Integrated monitoring method, device and equipment for safety control based on smart power plant

Abstract

The present application relates to the field of smart power plants, and in particular to an integrated monitoring method, device and equipment for safety management and control based on smart power plants. The method includes: obtaining an application request for factory entry permit from an outsourced personnel; analyzing whether the outsourced personnel are qualified to enter the factory based on the application request for factory entry permit; obtaining the real-time behavior information of the outsourced personnel in the factory when it is determined that the outsourced personnel are qualified to enter the factory; obtaining the behavior risk audit results of at least one audit node based on the real-time behavior information in the factory; obtaining a three-dimensional scene model diagram of each facility in the power plant, the three-dimensional scene model diagram containing risk facilities and risk routes; obtaining the safety monitoring results of the power plant based on the behavior risk audit results and the three-dimensional scene model diagram; and adjusting the factory entry qualifications of the outsourced personnel based on the safety monitoring results. This method can promptly discover and deal with safety hazards when outsourced personnel enter the power plant.

Description

Technical Field

[0001] The present application relates to the field of smart power plants, and in particular to a method, device and equipment for integrated safety management and control based on smart power plants. Background Art

[0002] With the rapid development of industrial automation and intelligence, the importance of safety management of power plants as important energy production facilities has become increasingly prominent. Traditional safety management methods mainly rely on manual inspections and video surveillance, which have problems such as low efficiency, untimely response, and difficulty in comprehensive coverage. In addition, as an indispensable part of power plant operations, the safety management of outsourced personnel is particularly critical, but safety accidents often occur due to information asymmetry, lax supervision and other problems.

[0003] At present, outsourced personnel have high mobility and complex backgrounds. The existing monitoring system cannot achieve real-time and comprehensive monitoring of the behavior of outsourced personnel. There is a lack of effective risk assessment mechanism, making it difficult to detect and deal with safety hazards in a timely manner.

[0004] Therefore, there is an urgent need for an integrated monitoring method, device and equipment for safety management and control based on a smart power plant, which can promptly detect and deal with safety hazards when external personnel enter the power plant. Summary of the invention

[0005] Based on this, it is necessary to provide an integrated safety management and control monitoring method, device and equipment based on a smart power plant, which can promptly detect and deal with safety hazards when external personnel enter the power plant, in response to the above technical problems.

[0006] In a first aspect, the present application provides a safety management and control integrated monitoring method based on a smart power plant. The method comprises:

[0007] Obtain factory entry permit application requests from outsourced personnel;

[0008] Analyze whether the outsourced personnel are qualified to enter the factory based on the factory entry permit application request;

[0009] After confirming that the outsourced personnel are qualified to enter the factory, obtain the outsourced personnel's real-time behavior information in the factory;

[0010] Based on the real-time behavior information within the factory, obtaining a behavior risk audit result of at least one audit node;

[0011] Obtaining a three-dimensional scene model diagram of each facility of the power plant, wherein the three-dimensional scene model diagram includes risk facilities and risk routes;

[0012] Obtaining safety monitoring results of the power plant according to the behavior risk review results and the three-dimensional scenario model diagram;

[0013] Adjust the factory entry qualifications of outsourced personnel based on the safety monitoring results.

[0014] In one embodiment, the real-time in-factory behavior information includes in-factory driving behavior information; and obtaining the real-time in-factory behavior information of outsourced personnel includes:

[0015] Obtain the in-plant vehicle configuration of outsourced personnel;

[0016] When it is determined that the outsourced personnel have configured the vehicle based on the vehicle configuration situation within the factory, the in-factory driving behavior information of the outsourced personnel is obtained, and the driving behavior information includes the frequency of passing the risk facilities and the average vehicle speed.

[0017] In one embodiment, obtaining the behavior risk audit result of at least one audit node based on the real-time behavior information within the factory includes:

[0018] The frequency of passing through risk facilities exceeding the preset frequency threshold is used as the screening basis to screen out target risk facilities;

[0019] Obtain in-plant work routes consisting of target risk facilities;

[0020] Obtaining the similarity between the in-plant work route and the risk route;

[0021] When the similarity exceeds a preset similarity threshold, the behavior risk review result is determined to be that there is a security risk.

[0022] In one embodiment, obtaining the behavior risk audit result of at least one audit node based on the real-time behavior information within the factory includes:

[0023] Based on the real-time behavior information within the factory, obtain the first behavior risk review result of the first-level review node;

[0024] Obtain the power task type and power operation level of the outsourced personnel;

[0025] According to the power task type and the power operation level, the first behavior risk review result is re-evaluated to obtain the second behavior risk review result of the secondary review node.

[0026] In one embodiment, after obtaining the similarity between the in-plant work route and the risk route, the method further includes:

[0027] When the similarity does not exceed a preset similarity threshold, obtaining historical interception data of the in-plant work route;

[0028] Analyze the historical intercepted data to obtain the interception reason;

[0029] When the interception reason is determined to be the vehicle speeding reason, and the average vehicle speed exceeds the preset speed threshold of the corresponding risk facility, the behavior risk review result is determined to be that there is a safety risk.

