A fire power supply control system with power distribution function and its control method

Abstract

The present invention discloses a fire power supply control system with a power distribution function and its control method, belonging to the technical field of power distribution of fire power supplies. It includes a power supply and a controller. The controller includes: a data acquisition module for collecting power supply data and data at the fire scene; a fire power supply control module connected to the data acquisition module, with a built-in real-time data analysis algorithm for receiving the data transmitted by the data acquisition module and analyzing the conditions of each area in case of a fire emergency; a data processing unit electrically connected to the fire power supply control module for quickly processing the output results of the real-time data analysis algorithm to identify the key areas where the fire spreads and the demand priorities of fire-fighting equipment; a dynamic power distribution strategy module that dynamically adjusts the power distribution strategy according to the output results of the data processing unit, achieving the effect of flexibly distributing power and improving the reliability of the fire power supply.

Description

Technical Field

[0001] The present invention relates to the technical field of power allocation of fire fighting power supplies, and specifically, to a fire fighting power supply control system with power allocation function and its control method. Background Art

[0002] The fire fighting power supply control system is a management system acting on the fire fighting power supply, aiming to comprehensively monitor the charging and discharging status and stability of the fire fighting power supply, and to real-time monitor key parameters such as the voltage and current of the fire fighting power supply, so as to ensure that the fire fighting power supply operates stably within the normal range. In case of power failure or abnormality of the commercial power, the control system immediately activates the fire fighting power supply to connect to the fire fighting equipment, so that the fire fighting equipment can continue to work in an emergency. In addition, when it is detected that the fire fighting power supply has an abnormal situation or insufficient stability, the control system will issue an alarm in time to remind the maintenance personnel to handle it.

[0003] For example, the patent with the publication number of CN106056827A specifically discloses a fire fighting power supply control system, which realizes quickly cutting off the power supply when a fire signal is detected through components such as a temperature sensing unit, a smoke detection unit, a power circuit breaker, a control unit, a wireless communication unit, and a backup power supply, and supplies power to the lighting lamp, the sensor, and the communication unit through the backup power supply to ensure safety. However, when a fire occurs, this patent cannot dynamically allocate power according to the real-time situation at the fire scene, and cannot ensure that the emergency area and important fire fighting equipment are given priority in power supply, with insufficient flexibility, which may affect the effective operation of the fire fighting equipment at critical moments.

[0004] It should be noted that the above information disclosed in this background art section is only used to understand the background art of the concept of the present application, and therefore, it may include information that does not constitute the prior art. Summary of the Invention

[0005] Based on the above problems existing in the prior art, the problem to be solved by the present application is: to provide a fire fighting power supply control system with power allocation function and its control method, so as to achieve the effect of flexibly allocating power and improving the reliability of the fire fighting power supply.

[0006] To solve the above technical problems, the technical solution of the present invention is: a fire fighting power supply control system with power allocation function and its control method, including a power supply and a controller, and the controller includes:

[0007] A data acquisition module, the data acquisition module includes a smoke concentration sensor, a temperature sensor, and a flame detector, and is used for collecting data at the fire scene;

[0008] The fire power control module is connected to the data acquisition module. The fire power control module is provided with a real-time data analysis algorithm for receiving the data transmitted by the data acquisition module and analyzing the fire conditions in different areas;

[0009] The data processing unit is electrically connected to the fire power control module and is used for quickly processing the output result of the real-time data analysis algorithm to identify the key areas of fire spread and the priority of the requirements of fire-fighting equipment;

[0010] The dynamic power distribution strategy module is electrically connected to the data processing unit and is used for dynamically adjusting the power distribution strategy according to the output result of the data processing unit to ensure the power supply in the key areas;

[0011] The intelligent prediction module is electrically connected to the dynamic power distribution strategy module. Based on the system big data and the real-time data of the current fire scene, it calculates the power requirements of each area and adjusts the power distribution strategy in advance;

[0012] The emergency guarantee module is electrically connected to the intelligent prediction module and is used for preferentially guaranteeing the power supply in the key areas and important fire-fighting equipment.

[0013] Further, the real-time data analysis algorithm includes a fire occurrence recognition algorithm, a fire spread trend prediction algorithm, and a regional safety condition assessment algorithm.

[0014] Further, the dynamic power distribution strategy module dynamically adjusts the power supply ratio of each fire-fighting equipment according to the key areas of fire spread and the priority of the requirements of fire-fighting equipment.

[0015] Further, the intelligent prediction module uses machine learning algorithms to analyze the system big data and the real-time data of the current fire scene.

[0016] Further, after the emergency guarantee module is started, it restricts the power supply to non-critical areas and non-important fire-fighting equipment.

