Fire-fighting facility full life cycle management method and system

Abstract

The invention provides a fire-fighting facility full life cycle management method and system, and the method comprises the steps: building an initial digital twinborn model with the basic information of a sensing node in a planning stage of fire-fighting facilities according to the design data of a building and the fire-fighting facilities; in the production and installation stage of the fire-fighting equipment, obtaining attribute data of the fire-fighting equipment, and correcting the initial digital twinborn model based on the attribute data to obtain a corrected digital twinborn model; in an operation and maintenance monitoring stage of the fire-fighting equipment, acquiring operation data of the fire-fighting equipment acquired by the sensing node, and dynamically updating the corrected digital twinborn model based on the operation data; and when the fire-fighting facility reaches the scrapping condition, generating an analysis report based on full life cycle data generated by the fire-fighting facility in the full life cycle, and generating a design optimization suggestion based on the analysis report to guide subsequent planning and design of the fire-fighting facility. According to the invention, based on the dynamically evolved digital twin model, the initiative, accuracy and scientificity of fire-fighting management are improved.

Description

Technical Field

[0001] This invention relates to the field of smart fire protection technology, specifically to a method and system for the full life cycle management of fire protection facilities. Background Technology

[0002] Fire protection facilities are the core physical barrier ensuring building safety, and their reliability directly affects the safety of people and property. With the development of smart cities and IoT technologies, fire management is evolving from a traditional manual model to a digital and intelligent one. However, existing technological solutions still have significant shortcomings in achieving full-process, refined, and intelligent management of fire protection facilities, specifically as follows: First, current fire protection facility management involves multiple independent stages, including planning and design (such as BIM), manufacturing, installation and commissioning, operation and maintenance monitoring, and disposal and recycling. Data from each stage is stored in different professional systems or paper archives, creating serious "data silos." For example, maintenance personnel can only obtain the current alarm status of equipment but cannot quickly trace its design parameters, production batches, installation records, and other key historical information, resulting in low efficiency in fault diagnosis, lack of root cause analysis, and inability to achieve full lifecycle data integration and asset tracking. Second, traditional management models heavily rely on manual periodic inspections and offline testing, which carries the risk of missed or false inspections and cannot achieve real-time, continuous perception of equipment operating status (such as minor pipeline leaks, overheating of lines, and mechanical fatigue). Third, existing technologies mostly focus on single-point monitoring during the operation and maintenance phase, lacking an integrated management framework covering the entire process from planning to production, installation, operation and maintenance, and disposal. Information is disconnected between stages, failing to form an effective feedback loop. For example, decommissioning decisions are often based solely on a fixed service life, failing to incorporate actual equipment wear and tear data and failure history for scientific assessment. Furthermore, the experience and data accumulated during operation and maintenance cannot be effectively fed back into the planning and design phase of next-generation facilities, leading to recurring problems and failing to maximize the full lifecycle value of assets. Fourth, existing twin models are mostly static or read-only, lacking real-time data synchronization and two-way interaction capabilities with physical entities. Moreover, predictive maintenance, simulation, and intelligent decision support based on twin models have not been established, thus their technological value has not been fully realized.

[0003] Therefore, there is an urgent need to provide a method and system for the full life cycle management of fire protection facilities that can break down data barriers, achieve full traceability, and drive intelligent decision-making based on dynamic digital twin models, so as to fundamentally improve the initiative, accuracy and scientific nature of fire protection management. Summary of the Invention

[0004] In view of this, it is necessary to provide a method and system for the full life cycle management of fire protection facilities to solve the technical problems existing in the prior art, such as data barriers between different stages of fire protection facilities, which prevent the realization of full life cycle management and thus result in low initiative, accuracy and scientificity of fire protection management.

[0005] To address the aforementioned technical problems, in a first aspect, the present invention provides a method for the full life-cycle management of fire protection facilities, comprising: During the planning phase of fire protection facilities, an initial digital twin model with basic information of sensing nodes is constructed based on the design data of the building and fire protection facilities. During the production and installation phase of fire protection facilities, attribute data of the fire protection facilities is acquired, and the initial digital twin model is corrected based on the attribute data to obtain a corrected digital twin model. During the operation and maintenance monitoring phase of fire protection facilities, the operation data of the fire protection facilities collected by the sensing nodes are acquired, and the modified digital twin model is dynamically updated based on the operation data. When fire protection facilities reach the conditions for being scrapped, an analysis report is generated based on the full life cycle data generated by the fire protection facilities throughout their entire life cycle. Based on the analysis report, design optimization suggestions are generated to guide the planning and design of subsequent fire protection facilities.

