New energy power station construction and operation and maintenance stage integrated safety management platform

Abstract

The invention relates to the technical field of new energy power safety management, in particular to an integrated safety management platform for construction and operation and maintenance stages of a new energy power station. Synchronously acquiring personnel, equipment and environment multi-source data in a construction period and an operation and maintenance period through a multi-modal data acquisition layer; after preprocessing of the edge computing gateway layer and judgment of a local threshold value, construction and operation and maintenance sub-twinborn models are constructed by a cross-period safety twinborn modeling module and are mapped and aligned, so that hidden danger cross-period association is realized; the intelligent analysis module performs conjoint analysis on the fused data to predict illegal behaviors and accident probability; the safety index calculation module quantifies safety indexes and divides risk levels in combination with the multi-dimensional difference degree; the dynamic double-domain isolation module dynamically generates a dangerous area according to the risk level and executes intrusion judgment; and the linkage control module realizes safety control through equipment interface interlocking according to a judgment result, so that the construction operation and maintenance cooperative safety protection capability is improved.

Description

Technical Field

[0001] This invention relates to the field of new energy power safety management technology, specifically to an integrated safety management platform for the construction and operation and maintenance phases of new energy power plants. Background Technology

[0002] As a crucial support for the current energy transition, new energy power plants, including wind power, photovoltaic power, and energy storage power stations, involve extensive construction activities and long-term operation and maintenance management. The construction phase typically includes high-risk procedures such as hoisting, working near edges, and confined space operations, while the operation and maintenance phase involves electrical inspections, equipment maintenance, and routine checks. All these stages present complex risks related to personnel safety, equipment condition, and environmental conditions, placing high demands on safety management.

[0003] Currently, in the construction and operation of new energy power plants, construction safety management and operation and maintenance safety management often employ independent systems or methods. During the construction phase, risk monitoring is frequently conducted using video surveillance, wearable sensors, and BIM modeling, while the operation and maintenance phase relies on SCADA systems, CMMS management platforms, and operation and maintenance work order systems for operational status and maintenance management. However, the lack of effective integration between the two in terms of data, models, and processes makes it difficult to fully track potential hazards identified during the construction phase during the operation and maintenance phase. Furthermore, safety strategies during the operation and maintenance phase cannot fully utilize the information accumulated during the construction phase, resulting in "information silos."

[0004] Therefore, the main problem with existing technologies is that safety management in the construction and operation and maintenance phases is fragmented, lacking a unified data modeling and risk control mechanism, and failing to achieve full lifecycle safety information transmission and closed-loop management. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide an integrated safety management platform for the construction and operation and maintenance phases of new energy power plants, which addresses the shortcomings of the prior art and solves the technical problem of the separation of safety management between the construction and operation and maintenance phases and the lack of a unified data modeling and risk control mechanism.

[0006] The objective of this invention is achieved through the following technical solutions: In a first aspect, the present invention provides an integrated safety management platform for the construction and operation and maintenance phases of new energy power plants, comprising: The multimodal data acquisition layer is used to simultaneously acquire multi-source data during the construction period and multi-source data during the operation and maintenance period. The multi-source data during the construction period and multi-source data during the operation and maintenance period both include personnel status information, equipment operating condition information, and environmental parameter information. The edge computing gateway layer is used to preprocess multi-source data during the construction period and multi-source data during the operation and maintenance period, respectively, compare them with local thresholds, and output the preprocessed data and local event response signals. The cross-period safety twin modeling module is used to construct construction sub-twin models and operation and maintenance sub-twin models based on the preprocessed multi-source data of the construction period and multi-source data of the operation and maintenance period, respectively, and to map and align them through unified equipment identifiers and spatial coordinates to obtain fused data, and to associate the hidden dangers identified in the construction phase with the corresponding equipment nodes in the operation and maintenance phase. The intelligent analysis module is used to perform joint analysis on the fused data to predict violations, accident probabilities, and residual risks, and output the prediction results. The safety index calculation module is used to calculate the coherent safety index based on the prediction results, and output the corresponding risk level according to the preset threshold and the coherent safety index. The dynamic dual-domain isolation module is used to dynamically generate dangerous areas based on the risk level and in combination with construction space domain information and operation and maintenance electrical domain information, and to perform intrusion judgment on personnel or equipment entering the dangerous areas. The linkage control module is used to perform corresponding operations based on the intrusion determination result by interlocking with the control interface of the field equipment.