[0030] In one embodiment, obtaining the safety monitoring result of the power plant according to the behavior risk review result and the three-dimensional scene model diagram includes:

[0031] When it is determined that the first behavior risk review result is no security risk, obtaining the continuous review duration of the secondary review node;

[0032] When the continuous audit duration is longer than the preset duration threshold, the qualification level of the outsourced personnel and the audit accuracy rate of the first-level audit node are obtained;

[0033] When the qualification level of the outsourced personnel and the audit accuracy rate of the first-level audit node meet the preset requirements, the safety monitoring results of the power plant are obtained according to the first behavioral risk audit results and the three-dimensional scenario model diagram.

[0034] In one embodiment, the method further comprises:

[0035] When the similarity exceeds a preset similarity threshold, marking risk facilities in the in-plant work route;

[0036] When the vehicle of the outsourced personnel enters the factory again, the navigation system controlling the vehicle adjusts the working route within the factory in real time.

[0037] In one embodiment, the navigation system controlling the vehicle adjusts the in-plant work route in real time, including:

[0038] Obtain the wireless communication signal level of each risk facility passed by the outsourced personnel, including transformers, circuit breakers and disconnectors;

[0039] According to the wireless communication signal level, the time point for the vehicle's navigation system to adjust the in-factory work route in real time is determined; and when the wireless communication signal level is lower than a preset level threshold, the average speed of the vehicle passing through the risk facility is reduced.

[0040] In a second aspect, the present application also provides a safety control integrated monitoring device based on a smart power plant. The device includes:

[0041] The acquisition module is used to obtain the factory entry permit application request from the outsourced personnel;

[0042] An analysis module, used to analyze whether the outsourced personnel are qualified to enter the factory according to the factory entry permit application request;

[0043] The acquisition module is also used to obtain the real-time behavior information of the outsourced personnel in the factory when it is determined that the outsourced personnel are qualified to enter the factory;

[0044] An audit module, configured to obtain a behavior risk audit result of at least one audit node based on the real-time behavior information within the factory;

[0045] The acquisition module is further used to acquire a three-dimensional scene model diagram of each facility of the power plant, wherein the three-dimensional scene model diagram includes risk facilities and risk routes;

[0046] A safety monitoring module, used to obtain safety monitoring results of the power plant according to the behavior risk review results and the three-dimensional scene model diagram;

[0047] The adjustment module is used to adjust the factory entry qualifications of outsourced personnel according to the safety monitoring results.

[0048] In a third aspect, the present application further provides a computer device. The memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0049] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the above method when the computer program is executed by a processor.

[0050] In a fifth aspect, the present application further provides a computer program product, wherein the computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0051] The above-mentioned integrated monitoring method, device and equipment for safety management and control based on smart power plants can timely discover and prevent safety accidents by real-time monitoring of the behavior of outsourced personnel and analyzing their risks, thereby improving the overall safety of the power plant. The automated audit process reduces the need for manual audits, improves management efficiency, and ensures the consistency and accuracy of audits. Using real-time behavior information and three-dimensional scenario models, the system can conduct risk assessments in real time and discover risk points in a timely manner, providing strong support for safety management. The entry qualifications of outsourced personnel are dynamically adjusted according to the safety monitoring results to ensure that only personnel who meet safety standards and requirements can enter the power plant, thereby enhancing the flexibility and adaptability of safety management. Through real-time monitoring and risk assessment of the behavior of outsourced personnel, power plants can more reasonably allocate safety supervision resources and focus on high-risk areas and behaviors. When the system detects unsafe behavior or risks, it can quickly trigger warnings and take countermeasures, thereby improving the emergency response capabilities of power plants to emergencies. Through real-time monitoring and risk assessment of outsourced personnel, employees' safety awareness can be enhanced, prompting them to comply with safety regulations and reducing human errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0053] Figure 1 This is an application environment diagram of a safety management and control integrated monitoring method based on a smart power plant in one embodiment;

[0054] Figure 2 A schematic diagram of a process of an integrated safety management and control monitoring method based on a smart power plant in one embodiment;

[0055] Figure 3 It is a flow chart of an integrated monitoring method for safety management and control based on a smart power plant in another embodiment;

[0056] Figure 4 It is a structural block diagram of a safety control integrated monitoring device based on a smart power plant in one embodiment;

[0057] Figure 5 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0059] The integrated safety control monitoring method based on the smart power plant provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. Among them, the terminal 102 can be but is not limited to various personal computers, laptops, smart phones, tablets, Internet of Things devices and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. Portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The server 104 can be implemented with an independent server or a server cluster consisting of multiple servers.

[0060] In an exemplary embodiment, Figure 2 As shown in the figure, a safety control integrated monitoring method based on a smart power plant is provided. Figure 1 The server in the example is used to illustrate, including the following steps S202 to S216. Among them:

[0061] Step S202, obtaining an entry permit application request from an outsourced personnel.

