltaic construction site, and determine the distance between each construction area and the sea area based on the location information of each construction area.

[0069] The risk coefficient processing module 520 is configured to determine the risk coefficient of each construction area based on the distance between each construction area and the sea area and the type of operation in each construction area, and to determine the alarm threshold based on the risk coefficient of each construction area.

[0070] Safety monitoring module 530 is configured to acquire monitoring information for each construction area and predict the safety risk value of each construction area based on the monitoring information;

[0071] The alarm processing module 540 is configured to generate alarm information for any construction area when the safety risk value of that construction area reaches the alarm threshold of that construction area.

[0072] In one implementation, acquiring monitoring information for each construction area and predicting the safety risk value for each construction area based on the monitoring information includes:

[0073] Obtain environmental monitoring information and operational monitoring information for each construction area;

[0074] The first safety risk value for each construction area is determined based on the environmental monitoring information.

[0075] A second safety risk value is determined for each construction area based on the aforementioned work monitoring information;

[0076] The final safety risk value is determined based on the first and second safety risk values ​​for each construction area.

[0077] In one implementation, determining the final safety risk value based on a first safety risk value and a second safety risk value for each construction area includes:

[0078] Based on the distance between each construction area and the sea area, the risk prediction weight for each construction area is determined;

[0079] The first and second safety risk values ​​of each construction area are weighted according to the risk prediction weight of each construction area to obtain the final safety risk value of each construction area.

[0080] In one implementation, determining the risk coefficient for each construction area based on its distance from the sea and the type of work performed in each construction area includes:

[0081] The highest risk coefficient is set when the distance between the construction area and the sea is 0 and the operation type is the highest risk operation type.

[0082] Set a first risk attenuation value for different distances, and set a second risk attenuation value for different job types;

[0083] Based on the distance between each construction area and the sea area, and the type of operation in each construction area, the first risk attenuation value and the second risk attenuation value corresponding to each construction area are determined, and attenuation is performed based on the highest risk coefficient to obtain the risk coefficient of each construction area.

[0084] In one implementation, the step of determining a first risk attenuation value and a second risk attenuation value for each construction area based on the distance between each construction area and the sea area and the type of operation in each construction area, and then attenuating the risk based on the highest risk coefficient to obtain a risk coefficient for each construction area, includes:

[0085] Based on the distance between each construction area and the sea area, and the type of operation in each construction area, determine the first risk attenuation value and the second risk attenuation value for each construction area, and select the minimum value between them. Subtract the minimum value from the maximum risk coefficient to obtain the risk coefficient for each construction area.

[0086] In one implementation, acquiring monitoring information for each construction area and predicting the safety risk value for each construction area based on the monitoring information includes:

[0087] The monitoring cycle for each construction area is determined based on historical alarm information for that area.

[0088] Monitoring information for each construction area is obtained according to the monitoring cycle of each construction area, and the safety risk value of each construction area is predicted based on the monitoring information.

[0089] In one embodiment, the alarm processing module 540 is further configured to generate risk warning information for other construction areas when an alarm message for a construction area is generated in response to the safety risk value of any construction area reaching the alarm threshold of that construction area.

[0090] The specific details of each part of the above-mentioned device have been described in detail in the method section of the implementation plan. For any undisclosed details, please refer to the implementation plan of the method section, and therefore will not be repeated here.

[0091] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to exemplary embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0092] Exemplary embodiments of this disclosure also provide a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the methods described above.

[0093] In one implementation, the computer program product can be a tangible product containing a computer program, such as a computer-readable storage medium storing the computer program. The readable storage medium can be a storage medium based on electrical, magnetic, optical, electromagnetic, infrared, or other signals, including but not limited to: Random Access Memory (RAM), Read-Only Memory (ROM), magnetic tape, floppy disk, flash memory, Hard Disk Drive (HDD), Solid State Disk (SSD), etc. For example, the computer program product can be implemented as a non-volatile storage medium storing a computer program, such as read-only memory, NAND flash memory, etc.

[0094] In one implementation, the computer program product can be an intangible product containing a computer program. For example, the computer program product can be implemented as a virtual digital product, such as an executable file, installation package, or other digital file storing the computer program.

[0095] Computer program code can be written in one or more programming languages. Examples of programming languages ​​include C, Java, and C++. Program code can execute entirely on the user's computing device, partially on the user's computing device, or as a standalone software package. It can also execute partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, such as a Local Area Network (LAN) or a Wide Area Network (WAN), or it can be connected to an external computing device (e.g., via an internet connection provided by a mobile network operator).

[0096] Computer programs can be carried or transmitted via signals such as electricity, magnetism, light, electromagnetic fields, and infrared radiation. Electronic devices can convert signals carrying computer programs into digital signals, thereby running the computer programs. When a computer program runs on an electronic device, its code is used to cause the electronic device to execute (more specifically, the processor of the electronic device to execute) the method steps of various exemplary embodiments of this disclosure, such as the following steps: Step S210, acquiring the location information of multiple construction areas at the offshore photovoltaic construction site, and determining the distance between each construction area and the sea area based on the location information of each construction area; Step S220, determining the risk coefficient of each construction area based on the distance between each construction area and the sea area and the operation type of each construction area, and determining an alarm threshold based on the risk coefficient of each construction area; Step S230, acquiring monitoring information of each construction area, and predicting the safety risk value of each construction area based on the monitoring information; Step S240, in response to the safety risk value of any construction area reaching the alarm threshold of that construction area, generating alarm information for that construction area.

