Electrical fire intelligent monitoring early warning top speed alarm automatic fire extinguishing system and method

Abstract

The invention relates to the technical field of intelligent fire fighting, in particular to an electrical fire intelligent monitoring and early warning top-speed alarm automatic fire extinguishing system and method, and the system comprises a ubiquitous sensing terminal, an intelligent decision-making platform, a linkage execution device, an energy guarantee module and a communication interaction unit; wherein the ubiquitous sensing terminal is used for collecting electrical equipment operation data and environmental parameters in real time and generating structured data; the intelligent decision-making platform is used for processing the structured data, evaluating an electrical fire risk level and generating an early warning and fire extinguishing strategy; the linkage execution device is used for realizing top-speed alarm and intelligent fire extinguishing according to early warning and fire extinguishing strategies; the energy guarantee module is used for providing three-level redundant power supply for the system and ensuring reliable operation of the system; and the communication interaction unit is used for multi-protocol data transmission and remote control. Therefore, the problems of high false alarm rate, large response delay, single fire extinguishing mode and the like of a single sensor in the prior art are solved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent fire protection technology, and in particular to an electrical fire intelligent monitoring and early warning extremely rapid alarm automatic fire extinguishing system and method. Background Art

[0002] With the acceleration of industrial automation and urbanization, the complexity and density of electrical equipment are increasing. Traditional fire prevention and control models can no longer meet the needs of modern fire safety. Therefore, there is an urgent need for an intelligent, integrated electrical fire monitoring, early warning, and fire extinguishing system to improve the efficiency and reliability of electrical fire prevention and control.

[0003] However, traditional electrical fire prevention and control face numerous pressing challenges. Existing monitoring methods primarily rely on single-point temperature sensors or smoke detectors, which capture only a single dimension of environmental parameters. This makes it difficult to comprehensively assess the complex operating conditions of electrical equipment and can easily miss early-stage fire hazards caused by aging wiring, poor contact, and other factors. Regarding data collection, manual inspections are inefficient and highly subjective, making real-time dynamic monitoring of electrical systems impossible, leading to delayed detection of potential hazards. Summary of the Invention

[0004] The present application provides an intelligent electrical fire monitoring and early warning system and method for rapid alarm and automatic fire extinguishing, in order to solve the problems of high false alarm rate of a single sensor, large response delay and single fire extinguishing method in the prior art.

[0005] The first aspect of the present application provides an intelligent monitoring, early warning, rapid alarm and automatic fire extinguishing system for electrical fires, including: a ubiquitous sensing terminal, an intelligent decision-making platform, a linkage execution device, an energy security module and a communication interaction unit; wherein, the ubiquitous sensing terminal is used to collect electrical equipment operating data and environmental parameters in real time, and generate structured data; the intelligent decision-making platform is used to process structured data, evaluate the risk level of electrical fires and generate early warning and fire extinguishing strategies; the linkage execution device is used to achieve rapid alarm and intelligent fire extinguishing according to the early warning and fire extinguishing strategies; the energy security module is used to provide the system with three-level redundant power supply to ensure reliable operation of the system; the communication interaction unit is used for multi-protocol data transmission and remote control.

[0006] Preferably, the ubiquitous sensing terminal includes a multimodal sensor group and an edge computing unit, wherein the multimodal sensor group includes a high-precision temperature sensor, a Hall current sensor, a nanoscale smoke sensor and an infrared flame detector, which are used to synchronously collect temperature, current, smoke and flame signals; the edge computing unit is used to preprocess the sensor data, extract key features and upload them to the intelligent decision-making platform.

[0007] Preferably, the intelligent decision-making platform includes a data processing module, a risk assessment module and a strategy generation module, wherein the data processing module is used to fuse structured data and construct an electrical equipment operating status model; the risk assessment module dynamically assesses electrical fire risks based on a deep learning algorithm; and the strategy generation module generates early warning and fire extinguishing strategies based on the risk assessment results.

[0008] Preferably, the linkage execution device includes an extremely fast alarm unit and an intelligent fire extinguishing unit, wherein the extremely fast alarm unit is used for local sound and light alarm and remote SMS / APP alarm; the intelligent fire extinguishing unit is used to extinguish the fire using a fine water mist spray system or a HFC-227ea gas fire extinguishing device according to the fire scene.

[0009] Preferably, the energy security module includes: a distributed energy supply network and a power fault-tolerant control algorithm. The distributed energy supply network adopts a lithium iron phosphate-supercapacitor composite power supply and electromagnetic induction wireless charging technology to perform fast charging and pulse discharge, improve charging efficiency, and provide energy for low-power devices. The power fault-tolerant control algorithm is based on MPC, which can seamlessly switch power supplies in 0ms and reduce voltage sags, ensuring the system's 72-hour power-off endurance and improving system stability and reliability.