[0062] Specifically, the outsourced personnel or their affiliated units need to proactively submit an entry application to the power plant management department. The application must include necessary personal information, such as name, identification, affiliated unit, contact information, etc., as well as the specific purpose of visiting the power plant, the area planned to enter, and the estimated time of visit. The power plant management department will review the background, qualifications, and previous safety records of the outsourced personnel to ensure that they meet the safety standards and requirements of the power plant.

[0063] Step S204: Analyze whether the outsourced personnel have the entry qualifications according to the entry permit application request.

[0064] Specifically, the management department checks whether all application documents submitted by the outsourced personnel are complete, including personal information, unit information, purpose of visit, etc. Verify whether the outsourced personnel have the corresponding professional qualifications, certificates or specific skills that are related to the safety requirements of the power plant or the nature of the work. Conduct background checks on outsourced personnel, including but not limited to criminal records, credit status, past work performance and safety records. Confirm whether the outsourced personnel have received necessary safety education and training, understand and can comply with the safety regulations of the power plant. Evaluate whether the purpose of the outsourced personnel entering the power plant is legitimate, clear, and related to their job responsibilities. Based on the above review results, the authorized personnel or management decides whether to approve the outsourced personnel's application for entry.

[0065] Step S206, when it is determined that the outsourced personnel have the qualifications to enter the factory, the real-time in-factory behavior information of the outsourced personnel is obtained.

[0066] Specifically, through video surveillance systems, sensors, positioning systems and other technical means, the actions and activities of outsourced personnel in the factory are observed and recorded in real time. Use behavior recognition software to analyze the behavior patterns of outsourced personnel to determine whether there are any violations of safety regulations or operating procedures. Use RFID, GPS or other positioning technologies to track the specific location of outsourced personnel in the factory to ensure that they only move in authorized areas. Integrate the collected behavioral information with data such as factory entry permits, safety regulations, and work plans to obtain a comprehensive overview of activities. Based on real-time behavioral information, assess the safety risks posed by outsourced personnel and whether their behavior leads to safety incidents.

[0067] Step S208, based on the real-time behavior information within the factory, obtain the behavior risk audit result of at least one audit node.

[0068] Specifically, identify key monitoring points within the plant, which are safety-sensitive areas, high-risk equipment operation areas, or links in specific work processes. Collect behavioral data of outsourced personnel at these key nodes, including video surveillance records, operation logs, sensor data, etc. Analyze behavioral data to identify any violations of safety regulations, operational errors, or potential safety hazards. Based on the results of behavioral analysis, assess the risk level of each audit node to determine whether there is an unacceptable risk. Based on the results of the risk assessment, generate audit opinions, which include continued monitoring, immediate correction, further investigation, or preventive measures. Feedback the audit results to relevant personnel or departments in real time so that necessary actions can be taken quickly. Auditing is not a one-time process, but an ongoing process that requires regular or irregular re-evaluation of key nodes.

[0069] Step S210, obtaining a three-dimensional scene model diagram of each facility in the power plant, wherein the three-dimensional scene model diagram includes risk facilities and risk routes.

[0070] Specifically, use 3D modeling technology to create a detailed and accurate virtual representation of the power plant, including all building structures, equipment layouts, and space configurations. Clearly mark facilities with safety risks in the 3D model, such as high-voltage equipment, chemical storage areas, and storage points for flammable and explosive items. Identify and mark potential risk paths that lead to safety accidents, such as the movement routes of personnel and vehicles, and areas affected by risky facilities. Through the 3D scene model diagram, risky facilities and risky routes are presented in an intuitive manner, making it easier for managers to identify and understand potential safety issues. Use the 3D model diagram for safety planning and layout optimization, such as planning safe distances, evacuation routes, and emergency response routes.

[0071] Step S212, obtaining the safety monitoring results of the power plant according to the behavior risk review results and the three-dimensional scene model diagram.

[0072] Specifically, the potential risk points identified in the risk audit are combined with the physical location and facility information in the 3D scene model diagram to form a comprehensive view of safety risks. Using the visualization characteristics of the 3D scene model diagram, the risk audit results are mapped to specific facilities and areas, making the risks more intuitive and easy to understand. The spatial distribution and interrelationships of risk points are analyzed to assess their potential impact on the surrounding environment and facilities. The 3D scene model diagram is updated in real time, combined with the risk audit results, to dynamically monitor the safety status of the power plant and respond to emerging risks in a timely manner. Each risk point in the 3D scene is evaluated in detail, the risk level is determined, and corresponding risk control and mitigation measures are formulated.

[0073] Step S214, adjusting the factory entry qualifications of outsourced personnel according to the safety monitoring results.