[0006] In one possible implementation, the sensing node includes an optical fiber sensor and a video probe; the basic information of the sensing node includes the preset installation location and identification of the optical fiber sensor and the video probe in the building.

[0007] In one possible implementation, the attribute data includes the manufacturing parameters of the fire protection facilities, measured data of the installation location, and factory inspection data.

[0008] In one possible implementation, if the fire protection facility includes multiple fire protection components, then the method further includes: Establish the binding relationship between the sensing node and the fire protection component; The step of dynamically updating the corrected digital twin model based on the operational data includes: The ownership of the running data is determined based on the binding relationship, so as to dynamically update the modified digital twin model.

[0009] In one possible implementation, establishing the binding relationship between the sensing node and the fire protection component includes: When the sensing node is a fiber optic sensor, a pre-built RFID-fiber optic integrated tag is integrated into the fire protection component. The RFID part of the RFID-fiber optic integrated tag stores the component's unique identifier, and the fiber optic sensing part is used to collect operational data. The binding relationship is established through the unique identifier. When the sensing node is a video probe, an association is established between the video probe's number and the fire protection component, and a binding relationship is established between the video probe and the fire protection component based on the association.

[0010] In one possible implementation, the sensing node transmits the operational data via a heterogeneous communication network; the heterogeneous communication network is configured with differentiated transmission protocols for the sensing data of the fiber optic sensor and the video data of the video probe. The heterogeneous communication network includes 5G / LoRa, a fiber optic ring network, and a base station. The base station is used to transmit data when the communication of the 5G / LoRa and fiber optic ring network is interrupted. The video data uses a compressed transmission protocol, and the sensor data uses a low-latency transmission protocol.

[0011] In one possible implementation, the dynamic updating of the modified digital twin model based on the operational data includes: The operational data is input into the hazard diagnosis deep learning model to obtain the hazard level, confidence level, and key evidence data source of the fire protection components; The status attributes of the virtual fire protection component in the modified digital twin model are dynamically updated based on the hazard level.

[0012] In one possible implementation, the method further includes: When the hazard level is a fire level and the confidence level is greater than the preset confidence level, the three-dimensional location of the fire point, the spread simulation area, the real-time status of the affected evacuation route, and the signal coverage strength data of the communication base station in the area are determined based on the dynamically updated digital twin model. Starting from the current location of the rescue forces and ending at the fire point, the rescue route is determined by using the accessibility of evacuation routes and the signal coverage strength as dynamic weights. Based on the rescue path and the spread simulation area, a dispatch plan is generated, including fire force deployment suggestions, evacuation guidance instructions, and a list of surrounding resources to be activated.

[0013] In one possible implementation, the method further includes: The predicted remaining service life and hazard level of fire protection components are determined based on the dynamically updated digital twin model; The historical maintenance costs of the fire protection components are obtained. An optimization model is established with the goal of minimizing the total expected cost and the risk level within the maintenance plan cycle. The optimization model is then solved using a genetic algorithm to obtain a maintenance strategy report that includes preventive maintenance time, required personnel skill combinations, and a spare parts list.

[0014] Secondly, the present invention also provides a fire protection facility lifecycle management system, comprising: The planning phase twin model building unit is used to construct an initial digital twin model with basic information of sensing nodes based on the design data of the building and fire protection facilities during the planning phase of fire protection facilities. The production and installation phase digital twin model establishment unit is used to acquire attribute data of fire protection facilities during the production and installation phase of fire protection facilities, and to modify the initial digital twin model based on the attribute data to obtain a modified digital twin model. The twin model establishment unit for the operation and maintenance monitoring phase is used to acquire the operation data of the fire protection facilities collected by the sensing nodes during the operation and maintenance monitoring phase of the fire protection facilities, and to dynamically update the modified digital twin model based on the operation data. The full life cycle analysis unit is used to generate an analysis report based on the full life cycle data generated by the fire protection facilities during their entire life cycle when the fire protection facilities reach the conditions for decommissioning. Based on the analysis report and the dynamically updated digital twin model, it generates design optimization suggestions to guide the planning and design of subsequent fire protection facilities.