[0007] As a further improvement of the present invention, the multimodal data acquisition layer includes: multi-source data during the construction period, including hoisting equipment operation sensors, personnel positioning and physiological monitoring devices, and gas and dust detection devices; and multi-source data during the operation and maintenance period, including wind turbine status sensors, photovoltaic array temperature rise detection units, energy storage battery monitoring units, and UAV inspection imaging devices.

[0008] As a further improvement of the present invention, the preprocessing of multi-source data during the construction period and multi-source data during the operation and maintenance period includes filtering, denoising, normalizing and time synchronization of the collected multi-source data during the construction period and multi-source data during the operation and maintenance period in sequence. The local event response includes generating an alarm signal or preliminary control command at the local gateway when the data exceeds a preset threshold.

[0009] As a further improvement of the present invention, the inter-period safety twin modeling module includes a graph database for storing construction process nodes and equipment installation nodes in the construction sub-twin model, as well as operation and maintenance equipment nodes and work ticket nodes in the operation and maintenance sub-twin model, and realizes the mapping of hidden danger nodes in the construction stage to equipment nodes in the operation and maintenance stage through risk association edges.

[0010] As a further improvement of the present invention, the intelligent analysis module is constructed based on a graph neural network. The input of the graph neural network is the relationship data of nodes and edges stored in the graph database of the intertemporal security twin modeling module. Joint learning is performed through feature transfer and fusion of intertemporal nodes to output the prediction result of the risk.

[0011] As a further improvement of the present invention, the safety index calculation module generates the coherent safety index by weighted calculation of topology difference degree, electrical state difference degree, residual risk intensity and work order consistency difference degree, and the weight of each difference degree is set according to historical safety data or expert rules.

[0012] As a further improvement of the present invention, a coherent security index is calculated based on the prediction results, and a corresponding risk level is output based on a preset threshold and the coherent security index, including: Based on the prediction results, a quantified coherent security index is calculated. Based on the coherent safety index, combined with real-time spatial information and electrical status, a dynamic danger zone integrating the spatial and electrical domains is determined and generated. Based on the determination of the dynamic hazardous area, corresponding control and alarm commands are sent to on-site equipment and personnel.

[0013] As a further improvement of the present invention, the dynamic dual-domain isolation module includes: Spatial domain isolation units are used to dynamically generate and update spatial hazard areas related to construction activities based on UWB positioning data and BIM models. Electrical domain isolation units are used to dynamically generate and update electrical hazard zones associated with live equipment based on electrical system topology and real-time monitoring data. The outputs of the spatial domain isolation unit and the electrical domain isolation unit are superimposed and fused to generate comprehensive dynamic hazardous area information.

[0014] As a further improvement of the present invention, the linkage control module includes: The equipment interlock unit is used to connect with the PLC, electrical ring network cabinet and access control system of the hoisting equipment, and to send speed limit, interlock or emergency stop control commands to the corresponding equipment according to the judgment result; The personnel alarm unit is used to connect with smart helmets, vibration wristbands, on-site broadcasts and warning lights, and send visual, tactile or auditory alarm commands based on the dynamic danger zone information.

[0015] As a further improvement of the present invention, it also includes an event review and optimization module, which is connected to the linkage control module and the inter-period safety twin modeling module respectively. The event review and optimization module is used to record the control events triggered by the linkage control module and related data, and to feed the event data back to the graph database of the inter-period safety twin modeling module in order to optimize the risk correlation.