[0074] Specifically, the safety monitoring system collects data on the behavior of outsourced personnel in the power plant to assess whether they comply with safety regulations and operating standards. Analyze whether the behavior of outsourced personnel has led to safety accidents and determine the risk level of their behavior. Compare the safety monitoring results with the entry qualification standards for outsourced personnel to determine whether adjustments are needed. If the behavior of outsourced personnel indicates that they pose a safety risk, their access to specific areas needs to be restricted or revoked. For outsourced personnel with poor safety performance, additional safety training or guidance is required to improve their safety awareness and operational skills. Set clearer safety conditions for outsourced personnel, such as requiring them to complete specific safety training within a specified time or work under specific supervision. For outsourced personnel with higher safety risks, increase the frequency and intensity of monitoring to ensure that their behavior meets safety requirements.

[0075] In the method of the above embodiment, by real-time monitoring of the behavior of outsourced personnel and analyzing their risks, safety accidents can be discovered and prevented in time, thereby improving the overall safety of the power plant. The automated audit process reduces the need for manual audits, improves management efficiency, and ensures the consistency and accuracy of the audit. Using real-time behavior information and three-dimensional scene models, the system can conduct risk assessments in real time, discover risk points in time, and provide strong support for safety management. The entry qualifications of outsourced personnel are dynamically adjusted according to the safety monitoring results to ensure that only personnel who meet safety standards and requirements can enter the power plant, thereby enhancing the flexibility and adaptability of safety management. Through real-time monitoring and risk assessment of the behavior of outsourced personnel, power plants can more reasonably allocate safety supervision resources and focus on high-risk areas and behaviors. When the system detects unsafe behavior or risks, it can quickly trigger an early warning and take countermeasures, thereby improving the emergency response capabilities of the power plant to emergencies. Through real-time monitoring and risk assessment of outsourced personnel, employees' safety awareness can be enhanced, prompting them to comply with safety regulations and reduce human errors.

[0076] In an exemplary embodiment, the real-time behavior information in the factory includes the driving behavior information in the factory; obtaining the real-time behavior information in the factory of the outsourced personnel includes:

[0077] Obtain the in-plant vehicle configuration of outsourced personnel;

[0078] When it is determined that the outsourced personnel have been allocated a vehicle based on the vehicle configuration situation within the factory, the outsourced personnel's driving behavior information within the factory is obtained, and the driving behavior information includes the frequency of passing risk facilities and the average vehicle speed.

[0079] Specifically, the monitoring equipment (such as cameras, sensors, etc.) installed in the factory area is used to collect the behavior information of outsourced personnel in the factory area in real time. The types, quantities and configurations of vehicles used by outsourced personnel in the factory area are recorded and obtained, including the size, load capacity, safety facilities, etc. of the vehicles. After confirming that the outsourced personnel have configured the vehicles, their driving behavior information is further collected and analyzed. The driving behavior of outsourced personnel is monitored, including their driving paths, speeds, parking and starting in the factory area. The number of times outsourced personnel pass through risk facilities (such as high-voltage lines, chemical storage areas, etc.) while driving is recorded to evaluate the impact of their driving behavior on safety risks. The average speed of outsourced personnel driving in the factory area is calculated to determine whether they comply with the speed limits and safe driving requirements in the factory area. The driving behavior data of outsourced personnel is analyzed to evaluate whether there is speeding, frequent passing through risk areas or other unsafe driving behaviors.

[0080] In this embodiment, by monitoring driving behavior, the risk of accidents caused by improper driving is reduced, the overall safety of the plant is improved, and high-risk areas and behavior patterns are identified, so that management can take preventive measures to reduce potential safety threats. It can optimize vehicle configuration and use, reduce unnecessary vehicle congestion and resource waste, and improve plant operation efficiency.

[0081] In an exemplary embodiment, based on the real-time behavior information in the factory, obtaining the behavior risk audit result of at least one audit node includes:

[0082] The frequency of passing through risk facilities exceeding the preset frequency threshold is used as the screening basis to screen out target risk facilities;

[0083] Obtain in-plant work routes consisting of target risk facilities;

[0084] Obtain the similarity between the work route and the risk route within the factory;

[0085] When the similarity exceeds a preset similarity threshold, the behavior risk review result is determined to be a security risk.

[0086] Specifically, based on the real-time monitoring system, collect information on the behavior of staff within the plant, focusing on driving behavior and interaction with risky facilities. Set a frequency threshold for risky facilities, that is, it is considered that the number of times passing through risky facilities within a certain period of time exceeds this threshold (for example, 3 times) indicates a safety risk. By analyzing the behavioral data, screen out those risky facilities that are frequently visited and exceed the preset frequency threshold. Determine the work routes of staff within the plant, especially those involving high-risk facilities. Identify pre-defined risky routes within the plant that are known to be potentially dangerous. Compare the similarity of the work route with the risk route to determine whether the work route exposes the staff to safety risks. Set a similarity threshold. When the similarity between the work route and the risk route exceeds this threshold (for example, 80%), it is considered that there is a safety risk. If the similarity between the work route and the risk route exceeds the preset similarity threshold, the behavioral risk audit result is determined to be a safety risk.