[0010] Preferably, the communication interaction unit includes a protocol processing unit and a synchronization control unit, wherein the protocol processing unit is used to process TSN and OPC UA industrial protocols to ensure that data transmission in the network is deterministic and real-time, and can perform time synchronization and traffic scheduling, and simultaneously perform information models, service calls and data exchanges between devices; the synchronization control unit is used to achieve full-link time synchronization, so that sensor nodes, edge computing nodes and cloud platforms can achieve μs-level, ms-level and second-level interactive responses respectively, and with the help of IEEE1588v2 precise clock synchronization protocol, ensure that the clock error between nodes is within ±1μs, and maintain the time consistency of data transmission and processing.

[0011] The second aspect of the present application provides an intelligent monitoring and early warning method for electrical fires with extremely rapid alarm and automatic fire extinguishing, including: obtaining electrical parameters and environmental data; preprocessing the electrical parameters and the environmental data through edge computing nodes to generate structured feature vectors; using a pulse neural network inference unit to extract spatiotemporal features of the feature vectors, combining a Bayesian inference network with a dynamic threshold algorithm to evaluate fire risks, generate early warning levels and fire extinguishing strategies; upon receiving the fire extinguishing strategy, synchronously starting local and remote alarms, and automatically starting fine water mist spraying or gas fire extinguishing devices according to the fire scenario to control the full-process response time; based on the full-process response time, continuously learning historical fire data through a cloud platform, and dynamically updating neural network parameters; real-time monitoring of power supply status, automatic switching of redundant power supplies and optimization of energy distribution to ensure stable operation of the system in extreme environments.

[0012] The third aspect of the present application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and runnable on the processor. The processor executes the program to implement an intelligent monitoring and early warning method for electrical fires with extremely rapid alarm and automatic fire extinguishing as described in the above embodiment.

[0013] The fourth aspect of the present application provides a computer-readable storage medium on which a computer program is stored. The program is executed by a processor to implement an intelligent monitoring and early warning method for electrical fires with rapid alarm and automatic fire extinguishing as described in the above embodiment.

[0014] The fifth embodiment of the present application provides a computer program product, including a computer program or instructions, for implementing an intelligent monitoring and early warning method for electrical fires with rapid alarm and automatic fire extinguishing as described in the above embodiment.

[0015] Therefore, this application has the following beneficial effects:

[0016] The embodiments of the present application use ubiquitous sensing terminals to collect data in real time and generate structured information to provide support for accurate monitoring; the intelligent decision-making platform uses technical processing to achieve accurate assessment of fire risks and strategy generation; the linkage execution device can quickly alarm and intelligently extinguish fires according to the scene, greatly shortening the response time; the energy security module provides redundant power supply to ensure stable operation of the system; the communication interaction unit supports multi-protocol transmission to ensure data synchronization. The overall construction of a full-link intelligent prevention and control system solves the problems of insufficient monitoring, slow response, and low reliability of traditional systems, significantly improves the electrical fire warning capability, fire extinguishing efficiency and system stability, and is applicable to a variety of high-risk scenarios. In this way, the problems of high false alarm rate of single sensors, large response delays and single fire extinguishing methods in the existing technology are solved.

[0017] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0019] Figure 1 This is a structural diagram of an intelligent electrical fire monitoring and early warning system with rapid alarm and automatic fire extinguishing according to an embodiment of the present application;

[0020] Figure 2 A schematic diagram of a ubiquitous sensing terminal provided according to an embodiment of the present application;

[0021] Figure 3 A schematic diagram of a cable tunnel edge computing node provided according to one embodiment of the present application;

[0022] Figure 4 A schematic diagram of an intelligent decision-making platform provided according to one embodiment of the present application;

[0023] Figure 5 A schematic diagram of a linkage execution device provided according to one embodiment of the present application;

[0024] Figure 6 A schematic diagram of an energy security module provided according to one embodiment of the present application;

[0025] Figure 7 A schematic diagram of a data center electrical fire monitoring scenario provided according to one embodiment of the present application;

[0026] Figure 8 A schematic diagram of a communication interaction unit provided according to one embodiment of the present application;

[0027] Figure 9 This is a flow chart of an intelligent monitoring, early warning, rapid alarm, and automatic fire extinguishing system for electrical fires in automobile manufacturing plants provided according to one embodiment of the present application;

[0028] Figure 10 This is a flow chart of a method for intelligent monitoring, early warning, rapid alarm and automatic fire extinguishing of electrical fires provided according to an embodiment of the present application;

[0029] Figure 11 A schematic diagram of an electrical fire monitoring system for a smart industrial park according to one embodiment of the present application;

[0030] Figure 12 This is a flow chart of a method for intelligent monitoring, early warning, rapid alarm and automatic fire extinguishing of electrical fires provided according to one embodiment of the present application;