[0016] The beneficial effects of this invention are as follows: This invention provides an integrated safety management platform for the construction and operation and maintenance phases of new energy power plants. The multimodal data acquisition layer synchronously collects multi-source data from both the construction and operation and maintenance phases, achieving full-cycle data integration and real-time perception, thus improving the comprehensiveness of data collection. The edge computing gateway layer preprocesses and performs local threshold judgments on construction and operation and maintenance data respectively, outputting preprocessed data and local event response signals, enhancing data preprocessing efficiency and rapid response capabilities. The cross-phase safety twin modeling module constructs construction and operation and maintenance sub-twin models and maps and aligns them to form fused data, associating construction hazards with operation and maintenance equipment nodes, enabling accurate tracking of cross-phase hazards. The intelligent analysis module jointly analyzes the fused data to predict violations, accident probabilities, and residual risks, improving the accuracy of risk prediction. The safety index calculation module combines multi-dimensional differential quantification to quantify coherent safety indices and classifies risk levels, enabling scientific decision-making on risk levels. The dynamic dual-domain isolation module dynamically generates dangerous areas based on risk levels and combines spatial and electrical domain information, and performs intrusion judgment, improving the accuracy of dynamic protection. The linkage control module executes operations through device interface interlocking based on intrusion judgment results, ensuring rapid and effective response. The collaborative full-cycle closed-loop safety management and control system of these modules significantly improves the collaborative safety protection capabilities and risk prevention and control efficiency of construction and operation and maintenance compared to existing technologies. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of a module of an integrated safety management platform for the construction and operation and maintenance phases of a new energy power plant, according to an embodiment of the present invention.

[0019] Figure 2 This is an internal structural diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0020] To make the objectives and technical solutions of this invention clearer and easier to understand, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. The specific embodiments described herein are for illustrative purposes only and are not intended to limit the invention.

[0021] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings and specific embodiments. The described embodiments are only some embodiments of the present invention, and not all embodiments.

[0022] Example 1 This embodiment provides an integrated safety management platform for the construction and operation and maintenance phases of a new energy power plant. It includes: a multimodal data acquisition layer for simultaneously acquiring multi-source data during the construction and operation and maintenance phases, both of which include personnel status information, equipment operating condition information, and environmental parameter information; an edge computing gateway layer for preprocessing the construction and operation and maintenance multi-source data separately, comparing them with local thresholds, and outputting the preprocessed data and local event response signals; and a cross-phase safety twin modeling module for constructing construction and operation and maintenance sub-twin models based on the preprocessed construction and operation and maintenance multi-source data, mapping and aligning them using unified equipment identifiers and spatial coordinates to obtain fused data. The system links potential hazards identified during the construction phase to corresponding equipment nodes during the operation and maintenance phase. An intelligent analysis module performs joint analysis on the fused data to predict violations, accident probabilities, and residual risks, and outputs the prediction results. A safety index calculation module calculates the coherent safety index based on the prediction results and outputs the corresponding risk level according to preset thresholds and the coherent safety index. A dynamic dual-domain isolation module dynamically generates hazardous areas based on the risk level, combined with construction space domain information and operation and maintenance electrical domain information, and performs intrusion detection on personnel or equipment entering the hazardous areas. A linkage control module executes corresponding operations based on the intrusion detection results by interlocking with the control interface of the field equipment.

[0023] The working principle of this embodiment is as follows: the multimodal data acquisition layer synchronously collects multi-source data such as personnel status, equipment operating conditions, and environmental parameters during the construction and operation and maintenance periods, and ensures data time consistency through clock synchronization; the collected data is transmitted to the edge computing gateway layer, where it is preprocessed to remove noise and redundant information, and then compared with local thresholds to output preprocessed data and local event response signals; the cross-period safety twin modeling module constructs construction and operation and maintenance sub-twin models based on the preprocessed data, and achieves model mapping alignment through unified equipment identification and spatial coordinates to obtain fused data and associate construction hazards with operation and maintenance equipment nodes; the intelligent analysis module uses graph neural networks to jointly learn the fused data to predict violations, accident probabilities, and residual risks; the safety index calculation module calculates the coherent safety index based on the prediction results, matches the preset threshold, and outputs the risk level; the dynamic dual-domain isolation module dynamically generates dangerous areas by combining risk level, construction spatial domain, and operation and maintenance electrical domain information, and performs intrusion judgment on personnel or equipment entering; the linkage control module executes corresponding control operations and alarm prompts based on the intrusion judgment results through interlocking with the field equipment control interface.

