Construction site management system and method for thermal power infrastructure and electronic equipment

Abstract

The invention relates to a construction site management system and method for thermal power infrastructure and electronic equipment. The system comprises a data acquisition module, a data analysis module, a strategy execution module and an interaction module. The data acquisition module is used for acquiring first operation data corresponding to a plurality of operation safety factors in a target operation area, and the operation safety factors comprise operators, operation equipment, operation materials or operation environments; the data analysis module is used for determining safety early warning data from the first operation data based on a safety identification model associated with a plurality of operation safety factors, and generating a safety control strategy execution instruction corresponding to each operation safety factor according to the safety early warning data; the strategy execution module is used for responding to the security management and control strategy execution instruction and synchronously executing the security management and control strategy corresponding to each operation security element; and the interaction module is used for displaying the security control strategy and the execution result corresponding to the security control strategy to a user.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of management, in particular to a construction site management system, method and electronic equipment for thermal power infrastructure construction. BACKGROUND

[0002] With the increasing demand for power generation unit construction, the demand for construction safety is also increasing. At present, a safety monitoring system is usually used for construction safety monitoring.

[0003] However, the existing safety monitoring system framework is old, and the stability and performance are low, which cannot adapt to the field requirements of complex application scenarios. SUMMARY

[0004] To solve the above problems, the present disclosure provides a construction site management system, method and electronic equipment for thermal power infrastructure construction.

[0005] According to a first aspect of the embodiments of the present disclosure, a construction site management system for thermal power infrastructure construction is provided, the system comprising a data acquisition module, a data analysis module, a policy execution module and an interaction module, the data analysis module being connected with the data acquisition module, the policy execution module and the interaction module respectively, and the interaction module being connected with the policy execution module; the data acquisition module is configured to acquire first job data corresponding to a plurality of job safety elements in a target job area, the job safety elements including job personnel, job equipment, job materials or job environment; the data analysis module is configured to determine safety warning data from the first job data based on a safety identification model associated with the plurality of job safety elements, and generate safety control policy execution instructions corresponding to each job safety element according to the safety warning data; the policy execution module is configured to execute the safety control policy corresponding to each job safety element in synchronization in response to the safety control policy execution instructions; and the interaction module is configured to show the safety control policy and the execution result corresponding to the safety control policy to a user.

[0006] Optionally, the data acquisition module comprises a personnel data acquisition component, an equipment data acquisition component, a material data acquisition component and an environment data acquisition component; the personnel data acquisition component is configured to acquire movement path data, job area entry and exit data and personnel safety behavior data of job personnel in the target job area; the equipment data acquisition component is configured to acquire equipment operation data of target job equipment and special equipment corresponding to the target job equipment in the target job area based on multi-protocol access and sensor collection; the material data acquisition component is configured to acquire job material data in the target job area based on video monitoring and tag positioning; and the environment data acquisition component is configured to acquire job environment data in the target job area based on video monitoring and sensor collection.

[0007] Optionally, the safety identification model comprises a trend prediction sub-model, a state identification sub-model, and a collaborative identification sub-model; the trend prediction sub-model is configured to take first job data that does not meet a preset data change trend as first safety warning data; the state identification sub-model is configured to take first job data that does not meet a preset state data threshold as second safety warning data; and the collaborative identification sub-model is configured to identify a safety risk of a plurality of job safety elements in the first job data, to obtain third safety warning data.

[0008] Optionally, the safety identification model is obtained by the following method: obtaining historical job data corresponding to a plurality of job safety elements in a target job area and historical safety warning data corresponding to the historical job data; taking the historical job data as an input of a multi-modal pre-training model and taking the historical safety warning data as an output of the multi-modal pre-training model, to train the safety identification model.

[0009] Optionally, the data analysis module is configured to generate a first warning strategy execution instruction according to the first safety warning data, generate a second warning strategy execution instruction according to the second safety warning data, and generate a safety element collaborative control strategy execution instruction according to the third safety warning data; the prompt strength of the second warning strategy is greater than that of the first warning strategy; the execution priority of the safety element collaborative control strategy is higher than that of the first warning strategy and the second warning strategy; and the safety element collaborative control strategy represents a safety risk caused by the collaboration of at least two of a plurality of job safety elements, and determines a multi-element collaborative control measure.

[0010] Optionally, the data analysis module is further configured to obtain second job data after execution of the safety control strategy, and verify the second job data according to the safety identification model.

[0011] Optionally, the interaction module comprises a visual interaction module; and the visual interaction module is configured to display the first job data based on a job data query instruction of a user.