[0031] Figure 13 A schematic diagram of the structure of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0033] The following describes an electrical fire intelligent monitoring and early warning system with extremely fast alarm and automatic fire extinguishing according to an embodiment of the present application with reference to the accompanying drawings. In response to the problem of large response delay mentioned in the above background technology, the present application provides an electrical fire intelligent monitoring and early warning system with extremely fast alarm and automatic fire extinguishing. In this system, data is collected and structured information is generated in real time through ubiquitous sensing terminals to provide support for accurate monitoring; the intelligent decision-making platform uses technical processing to achieve accurate assessment of fire risks and strategy generation; the linkage execution device can alarm extremely quickly and intelligently extinguish fires according to the scene, greatly shortening the response time; the energy security module provides redundant power supply to ensure stable operation of the system; the communication interaction unit supports multi-protocol transmission to ensure data synchronization. The overall construction of a full-link intelligent prevention and control system solves the problems of insufficient monitoring, slow response, and low reliability of traditional systems, significantly improves the electrical fire early warning capability, fire extinguishing efficiency and system stability, and is suitable for a variety of high-risk scenarios. As a result, the problems of high false alarm rate of single sensors, large response delays and single fire extinguishing methods in the prior art are solved.

[0034] Figure 1 A schematic diagram of the composition of an intelligent electrical fire monitoring, early warning, rapid alarm and automatic fire extinguishing system provided in an embodiment of the present application.

[0035] The present application provides an intelligent electrical fire monitoring and early warning system with rapid alarm and automatic fire extinguishing. The system 10 includes:

[0036] Ubiquitous sensing terminal 100, intelligent decision-making platform 200, linkage execution device 300, energy security module 400, communication interaction unit 500.

[0037] Among them, the ubiquitous sensing terminal is used to collect electrical equipment operating data and environmental parameters in real time and generate structured data; the intelligent decision-making platform is used to process structured data, evaluate the risk level of electrical fires and generate early warning and fire extinguishing strategies; the linkage execution device is used to achieve extremely fast alarms and intelligent fire extinguishing according to the early warning and fire extinguishing strategies; the energy security module is used to provide the system with three-level redundant power supply to ensure reliable operation of the system; the communication interaction unit is used for multi-protocol data transmission and remote control.

[0038] It can be understood that in the embodiments of the present application, ubiquitous sensing terminals are used to collect data in real time and generate structured information to provide support for precise monitoring; the intelligent decision-making platform processes data, assesses risks and generates strategies to achieve intelligent conversion of data to instructions; the linkage execution device quickly alarms and extinguishes fires according to the scenario, shortening the response time; the energy security module ensures stable operation of the system through redundant power supply; the communication interaction unit supports multi-protocol transmission to ensure data collaboration between modules, solving problems such as material performance limitations, operation accuracy risks and material stress shielding in the existing technology.

[0039] In the embodiment of the present application, the ubiquitous perception terminal 100 further includes: Figure 2 As shown, multimodal sensor group, edge computing unit.

[0040] Among them, the multimodal sensor group includes high-precision temperature sensors, Hall current sensors, nanoscale smoke sensors and infrared flame detectors, which are used to synchronously collect temperature, current, smoke and flame signals; the edge computing unit is used to pre-process sensor data, extract key features and upload them to the intelligent decision-making platform.

[0041] It can be understood that the multimodal sensor group in the embodiment of the present application synchronously collects multi-dimensional signals through high-precision temperature, current, smoke and flame detectors, breaking through the limitations of single monitoring and comprehensively capturing equipment operation and environmental anomalies; the edge computing unit pre-processes sensor data, extracts key features and uploads them to the platform, filters noise, compresses data volume, and improves transmission efficiency and availability.

[0042] For example, Figure 3 As shown in the figure, edge computing nodes deployed in cable tunnels can collect real-time wire temperature rise data (accuracy of ±0.1°C) from temperature sensors and harmonic distortion (THD) from Hall effect current sensors. Using built-in algorithms to remove electromagnetic interference noise, they extract over 20 key features, such as the temperature rise rate (ΔT / Δt) and current kurtosis value. After compression, these features are uploaded to the cloud via the LoRaWAN protocol. If a cable section's temperature rise rate reaches 5°C / min and its current harmonics are abnormal, the edge computing unit can preliminarily identify a potential poor contact hazard, immediately triggering a local warning and encrypting the transmitted feature data. This reduces cloud data processing pressure and enables millisecond-level anomaly feature identification, providing real-time, accurate preprocessing information for subsequent intelligent decision-making, significantly improving system response speed and hazard identification efficiency.

[0043] In the embodiment of the present application, the intelligent decision-making platform 200 includes: Figure 4 As shown, there are data processing module, risk assessment module and strategy generation module.

[0044] Among them, the data processing module is used to integrate and process structured data and build an electrical equipment operating status model; the risk assessment module dynamically assesses electrical fire risks based on deep learning algorithms; and the strategy generation module generates early warning and fire extinguishing strategies based on the risk assessment results.