[0024] The multimodal data acquisition layer includes: multi-source data during the construction phase, including sensors for hoisting equipment operation, personnel positioning and physiological monitoring devices, and gas and dust detection devices; and multi-source data during the operation and maintenance phase, including sensors for wind turbine status, photovoltaic array temperature rise detection units, energy storage battery pack monitoring units, and drone inspection imagery devices. The multimodal data acquisition layer, targeting different operational scenarios during the construction and operation and maintenance phases, uses dedicated acquisition equipment to collect data on hoisting equipment operation, personnel positioning and physiological data, and gas and dust concentration during the construction phase, and data on wind turbine status, photovoltaic array temperature rise, energy storage battery pack operation, and drone inspection imagery during the operation and maintenance phase. Each acquisition device collects data at a preset frequency, and after initial processing by its own data processing module, the data is transmitted to the edge computing gateway layer via corresponding communication methods, providing accurate and effective data support for subsequent preprocessing and analysis.

[0025] Preprocessing is performed on multi-source data during the construction period and multi-source data during the operation and maintenance period, including filtering, denoising, normalization and time synchronization of the collected multi-source data during the construction period and multi-source data during the operation and maintenance period respectively; local event response includes generating alarm signals or preliminary control commands on the local gateway when the data exceeds the preset threshold.

[0026] The inter-period safety twin modeling module includes a graph database, which stores construction process nodes and equipment installation nodes in the construction sub-twin model, as well as operation and maintenance equipment nodes and work ticket nodes in the operation and maintenance sub-twin model. It also uses risk-related edges to map potential hazard nodes in the construction phase to equipment nodes in the operation and maintenance phase.

[0027] The intelligent analysis module is built upon a graph neural network. The input to the graph neural network is the node-edge relationship data stored in the graph database of the inter-period safety twin modeling module. Through joint learning via feature transfer and fusion of inter-period nodes, it outputs risk prediction results. The intelligent analysis module, based on a graph neural network architecture, first obtains node-edge relationship data from the graph database of the inter-period safety twin modeling module. After preprocessing by the input layer, standardized node feature matrices and adjacency matrices are obtained. Multiple graph convolutional hidden layers extract and transform node features, and an attention mechanism is used to achieve feature transfer and fusion of inter-period nodes, resulting in fused node features. Finally, the output layer outputs prediction results such as the probability of violations, the probability of accidents, and residual risk values, and transmits these prediction results to the safety index calculation module.

[0028] The safety index calculation module generates a coherent safety index by weighting the topology difference, electrical condition difference, residual risk intensity and work permit consistency difference. The weight of each difference is set according to historical safety data or expert rules.

[0029] Example 2 An embodiment of the present invention provides an integrated safety management platform for the construction and operation and maintenance stages of a new energy power station. This platform is designed for the safety management requirements of the entire life cycle of a new energy power station from construction to operation, aiming to solve the problems of fragmented safety management, discontinuous information, and difficult risk transmission in the existing technology. By deploying multi-modal sensors, edge computing gateways, and digital twin modeling systems on-site, and combining artificial intelligence analysis methods with a safety index calculation mechanism, the platform realizes a closed-loop safety management from data perception to risk prediction and from dynamic isolation to linkage control.