[0015] The beneficial effects of this invention are as follows: The fire protection facility full lifecycle management method provided by this invention, after constructing an initial digital twin model with basic information of sensing nodes at the planning node of the fire protection facility, updates the digital twin model of the previous stage based on the data of each node in the subsequent production and installation stage and operation and maintenance monitoring stage, completely breaking down data silos and realizing the full-process association of fire protection facility identity, status, and location information. This enables the rapid retrieval of all-dimensional historical data (design parameters, production records, maintenance logs, etc.) of the fire protection facility during subsequent fault diagnosis / troubleshooting, greatly improving the efficiency and accuracy of fault root cause analysis and realizing the management of the entire lifecycle of fire protection facilities.

[0016] Furthermore, the present invention sets up sensing nodes to collect operational data of fire protection facilities. Compared with the technical problems of lagging and one-sided monitoring by manual inspection, it achieves accurate prevention in advance and significantly reduces the probability of fire accidents.

[0017] Furthermore, the digital twin models at each stage of this invention are dynamically evolving, maintaining consistency with the physical entity through real-time data. Based on this high-fidelity digital twin model, reliable analysis can be performed, yielding reliable and accurate analysis reports. This provides a solid data foundation for subsequent in-depth analyses such as fault simulation, emergency drills, and maintenance strategy optimization. Simultaneously, the full-cycle analysis report generated during the decommissioning stage produces design optimization suggestions, guiding the planning and design of subsequent fire protection facilities. This forms a continuous closed loop of data-driven optimization design, improving the reliability and economy of subsequent fire protection facilities. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A schematic flowchart of an embodiment of the fire protection facility full life cycle management method provided by the present invention; Figure 2 For the present invention Figure 1 A schematic diagram of an embodiment of S103; Figure 3 A schematic flowchart of an embodiment of the rescue route determination and dispatch scheme provided by the present invention; Figure 4 A schematic flowchart of an embodiment of the maintenance strategy determination report provided by the present invention; Figure 5 This is a schematic diagram of an embodiment of the fire protection facility life cycle management system provided by the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0021] It should be understood that the illustrative drawings are not drawn to scale. The flowcharts used in this invention illustrate operations implemented according to some embodiments of the invention. It should be understood that the operations in the flowcharts may be implemented out of order, and steps without logical contextual relationships may be reversed or performed simultaneously. Furthermore, those skilled in the art, guided by the content of this invention, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor systems and / or microcontroller systems.

[0022] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0023] This invention provides a method and system for the full life cycle management of fire protection facilities, which will be described below.

[0024] Figure 1 A schematic flowchart of an embodiment of the fire protection facility lifecycle management method provided by the present invention is shown below. Figure 1 As shown, the full life-cycle management method for fire protection facilities includes: S101. During the planning stage of fire protection facilities, an initial digital twin model with basic information of sensing nodes is constructed based on the design data of the building and fire protection facilities.

[0025] Specifically, the design data for building and fire protection facilities includes, but is not limited to, drone aerial photography data, geographic information system (GIS) data, and building information model data.

[0026] The specific construction process of the initial digital twin model is as follows: First, an integrated panoramic model of the building and fire protection facilities is constructed based on the design data. Then, the basic information of the perception nodes is marked in the integrated panoramic model to obtain the initial digital twin model.

[0027] In a specific embodiment of the present invention, the sensing node includes an optical fiber sensor and a video probe; the basic information of the sensing node includes the preset installation location and identification of the optical fiber sensor and the video probe in the building.

[0028] The preset installation location includes positional information such as three-dimensional coordinates, orientation, and viewing angle. The identification identifier represents a unique code for each sensing node, which includes the sensing node's device type, model, and the object it is monitoring.