[0017] A fire power control method with a power allocation function, the method comprising:

[0018] Step S1: Collect the data of the fire scene in real time through the data acquisition module;

[0019] Step S2: Transmit the collected data to the fire power control module and use the real-time data analysis algorithm to analyze the safety conditions of each area in case of fire emergency;

[0020] Step S3: The output results of the real-time data analysis algorithm are quickly processed by the data processing unit to identify the key areas of fire spread and the priority of fire-fighting equipment requirements;

[0021] Step S4: According to the identification results, the power distribution strategy is dynamically adjusted to ensure the power supply in key areas;

[0022] Step S5: The intelligent prediction module is used to predict the power demand in each area in the next period of time and adjust the power distribution strategy in advance;

[0023] Step S6: When a fire or other emergency is detected, the emergency support module is automatically activated.

[0024] The beneficial effects of this application are as follows: By integrating the data acquisition module and the fire-fighting equipment power control module, the intelligent management of the power supply at the fire scene is realized. The data acquisition module collects data such as smoke concentration and temperature, and detects the distribution of personnel at the fire scene, providing information for power allocation. The fire-fighting equipment power control module is built-in with a real-time data analysis algorithm to quickly evaluate the regional safety status and personnel safety in the event of a fire emergency. The data processing unit further processes these data to identify the key areas of fire spread, the priority of fire-fighting equipment requirements, and the crowded areas of personnel. The dynamic power distribution strategy module adjusts the power distribution dynamically based on the above information to ensure the power supply in key areas, ensuring personnel safety and the effective operation of fire-fighting equipment. The intelligent prediction module predicts the future power demand based on the system's big data and real-time data and adjusts the strategy in advance. Through the collaborative work of the above modules, the reliability of the fire-fighting power supply in fire response is improved, and the flexible allocation of the fire-fighting power supply is realized. Brief Description of the Drawings

[0025] The present invention will be further described in detail below with reference to the drawings and specific embodiments.

[0026] Figure 1 It is a schematic diagram of the module composition of a fire-fighting power supply control system with a power allocation function in the present invention;

[0027] Figure 2 It is a schematic flowchart of a fire-fighting power supply control method with a power allocation function in the present invention.

[0028] In the figure: 1. Power supply; 2. Controller; 21. Data acquisition module; 22. Fire-fighting power supply control module; 23. Data processing unit; 24. Dynamic power distribution strategy module; 25. Intelligent prediction module; 26. Emergency support module. Detailed Embodiments

[0029] In order to make the content of the present invention easier to be clearly understood, the present invention will be further described in detail below according to specific embodiments and with reference to the drawings.

[0030] As Figure 1 shown, the present application provides a fire power control system with a power distribution function, including a power supply 1 and a controller 2. The controller 2 includes:

[0031] A data acquisition module 21, which includes a smoke concentration sensor, a temperature sensor, and a flame detector, and is used to collect data at the fire scene;

[0032] A fire power control module 22, connected to the data acquisition module 21, and the fire power control module 22 is provided with a real-time data analysis algorithm, which is used to receive the data transmitted by the data acquisition module 21 and analyze the fire conditions in different areas;

[0033] A data processing unit 23, electrically connected to the fire power control module 22, and is used to quickly process the output result of the real-time data analysis algorithm, identify the key areas where the fire spreads and the priority of the requirements of fire-fighting equipment;

[0034] A dynamic power distribution strategy module 24, electrically connected to the data processing unit 23, and is used to dynamically adjust the power distribution strategy according to the output result of the data processing unit 23 to ensure the power supply in the key areas;

[0035] An intelligent prediction module 25, electrically connected to the dynamic power distribution strategy module 24, calculates the power demand of each area based on the system big data and the real-time data of the current fire scene, and adjusts the power distribution strategy in advance;

[0036] An emergency guarantee module 26, electrically connected to the intelligent prediction module 25, and is used to preferentially guarantee the power supply in the key areas and important fire-fighting equipment.

[0037] As Figure 1-2 shown, the real-time data analysis algorithm includes a fire occurrence recognition algorithm, a fire spread trend prediction algorithm, and a regional safety condition assessment algorithm.

[0038] As Figure 1-2 shown, the dynamic power distribution strategy module 24 dynamically adjusts the power supply ratio of each fire-fighting equipment according to the key areas where the fire spreads and the priority of the requirements of fire-fighting equipment. The intelligent prediction module 25 uses machine learning algorithms to analyze the system big data and the real-time data of the current fire scene. After the emergency guarantee module 26 is started, it restricts the power supply in non-critical areas and non-important fire-fighting equipment.

[0039] Embodiment 2

[0040] The present invention also provides a method embodiment for implementing the above system. AsFigure 2 It is a schematic flowchart of a fire power supply control method with power distribution function in the present invention. The system includes:

[0041] Step S1: Collect data at the fire scene in real time through the data acquisition module 21;

[0042] Step S2: Transmit the collected data to the fire equipment power supply control module, and use real-time data analysis algorithm to analyze the safety status of each area in case of fire emergency;

[0043] Step S3: Quickly process the output result of the real-time data analysis algorithm through the data processing unit 23 to identify the key areas where the fire spreads and the priority of the demand for fire equipment;

[0044] Step S4: According to the identification result, dynamically adjust the power distribution strategy to ensure the power supply of key areas;

[0045] Step S5: Use the intelligent prediction module 25 to predict the power demand of each area in the next period of time and adjust the power distribution strategy in advance;

[0046] Step S6: Automatically start the emergency support module 26 when a fire or other emergency is detected.