[0045] It can be understood that the embodiment of the present application integrates multi-dimensional structured data such as temperature and current through the data processing module to construct an electrical equipment operating status model, providing comprehensive and orderly basic data for risk assessment; the risk assessment module dynamically analyzes data based on deep learning algorithms, accurately identifies early hidden dangers such as overload and insulation aging, and predicts risk trends, significantly improving the assessment accuracy compared to traditional methods; the strategy generation module generates matching early warnings (sound and light alarms, SMS notifications) and fire extinguishing strategies (fine water mist spraying, gas fire extinguishing activation) in real time based on the assessment results, realizing the intelligent conversion from data to instructions.

[0046] In the embodiment of the present application, the linkage execution device 300 includes: Figure 5 As shown, rapid alarm unit and intelligent fire extinguishing unit.

[0047] Among them, the rapid alarm unit is used for local sound and light alarm and remote SMS / APP alarm; the intelligent fire extinguishing unit is used to extinguish fires using a fine water mist spray system or a HFC-227ea gas fire extinguishing device according to the fire scene.

[0048] It can be understood that the rapid alarm unit in the embodiment of the present application is triggered simultaneously by local sound and light and remote SMS / APP alarms, achieving dual coverage of on-site warnings and remote notifications, ensuring that fire hazards are detected in a timely manner and avoiding response delays of a single alarm method; the intelligent fire extinguishing unit automatically selects fine water mist spraying (fast cooling and no residue) or HFC-227ea gas fire extinguishing (quickly suppressing fire) according to open or closed scenes, accurately extinguishing the fire while reducing equipment damage.

[0049] In the embodiment of the present application, the energy security module 400 includes: Figure 6 As shown, it includes distributed energy supply network and power supply fault-tolerant control algorithm.

[0050] Among them, the distributed energy supply network adopts lithium iron phosphate-supercapacitor composite power supply and electromagnetic induction wireless charging technology for fast charging and pulse discharge, improving charging efficiency and providing energy for low-power devices; the power supply fault-tolerant control algorithm is based on MPC, which can seamlessly switch power supply in 0ms and reduce voltage sag, ensuring the system's 72-hour power-off endurance and improving system stability and reliability.

[0051] It can be understood that the embodiment of the present application adopts a lithium iron phosphate-supercapacitor composite power supply and electromagnetic induction wireless charging technology through a distributed energy supply network to achieve fast charging, pulse discharge and improve charging efficiency, flexibly provide energy for low-power devices, and meet the needs of fast energy replenishment and instantaneous high-power output; the power supply fault-tolerant control algorithm is based on MPC to achieve 0ms seamless power switching and reduce voltage sag, and combined with the composite power supply to ensure the system's 72-hour power outage endurance.

[0052] For example, Figure 7 As shown in the following example, in a data center electrical fire monitoring scenario, when the utility power is suddenly interrupted, the power supply fault-tolerant control algorithm, based on MPC, monitors bus voltage fluctuations in real time (with a threshold set to ±10% of rated voltage). Within 0ms, the lithium iron phosphate-supercapacitor composite power supply is seamlessly switched on, keeping voltage sags within 3%, ensuring continuous operation of the ubiquitous sensing terminal and the linked actuators. The algorithm also adjusts the energy allocation strategy, prioritizing power to the alarm unit (8W power consumption) and the fire extinguishing driver module (50W instantaneous power consumption), while reducing the energy consumption of non-critical modules (such as the remote control interface) by 30%, ensuring stable system operation for 72 hours after the power outage.

[0053] In the embodiment of the present application, the communication interaction unit 500 includes: Figure 8 As shown, protocol processing unit, synchronization control unit.

[0054] Among them, the protocol processing unit is used to process TSN and OPC UA industrial protocols to ensure that data transmission in the network is deterministic and real-time, and can perform time synchronization and traffic scheduling, while performing information models, service calls and data exchange between devices; the synchronization control unit is used to achieve full-link time synchronization, so that sensor nodes, edge computing nodes and cloud platforms can achieve μs-level, ms-level and second-level interactive responses respectively. With the help of IEEE1588v2 precise clock synchronization protocol, the clock error between nodes is guaranteed to be within ±1μs, maintaining the time consistency of data transmission and processing.

[0055] It can be understood that the embodiment of the present application uses the TSN and OPC UA protocols through the protocol processing unit to achieve deterministic real-time transmission and traffic scheduling of data, support information interaction and data exchange between devices, and solve the problems of high latency and poor interoperability in traditional industrial networks; the synchronization control unit uses the IEEE1588v2 protocol to achieve full-link time synchronization, ensuring that the clock error of sensors, edge computing and cloud platforms is controlled within ±1μs, and ensuring the time consistency of multi-source data collection, transmission and processing.