[0029] It should be noted that, since the initial digital twin model needs to be constructed simultaneously with the planning of how to transmit data back, the sensing node also needs to include the base station for communication. That is, the initial digital twin model also includes the basic information of the base station.

[0030] It should be understood that the buildings in the embodiments of the present invention can be buildings in environments such as hospitals, chemical industrial parks, and residential areas.

[0031] S102. During the production and installation phase of fire protection facilities, acquire the attribute data of the fire protection facilities, and modify the initial digital twin model based on the attribute data to obtain a modified digital twin model.

[0032] Specifically, the attribute data includes the manufacturing parameters of the fire protection facilities, the measured data of the installation location, and the factory inspection data.

[0033] Manufacturing parameters include, but are not limited to, pipe dimensions and thickness. Factory inspection data includes, but is not limited to, spectral analysis reports of material composition, valve factory pressure test curves, bolt tightening torque values, and X-ray flaw detection reports of pipe welds. Actual installation location measurement data includes the three-dimensional coordinates of the final installation of the fire protection facilities.

[0034] S103. During the operation and maintenance monitoring phase of fire protection facilities, acquire the operation data of fire protection facilities collected by the sensing nodes, and dynamically update the modified digital twin model based on the operation data.

[0035] Dynamic updates include not only updating the status of fire protection facilities in the digital twin model, but also calibrating the input parameters or internal equations within the model. For example, by analyzing the relationship between pressure and flow rate, it was found that the actual pipeline resistance coefficient was 15% higher than the design value, so the resistance coefficient parameter in the digital twin model was modified. This changes the behavioral logic of the digital twin model, making its future pressure predictions for all flow rates more accurate.

[0036] To avoid the technical problem of low accuracy in dynamically updating the corrected digital twin model due to single-dimensional operational data, in some embodiments of the present invention, the operational data includes pipeline pressure, temperature, and strain data collected by fiber optic sensors, ultraviolet-visible dual-spectral data obtained by video probes, and chemical particle data collected by a pyrolysis particle-fiber optic co-probe based on fiber optic sensors.

[0037] It should be understood that the introduction of fiber optic sensors has solved the technical problem of extracting pipeline data in complex scenarios such as chemical industrial parks and hospitals. Ultraviolet-visible dual-spectral data can be combined with AI video recognition technology, using cross-verification technology of smoke characteristic spectra and flame dynamic contours to ensure accurate extraction and identification of fire events. Chemical particulate data refers to specific particles released in the early stages of combustion; by monitoring this parameter, ultra-early intervention before disasters can be achieved, enabling proactive safety prevention and control.

[0038] In summary, the embodiments of the present invention dynamically update the modified digital twin model by using multimodal and multidimensional operational data, which can improve the consistency between the updated digital twin model and the physical world, thereby improving the accuracy and reliability of subsequent analysis results.

[0039] S104. When fire protection facilities reach the conditions for being scrapped, an analysis report is generated based on the full life cycle data generated during the entire life cycle of the fire protection facilities. Based on the analysis report, design optimization suggestions are generated to guide the planning and design of subsequent fire protection facilities.

[0040] It should be noted that the analysis report includes comparative analysis results from multiple stages, such as the planning stage, production and installation stage, and operation and maintenance monitoring stage, in order to identify the stage at which a fault or problem occurs and provide detailed guidance and suggestions for the subsequent planning and design of fire protection facilities.

[0041] For example, the digital twin model alarms when the pressure drops to 5 MPa, but actual data shows that a leak has already occurred at 5.5 MPa. Based on this comparison, the leak alarm threshold can be optimized in subsequent design processes to avoid missed or false alarms.

[0042] It should be understood that the fire protection facility lifecycle management method in this embodiment of the invention can be implemented in any device based on the fire protection facility lifecycle management method, such as electronic devices like fire protection facility evaluation equipment. Specifically, the fire protection facility lifecycle management method is stored in the aforementioned device as a pre-programmed program. When the device is started, the program is invoked, and the fire protection facility lifecycle management method is implemented.