[0087] In this embodiment, by monitoring the frequency of passing through risky facilities, those areas or facilities with a higher probability of accidents can be accurately identified. Identifying the work routes related to risky facilities provides a basis for further optimizing the routes and avoiding potential dangers. By analyzing the similarity between the work routes and the risk routes in real time, safety risks can be quickly assessed and measures can be taken in a timely manner. When it is detected that the similarity between the work route and the risk route exceeds the threshold, an immediate response can be made to reduce the probability of accidents. By identifying and adjusting high-risk work routes, the time and frequency of outsourced personnel being exposed to potentially dangerous environments can be reduced.

[0088] In an exemplary embodiment, Figure 3 As shown, based on the real-time behavior information in the factory, the behavior risk audit result of at least one audit node is obtained, including:

[0089] Step S302, based on the real-time behavior information in the factory, obtaining the first behavior risk audit result of the first-level audit node;

[0090] Step S304, obtaining the power task type and power operation level of the outsourced personnel;

[0091] Step S306, re-evaluate the first behavior risk review result according to the power task type and the power operation level, and obtain the second behavior risk review result of the secondary review node.

[0092] Specifically, the first level audit node - the first behavior risk audit result:

[0093] The initial audit is based on real-time information collected on the behavior of external personnel, such as their location, type of activities, interaction with risky facilities, etc. The purpose of this stage is to identify any immediate or obvious risky behavior, such as entering restricted areas or failing to follow safe operating procedures.

[0094] Capture power task types and power work grades: Collect detailed information about the specific power tasks performed by outsourced personnel, including the nature, complexity, and potential risk level of the tasks. The power work grade is based on the risk assessment of the task, such as low, medium, or high.

[0095] Secondary audit node - Second behavior risk audit results:

[0096] Combined with the results of the first-level audit and the type of power tasks and work levels of the outsourced personnel, a more in-depth risk assessment is conducted. This stage considers more factors, such as the complexity of the task, the required professional skills, and the special requirements of the working environment.

[0097] The initial risk assessment is adjusted and refined based on the specific tasks and work levels of the outsourced personnel. This involves revisiting the risk thresholds and safety standards for specific tasks.

[0098] The purpose of multi-level audit is to ensure the comprehensiveness and accuracy of safety risk assessment, and to adapt to the needs of different tasks and working environments through different levels of audit. Provide appropriate safety guidance and supervision to outsourced personnel to ensure that they understand the risks of their tasks and take appropriate preventive measures.

[0099] In this embodiment, through the multi-level audit process, safety risks can be more accurately identified and controlled, reducing the probability of accidents. This helps to improve the efficiency and effectiveness of safety management and ensure that safety measures match actual work risks. It also enhances the safety management of external staff and ensures that their behavior complies with the safety requirements of the power plant.

[0100] In an exemplary embodiment, after obtaining the similarity between the in-plant work route and the risk route, the following steps are performed:

[0101] When the similarity does not exceed the preset similarity threshold, the historical interception data of the working route within the factory is obtained;

[0102] Analyze historical interception data to obtain interception reasons;

[0103] When the reason for the interception is determined to be speeding, and the average speed exceeds the preset speed threshold of the corresponding risk facility, the behavioral risk review result is determined to be a safety risk.

[0104] Specifically, first, by comparing the in-plant work route with the known risk route, the similarity between the two is evaluated. If the similarity does not exceed the preset similarity threshold, it means that the current work route is not similar enough to the risk route and no immediate action is required. In the case that the similarity does not cause safety concerns, further obtain the historical interception data of the work route. Analyze the historical interception data to determine the reasons for the interception. This includes a variety of factors, such as vehicle speeding, violation of traffic rules, approaching restricted areas, etc. Pay special attention to interception events caused by vehicle speeding, and analyze the frequency, distribution and related circumstances of these events. For interceptions caused by speeding, compare the average vehicle speed with the preset speed threshold of the corresponding risk facility. If the analysis finds that the average vehicle speed exceeds the preset speed threshold of the risk facility, it should be determined that there is a safety risk even if the similarity between the work route and the risk route does not exceed the standard. Based on the above analysis, update the behavioral risk review results, mark the existence of safety risks, and take corresponding measures.

[0105] In this embodiment, by analyzing the similarity between the working route and the risk route and combining it with historical interception data, potential safety risk points can be identified more accurately. Historical interception data provides valuable information to help management make more reasonable safety management decisions based on actual data. Pay special attention to speeding behavior to ensure that vehicles maintain a safe speed around risk facilities and reduce the probability of accidents. Before the risk reaches a critical point, it is possible to predict potential risks through historical data analysis and take preventive measures. By identifying and providing feedback on violations such as speeding, the compliance of outsourced personnel with safety standards can be improved.