[0097] The above method, implemented using a computer program, acquires location information of multiple construction areas at an offshore photovoltaic (PV) construction site. Based on the location information of each construction area, it determines the distance between each construction area and the sea area. Based on the distance and operation type of each construction area, it determines the risk coefficient of each construction area and establishes an alarm threshold. It acquires monitoring information for each construction area and predicts its safety risk value. In response to any construction area's safety risk value reaching its alarm threshold, it generates an alarm message for that area. Therefore, it can employ appropriate safety risk alarm intensity based on the location characteristics and operation type of different construction areas, predict safety risk values ​​based on monitoring information, and generate corresponding alarm messages when the safety risk value reaches the alarm threshold. This facilitates the timely detection of potential safety risks, allows for the implementation of countermeasures to reduce or eliminate safety hazards, and improves the safety of offshore PV projects.

[0098] Exemplary embodiments of this disclosure also provide an electronic device. The electronic device may include a processor and a memory. The memory stores executable instructions for the processor, such as computer programs. The processor executes these executable instructions to perform the method steps of various exemplary embodiments of this disclosure.

[0099] The following is for reference. Figure 6 The electronic device is illustrated by way of a general-purpose computing device. It should be understood that... Figure 6 The electronic device 600 shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments disclosed herein.

[0100] like Figure 6 As shown, the electronic device 600 may include: a processor 610, a memory 620, a bus 630, an I / O (input / output) interface 640, and a network adapter 650.

[0101] Memory 620 may include volatile memory, such as RAM 621 and cache unit 622, and may also include non-volatile memory, such as ROM 623. Memory 620 may also include one or more program modules 624, such program modules 624 including, but not limited to: operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. For example, program module 624 may include the modules in the above-described device.

[0102] The processor 610 may include one or more processing units, such as an AP (Application Processor), a modem processor, a GPU (Graphics Processing Unit), an ISP (Image Signal Processor), a controller, an encoder, a decoder, a DSP (Digital Signal Processor), a baseband processor, and / or an NPU (Neural-Network Processing Unit).

[0103] The processor 610 can be used to execute executable instructions stored in the memory 620, which may include method steps of various exemplary embodiments of the present disclosure, such as performing the following steps: Step S210, acquiring location information of multiple construction areas at the offshore photovoltaic construction site, and determining the distance between each construction area and the sea area based on the location information of each construction area; Step S220, determining the risk coefficient of each construction area based on the distance between each construction area and the sea area and the operation type of each construction area, and determining an alarm threshold based on the risk coefficient of each construction area; Step S230, acquiring monitoring information of each construction area, and predicting the safety risk value of each construction area based on the monitoring information; Step S240, generating alarm information for the construction area in response to the safety risk value of any construction area reaching the alarm threshold of that construction area.

[0104] The processor 610 executes the above method to obtain location information of multiple construction areas at the offshore photovoltaic construction site. Based on the location information of each construction area, the distance between each construction area and the sea is determined. Based on the distance between each construction area and the sea, and the operation type of each construction area, a risk coefficient is determined for each construction area, and an alarm threshold is determined based on the risk coefficient. Monitoring information for each construction area is obtained, and the safety risk value for each construction area is predicted based on the monitoring information. In response to any construction area's safety risk value reaching its alarm threshold, an alarm message is generated for that construction area. Therefore, appropriate safety risk alarm intensity can be adopted based on the location characteristics and operation type of different construction areas, and the safety risk value can be predicted based on the monitoring information of the construction area. When the safety risk value reaches the alarm threshold, corresponding alarm messages are generated, which is beneficial for timely detection of potential safety risks, facilitating the implementation of measures to reduce or eliminate safety hazards, and improving the safety of offshore photovoltaic projects.

[0105] Bus 630 is used to connect different components of electronic device 600 and may include a data bus, an address bus and a control bus.

[0106] Electronic device 600 can communicate with one or more external devices 700 (such as keyboard, mouse, external controller, etc.) through I / O interface 640.

[0107] Electronic device 600 can communicate with one or more networks via network adapter 650. For example, network adapter 650 can provide mobile communication solutions such as 3G / 4G / 5G, or wireless communication solutions such as wireless LAN, Bluetooth, and near-field communication. Network adapter 650 can communicate with other modules of electronic device 600 via bus 630.

[0108] although Figure 6 Other hardware and / or software modules may also be configured in the electronic device 600, including but not limited to: display, microcode, device driver, redundant processor, external disk drive array, tape drive, and data backup storage system.