[0043] Compared with existing technologies, the fire protection facility lifecycle management method provided in this invention, after constructing an initial digital twin model with basic information of sensing nodes at the planning node of the fire protection facility, updates the digital twin model of the previous stage based on the data of each node in the subsequent production and installation and operation and maintenance monitoring stages. This completely breaks down data silos and realizes the full-process association of fire protection facility identity, status, and location information. This enables the rapid retrieval of all-dimensional historical data (design parameters, production records, maintenance logs, etc.) of the fire protection facility during subsequent fault diagnosis / troubleshooting, greatly improving the efficiency and accuracy of fault root cause analysis and realizing the management of the entire lifecycle of fire protection facilities.

[0044] Furthermore, in this embodiment of the invention, sensing nodes are set up to collect operational data of fire protection facilities. Compared with the technical problems of lagging and one-sided monitoring by manual inspection, accurate prevention is achieved and the probability of fire accidents is significantly reduced.

[0045] Furthermore, in this embodiment of the invention, the digital twin model at each stage is dynamically evolving, maintaining consistency with the physical entity through real-time data. Based on this high-fidelity digital twin model, reliable analysis can be performed, yielding reliable and accurate analysis reports. This provides a solid data foundation for subsequent in-depth analyses such as fault simulation, emergency drills, and maintenance strategy optimization. Simultaneously, the full-cycle analysis report generated during the decommissioning stage generates design optimization suggestions, guiding the planning and design of subsequent fire protection facilities. This forms a continuous closed loop of data-driven optimization design, improving the reliability and economy of subsequent fire protection facilities.

[0046] In practical applications, buildings include multiple fire protection components, such as fire curtains and fire hydrants. Therefore, in some embodiments of the present invention, the fire protection facilities include multiple fire protection components, and the method further includes: Establish the binding relationship between sensing nodes and fire protection components; The digital twin model is then dynamically updated based on operational data, including: The ownership of runtime data is determined based on the binding relationship, so as to dynamically update the modified digital twin model.

[0047] By establishing a binding relationship between sensing nodes and fire protection components, this invention can accurately overlay the operational data collected by the sensing nodes onto the corresponding fire protection components, thereby achieving precise updates to the fire protection components and improving the accuracy of the digital twin model.

[0048] In a specific embodiment of the present invention, the binding relationship between the sensing node and the fire protection component is constructed, including: When the sensing node is a fiber optic sensor, the pre-built RFID-fiber optic integrated tag is integrated into the fire protection component. The RFID part of the RFID-fiber optic integrated tag stores the component's unique identifier, and the fiber optic sensing part is used to collect operational data. The binding relationship is established through the unique identifier. When the sensing node is a video probe, the association between the video probe's number and the fire protection component is established, and the binding relationship between the video probe and the fire protection component is established based on the association.

[0049] It should be understood that the binding relationship between the fiber optic sensor and the fire protection component can also be established by establishing an association through the location number and identification of the fiber optic sensor. That is, the embodiments of the present invention provide two different ways to build the binding relationship, which improves the diversity and applicability of the methods.

[0050] Since a communication link is required to transmit data from the sensing node to the digital twin model, in order to ensure the reliability and redundancy of the communication link, in some embodiments of the present invention, the sensing node transmits operational data through a heterogeneous communication network; the heterogeneous communication network configures different transmission protocols for the sensing data of the fiber optic sensor and the video data of the video probe. Heterogeneous communication networks include 5G / LoRa, fiber optic ring networks, and base stations. Base stations are used to transmit data when communication in 5G / LoRa or fiber optic ring networks is interrupted. Video data uses a compressed transmission protocol, while sensor data uses a low-latency transmission protocol.

[0051] Among them, 5G and LoRa are mainly used to transmit sensor data and low-bit-rate status signaling from mobile or distributed sensing nodes; the fiber optic ring network, as the core bearer network, is used to transmit video data, high-precision sensor data from key sensing nodes, and synchronization data of digital twin models; the base station is used to transmit emergency command data, including fire alarms, fault location, and evacuation instructions, as well as the most critical compressed sensor data, when the 5G / LoRa and fiber optic ring network communication networks are interrupted.

[0052] The embodiments of the present invention, through a multi-redundant communication architecture design, can ensure uninterrupted data transmission and achieve reliable data transmission.