[0106] In an exemplary embodiment, the safety monitoring results of the power plant are obtained according to the behavior risk review results and the three-dimensional scenario model diagram, including:

[0107] When the first behavior risk review result is determined to be no security risk, obtain the continuous review time of the secondary review node;

[0108] When the continuous audit duration exceeds the preset duration threshold, obtain the qualification level of the outsourced personnel and the audit accuracy rate of the first-level audit node;

[0109] When the qualification level of the outsourced personnel and the audit accuracy rate of the first-level audit node meet the preset requirements, the safety monitoring results of the power plant are obtained based on the first-line risk audit results and the three-dimensional scenario model diagram.

[0110] Specifically, the first-level audit evaluates the current safety status based on the behavioral risk audit results and the three-dimensional scenario model diagram. If the first-level audit shows that there is no safety risk, the system will enter the second-level audit node and start calculating the continuous audit duration. If the first-level audit result is no risk, the system will continue to monitor for a period of time to verify the accuracy of the first-level audit. If the continuous audit duration exceeds the preset duration threshold, according to the process rules, the second-level audit will be skipped and the current safety status is considered stable. If a second-level audit is not required, the system will obtain the qualification level of the outsourced personnel and the audit accuracy rate of the first-level audit node. Evaluate whether the qualification level of the outsourced personnel meets the safety requirements and whether the audit accuracy rate of the first-level audit node meets the preset standards. When the qualification level and audit accuracy rate of the outsourced personnel meet the preset requirements, the system will combine the first-level audit results and the three-dimensional scenario model diagram to generate the safety monitoring results of the power plant.

[0111] In this embodiment, through a multi-level, condition-driven safety monitoring system, by comprehensively considering personnel qualifications, audit accuracy and real-time scenario data, the scientificity, accuracy and effectiveness of power plant safety management are improved.

[0112] In an exemplary embodiment, when the similarity exceeds a preset similarity threshold, risk facilities in the in-plant work route are marked;

[0113] When the outsourced personnel's vehicle enters the factory again, the navigation system that controls the vehicle adjusts the work route within the factory in real time.

[0114] Specifically, when the outsourced personnel's vehicle re-enters the plant, the system will access the vehicle's navigation system for real-time route adjustment. Based on the location of the risk facility and the current location of the vehicle, the navigation system will automatically adjust the work route to guide the vehicle to avoid high-risk areas. By optimizing the route, the contact between outsourced personnel and vehicles and risk facilities is reduced, thereby reducing the probability of safety accidents. The real-time adjustment function of the navigation system allows for rapid response to emergencies, such as temporary construction areas or newly identified risk points. This process requires the integration of geographic information systems (GIS), vehicle navigation systems, and risk assessment systems to achieve automated risk management.

[0115] In this embodiment, through real-time monitoring and automatic adjustment measures of the work routes within the factory, the risk management capability of the factory is improved, the safety of outsourced personnel is ensured, and the overall operational efficiency is also improved.

[0116] In an exemplary embodiment, controlling a navigation system of a vehicle to adjust a factory work route in real time includes:

[0117] Obtain the wireless communication signal level of each risk facility passed by the outsourced personnel, including transformers, circuit breakers and disconnectors;

[0118] According to the wireless communication signal level, the time point at which the vehicle's navigation system adjusts the work route within the factory in real time is determined; and when the wireless communication signal level is lower than the preset level threshold, the average speed of the vehicle passing through the risk facilities is reduced.

[0119] Specifically, the system continuously monitors the wireless communication signal level when the outsourced personnel pass through various risk facilities (such as transformers, circuit breakers and disconnectors). The wireless communication signal level is used as an indicator to reflect the relative distance between the outsourced personnel and the risk facilities or the potential risk level. When the wireless communication signal level is low, it means that there is a delay in the navigation system's information and it cannot be adjusted and controlled in time, so adjustments can be made in advance or adjustment reminders can be sent; and based on the strength of the wireless communication signal, the navigation system will determine when it is necessary to adjust the vehicle's driving route to avoid potential high-risk areas. When the wireless communication signal level changes and reaches the preset conditions, the navigation system will automatically trigger the time point for route adjustment. In addition, when the wireless communication signal level is lower than the preset level threshold, the system will automatically instruct the vehicle to reduce speed to improve safety when passing through the risk area. By adjusting the vehicle speed and route, ensure that the vehicle maintains a safe distance from the risk facilities. The system can dynamically respond to changes in wireless signals and adjust the vehicle's driving status in real time to cope with changing environmental conditions. The entire process takes safety as the highest priority to ensure the safety of outsourced personnel traveling within the factory area.

[0120] In this embodiment, by real-time monitoring of the wireless communication signal level, the vehicle route and speed are adjusted in time to effectively reduce the safety risk when approaching risk facilities. The navigation system can dynamically adjust the route according to the wireless signal strength to prevent the vehicle from getting too close to risk facilities. When the wireless communication signal level is lower than the preset threshold, the system automatically reduces the speed of the vehicle to improve the safety of passing through the risk area.