[0056] The embodiment of the present application proposes an intelligent monitoring and early warning system for electrical fires with extremely fast alarms and automatic fire extinguishing. The system collects data in real time and generates structured information through ubiquitous sensing terminals to provide support for accurate monitoring. The intelligent decision-making platform uses technical processing to achieve accurate assessment of fire risks and strategy generation. The linkage execution device can alarm extremely quickly and intelligently extinguish fires according to the scenario, greatly shortening the response time. The energy security module provides redundant power supply to ensure stable operation of the system. The communication interaction unit supports multi-protocol transmission to ensure data synchronization. The overall construction of a full-link intelligent prevention and control system solves the problems of insufficient monitoring, slow response, and low reliability of traditional systems, significantly improves the early warning capability of electrical fires, fire extinguishing efficiency, and system stability, and is applicable to a variety of high-risk scenarios. In this way, the problems of high false alarm rate of single sensors, large response delays, and single fire extinguishing methods in the existing technology are solved.

[0057] The following will describe an electrical fire intelligent monitoring and early warning rapid alarm automatic fire extinguishing system through a specific embodiment. Figure 9 As shown, including:

[0058] High-precision multimodal sensors such as temperature, current, smoke, and flame are deployed in the power distribution cabinet cluster of the final assembly workshop of the automobile manufacturing plant to collect equipment operation data and environmental parameters in real time; edge computing nodes are arranged at intervals in the cable tunnel, and the STM32H7 processor equipped with the Kalman filter algorithm is used to denoise, extract features (such as temperature rise rate and current kurtosis value), and compress the sensor data. Finally, the data is quickly uploaded to the intelligent decision-making platform through the TSN network to ensure accurate and efficient data transmission.

[0059] The data processing module of the intelligent decision-making platform integrates the multi-dimensional operating data of the distribution cabinet, builds a baseline for the normal operating status of the equipment based on the Gaussian mixture model, and distinguishes abnormal data; the risk assessment module uses the LSTM neural network to train the model based on historical fault data, and outputs three-dimensional risk values ​​of hidden danger type, development stage and impact range in real time; the strategy generation module automatically matches the graded response strategy according to the risk level, realizing the intelligent generation of data monitoring, early warning and fire extinguishing instructions.

[0060] After receiving the strategy of the intelligent decision-making platform, the linkage execution device activates the local sound and light alarm within 0.5 seconds through the rapid alarm unit, and sends alarm information containing detailed data to the remote side; the intelligent fire extinguishing unit activates the fine water mist spray or HFC-227ea gas fire extinguishing device according to the open or closed scene characteristics of the distribution cabinet, compressing the entire process time from risk identification to fire extinguishing to 22 seconds, greatly improving the efficiency of fire handling.

[0061] In terms of energy security, a lithium iron phosphate-supercapacitor composite power supply is used in combination with electromagnetic induction wireless charging. When the mains power is normal, it continuously replenishes energy. In the event of an interruption, it switches to the backup power supply in 0ms based on the MPC algorithm, giving priority to power supply to key modules and ensuring the system's 72-hour power outage endurance. In terms of communication, full-link time synchronization is achieved through TSN switches and IEEE1588v2 protocols, and the timestamp error of each node is controlled to an extremely small range, ensuring the time consistency of data transmission and processing, and improving the communication reliability of the system in complex environments.

[0062] Next, a method for intelligent monitoring, early warning, rapid alarm and automatic fire extinguishing of electrical fires proposed in accordance with an embodiment of the present application will be described with reference to the accompanying drawings.

[0063] like Figure 10 As shown, the electrical fire intelligent monitoring and early warning rapid alarm automatic fire extinguishing method includes the following steps:

[0064] In step S101 , electrical parameters and environmental data are acquired.

[0065] It can be understood that the embodiments of the present application provide data for intelligent analysis of hidden dangers and accurate assessment of fire risks through comprehensive real-time monitoring of equipment operation and environmental changes, thereby avoiding missed judgments and improving the accuracy of early warning of electrical fires.

[0066] In step S102, the electrical parameters and environmental data are pre-processed by the edge computing node to generate a structured feature vector.

[0067] Among them, edge computing nodes are small computing devices or devices that are close to the data collection source or user end and have the ability to process, store and transmit data.

[0068] As you can understand, the embodiments of this application utilize edge computing nodes deployed near distribution cabinets and cable tunnels to receive multimodal sensor data in real time. Using built-in algorithms to filter out noise, extract key features, and compress them, the data is quickly uploaded to the intelligent decision-making platform. This shifts data processing forward, reducing transmission volume and cloud pressure, and avoiding data lag.

[0069] For example, in the fire prevention and control of distribution cabinets in the final assembly workshop of an automobile manufacturing plant, edge computing nodes deployed every 10 meters in the cable tunnel are equipped with STM32H7 processors. When the high-precision temperature sensor on the inner wall of the distribution cabinet detects changes in contact temperature and the Hall current sensor captures abnormal current waveforms, the edge computing node receives 20 sets of sensor data in real time, uses the Kalman filter algorithm to filter out electromagnetic interference noise, and quickly extracts 15 key characteristic parameters such as temperature rise rate and current kurtosis value. The data is compressed and uploaded to the intelligent decision-making platform through the TSN network with a delay of ≤2ms, helping the platform to quickly determine whether there are hidden dangers such as poor contact and overload, and realize early identification and early warning of electrical fire hazards.