[0012] According to a second aspect of the present disclosure, a site management method for thermal power infrastructure is provided, applied to a site management system for thermal power infrastructure. The system includes a data acquisition module, a data analysis module, a strategy execution module, and an interaction module. The data analysis module is connected to the data acquisition module, the strategy execution module, and the interaction module, respectively. The interaction module is connected to the strategy execution module. The method includes: acquiring first operational data corresponding to multiple operational safety elements in a target operational area, wherein the operational safety elements include personnel, equipment, materials, or environment; determining safety warning data from the first operational data based on a safety identification model associated with multiple operational safety elements, and generating a safety control strategy execution instruction corresponding to each operational safety element based on the safety warning data; synchronously executing the safety control strategy corresponding to each operational safety element in response to the safety control strategy execution instruction; and displaying the safety control strategy and the execution results corresponding to the safety control strategy to the user.

[0013] Optionally, the data acquisition module includes a personnel data acquisition component, an equipment data acquisition component, a material data acquisition component, and an environmental data acquisition component; acquiring the first operational data corresponding to multiple operational safety elements in the target operational area includes: acquiring the movement path data, entry and exit data, and personnel safety behavior data of the workers in the target operational area through the personnel data acquisition component; acquiring the equipment operation data of the target operational equipment and the special equipment corresponding to the target operational equipment in the target operational area through the equipment data acquisition component based on multi-protocol access and sensor acquisition; acquiring the operational material data in the target operational area through the material data acquisition component based on video surveillance and tag positioning; and acquiring the operational environment data in the target operational area through the environmental data acquisition component based on video surveillance and sensor acquisition.

[0014] Optionally, the safety identification model includes a trend prediction sub-model, a state identification sub-model, and a collaborative identification sub-model; the safety identification model based on the association of multiple operational safety elements determines safety warning data from the first operational data by: based on the trend prediction sub-model, taking the first operational data that does not meet a preset data change trend as the first safety warning data; based on the state identification sub-model, taking the first operational data that does not meet a preset state data threshold as the second safety warning data; and based on the collaborative identification sub-model, identifying the safety risks of multiple operational safety elements co-located in the first operational data to obtain the third safety warning data.

[0015] Optionally, the safety identification model is trained by: acquiring historical operation data corresponding to multiple operation safety elements in the target operation area and historical safety warning data corresponding to the historical operation data; using the historical operation data as input to the multimodal pre-trained model and the historical safety warning data as output to the multimodal pre-trained model to train the safety identification model.

[0016] Optionally, generating the safety control strategy execution instruction corresponding to each operational safety element based on the safety warning data includes: generating a first warning strategy execution instruction based on the first safety warning data; generating a second warning strategy execution instruction based on the second safety warning data; and generating a safety element collaborative control strategy execution instruction based on the third safety warning data. The warning intensity of the second warning strategy is greater than that of the first warning strategy, and the execution priority of the safety element collaborative control strategy is higher than that of the first and second warning strategies. The safety element collaborative control strategy characterizes the multi-element collaborative control measures determined for safety risks caused by the collaboration of at least two elements among multiple operational safety elements.

[0017] Optionally, the method further includes: acquiring second operation data after the security control strategy is executed, and verifying the second operation data according to the security identification model.

[0018] Optionally, the interaction module includes a visual interaction module; the method further includes: displaying the first job data based on the user's job data query command.

[0019] According to a third aspect of the present disclosure, an electronic device is provided, comprising: A memory on which computer programs are stored; A processor is configured to execute the computer program in the memory to implement the steps of the site management method for thermal power infrastructure as described in the second aspect of this disclosure.

[0020] According to the above technical solution, the data acquisition module acquires first operational data corresponding to multiple operational safety elements in the target operational area, including workers, equipment, materials, and the working environment. The data analysis module, based on a safety identification model associated with these multiple operational safety elements, determines safety warning data from the first operational data and generates safety control strategy execution instructions for each operational safety element based on the warning data. The strategy execution module responds to these instructions, synchronously executing the safety control strategies corresponding to each operational safety element. The interaction module then displays the safety control strategies and their execution results to the user. In this way, by establishing a site management system for multiple operational safety elements, the stability and performance of the site management system can be improved. Furthermore, by performing safety risk analysis on operational data based on multiple operational safety elements and presenting the integrated data analysis results intuitively to the user, it can adapt to the on-site needs of complex application scenarios, reduce management costs, and improve management effectiveness.

[0021] Other features and advantages of this disclosure will be described in detail in the following detailed description section. Attached Figure Description

[0022] The accompanying drawings are provided to further illustrate the present disclosure and form part of the specification. They are used together with the following detailed description to explain the present disclosure, but do not constitute a limitation thereof. In the drawings: Figure 1 This is a structural block diagram of a construction site management system for thermal power infrastructure, according to an exemplary embodiment.

[0023] Figure 2 This is a structural block diagram of another site management system for thermal power infrastructure, illustrated according to an exemplary embodiment.