[0121] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0122] Based on the same inventive concept, the embodiment of the present application also provides a safety control integrated monitoring device based on a smart power plant for implementing the above-mentioned safety control integrated monitoring method based on a smart power plant. The implementation solution provided by the device to solve the problem is similar to the implementation solution recorded in the above-mentioned method, so the specific limitations in one or more embodiments of the safety control integrated monitoring device based on a smart power plant provided below can be referred to the above limitations on the safety control integrated monitoring method based on a smart power plant, and will not be repeated here.

[0123] In an exemplary embodiment, Figure 4 As shown, a safety control integrated monitoring device based on a smart power plant is provided, comprising:

[0124] The acquisition module 402 is used to obtain the factory entry permit application request of the outsourced personnel;

[0125] The analysis module 404 is used to analyze whether the outsourced personnel have the entry qualifications according to the entry permit application request;

[0126] The acquisition module 402 is also used to acquire the real-time in-factory behavior information of the outsourced personnel when it is determined that the outsourced personnel have the qualifications to enter the factory;

[0127] Audit module 406, used to obtain the behavior risk audit result of at least one audit node based on the real-time behavior information in the factory;

[0128] The acquisition module 402 is also used to acquire a three-dimensional scene model diagram of each facility of the power plant, wherein the three-dimensional scene model diagram includes risk facilities and risk routes;

[0129] The safety monitoring module 408 is used to obtain the safety monitoring results of the power plant according to the behavior risk review results and the three-dimensional scene model diagram;

[0130] The adjustment module 410 is used to adjust the factory entry qualifications of outsourced personnel according to the safety monitoring results.

[0131] In an exemplary embodiment, the in-plant real-time behavior information includes in-plant driving behavior information;

[0132] The acquisition module 402 is also used to obtain the in-plant vehicle configuration of the outsourced personnel; when it is determined that the outsourced personnel have configured the vehicle based on the in-plant vehicle configuration, the in-plant driving behavior information of the outsourced personnel is obtained, and the driving behavior information includes the frequency of passing through risk facilities and the average vehicle speed.

[0133] In an exemplary embodiment, the audit module 406 is also used to use the frequency of passing through risk facilities exceeding a preset frequency threshold as a screening basis to screen out target risk facilities; obtain the in-plant work route consisting of the target risk facilities; obtain the similarity between the in-plant work route and the risk route; and when the similarity exceeds a preset similarity threshold, determine that the behavioral risk audit result is that there is a safety risk.

[0134] In an exemplary embodiment, the audit module 406 is also used to obtain the first behavior risk audit result of the first-level audit node based on real-time behavior information within the factory; obtain the power task type and power operation level of the outsourced personnel; re-evaluate the first behavior risk audit result based on the power task type and power operation level, and obtain the second behavior risk audit result of the second-level audit node.

[0135] In an exemplary embodiment, the audit module 406 is also used to obtain historical interception data of the work route within the factory when the similarity does not exceed the preset similarity threshold; analyze the historical interception data to obtain the reason for the interception; and when the interception reason is determined to be speeding, and the average vehicle speed exceeds the preset speed threshold of the corresponding risk facility, determine that the behavioral risk audit result is that there is a safety risk.

[0136] In an exemplary embodiment, the safety monitoring module 408 is also used to obtain the continuous audit duration of the second-level audit node when it is determined that the first behavior risk audit result is no safety risk; when the continuous audit duration is greater than the preset duration threshold, obtain the qualification level of the outsourced personnel and the audit accuracy rate of the first-level audit node; when the qualification level of the outsourced personnel and the audit accuracy rate of the first-level audit node meet the preset requirements, obtain the safety monitoring results of the power plant based on the first behavior risk audit result and the three-dimensional scenario model diagram.

[0137] In an exemplary embodiment, the control module is used to mark risky facilities in the factory work route when the similarity exceeds a preset similarity threshold; when the vehicle of the outsourced personnel enters the factory again, the navigation system of the vehicle is controlled to adjust the factory work route in real time.

[0138] In an exemplary embodiment, the control module is also used to obtain the wireless communication signal level of each risk facility passed by the outsourced personnel, the risk facilities including transformers, circuit breakers and disconnectors; determine the real-time adjustment time point of the vehicle's navigation system to the work route within the factory according to the wireless communication signal level; and reduce the average speed of the vehicle passing through the risk facility when the wireless communication signal level is lower than a preset level threshold.

[0139] Each module in the above-mentioned integrated safety control monitoring device based on smart power plants can be implemented in whole or in part through software, hardware and their combination. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0140] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 5As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store digital learning data, learner information and learning activity information. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a safety management and control integrated monitoring method based on a smart power plant is implemented.

[0141] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0142] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps of the above method when executing the computer program.

[0143] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0144] In one embodiment, a computer program product is provided, comprising a computer program, which implements the steps of the above method when executed by a processor.