[0070] In step S103, the pulse neural network inference unit is used to extract spatiotemporal features of the feature vector, and the Bayesian inference network and dynamic threshold algorithm are combined to evaluate the fire risk and generate the warning level and fire extinguishing strategy.

[0071] Among them, the pulse neural network inference unit is a new computing unit that simulates the pulse signal transmission mechanism of biological neurons, extracts and calculates data features by processing discrete pulse sequences, and realizes fast and real-time inference tasks with extremely low energy consumption.

[0072] It is understood that the embodiments of this application capture the dynamics of electrical and environmental data by processing pulse signals. Combining a Bayesian network with a dynamic threshold algorithm, it can assess fire risk in real time with low energy consumption, lowering power consumption compared to traditional units. This improves assessment timeliness and accuracy, allowing for precise generation of early warning and firefighting strategies, and enabling intelligent monitoring systems to rapidly respond and make informed decisions.

[0073] For example, Figure 11 As shown in the figure, in the electrical fire monitoring system of the smart industrial park, the pulse neural network inference unit simulates the pulse transmission mechanism of biological neurons and receives the feature vectors formed by parameters such as current, voltage, and temperature collected by edge sensors in real time. By processing discrete pulse sequences, the unit quickly captures the dynamic changing trends of electrical parameters and environmental data. For example, when the temperature of the cable insulation layer rises abnormally and is accompanied by current fluctuations, it combines the Bayesian inference network to analyze the historical risk probability model and uses the dynamic threshold algorithm to dynamically adjust the risk assessment threshold. Compared with traditional computing units, it achieves millisecond-level response with 1 / 5 of the energy consumption. It not only accurately identifies the early overheating risk caused by poor contact in a distribution box (reducing the false alarm rate by 40%), but also simultaneously generates graded warning signals and targeted power-off and fire-fighting strategies, helping the monitoring system to quickly block fire hazards under complex working conditions with multiple devices linked together, demonstrating the industrial-grade application advantages of low power consumption, high timeliness, and strong robustness.

[0074] In step S104, after receiving the fire extinguishing strategy, local and remote alarms are activated synchronously, and fine water mist spraying or gas fire extinguishing equipment is automatically started according to the fire scene to control the response time of the entire process.

[0075] Among them, the gas fire extinguishing device is an automated equipment that suppresses combustion reactions and extinguishes fires by releasing specific fire extinguishing gases.

[0076] It can be understood that the embodiments of the present application can quickly suppress combustion reactions and extinguish fires by automatically releasing specific fire extinguishing gases such as heptafluoropropane and carbon dioxide. Its advantages lie in efficient response (synchronous activation with the alarm system) and precise fire extinguishing (adapted to different fire scenarios). The released clean gas causes minimal damage to protected objects such as electrical equipment and precision instruments, and can avoid secondary damage that may be caused by traditional water-based fire extinguishing.

[0077] For example, in a large data center, when a pulse neural network inference unit determines a fire risk by monitoring electrical parameters, combining a Bayesian inference network with a dynamic threshold algorithm, and generates a fire extinguishing strategy, the system immediately initiates local and remote alarms and automatically activates a gas fire extinguishing device based on the fire scenario. The released HFC-227ea gas quickly fills the computer room, suppressing the combustion reaction and extinguishing the fire without damaging delicate equipment like servers and storage devices. This prevents secondary damage such as equipment short circuits caused by traditional water-based fire extinguishing. The entire process response time is kept within seconds, effectively ensuring the safe and stable operation of the data center.

[0078] In step S105, based on the full-process response time, historical fire data is continuously learned through the cloud platform and the neural network parameters are dynamically updated; the power supply status is monitored in real time, redundant power supplies are automatically switched and energy distribution is optimized to ensure stable operation of the system in extreme environments.

[0079] Among them, redundant power supply is a power supply system equipped with two or more power modules.

[0080] It can be understood that the embodiment of the present application is equipped with multiple power modules, which automatically and seamlessly switch to the backup power supply when the main power supply fails, ensuring the continuous operation of key equipment such as alarms and fire extinguishing devices, and avoiding power outages that cause system paralysis; at the same time, it can optimize energy distribution in real time, improve power efficiency in extreme environments, and extend equipment life.

[0081] According to the embodiment of the present application, a method for intelligent monitoring and early warning of electrical fires with extremely fast alarm and automatic fire extinguishing is proposed. The ubiquitous sensing terminal collects data in real time and generates structured information to provide support for accurate monitoring. The intelligent decision-making platform uses technical processing to achieve accurate assessment of fire risks and strategy generation. The linkage execution device can alarm extremely quickly and intelligently extinguish fires according to the scene, greatly shortening the response time. The energy security module provides redundant power supply to ensure stable operation of the system. The communication interaction unit supports multi-protocol transmission to ensure data synchronization. The overall construction of a full-link intelligent prevention and control system solves the problems of insufficient monitoring, slow response, and low reliability of traditional systems, significantly improves the early warning capability of electrical fires, fire extinguishing efficiency and system stability, and is applicable to a variety of high-risk scenarios. As a result, the problems of high false alarm rate of single sensors, large response delays and single fire extinguishing methods in the existing technology are solved.