[0024] Figure 3 This is a structural block diagram of another site management system for thermal power infrastructure, illustrated according to an exemplary embodiment.

[0025] Figure 4 This is a structural block diagram of another site management system for thermal power infrastructure, illustrated according to an exemplary embodiment.

[0026] Figure 5 This is a structural block diagram for a specific application scenario generated based on the structural block diagram of the construction site management system for thermal power infrastructure shown in the embodiments of this disclosure.

[0027] Figure 6 This is a flowchart illustrating a site management method for thermal power infrastructure according to an exemplary embodiment of the present disclosure.

[0028] Figure 7This is a block diagram of an electronic device provided according to an exemplary embodiment of the present disclosure. Detailed Implementation

[0029] The specific embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit this disclosure.

[0030] In the following description, the words "first" and "second" are used only to distinguish the purpose of the description and should not be interpreted as indicating or implying relative importance or order.

[0031] In related technologies, as the construction needs of power generation units increase, the demand for construction safety also grows. Currently, safety monitoring systems are commonly used for construction safety monitoring. However, existing safety monitoring systems have outdated frameworks, low stability and performance, and cannot meet the on-site requirements of complex application scenarios.

[0032] To address the aforementioned issues, this disclosure provides a site management system, method, and electronic device for thermal power infrastructure construction. The system involves a data acquisition module acquiring first operational data corresponding to multiple operational safety elements within a target work area, including personnel, equipment, materials, and the work environment. A data analysis module, based on a safety identification model linking these multiple operational safety elements, identifies safety warning data from the first operational data. Based on the safety warning data, a safety control strategy execution instruction is generated for each operational safety element. A strategy execution module responds to this instruction, synchronously executing the safety control strategy for each operational safety element. An interaction module displays the safety control strategy and its execution results to the user. This site management system, designed for multiple operational safety elements, improves stability and performance. Furthermore, by performing safety risk analysis on operational data based on these multiple elements and presenting the integrated analysis results intuitively to the user, it can adapt to the needs of complex application scenarios, reduce management costs, and improve management effectiveness.

[0033] The present disclosure will now be described in conjunction with specific embodiments.

[0034] Figure 1 This is a structural block diagram of a construction site management system for thermal power infrastructure, as illustrated in an exemplary embodiment. Figure 1As shown, the construction site management system 100 for thermal power infrastructure may include: a data acquisition module 101, a data analysis module 102, a strategy execution module 103, and an interaction module 104. The data analysis module 102 is connected to the data acquisition module 101, the strategy execution module 103, and the interaction module 104, respectively. The interaction module 104 is connected to the strategy execution module 103. The data acquisition module 101 is used to acquire first operation data corresponding to multiple operation safety elements in the target operation area. The data analysis module 102 is used to determine safety warning data from the first operation data based on a safety identification model 1021 associated with multiple operation safety elements, and generate a safety control strategy execution instruction corresponding to each operation safety element according to the safety warning data. The strategy execution module 103 is used to synchronously execute the safety control strategy corresponding to each operation safety element in response to the safety control strategy execution instruction. The interaction module 104 is used to display the safety control strategy and the execution result corresponding to the safety control strategy to the user.

[0035] The site management system 100 for thermal power infrastructure can be applied to the work areas of thermal power generation units, as well as hydropower, wind power, photovoltaic power generation, and energy storage power stations. The work area can include infrastructure construction work areas, such as the deep foundation pit work area and tower crane installation work area of ​​a thermal power generation unit. The work safety elements include workers, equipment, materials, and the work environment. Correspondingly, the first work data can include worker data, equipment data, material data, and environment data, which can be obtained through the Internet of Things (IoT), UWB (Ultra-Wideband), AI (Artificial Intelligence) analysis, and AR (Augmented Reality) monitoring. The personnel data can include identity data such as qualification certificates and behavioral data such as personnel work behavior. The equipment data can include equipment operating status data such as tower crane operating parameters and equipment safety monitoring data such as tower crane verticality deviation. The material data can include material inventory data and material consumption data. The environment data can include meteorological data such as humidity, wind speed, and ambient temperature. The safety warning data can include the first operational data that does not meet the preset standards. For example, for personnel data, personnel behavior data such as failure to follow procedures or failure to wear safety protective equipment can be used as safety warning data. For equipment data, tower crane data with verticality deviation greater than a preset threshold can be used as safety warning data. For material data, tower crane data with the weight of the hoisted material exceeding the tower crane's rated lifting capacity can be used as safety warning data. For environment data, humidity data with air humidity exceeding a preset humidity threshold can be used as safety warning data. This safety management strategy can include the management of individual operational safety elements, such as issuing a warning signal to the user when the air humidity exceeds a preset humidity threshold, or it can include the management of multiple operational safety elements, such as simultaneously executing audible and visual alarms for operators and suspending operations of equipment in the risk area when operators do not enter the risk area as required.