[0030] As Figure 1 shown, the platform includes a multi-modal data acquisition layer, an edge computing gateway layer, an inter-period safety twin modeling module, an intelligent analysis module, a safety index calculation module, a dynamic dual-domain isolation module, and a linkage control module. The functional modules are connected in sequence according to the data flow and control flow: the acquisition layer transmits multi-source heterogeneous data to the edge gateway for preprocessing, the inter-period twin modeling module uniformly maps the information in the construction period and the operation and maintenance period, the intelligent analysis module uses a phase-aware graph neural network to fuse and reason the data, the safety index calculation module quantitatively evaluates the risk, the dynamic dual-domain isolation module constructs a dangerous area that integrates space and electricity, and finally the linkage control module converts the judgment result into a forced control action on-site. Through this architecture, the platform can cover the two major stages of construction and operation and maintenance, ensuring continuous monitoring and control of safety risks.

[0031] In an embodiment of the present invention, the platform first includes a multi-modal data acquisition layer. During the construction stage, the acquisition layer collects the human body state, mechanical working conditions, and environmental risks at the construction site in real time by deploying sensors for the operation of lifting equipment, positioning tags for construction workers, and heart rate acceleration sensor wristbands, as well as environmental gas and dust detection devices. During the operation and maintenance stage, the acquisition layer realizes a comprehensive perception of the operation state of the new energy power station by installing vibration sensors, temperature sensors, and current transformers on wind turbines, combined with a temperature rise detection unit for photovoltaic arrays, a state monitoring unit for energy storage battery packs, and an unmanned aerial vehicle inspection image acquisition device. Various acquisition devices are connected to the edge computing gateway through wired or wireless communication methods to ensure real-time data transmission.

[0032] After the data enters the platform, it is preprocessed by the edge computing gateway layer. The edge gateway is built with an industrial-grade processing unit and a storage module, which can filter, denoise, and normalize multi-modal data, and at the same time perform threshold judgment on key data such as heart rate, gas concentration, and current amplitude. Once the limit is exceeded, a local alarm is immediately triggered. The gateway also uses a differential compression algorithm to reduce the transmission pressure and achieves time synchronization through RTK and NTP, ensuring that the timestamp error of data from different sources does not exceed 80 milliseconds. In addition, the edge computing gateway also has the ability to respond to local events and can directly send linkage signals to on-site devices in case of network interruption or central delay.

[0033] After data preprocessing, the system proceeds to the cross-period safety twin modeling module. This module simultaneously establishes construction and operation / maintenance sub-twins: the construction sub-twin generates process topology, hoisting paths, and edge work areas based on the 4D-BIM model, while the operation / maintenance sub-twin constructs the operation / maintenance topology based on primary wiring and electrical zoning, and integrates it with the work ticket system and operation / maintenance work order data. Through a unified equipment identifier and spatial coordinate system, the construction and operation / maintenance sub-twin models are mapped and aligned in the graph database. Unresolved hazards during the construction phase can be directly linked to equipment nodes in the operation / maintenance phase through "legacy risk" edges, forming a cross-period knowledge graph.

[0034] Building upon this foundation, the platform's intelligent analysis module employs a phase-aware graph neural network to jointly learn the construction and operation and maintenance (O&M) graphs. Shared nodes between the construction and O&M subgraphs serve as cross-phase mapping points, leveraging a cross-phase message passing mechanism to achieve feature fusion, thereby establishing a causal link between construction legacy risks and O&M accident probabilities. This module can output violation prediction results, accident probability regression values, and residual risk estimates, and utilizes a federated learning model to ensure collaborative training and continuous optimization of construction and O&M data.

[0035] To achieve quantitative assessment, the platform includes a safety index calculation module. This module integrates four types of parameters—topology difference, electrical condition difference, residual risk intensity, and work permit consistency—to calculate the Coherent Safety Index (CSI), with the following formula:

[0036] in, Indicates the coherence security index; Indicates the degree of topological difference between the construction and operation and maintenance maps; Indicates the degree of difference in electrical condition; This indicates the intensity of risk that construction-related hazards persist during the operation and maintenance phase; Indicates the degree of consistency between the on-site operation status and the work order / ticket; The weighting parameter is determined based on historical accident data or expert experience. When the CSI value exceeds the set threshold, the system immediately enters a high-risk state and transmits the signal to downstream modules.