[0053] In traditional networks employing a single transmission strategy, large-volume video streams, which are insensitive to latency, relentlessly consume network resources. This results in critical sensor alarm signals, which are extremely sensitive to latency but have small data volumes, failing to arrive in a timely manner, creating a transmission conflict where high-volume traffic blocks low-critical-value signals. This directly threatens the real-time performance and timely warnings of the digital twin model. This invention, by using a compressed transmission protocol for video data and a low-latency transmission protocol for sensor data, effectively solves the aforementioned multimodal transmission conflict problem, ensuring the real-time dynamic updates of the digital twin model and the timely warnings.

[0054] It should be noted that: regular data is synchronized once per second, while events such as sudden changes in fiber optic strain or video recognition anomalies trigger millisecond-level synchronization.

[0055] In some embodiments of the present invention, such as Figure 2 As shown, step S103 includes: S201. Input the operational data into the deep learning model for hazard diagnosis to obtain the hazard level, confidence level, and key evidence data source of the fire protection components.

[0056] Specifically, the deep learning model for hazard diagnosis employs a random forest + attention mechanism. The operational data includes strain and temperature data collected by fiber optic sensors, visual feature data collected by video probes, and equipment operating condition data of fire protection components (such as pump current, valve opening, and pipeline pressure). When inputting the operational data into the deep learning model, different weights are assigned to different types of operational data to achieve multimodal data fusion. Specifically, the weights for strain / temperature data, visual feature data, and equipment operating condition data are 40%, 30%, and 30%, respectively.

[0057] S202. Dynamically update the status attributes of the virtual fire protection components in the modified digital twin model based on the hazard level.

[0058] Among them, the hazard level is divided into those where a disaster has already occurred and those where a hazard exists even though no disaster has occurred.

[0059] By obtaining key evidence data sources for potential hazards in fire protection components, embodiments of the present invention can improve the interpretability of the identified hazard levels.

[0060] In actual working conditions, when a potential hazard occurs, rapid response is of paramount importance. Therefore, in some embodiments of the present invention, such as... Figure 3 As shown, taking fire as an example to illustrate the full life cycle management method of fire protection facilities, the following are also included: S301. When the hazard level is fire level and the confidence level is greater than the preset confidence level, the three-dimensional location of the fire point, the spread simulation area, the real-time status of the affected evacuation route, and the signal coverage strength data of the communication base station in the area are determined based on the dynamically updated digital twin model. S302. Starting from the current location of the rescue force and ending at the fire point, the rescue route is determined by using the accessibility of evacuation routes and the signal coverage strength as dynamic weights.

[0061] Specifically, the path determination algorithm used in the rescue route determination process can be Dijkstra's algorithm.

[0062] S303. Generate a dispatch plan based on the rescue path and the spread simulation area, including fire force deployment suggestions, evacuation guidance instructions, and a list of surrounding resources to be activated.

[0063] This invention can generate rescue routes based on the level of potential hazards, thereby improving rescue efficiency and allocating rescue resources. While improving the accuracy of resource allocation, it can also improve the reliability of rescue operations.

[0064] Furthermore, in cases where no disaster has occurred, to enhance the ability to respond to potential future hazards or disasters, in some embodiments of the present invention, such as... Figure 4 As shown, the full life-cycle management method for fire protection facilities also includes: S401. Determine the predicted remaining service life and hazard level of fire protection components based on the dynamically updated digital twin model; S402. Obtain the historical maintenance costs of fire protection components. With the goal of minimizing the total expected cost and risk level within the maintenance plan cycle, establish an optimization model and use a genetic algorithm to solve the optimization model to obtain a maintenance strategy report that includes preventive maintenance time, required personnel skill combinations, and spare parts list.

[0065] This invention combines the predicted remaining service life of fire protection facilities, maintenance costs, and fire risk levels, and optimizes maintenance time and personnel allocation through a genetic algorithm to achieve a risk-cost balance and improve the ability to respond to risks in the future.

[0066] It should be noted that the fire protection facility lifecycle management method provided in this embodiment of the invention is based on a four-layer architecture, which consists of, from top to bottom, the application layer, the digital twin core layer, the network layer, and the perception layer. The perception layer is used to collect data on the status of fire protection facilities and the environment, providing a data source for full-process management.