[0036] By adopting the above solution, the stability and performance of the construction site management system can be improved by establishing a construction site management system that targets multiple operational safety factors. At the same time, safety risk analysis can be performed on operational data based on multiple operational safety factors, and the integrated data analysis results can be presented to users intuitively. This approach can adapt to the on-site needs of complex application scenarios, reduce management costs, and improve management effectiveness.

[0037] In some embodiments, such as Figure 2As shown, the data acquisition module 101 includes a personnel data acquisition component 1011, an equipment data acquisition component 1012, a material data acquisition component 1013, and an environmental data acquisition component 1014. The personnel data acquisition component 1011 is used to acquire the movement path data, entry and exit data, and personnel safety behavior data of the workers in the target work area. The equipment data acquisition component 1012 is used to acquire the equipment operation data of the target work equipment and the special equipment corresponding to the target work equipment in the target work area based on multi-protocol access and sensor acquisition. The material data acquisition component 1013 is used to acquire the work material data in the target work area based on video surveillance and tag positioning. The environmental data acquisition component 1014 is used to acquire the work environment data in the target work area based on video surveillance and sensor acquisition.

[0038] Among them, the personnel data acquisition component 1011 is configured with a personnel information acquisition component and a personnel positioning component. The personnel information acquisition component can obtain the personal identity information of on-site operators, such as work unit, job type, work contract, etc., and can also obtain the education and training information of the operator for the operation area. When the personal identity information of the operator has been entered into the construction site management system 100 of thermal power infrastructure and the operator has completed the safety education and training for the operation area, the access permission for the operation area can be issued to the operator, and a personnel positioning tag can be configured for the operator (the positioning tag can be built into a safety protection device such as a safety helmet). The personnel positioning component can combine multiple (such as 100) positioning base stations, multiple (such as 10) law enforcement recording devices, and access control devices pre-configured in the target area to achieve personnel positioning and trajectory analysis. The equipment data acquisition component 1012 can, through an industrial data acquisition protocol, achieve the access, data acquisition, and storage of a heat network heat integrator and DTU (Data Transfer Unit) equipment, so as to have the capabilities of flow data storage, remote valve control, etc. It can also, through relevant protocols of SDK (Software Development Kit) and API (Application Programming Interface), achieve the access of video surveillance equipment supporting the target operation equipment, so as to have the capabilities of video transcoding, live stream playback, camera steering control, video storage, etc. It can also access through various databases such as TDengine and VeStore to achieve data acquisition, data format conversion, data storage, real-time data query, and historical data query functions. At the same time, the equipment data acquisition component 1012 can convert physical information into electrical signals or digital signals through tower crane sensors and intelligent sensors such as deep foundation pits and high formwork to achieve the acquisition of equipment data such as tower crane data, deep foundation pit data, and high formwork data. The material data acquisition component 1013 can, through UWB positioning technology, position the operation materials according to the tag information of the operation materials, and can also, in combination with the video acquisition equipment configured in the target operation area, assist in positioning the operation materials to obtain the operation material data. The environmental data acquisition component 1014 can, based on basic environmental data sensors such as temperature sensors, humidity sensors, and wind speed sensors, obtain the temperature data, humidity data, and wind speed data of the target operation area, and can also, based on the video acquisition equipment configured in the target operation area, obtain disaster environment data such as smoke and open fire in the target operation area.

[0039] The above technical solution can collect the operator data, operation equipment data, operation material data, and operation environment data in the target operation area according to multiple operation safety elements for subsequent Conducting safety risk analysis on operational data can adapt to the on-site needs of complex application scenarios, reduce management costs, and improve management effectiveness.

[0040] In some embodiments, such as Figure 3 As shown, the safety identification model 1021 includes a trend prediction sub-model 211, a state identification sub-model 212, and a collaborative identification sub-model 213. The trend prediction sub-model 211 is used to take the first operation data that does not meet the preset data change trend as the first safety warning data. The state identification sub-model 212 is used to take the first operation data that does not meet the preset state data threshold as the second safety warning data. The collaborative identification sub-model 213 is used to identify the safety risks of multiple operation safety elements in the first operation data and obtain the third safety warning data.