[0037] Furthermore, the platform integrates and isolates the construction space domain and the operation and maintenance electrical domain through a dynamic dual-domain isolation module. The space domain generates dynamic fences based on UWB base stations and BIM boundaries, and during hoisting operations, it generates a following ellipsoidal restricted area based on the hook trajectory. The electrical domain constructs a live equipotential zone through primary wiring and real-time SCADA data, and combines this with work permit authorization decisions. The isolation results of the two domains are superimposed; when personnel or equipment enter the overlapping area, the system identifies it as a high-level risk.

[0038] Ultimately, the platform relies on a linkage control module to translate the aforementioned risk assessment and isolation decisions into actual control actions. This module achieves interlocking with the hoisting equipment's PLC and electrical ring main unit through interfaces. When danger occurs during construction, it can limit the lifting speed or execute an emergency stop; when there is a risk of energization or inconsistencies in the work permit during maintenance, it can directly lock and close the circuit breaker. Simultaneously, the platform also alerts workers through methods such as displaying prohibited boundaries on the smart helmet HUD, wristband vibration, broadcasts, and flashing warning lights. All triggered events are written into a cross-period knowledge graph, which is used by the event review unit for subsequent model optimization.

[0039] Through the above implementation methods, the integrated safety management platform for the construction and operation and maintenance phases of new energy power plants described in this invention achieves an organic combination of data acquisition, intelligent analysis, and coordinated control. The platform can not only perform real-time risk identification for hoisting, edge-prone, and confined-space operations during the construction phase, but also accurately monitor and predict the operating status and risks of wind turbines, photovoltaic arrays, and energy storage devices during the operation and maintenance phase. The introduction of the Coherent Safety Index (CSI) allows for the quantitative assessment of inter-phase risks, and the application of phase-aware graph neural networks improves the accuracy of risk prediction and the ability to trace potential hazards left over from construction.

[0040] Meanwhile, the platform achieves dual protection for the spatial and electrical domains through a dynamic dual-domain isolation mechanism, and ensures the immediacy and effectiveness of control actions through interlocking interfaces with field equipment, keeping risk response delays within the sub-second range. The event review mechanism further feeds actual triggered data back into the knowledge graph and model, forming a closed loop for continuous optimization. Therefore, this invention not only solves the problem of separating safety management during the construction and operation / maintenance phases, but also constructs an integrated safety management system throughout the entire lifecycle, possessing strong practicality and promotional value.

[0041] Example 3 In another embodiment of the present invention, a computer-readable storage medium is provided as a storage component within a terminal device, the function of which is to store programs and data. It should be noted that the computer-readable storage medium here encompasses not only the built-in storage components of the terminal device but also extended storage components supported by the device. Essentially, it is a tangible medium capable of containing or storing programs that can be invoked by or in conjunction with an instruction execution system, device, or apparatus. This storage medium provides storage areas for the terminal's operating system and stores one or more instructions suitable for processor loading and execution, which can constitute one or more computer programs containing program code.

[0042] Specifically, examples of computer-readable storage media (a non-exclusive list) include: electrical connections with one or more wires, portable disks, hard disks, random access memory, read-only memory, erasable programmable read-only memory, optical fibers, portable optical disc read-only memory, optical storage devices, magnetic storage devices, or any reasonable combination of the above types.

[0043] The storage medium may also include data signals propagated as part of a baseband portion or a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any reasonable combination of both. Furthermore, computer-readable storage medium may also refer to other readable media besides conventional readable storage media, capable of sending, propagating, or transmitting programs for use or operation by an instruction execution system, apparatus, or device. Program code on the storage medium can be transmitted via any suitable medium, including but not limited to wireless, wired, optical fiber, or any reasonable combination thereof.