[0082] The following will describe the electrical fire intelligent monitoring and early warning rapid alarm automatic fire extinguishing method through a specific embodiment. Figure 12 As shown, including:

[0083] In the underground distribution room of a large commercial complex, the edge computing node collects the current (±0.1A accuracy), voltage (±1V accuracy), cable surface temperature (±0.5℃ accuracy) and ambient smoke concentration (0.01dB / m resolution) of the distribution cabinet in real time, generates a vector containing 128-dimensional time series features and transmits it to the pulse neural network inference unit.

[0084] The inference unit processes discrete pulse sequences at a frequency of 200μs. Using a Life Influence (LIF) model simulating biological neurons, it captures parameter mutation characteristics (such as a 5°C temperature jump and a current fluctuation exceeding 15% within 30ms). Combined with a Bayesian network's historical fault probability library (containing over 100,000 fault samples) and a dynamic threshold algorithm (adaptively updating the threshold every 5 minutes), it outputs a three-level risk assessment within 1.2ms. If a feeder cabinet is identified as exhibiting an early overheating risk (risk value ≥ 85) caused by an abnormal increase in contact resistance, a "secondary warning + local power outage + gas fire extinguishing" strategy is immediately initiated.

[0085] After receiving the strategy, the system will synchronously trigger the distribution room sound and light alarm (85dB) and remote APP push (including positioning, risk level, and three-dimensional schematic diagram of the fault point) within 0.5 seconds. At the same time, it will automatically start the heptafluoropropane gas fire extinguishing device in the cabinet according to the fire scenario (electrical fires are prioritized). The nozzle will complete the gas release within 1.8 seconds, and the closed-loop control will be feedback through the pipe network pressure sensor to ensure that the agent concentration reaches the fire extinguishing critical value (9% volume ratio) within 30 seconds.

[0086] When the main power supply voltage drops suddenly (<80% of the rated value) due to a fire, the redundant power supply module (dual-channel 2N configuration) completes seamless switching within 100μs through solid-state relays, continuously supplying power to the monitoring host, alarm device and fire extinguishing system; at the same time, based on the fire data (including 1200 sets of pulse sequence samples), the cloud platform completes the neural network parameter iteration within 10 minutes, updates the recognition threshold of contact resistance anomalies (from 0.3mΩ to 0.25mΩ), and enhances the ability to capture subtle faults.

[0087] Figure 13 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0088] Memory 1301 , processor 1302 , and computer programs stored in the memory 1301 and executable on the processor 1302 .

[0089] When the processor 1302 executes the program, the electrical fire intelligent monitoring, early warning, rapid alarm and automatic fire extinguishing method provided in the above embodiment is implemented.

[0090] Furthermore, the electronic device further includes:

[0091] The communication interface 1303 is used for communication between the memory 1301 and the processor 1302 .

[0092] The memory 1301 is used to store computer programs that can be run on the processor 1302 .

[0093] The memory 1301 may include a high-speed RAM (Random Access Memory) memory, and may also include a non-volatile memory, such as at least one disk memory.

[0094] If the memory 1301, the processor 1302, and the communication interface 1303 are implemented independently, the communication interface 1303, the memory 1301, and the processor 1302 can be connected to each other via a bus and communicate with each other. The bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 13 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0095] Optionally, in a specific implementation, if the memory 1301, the processor 1302 and the communication interface 1303 are integrated on a chip, the memory 1301, the processor 1302 and the communication interface 1303 can communicate with each other through an internal interface.

[0096] The processor 1302 may be a CPU (Central Processing Unit), or an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present application.

[0097] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for intelligent monitoring, early warning, rapid alarm and automatic fire extinguishing of electrical fires.

[0098] In addition, an embodiment of the present application also provides a computer program product, including a computer program or instructions, which, when executed, implements the above-mentioned method for intelligent monitoring, early warning, rapid alarm and automatic fire extinguishing of electrical fires.

[0099] In the description of this specification, reference to the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any appropriate manner in any one or more embodiments or examples. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification, as well as features of different embodiments or examples, unless they are mutually inconsistent.

[0100] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features being referred to. Thus, a feature specified as "first" or "second" may explicitly or implicitly include at least one such feature. Throughout the description of this application, "plurality" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0101] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application belong.

[0102] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0103] Those skilled in the art will appreciate that all or part of the steps in the method for implementing the above-mentioned embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0104] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. An intelligent electrical fire monitoring and early warning system with rapid alarm and automatic fire extinguishing, characterized in that: include: Ubiquitous sensing terminal, intelligent decision-making platform, linkage execution device, energy security module and communication interaction unit; among them, The ubiquitous sensing terminal is used to collect electrical equipment operating data and environmental parameters in real time and generate structured data; The intelligent decision-making platform is used to process structured data, assess the risk level of electrical fires, and generate early warning and fire extinguishing strategies; The linkage execution device is used to realize extremely fast alarm and intelligent fire extinguishing according to the early warning and fire extinguishing strategies; The energy security module is used to provide three-level redundant power supply for the system to ensure reliable operation of the system; The communication interaction unit is used for multi-protocol data transmission and remote control.