[0041] The first safety warning data represents operational data where the immediate value does not exceed the standard but deviates from the data change pattern, indicating potential safety hazards. The second safety warning data represents operational data where the immediate value has exceeded the standard, indicating safety risks that require timely handling. The third safety warning data represents operational data where multiple operational safety elements present safety risks. The safety identification model 1021 can use operational data collected in the data acquisition module 101 and stored in the PostgreSQL database and real-time database as input to obtain the safety warning data as output. For example, this trend prediction sub-model 211 can, for the worker element, identify worker density data in the work area that deviates from the historical average as abnormal handover of processes, indicating a risk of cross-operations, and use this worker density data as the first safety warning data. It can also identify minor worker violations, such as smoking and climbing over walls, as fire hazards and fall hazards, respectively, and use these minor violations as the first safety warning data. For the equipment element, it can identify abnormal equipment start-up and shutdown frequency data, such as an increase in the start-up and shutdown frequency of a lift for three consecutive days, as a loose switch, and use this as the first safety warning data. For the material element, it can identify material transportation loss rate data that deviates from the historical average as a potential safety hazard for transport vehicles, and use this as the first safety warning data. For the work environment element, it can identify equipment noise values ​​that deviate from the historical average as equipment aging, and use this as the first safety warning data. This state recognition sub-model 212… For personnel factors, severe violations such as not wearing safety belts while working at heights can be used as secondary safety warning data; for equipment factors, equipment exceeding standards such as tower crane overloading can be used as secondary safety warning data; for materials factors, hazardous materials exceeding standards such as gasoline exceeding temperatures can be used as secondary safety warning data; and for environmental factors, environmental exceeding standards such as toxic gas concentrations can be used as secondary safety warning data. This collaborative identification sub-model 213 can dynamically adjust the risk weights of multiple operational safety factors according to the actual operational scenario, and through multi-factor fusion and the establishment of risk transmission paths, it can pre-identify the collaborative risks of multiple factors. For example, in the case of simultaneous dust concentration exceeding standards and equipment sparks, it can identify the risk of explosion; and in the case of simultaneous personnel climbing over the tower crane area fence and tower crane operation, it can identify the risk of personnel injury or death, thereby determining the third safety warning data.

[0042] The above technical solution can determine different safety warning data for multiple operational safety elements through a safety identification model, thereby improving the efficiency and accuracy of safety risk identification. Subsequent management based on different safety warning data can adapt to the on-site needs of complex application scenarios, reduce management costs, and improve management effectiveness.

[0043] In some embodiments, the safety identification model 1021 can be trained by: acquiring historical operation data corresponding to multiple operation safety elements in the target operation area and historical safety warning data corresponding to the historical operation data; using the historical operation data as input to the multimodal pre-trained model and the historical safety warning data as output to the multimodal pre-trained model to train the safety identification model 1021.

[0044] The historical operation data includes operation data for historical time periods, which can be determined based on the operation cycle of the target operation area, for example, 24 months. This historical operation data can include multimodal data on operational elements such as personnel, equipment, materials, and environment. This multimodal data can include numerical data (e.g., equipment parameter data), image data (e.g., video surveillance images), and text data (e.g., violation record data). The historical safety warning data can include safety warning labels corresponding to the historical operation data, including the warning data type and triggering elements. The multimodal pre-trained model can employ the Transformer's cross-modal attention mechanism to extract features from the historical operation data and historical safety warning data. Through model fitting and generalization, the safety recognition model 1021 is trained. Furthermore, incremental learning can be performed by periodically (e.g., monthly) injecting new operation data.

[0045] It should be noted that the specific steps of training this multimodal pre-trained model can be found in the relevant steps of model training in related technologies, and will not be repeated here.

[0046] In some embodiments, the data analysis module 102 is configured to generate a first warning strategy execution instruction based on the first security warning data; generate a second warning strategy execution instruction based on the second security warning data; and generate a security element collaborative control strategy execution instruction based on the third security warning data. The second early warning strategy has a stronger alert intensity than the first early warning strategy. The safety element collaborative control strategy has a higher execution priority than both the first and second early warning strategies. This safety element collaborative control strategy characterizes multi-element collaborative control measures determined for safety risks arising from the synergy of at least two of various operational safety elements. For example, the first early warning strategy may include outputting early warning information to inspection personnel in the target work area. The early warning information may include audible and visual alerts such as low-frequency buzzers and slow-flashing yellow lights, or terminal alerts such as issuing a yellow alert to the inspection personnel's terminal. The first early warning strategy may also include checking the corresponding first safety early warning data and generating an analysis report based on the first safety early warning data, as well as subsequent continuous monitoring. The second early warning strategy may include outputting alarm information to all relevant personnel in the target work area. The alarm information may include audible and visual alarms such as high-frequency sirens and fast-flashing red lights, and terminal alerts such as issuing a red alert to the relevant personnel's terminal. This red alert requires manual confirmation. The second early warning strategy may also include temporarily suspending the hazardous operation, controlling the risk source, issuing a special rectification report, and subsequent follow-up by designated personnel. The third early warning strategy may include emergency warnings to all personnel, such as activating all alarm devices in the target work area, as well as rapid evacuation of all personnel and cutting off the source of risk. It may also include emergency rescue, expert acceptance, and phased resumption of work.