[0044] The program code used to implement the operations of this invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C. The execution modes of the program code include: running entirely on the user's computing device, running partially on the user's device as a standalone software package, running partially in a distributed manner on both the user's device and a remote computing device, or running entirely on a remote computing device or server. When a remote computing device is involved, the device can be connected to the user's computing device via any type of network such as a local area network (LAN) or a wide area network (WAN), or connected to an external computing device via the Internet through an Internet service provider.

[0045] The processor is capable of loading and executing one or more instructions stored in a computer-readable storage medium to implement the integrated safety management platform for the construction and operation and maintenance phases of the new energy power plant described in Example 1.

[0046] Example 4 Figure 2 This is a schematic diagram of a computer device provided according to an embodiment of the present invention.

[0047] Please see Figure 2The terminal device is a computer device. In this embodiment, the computer device 60 includes a processor 61, a memory 62, and a computer program 63 stored in the memory 62 and executable on the processor 61. When the processor 61 executes the computer program 63, it implements the integrated safety management platform for the construction and operation and maintenance phases of the new energy power plant in this embodiment. To avoid repetition, these details are not elaborated here. Alternatively, when the processor 61 executes the computer program 63, it implements the functions of each model / unit in the computational system constituting the integrated safety management platform for the construction and operation and maintenance phases of the new energy power plant in this embodiment. To avoid repetition, these details are not elaborated here.

[0048] Computer device 60 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device. Computer device 60 may include, but is not limited to, a processor 61 and a memory 62. Those skilled in the art will understand that... Figure 2 This is merely an example of computer device 60 and does not constitute a limitation on computer device 60. It may include more or fewer components than shown, or combine certain components, or different components. For example, computer device may also include input / output devices, network access devices, buses, etc.

[0049] The processor 61 may be a central processing unit (CPU), or other general-purpose processors, CPUs, graphics processing units (GPUs), digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, quantum computing-based data processing logic units, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0050] The memory 62 can be an internal storage unit of the computer device 60, such as a hard disk or RAM of the computer device 60. The memory 62 can also be an external storage device of the computer device 60, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. equipped on the computer device 60.

[0051] Furthermore, the memory 62 may include both internal storage units of the computer device 60 and external storage devices. The memory 62 is used to store computer programs and other programs and data required by the computer device. The memory 62 can also be used to temporarily store data that has been output or will be output.

[0052] Any references to memory, database, or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (Read-Only Memory). Memory includes ROM, magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic 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. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0053] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

Claims

1. An integrated safety management platform for the construction and operation and maintenance phases of a new energy power plant, characterized in that, include: The multimodal data acquisition layer is used to simultaneously acquire multi-source data during the construction period and multi-source data during the operation and maintenance period. The multi-source data during the construction period and multi-source data during the operation and maintenance period both include personnel status information, equipment operating condition information, and environmental parameter information. The edge computing gateway layer is used to preprocess multi-source data during the construction period and multi-source data during the operation and maintenance period, respectively, compare them with local thresholds, and output the preprocessed data and local event response signals. The cross-period safety twin modeling module is used to construct construction sub-twin models and operation and maintenance sub-twin models based on the preprocessed multi-source data of the construction period and multi-source data of the operation and maintenance period, respectively, and to map and align them through unified equipment identifiers and spatial coordinates to obtain fused data, and to associate the hidden dangers identified in the construction phase with the corresponding equipment nodes in the operation and maintenance phase. The intelligent analysis module is used to perform joint analysis on the fused data to predict violations, accident probabilities, and residual risks, and output the prediction results. The safety index calculation module is used to calculate the coherent safety index based on the prediction results, and output the corresponding risk level according to the preset threshold and the coherent safety index. The dynamic dual-domain isolation module is used to dynamically generate dangerous areas based on the risk level and in combination with construction space domain information and operation and maintenance electrical domain information, and to perform intrusion judgment on personnel or equipment entering the dangerous areas. The linkage control module is used to perform corresponding operations based on the intrusion determination result by interlocking with the control interface of the field equipment.