2. The electrical fire intelligent monitoring, early warning, rapid alarm and automatic fire extinguishing system according to claim 1 is characterized in that: The ubiquitous sensing terminal includes a multimodal sensor group and an edge computing unit, wherein the multimodal sensor group includes a high-precision temperature sensor, a Hall current sensor, a nanoscale smoke sensor and an infrared flame detector, which are used to synchronously collect temperature, current, smoke and flame signals; the edge computing unit is used to preprocess the sensor data, extract key features and upload them to the intelligent decision-making platform.

3. The intelligent electrical fire monitoring, early warning, rapid alarm and automatic fire extinguishing system according to claim 1 is characterized in that: The intelligent decision-making platform includes a data processing module, a risk assessment module and a strategy generation module. The data processing module is used to integrate structured data and build an electrical equipment operating status model; the risk assessment module dynamically assesses electrical fire risks based on a deep learning algorithm; and the strategy generation module generates early warning and fire extinguishing strategies based on the risk assessment results.

4. The electrical fire intelligent monitoring, early warning, rapid alarm and automatic fire extinguishing system according to claim 1 is characterized in that: The linkage execution device includes an extremely fast alarm unit and an intelligent fire extinguishing unit, wherein the extremely fast alarm unit is used for local sound and light alarm and remote SMS / APP alarm; the intelligent fire extinguishing unit is used to extinguish the fire using a fine water mist spray system or a HFC-227ea gas fire extinguishing device according to the fire scene.

5. The intelligent electrical fire monitoring, early warning, rapid alarm and automatic fire extinguishing system according to claim 1 is characterized in that: The energy security module includes: a distributed energy supply network and a power fault-tolerant control algorithm. The distributed energy supply network adopts a lithium iron phosphate-supercapacitor composite power supply and electromagnetic induction wireless charging technology to perform fast charging and pulse discharge, improve charging efficiency, and provide energy for low-power devices; the power fault-tolerant control algorithm is based on MPC, which can seamlessly switch power supplies in 0ms and reduce voltage sags, ensuring the system's 72-hour power-off endurance and improving system stability and reliability.

6. The electrical fire intelligent monitoring, early warning, rapid alarm and automatic fire extinguishing system according to claim 1 is characterized in that: The communication interaction unit includes a protocol processing unit and a synchronization control unit, wherein the protocol processing unit is used to process TSN and OPC UA industrial protocols to ensure that data transmission in the network is deterministic and real-time, and can perform time synchronization and traffic scheduling, and at the same time perform information models, service calls and data exchange between devices; the synchronization control unit is used to achieve full-link time synchronization, so that sensor nodes, edge computing nodes and cloud platforms can achieve μs-level, ms-level and second-level interactive responses respectively, and with the help of IEEE1588v2 precise clock synchronization protocol, ensure that the clock error between nodes is within ±1μs, and maintain the time consistency of data transmission and processing.

7. An electrical fire intelligent monitoring, early warning, rapid alarm and automatic fire extinguishing method applied to any one of claims 1-6, characterized in that: The method comprises: Obtain electrical parameters and environmental data; Preprocessing is performed by an edge computing node according to the electrical parameters and the environmental data to generate a structured feature vector; Using a spiking neural network inference unit to extract spatiotemporal features from the feature vector, combining a Bayesian inference network with a dynamic threshold algorithm, the fire risk is assessed, and a warning level and fire extinguishing strategy are generated; When the fire extinguishing strategy is received, local and remote alarms are activated simultaneously, and water mist spraying or gas fire extinguishing devices are automatically activated according to the fire scenario to control the response time of the entire process; Based on the described full-process response time, historical fire data is continuously learned through the cloud platform and neural network parameters are dynamically updated; power supply status is monitored in real time, redundant power supplies are automatically switched and energy distribution is optimized to ensure stable operation of the system in extreme environments.

8. An electronic device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and runnable on the processor, wherein the processor executes the program to implement an intelligent monitoring and early warning method for electrical fires with extremely rapid alarm and automatic fire extinguishing as claimed in any one of claim 7.

9. A computer-readable storage medium having a computer program or instruction stored thereon, characterized in that: When the computer program or instruction is executed, it implements an electrical fire intelligent monitoring, early warning, rapid alarm and automatic fire extinguishing method as claimed in any one of claim 7.

10. A computer program product comprising a computer program or instructions, characterized in that When the computer program or instruction is executed, it implements an electrical fire intelligent monitoring, early warning, rapid alarm and automatic fire extinguishing method as claimed in any one of claim 7.

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