[0047] By adopting the above solution, safety management can be carried out based on different safety early warning data, which can adapt to the on-site needs of complex application scenarios, reduce management costs, improve management effectiveness, and enhance operational safety.

[0048] In some embodiments, the data analysis module 102 is further configured to acquire second operation data after the execution of the security control strategy, and verify the second operation data according to the security identification model 1021.

[0049] For example, for the second operational data after the execution of the first early warning strategy, tracking and investigation can be carried out according to a first preset period (e.g., 3 hours). If the safety identification model 1021 determines that the second operational data has returned to the preset range (e.g., environmental data meets the standard threshold and there is no collaborative risk among multiple elements), the first early warning strategy is considered to be effective, and the safety control process ends. Alternatively, if the second operational data is still not within the preset range, the first early warning strategy is considered to be ineffective, and the first early warning strategy is upgraded to a second early warning strategy. For the second operational data after the execution of the first early warning strategy, tracking and investigation can be carried out according to a second preset period (e.g., 1 hour). If the safety identification model 1021 determines that the second operational data has returned to the preset range, it is considered to be effective. If the second early warning strategy is effective, it will be downgraded to the first early warning strategy. Alternatively, if the second operation data is still outside the preset range, the second early warning strategy will be considered ineffective and upgraded to the third early warning strategy. For the second operation data after the third early warning strategy is implemented, it can be tracked and investigated according to the third preset period (e.g., 30 minutes). If the safety identification model 1021 determines that the second operation data has returned to the preset range, the third early warning strategy will be considered effective and downgraded to the second early warning strategy. Alternatively, if the second operation data is still outside the preset range, the third early warning strategy will be considered ineffective and the third early warning strategy will be repeated until the second operation data returns to the preset range.

[0050] By adopting the above solution, it is possible to obtain operational data after implementing different early warning strategies, improve the accuracy of strategy execution, adapt to the on-site needs of complex application scenarios, enhance management effectiveness, and improve operational safety.

[0051] In some embodiments, such as Figure 4 As shown, the interaction module 104 includes a visualization interaction module 1041, which is used to display the first job data based on the user's job data query command.

[0052] The visualization interaction module 1041 is built on the Vue.js framework to improve code reusability and maintainability. The visualization interaction module 1041 can adopt the IMS (Industrial Management System Development Platform) development platform, receive front-end requests through Spring Cloud Gateway, and perform back-end services such as service registration and configuration through Nacos (Dynamic Naming and Configuration Service). Display components such as Echarts (Enterprise Charts), Vue, H5 (HyperText Markup Language 5), and Miniui (Mini User Interface) are used to display operation data of multiple operation safety elements such as operators, operation equipment, operation materials, or operation environment.

[0053] The above technical solution can meet users' needs for querying operation data, and present the operation data corresponding to various operation safety elements to users in an intuitive way, so that users can manage according to on-site needs, thereby improving management effectiveness and enhancing operation safety.

[0054] Figure 5 This is a structural block diagram of a construction site management system for thermal power infrastructure, generated based on the structural block diagram of the embodiments shown in this disclosure, for a specific application scenario, such as... Figure 5 As shown, the system uses the Spring Cloud framework to build a microservice infrastructure, Nacos as the service registration and discovery center, PostgreSQL as the database, and Redis (Remote Dictionary Server) as the cache. The specific application methods of each component within the module can be found in the preceding descriptions and related technologies; they will not be elaborated upon here.

[0055] Figure 6 This is a flowchart illustrating a site management method for thermal power infrastructure according to an exemplary embodiment of this disclosure, such as... Figure 6As shown, this method can be applied to a construction site management system 100 for thermal power infrastructure. The system 100 includes a data acquisition module 101, a data analysis module 102, a strategy execution module 103, and an interaction module 104. The data analysis module 102 is connected to the data acquisition module 101, the strategy execution module 103, and the interaction module 104, respectively. The interaction module 104 is connected to the strategy execution module 103. The method may include the following steps: S601. Obtain the first operation data corresponding to multiple operation safety elements in the target operation area.

[0056] The safety elements of this operation include the operators, equipment, materials, or environment. S602. Based on a safety identification model that associates multiple operational safety elements, determine safety warning data from the first operational data, and generate safety control strategy execution instructions corresponding to each operational safety element according to the safety warning data.

[0057] S603. In response to the safety control strategy execution instruction, the safety control strategy corresponding to each work safety element is executed synchronously.

[0058] S604. Display the security control policy and the corresponding execution results to the user.