[0067] The network layer is used to achieve secure data transmission, support access for multiple types of devices and data encryption, and ensure the reliability and security of data transmission.

[0068] The core layer of the digital twin is the platform's core engine, responsible for twin model construction, data fusion processing, real-time mapping and synchronization, and providing technical support for the application layer.

[0069] The data at each stage can be stored based on a multimodal data engine. Specifically, structured data (design parameters, fault records) is stored using PostgreSQL+TimescaleDB, supporting full lifecycle related queries; unstructured data (videos, BIM models) uses a distributed file system, linked to a three-dimensional index of "sensor data-video frames-twin coordinates".

[0070] It should also be noted that for cross-regional data, a federated learning mechanism can be introduced to achieve cross-regional data privacy protection and sharing, and support collaborative prevention and control of buildings in multiple regions.

[0071] The application layer consists of user-facing functional modules that enable phased management, intelligent decision-making, and visual display, meeting the needs of different users.

[0072] In summary, the fire protection facility lifecycle management method proposed in this invention divides the entire lifecycle of fire protection facilities into the planning and design stage, the production and installation stage, the operation and maintenance monitoring stage, and the scrapping and recycling stage. Each stage achieves data connectivity and process integration through a digital twin model, forming a closed-loop management of data input-processing-feedback-optimization. This improves the intelligent management of fire protection facilities and can enhance the efficiency and success rate of rescue operations in the event of a disaster.

[0073] On the other hand, embodiments of the present invention also provide a fire protection facility lifecycle management system, such as... Figure 5 As shown, the fire protection facility lifecycle management system 500 includes: The planning phase twin model building unit 501 is used to construct an initial digital twin model with basic information of sensing nodes based on the design data of the building and fire protection facilities during the planning phase of fire protection facilities. The production and installation phase digital twin model establishment unit 502 is used to acquire attribute data of fire protection facilities during the production and installation phase of fire protection facilities, and to modify the initial digital twin model based on the attribute data to obtain a modified digital twin model. The twin model establishment unit 503 for the operation and maintenance monitoring phase is used to acquire the operation data of the fire protection facilities collected by the sensing nodes during the operation and maintenance monitoring phase of the fire protection facilities, and to dynamically update the modified digital twin model based on the operation data. The full life cycle analysis unit 504 is used to generate an analysis report based on the full life cycle data generated during the entire life cycle of fire protection facilities when the fire protection facilities reach the conditions for decommissioning. Based on the analysis report and the dynamically updated digital twin model, it generates design optimization suggestions to guide the planning and design of subsequent fire protection facilities.

[0074] The fire protection facility life cycle management system 500 provided in the above embodiments can realize the technical solutions described in the above embodiments of the fire protection facility life cycle management method. The specific implementation principles of each module or unit can be found in the corresponding content in the above embodiments of the fire protection facility life cycle management method, which will not be repeated here.

[0075] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware (such as a processor, controller, etc.), and the computer program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0076] The above provides a detailed description of a method and system for full life-cycle management of fire protection facilities provided by the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for managing the entire life cycle of fire protection facilities, characterized in that, include: During the planning phase of fire protection facilities, an initial digital twin model with basic information of sensing nodes is constructed based on the design data of the building and fire protection facilities. During the production and installation phase of fire protection facilities, attribute data of the fire protection facilities is acquired, and the initial digital twin model is corrected based on the attribute data to obtain a corrected digital twin model. During the operation and maintenance monitoring phase of fire protection facilities, the operation data of the fire protection facilities collected by the sensing nodes are acquired, and the modified digital twin model is dynamically updated based on the operation data. When fire protection facilities reach the conditions for being scrapped, an analysis report is generated based on the full life cycle data generated by the fire protection facilities throughout their entire life cycle. Based on the analysis report, design optimization suggestions are generated to guide the planning and design of subsequent fire protection facilities.

2. The method for full life-cycle management of fire protection facilities according to claim 1, characterized in that, The sensing node includes a fiber optic sensor and a video probe; the basic information of the sensing node includes the preset installation location and identification of the fiber optic sensor and the video probe in the building.

3. The method for full life-cycle management of fire protection facilities according to claim 1, characterized in that, The attribute data includes the manufacturing parameters of the fire protection facilities, the measured data of the installation location, and the factory inspection data.