[0109] As can be seen from the above, the technical solutions disclosed herein can be implemented as methods, apparatus, systems, computer program products, storage media, electronic devices, etc. Those skilled in the art will understand that various aspects of this disclosure can be specifically implemented in the following forms: a completely hardware implementation, a completely software implementation (including firmware, microcode, etc.), or a combination of hardware and software implementations, which may be referred to as "circuit," "module," or "system," respectively.

[0110] It should be understood that this disclosure is not limited to the specific methods, steps, or structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. Those skilled in the art will readily conceive of other embodiments based on the specific implementations provided in this disclosure. Therefore, the specific implementations provided in this disclosure are merely exemplary, and the scope and spirit of this disclosure are indicated by the claims, and should cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary technical means in the art not disclosed in this disclosure.

Claims

1. A method for predicting safety risks in offshore photovoltaic power generation, characterized in that, The method includes: Obtain the location information of multiple construction areas at the offshore photovoltaic construction site, and determine the distance between each construction area and the sea area based on the location information of each construction area; Based on the distance between each construction area and the sea area, and the type of operation in each construction area, the risk coefficient of each construction area is determined, and the alarm threshold is determined based on the risk coefficient of each construction area. Acquire monitoring information for each construction area, and predict the safety risk value of each construction area based on the monitoring information; In response to the safety risk value of any construction area reaching the alarm threshold for that construction area, an alarm message is generated for that construction area. The determination of the risk coefficient for each construction area based on its distance from the sea and the type of work performed in each construction area includes: The highest risk coefficient is set when the distance between the construction area and the sea is 0 and the operation type is the highest risk operation type. Set a first risk attenuation value for different distances, and set a second risk attenuation value for different job types; Based on the distance between each construction area and the sea area, and the type of operation in each construction area, the first risk attenuation value and the second risk attenuation value corresponding to each construction area are determined, and attenuation is performed based on the highest risk coefficient to obtain the risk coefficient of each construction area.

2. The method according to claim 1, characterized in that, The process of acquiring monitoring information for each construction area and predicting the safety risk value for each construction area based on the monitoring information includes: Obtain environmental monitoring information and operational monitoring information for each construction area; The first safety risk value for each construction area is determined based on the environmental monitoring information. A second safety risk value is determined for each construction area based on the aforementioned work monitoring information; The final safety risk value is determined based on the first and second safety risk values ​​for each construction area.

3. The method according to claim 2, characterized in that, The determination of the final safety risk value based on the first and second safety risk values ​​for each construction area includes: Based on the distance between each construction area and the sea area, the risk prediction weight for each construction area is determined; The first and second safety risk values ​​of each construction area are weighted according to the risk prediction weight of each construction area to obtain the final safety risk value of each construction area.

4. The method according to claim 1, characterized in that, The process involves determining a first risk attenuation value and a second risk attenuation value for each construction area based on its distance from the sea area and the type of operation in each construction area. Then, based on the highest risk coefficient, an attenuation is applied to obtain the risk coefficient for each construction area, including: Based on the distance between each construction area and the sea area, and the type of operation in each construction area, determine the first risk attenuation value and the second risk attenuation value for each construction area, and select the minimum value between them. Subtract the minimum value from the maximum risk coefficient to obtain the risk coefficient for each construction area.

5. The method according to claim 1, characterized in that, The process of acquiring monitoring information for each construction area and predicting the safety risk value for each construction area based on the monitoring information includes: The monitoring cycle for each construction area is determined based on historical alarm information for that area. Monitoring information for each construction area is obtained according to the monitoring cycle of each construction area, and the safety risk value of each construction area is predicted based on the monitoring information.

6. The method according to claim 1, characterized in that, The method further includes: In response to any construction area's safety risk value reaching the alarm threshold for that construction area, and generating alarm information for that construction area, risk warning information for other construction areas is also generated.

7. A safety risk prediction device for offshore photovoltaic systems, characterized in that, The device includes: The location information processing module is configured to acquire the location information of multiple construction areas at the offshore photovoltaic construction site, and determine the distance between each construction area and the sea area based on the location information of each construction area. The risk factor processing module is configured to determine the risk factor of each construction area based on the distance between each construction area and the sea area and the type of operation in each construction area, and to determine the alarm threshold based on the risk factor of each construction area. The safety monitoring module is configured to acquire monitoring information for each construction area and predict the safety risk value of each construction area based on the monitoring information. The alarm processing module is configured to generate alarm information for any construction area when the safety risk value of that construction area reaches the alarm threshold of that construction area. The determination of the risk coefficient for each construction area based on its distance from the sea and the type of work performed in each construction area includes: The highest risk coefficient is set when the distance between the construction area and the sea is 0 and the operation type is the highest risk operation type. Set a first risk attenuation value for different distances, and set a second risk attenuation value for different job types; Based on the distance between each construction area and the sea area, and the type of operation in each construction area, the first risk attenuation value and the second risk attenuation value corresponding to each construction area are determined, and attenuation is performed based on the highest risk coefficient to obtain the risk coefficient of each construction area.

8. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method according to any one of claims 1 to 6.

9. An electronic device, characterized in that, include: processor; as well as Memory for storing the executable instructions of the processor; The processor is configured to execute the method of any one of claims 1 to 6 by executing the executable instructions.

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