[0059] Optionally, the data acquisition module includes a personnel data acquisition component, an equipment data acquisition component, a material data acquisition component, and an environmental data acquisition component. The personnel data acquisition component is used to acquire the movement path data, entry and exit data, and personnel safety behavior data of the workers in the target work area. The equipment data acquisition component is used to acquire the equipment operation data of the target work equipment and the special equipment corresponding to the target work equipment in the target work area based on multi-protocol access and sensor acquisition. The material data acquisition component is used to acquire the work material data in the target work area based on video surveillance and tag positioning. The environmental data acquisition component is used to acquire the work environment data in the target work area based on video surveillance and sensor acquisition.

[0060] Optionally, the safety identification model includes a trend prediction sub-model, a state identification sub-model, and a collaborative identification sub-model; the trend prediction sub-model is used to identify first operational data that does not meet a preset data change trend as first safety warning data; the state identification sub-model is used to identify first operational data that does not meet a preset state data threshold as second safety warning data; and the collaborative identification sub-model is used to identify the safety risks of multiple operational safety elements co-operating in the first operational data to obtain third safety warning data.

[0061] Optionally, the safety identification model is trained by: acquiring historical operation data corresponding to multiple operation safety elements in the target operation area and historical safety warning data corresponding to the historical operation data; using the historical operation data as input to the multimodal pre-trained model and the historical safety warning data as output to the multimodal pre-trained model to train the safety identification model.

[0062] Optionally, the data analysis module is used to generate a first warning strategy execution instruction based on the first safety warning data; generate a second warning strategy execution instruction based on the second safety warning data; and generate a safety element collaborative control strategy execution instruction based on the third safety warning data. The warning intensity of the second warning strategy is greater than that of the first warning strategy, and the execution priority of the safety element collaborative control strategy is higher than that of the first and second warning strategies. The safety element collaborative control strategy characterizes the multi-element collaborative control measures determined for safety risks caused by the collaboration of at least two elements among multiple operational safety elements.

[0063] Optionally, the data analysis module is also used to obtain second operation data after the execution of the security control strategy, and to verify the second operation data according to the security identification model.

[0064] Optionally, the interaction module includes a visualization interaction module; the visualization interaction module is used to display the first job data based on the user's job data query command.

[0065] Using the above method, the data acquisition module acquires first operational data corresponding to multiple operational safety elements in the target work area, including workers, equipment, materials, and the work environment. The data analysis module, based on a safety identification model associated with these multiple operational safety elements, determines safety warning data from the first operational data and generates safety control strategy execution instructions for each operational safety element based on the warning data. The strategy execution module responds to these instructions, synchronously executing the safety control strategies for each operational safety element. The interaction module then displays the safety control strategies and their execution results to the user. This approach, by establishing a site management system for multiple operational safety elements, improves the stability and performance of the site management system. Furthermore, by performing safety risk analysis on operational data based on multiple operational safety elements and presenting the integrated data analysis results intuitively to the user, it can adapt to the needs of complex application scenarios, reduce management costs, and improve management effectiveness.

[0066] It should be noted that the relevant descriptions of each step in the methods described in the above embodiments have been described in detail in the embodiments of the system, and will not be elaborated here.

[0067] Figure 7 This is a block diagram of an electronic device 700 provided according to an exemplary embodiment of the present disclosure. For example... Figure 7 As shown, the electronic device 700 may include a processor 701 and a memory 702. The electronic device 700 may also include one or more of a multimedia component 703, an input / output (I / O) interface 704, and a communication component 705.

[0068] The processor 701 controls the overall operation of the electronic device 700 to complete all or part of the steps in the aforementioned site management method for thermal power infrastructure. The memory 702 stores various types of data to support the operation of the electronic device 700. This data may include, for example, instructions for any application or method operating on the electronic device 700, and application-related data such as contact data, sent and received messages, images, audio, video, etc. The memory 702 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. Multimedia component 703 may include a screen and an audio component. The screen may be, for example, a touchscreen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in memory 702 or transmitted via communication component 705. The audio component also includes at least one speaker for outputting audio signals. I / O interface 704 provides an interface between processor 701 and other interface modules, such as a keyboard, mouse, buttons, etc. These buttons may be virtual or physical buttons. Communication component 705 is used for wired or wireless communication between the electronic device 700 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IoT, eMTC, or other 5G technologies, or combinations thereof, is not limited here. Therefore, the corresponding communication component 705 may include: a Wi-Fi module, a Bluetooth module, an NFC module, etc.

[0069] In an exemplary embodiment, the electronic device 700 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-described site management method for thermal power infrastructure.

[0070] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, which, when executed by a processor, implement the steps of the above-described site management method for thermal power infrastructure. For example, the computer-readable storage medium may be the memory 702 including program instructions, which may be executed by the processor 701 of the electronic device 700 to complete the above-described site management method for thermal power infrastructure.

[0071] The preferred embodiments of this disclosure have been described in detail above with reference to the accompanying drawings. However, this disclosure is not limited to the specific details of the above embodiments. Within the scope of the technical concept of this disclosure, various simple modifications can be made to the technical solutions of this disclosure, and these simple modifications all fall within the protection scope of this disclosure.