4. The method for full life-cycle management of fire protection facilities according to claim 2, characterized in that, If the fire protection facility includes multiple fire protection components, then the method further includes: Establish the binding relationship between the sensing node and the fire protection component; The step of dynamically updating the corrected digital twin model based on the operational data includes: The ownership of the running data is determined based on the binding relationship, so as to dynamically update the modified digital twin model.

5. The method for full life-cycle management of fire protection facilities according to claim 4, characterized in that, The process of establishing the binding relationship between the sensing node and the fire protection component includes: When the sensing node is a fiber optic sensor, a pre-built RFID-fiber optic integrated tag is integrated into the fire protection component. The RFID part of the RFID-fiber optic integrated tag stores the component's unique identifier, and the fiber optic sensing part is used to collect operational data. The binding relationship is established through the unique identifier. When the sensing node is a video probe, an association is established between the video probe's number and the fire protection component, and a binding relationship is established between the video probe and the fire protection component based on the association.

6. The method for full life-cycle management of fire protection facilities according to claim 2, characterized in that, The sensing node transmits the operational data through a heterogeneous communication network; the heterogeneous communication network configures differentiated transmission protocols for the sensing data of the fiber optic sensor and the video data of the video probe. The heterogeneous communication network includes 5G / LoRa, a fiber optic ring network, and a base station. The base station is used to transmit data when the communication of the 5G / LoRa and fiber optic ring network is interrupted. The video data uses a compressed transmission protocol, and the sensor data uses a low-latency transmission protocol.

7. The method for full life-cycle management of fire protection facilities according to claim 1, characterized in that, The dynamic updating of the modified digital twin model based on the operational data includes: The operational data is input into the hazard diagnosis deep learning model to obtain the hazard level, confidence level, and key evidence data source of the fire protection components; The status attributes of the virtual fire protection component in the modified digital twin model are dynamically updated based on the hazard level.

8. The method for full life-cycle management of fire protection facilities according to claim 7, characterized in that, The method further includes: When the hazard level is a fire level and the confidence level is greater than the preset confidence level, the three-dimensional location of the fire point, the spread simulation area, the real-time status of the affected evacuation route, and the signal coverage strength data of the communication base station in the area are determined based on the dynamically updated digital twin model. Starting from the current location of the rescue forces and ending at the fire point, the rescue route is determined by using the accessibility of evacuation routes and the signal coverage strength as dynamic weights. Based on the rescue path and the spread simulation area, a dispatch plan is generated, including fire force deployment suggestions, evacuation guidance instructions, and a list of surrounding resources to be activated.

9. The method for full life-cycle management of fire protection facilities according to claim 7, characterized in that, The method further includes: The predicted remaining service life and hazard level of fire protection components are determined based on the dynamically updated digital twin model; The historical maintenance costs of the fire protection components are obtained. An optimization model is established with the goal of minimizing the total expected cost and the risk level within the maintenance plan cycle. The optimization model is then solved using a genetic algorithm to obtain a maintenance strategy report that includes preventive maintenance time, required personnel skill combinations, and a spare parts list.

10. A life-cycle management system for fire protection facilities, characterized in that, include: The planning phase twin model building unit is used to construct an initial digital twin model with basic information of sensing nodes based on the design data of the building and fire protection facilities during the planning phase of fire protection facilities. The production and installation phase digital twin model establishment unit is used to acquire attribute data of fire protection facilities during the production and installation phase of fire protection facilities, and to modify the initial digital twin model based on the attribute data to obtain a modified digital twin model. The twin model establishment unit for the operation and maintenance monitoring phase is used to acquire the operation data of the fire protection facilities collected by the sensing nodes during the operation and maintenance monitoring phase of the fire protection facilities, and to dynamically update the modified digital twin model based on the operation data. The full life cycle analysis unit is used to generate an analysis report based on the full life cycle data generated by the fire protection facilities during their entire life cycle when the fire protection facilities reach the conditions for decommissioning. Based on the analysis report and the dynamically updated digital twin model, it generates design optimization suggestions to guide the planning and design of subsequent fire protection facilities.

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