2. The integrated safety management platform for the construction and operation and maintenance phases of new energy power plants according to claim 1, characterized in that, The multimodal data acquisition layer includes: multi-source data during the construction phase, including sensors for hoisting equipment operation, personnel positioning and physiological monitoring devices, and gas and dust detection devices; and multi-source data during the operation and maintenance phase, including sensors for wind turbine status, photovoltaic array temperature rise detection units, energy storage battery monitoring units, and drone inspection imaging devices.

3. The integrated safety management platform for the construction and operation and maintenance phases of new energy power plants according to claim 2, characterized in that, The preprocessing of multi-source data during the construction period and multi-source data during the operation and maintenance period includes filtering, denoising, normalizing and time synchronization of the collected multi-source data during the construction period and multi-source data during the operation and maintenance period, respectively. The local event response includes generating an alarm signal or preliminary control command at the local gateway when the data exceeds a preset threshold.

4. The integrated safety management platform for the construction and operation and maintenance phases of new energy power plants according to claim 1, characterized in that, The inter-period safety twin modeling module includes a graph database for storing construction process nodes and equipment installation nodes in the construction sub-twin model, as well as operation and maintenance equipment nodes and work order nodes in the operation and maintenance sub-twin model. It also uses risk-related edges to map potential hazards in the construction phase to equipment nodes in the operation and maintenance phase.

5. The integrated safety management platform for the construction and operation and maintenance phases of new energy power plants according to claim 1, characterized in that, The intelligent analysis module is built on a graph neural network. The input of the graph neural network is the relationship data of nodes and edges stored in the graph database of the intertemporal security twin modeling module. Through feature transfer and fusion of intertemporal nodes, joint learning is performed to output the prediction result of the risk.

6. The integrated safety management platform for the construction and operation and maintenance phases of new energy power plants according to claim 5, characterized in that, The safety index calculation module generates the coherent safety index by weighted calculation of topology difference, electrical condition difference, residual risk intensity and work order consistency difference. The weight of each difference is set according to historical safety data or expert rules.

7. The integrated safety management platform for the construction and operation and maintenance phases of new energy power plants according to claim 6, characterized in that, The coherence security index is calculated based on the prediction results, and the corresponding risk level is output according to the preset threshold and the coherence security index, including: Based on the prediction results, a quantified coherent security index is calculated. Based on the coherent safety index, combined with real-time spatial information and electrical status, a dynamic danger zone integrating the spatial and electrical domains is determined and generated. Based on the determination of the dynamic hazardous area, corresponding control and alarm commands are sent to on-site equipment and personnel.

8. The integrated safety management platform for the construction and operation and maintenance phases of new energy power plants according to claim 1, characterized in that, The dynamic dual-domain isolation module includes: Spatial domain isolation units are used to dynamically generate and update spatial hazard areas related to construction activities based on UWB positioning data and BIM models. Electrical domain isolation units are used to dynamically generate and update electrical hazard zones associated with live equipment based on electrical system topology and real-time monitoring data. The outputs of the spatial domain isolation unit and the electrical domain isolation unit are superimposed and fused to generate comprehensive dynamic hazardous area information.

9. The integrated safety management platform for the construction and operation and maintenance phases of new energy power plants according to claim 1, characterized in that, The linkage control module includes: The equipment interlock unit is used to connect with the PLC, electrical ring network cabinet and access control system of the hoisting equipment, and to send speed limit, interlock or emergency stop control commands to the corresponding equipment according to the judgment result; The personnel alarm unit is used to connect with smart helmets, vibration wristbands, on-site broadcasts and warning lights, and send visual, tactile or auditory alarm commands based on the dynamic danger zone information.

10. The integrated safety management platform for the construction and operation and maintenance phases of new energy power plants according to claim 8, characterized in that, It also includes an event review and optimization module, which is connected to the linkage control module and the inter-period safety twin modeling module respectively. The event review and optimization module is used to record the control events triggered by the linkage control module and related data, and feed the event data back to the graph database of the inter-period safety twin modeling module to optimize the risk correlation.

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