[0072] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, this disclosure will not describe the various possible combinations separately.

[0073] Furthermore, various different embodiments of this disclosure can be combined in any way, as long as they do not violate the spirit of this disclosure, they should also be regarded as the content disclosed in this disclosure.

Claims

1. A construction site management system for thermal power plant infrastructure, characterized in that, The system includes a data acquisition module, a data analysis module, a strategy execution module, and an interaction module. The data analysis module is connected to the data acquisition module, the strategy execution module, and the interaction module, respectively. The interaction module is connected to the strategy execution module. The data acquisition module is used to acquire first operation data corresponding to multiple operation safety elements in the target operation area. The operation safety elements include operators, operation equipment, operation materials or operation environment. The data analysis module is used to determine safety warning data from the first operation data based on a safety identification model that associates multiple operation safety elements, and to generate safety control strategy execution instructions corresponding to each operation safety element based on the safety warning data. The strategy execution module is used to respond to the safety control strategy execution instruction and synchronously execute the safety control strategy corresponding to each operational safety element; The interactive module is used to display the security control strategy and the corresponding execution results to the user.

2. The system according to claim 1, characterized in that, The data acquisition module includes a personnel data acquisition component, an equipment data acquisition component, a material data acquisition component, and an environmental data acquisition component; The personnel data acquisition component is used to acquire the movement path data, entry and exit data, and personnel safety behavior data of the personnel in the target work area. The equipment data acquisition component is used to acquire equipment operation data of the target operating equipment and the special equipment corresponding to the target operating equipment in the target operating area based on multi-protocol access and sensor acquisition. The material data acquisition component is used to acquire work material data in the target work area based on video surveillance and tag positioning; The environmental data acquisition component is used to acquire work environment data in the target work area based on video surveillance and sensor acquisition.

3. The system according to claim 1, characterized in that, The security identification model includes a trend prediction sub-model, a state identification sub-model, and a collaborative identification sub-model; The trend prediction sub-model is used to take the first operational data that does not meet the preset data change trend as the first safety warning data. The state recognition sub-model is used to take the first operation data that does not meet the preset state data threshold as the second safety warning data. The collaborative identification sub-model is used to identify the safety risks associated with the collaboration of multiple operational safety elements in the first operational data, and to obtain the third safety warning data.

4. The system according to claim 3, characterized in that, The security identification model is trained in the following way: Acquire historical operation data corresponding to multiple operation safety elements in the target operation area and historical safety warning data corresponding to the historical operation data; The historical operation data is used as the input to the multimodal pre-trained model, and the historical safety warning data is used as the output of the multimodal pre-trained model to train the safety identification model.

5. The system according to claim 3, characterized in that, The data analysis module is used to generate a first warning strategy execution instruction based on the first security warning data; and to generate a second warning strategy execution instruction based on the second security warning data. Based on the third security early warning data, generate execution instructions for the collaborative control strategy of security elements; The warning intensity of the second warning strategy is greater than that of the first warning strategy, and the execution priority of the safety element collaborative control strategy is higher than that of the first warning strategy and the second warning strategy. The safety element collaborative control strategy characterizes the multi-element collaborative control measures determined for safety risks caused by the collaboration of at least two elements among multiple operational safety elements.

6. The system according to claim 1, characterized in that, The data analysis module is also used to acquire second operation data after the execution of the security control strategy, and to verify the second operation data according to the security identification model.

7. The system according to claim 1, characterized in that, The interaction module includes a visual interaction module; The visualization interaction module is used to display the first job data based on the user's job data query command.

8. A construction site management method for thermal power plant infrastructure, characterized in that, A site management system for thermal power plant infrastructure construction, the system comprising a data acquisition module, a data analysis module, a strategy execution module, and an interaction module, wherein the data analysis module is connected to the data acquisition module, the strategy execution module, and the interaction module, and the interaction module is connected to the strategy execution module; the method includes: Acquire first operational data corresponding to multiple operational safety elements in the target operational area, wherein the operational safety elements include operational personnel, operational equipment, operational materials, or operational environment; Based on a safety identification model that associates multiple operational safety elements, safety warning data is determined from the first operational data, and safety control strategy execution instructions corresponding to each operational safety element are generated according to the safety warning data. In response to the safety control strategy execution command, the safety control strategy corresponding to each operational safety element is executed synchronously. The security control policy and the corresponding execution results are displayed to the user.

9. The method according to claim 8, characterized in that, The method further includes: Obtain the second operation data after the security control strategy is executed, and verify the second operation data according to the security identification model.

10. An electronic device, characterized in that, include: A memory on which computer programs are stored; A processor for executing the computer program in the memory to implement the steps of the method of claims 8-9.

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