[0145] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0146] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0147] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0148] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be construed as limiting the scope of the present application. It should be noted that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A safety control integrated monitoring method based on a smart power plant, characterized in that: include: Obtain factory entry permit application requests from outsourced personnel; Analyze whether the outsourced personnel are qualified to enter the factory based on the factory entry permit application request; When it is determined that the outsourced personnel are qualified to enter the factory, the real-time behavior information of the outsourced personnel in the factory is obtained, wherein the real-time behavior information in the factory includes driving behavior information in the factory. The steps specifically include: Obtain the in-plant vehicle configuration of outsourced personnel; When it is determined that the outsourced personnel have configured a vehicle based on the vehicle configuration in the factory, obtaining the outsourced personnel's in-factory driving behavior information, wherein the driving behavior information includes the frequency of passing through risk facilities and the average vehicle speed; Based on the real-time behavior information within the factory, obtaining a behavior risk audit result of at least one audit node; Obtaining a three-dimensional scene model diagram of each facility of the power plant, wherein the three-dimensional scene model diagram includes risk facilities and risk routes; Obtaining safety monitoring results of the power plant according to the behavior risk review results and the three-dimensional scenario model diagram; Adjust the factory entry qualifications of outsourced personnel based on the safety monitoring results.

2. The method according to claim 1, characterized in that: The obtaining, based on the real-time in-plant behavior information, a behavior risk audit result of at least one audit node includes: The frequency of passing through risk facilities exceeding the preset frequency threshold is used as the screening basis to screen out target risk facilities; Obtain in-plant work routes consisting of target risk facilities; Obtaining the similarity between the in-plant work route and the risk route; When the similarity exceeds a preset similarity threshold, the behavior risk review result is determined to be that there is a security risk.

3. The method according to claim 1, characterized in that The obtaining, based on the real-time in-plant behavior information, a behavior risk audit result of at least one audit node includes: Based on the real-time behavior information within the factory, obtain the first behavior risk review result of the first-level review node; Obtain the power task type and power operation level of the outsourced personnel; According to the power task type and the power operation level, the first behavior risk review result is re-evaluated to obtain the second behavior risk review result of the secondary review node.

4. The method according to claim 2, characterized in that: After obtaining the similarity between the in-plant work route and the risk route, the method further comprises: When the similarity does not exceed a preset similarity threshold, obtaining historical interception data of the in-plant work route; Analyze the historical intercepted data to obtain the interception reason; When the interception reason is determined to be the vehicle speeding reason, and the average vehicle speed exceeds the preset speed threshold of the corresponding risk facility, the behavior risk review result is determined to be that there is a safety risk.

5. The method according to claim 3, characterized in that: The obtaining of the safety monitoring results of the power plant according to the behavior risk audit results and the three-dimensional scene model diagram includes: When it is determined that the first behavior risk review result is no security risk, obtaining the continuous review duration of the secondary review node; When the continuous audit duration is longer than the preset duration threshold, the qualification level of the outsourced personnel and the audit accuracy rate of the first-level audit node are obtained; When the qualification level of the outsourced personnel and the audit accuracy rate of the first-level audit node meet the preset requirements, the safety monitoring results of the power plant are obtained according to the first behavioral risk audit results and the three-dimensional scenario model diagram.

6. The method according to claim 2, characterized in that The method further comprises: When the similarity exceeds a preset similarity threshold, marking risk facilities in the in-plant work route; When the vehicle of the outsourced personnel enters the factory again, the navigation system controlling the vehicle adjusts the working route within the factory in real time.

7. The method according to claim 6, characterized in that The navigation system controlling the vehicle adjusts the in-plant work route in real time, including: Obtain the wireless communication signal level of each risk facility passed by the outsourced personnel, including transformers, circuit breakers and disconnectors; According to the wireless communication signal level, the time point for the vehicle's navigation system to adjust the in-factory work route in real time is determined; and when the wireless communication signal level is lower than a preset level threshold, the average speed of the vehicle passing through the risk facility is reduced.

8. A safety control integrated monitoring device based on a smart power plant, characterized in that: The device comprises: The acquisition module is used to obtain the factory entry permit application request from the outsourced personnel; An analysis module, used to analyze whether the outsourced personnel are qualified to enter the factory according to the factory entry permit application request; The acquisition module is further used to acquire the real-time in-factory behavior information of the outsourced personnel when it is determined that the outsourced personnel are qualified to enter the factory, and the real-time in-factory behavior information includes the in-factory driving behavior information; the acquisition module is specifically used to acquire the in-factory vehicle configuration of the outsourced personnel; when it is determined that the outsourced personnel have configured a vehicle based on the in-factory vehicle configuration, the in-factory driving behavior information of the outsourced personnel is acquired, and the driving behavior information includes the frequency of passing through risk facilities and the average vehicle speed; An audit module, configured to obtain a behavior risk audit result of at least one audit node based on the real-time behavior information within the factory; The acquisition module is further used to acquire a three-dimensional scene model diagram of each facility of the power plant, wherein the three-dimensional scene model diagram includes risk facilities and risk routes; A safety monitoring module, used to obtain safety monitoring results of the power plant according to the behavior risk review results and the three-dimensional scene model diagram; The adjustment module is used to adjust the factory entry qualifications of outsourced personnel according to the safety monitoring results.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

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