[0047] The working principle of the present invention is as follows: The fire power supply control system includes a power supply part and a control part. The power supply part is the commercial power and the standby power supply. When the commercial power is interrupted, the fire power supply control system can automatically switch to the standby power supply to supply power to the fire equipment. When a fire occurs, the control system responds. First, the data acquisition module 21 collects power data and fire data. The fire data is collected jointly by the smoke concentration sensor, the temperature sensor and the flame detector;

[0048] The function of the smoke concentration sensor is to capture the change of the smoke concentration in the air. Once the smoke concentration exceeds the preset safety threshold, it will immediately issue an alarm. According to the fire safety standard regulations, the safety threshold of the smoke concentration is set to 0.5 optical density units. Specifically, once the smoke concentration exceeds 0.5 OD, that is, when it reaches or exceeds the critical level that may pose a threat to the human body or indicate that the fire is spreading rapidly, the smoke concentration sensor will immediately send an alarm signal to the control system;

[0049] In addition, the function of the temperature sensor is to monitor the temperature change inside the building, continuously monitor the ambient temperature. Once the detected temperature rises abnormally, exceeds the normal range and reaches the preset alarm threshold, the temperature sensor will quickly transmit a signal to the control system. The flame detector uses thermal sensitive technology to capture the flame. Once the flame detector detects the flame, it will also transmit the alarm information to the control system to ensure that the system can respond in the first time;

[0050] The smoke concentration sensor, temperature sensor, and flame detector together constitute the data acquisition module 21, providing comprehensive and real-time fire monitoring data for the fire power supply from three directions: smoke concentration, temperature anomaly, and flame, enabling the control system to respond and make decisions quickly in the initial stage of a fire;

[0051] It should be noted that the smoke concentration sensor, temperature sensor, and flame detector are installed in places such as corridors, stairwells, machine rooms, and warehouses in buildings, which are usually key passages and areas for personnel evacuation and fire-fighting equipment use during a fire;

[0052] Furthermore, after the data acquisition module 21 provides comprehensive and real-time fire monitoring data, the data information is immediately transmitted to the fire power supply control module 22. The fire power supply control module 22 is built-in with real-time data analysis algorithms, including fire occurrence recognition algorithms, fire spread trend prediction algorithms, and regional safety status assessment algorithms. By processing the data from the data acquisition module 21 through these algorithms, it identifies whether a fire has truly occurred, predicts the spread direction of the fire, and analyzes the safety status of each area in the building;

[0053] Specifically, the fire occurrence recognition algorithm is based on the characteristics of flames and smoke for recognition. When the smoke concentration sensor, temperature sensor, and flame detector detect that the smoke concentration exceeds the preset threshold, the temperature rises abnormally, and a flame is detected, this data is transmitted to the fire power supply control module 22. The fire occurrence recognition algorithm will process and analyze this data. By comparing with the preset flame and smoke characteristic models, it determines whether there is a possibility of a fire. If the algorithm determines that a fire has occurred, the system will immediately trigger an alarm;

[0054] The fire spread trend prediction algorithm will analyze based on the distribution of combustibles, the structure of the building, wind direction, and wind speed, etc. Using historical fire data and real-time fire data, it is trained and optimized through technologies such as deep learning. During a fire, according to the current scale and location of the fire, as well as the structure and environment of the building, it predicts the spread direction and speed of the fire, which helps to formulate fire extinguishing and evacuation plans in advance;

[0055] The regional safety status assessment algorithm conducts a safety assessment of each area based on factors such as the location of the fire, the spread trend of the fire, and the distribution of fire-fighting equipment. Through calculation and analysis, it analyzes safe areas and dangerous areas, including areas that need to be evacuated first;

[0056] Once a fire is confirmed, the data processing unit 23 immediately intervenes. The data processing unit 23 is set within the power control module. According to the output result of the real-time data analysis algorithm, the data processing unit 23 identifies the key areas where the fire spreads, including the area with the largest fire and the areas about to be threatened, so as to determine the priority of the demand for fire-fighting equipment and ensure the power supply according to the priority level.

[0057] In addition, based on the output result of the data processing unit 23, the dynamic power distribution strategy module 24 is activated. According to the key areas where the fire spreads and the priority of the demand for fire-fighting equipment, in the area with the largest fire, the power supply to the automatic sprinkler system will be increased to ensure that it can work continuously and effectively. In the relatively safe areas with less threat, the power supply to some non-critical fire-fighting equipment will be reduced, ensuring the power resources of the fire-fighting power supply and ensuring that the key equipment can obtain stable power supply for a long time, realizing the dynamic supply of the power of the fire-fighting power supply.

[0058] Meanwhile, the intelligent prediction module 25 analyzes the system big data and the real-time data of the current fire scene through machine learning algorithms to predict the power demand of each area in the next period of time. The intelligent prediction module 25 first integrates two types of data: one is the historical power consumption data, equipment energy consumption patterns and power demand change data in previous fire responses accumulated during the long-term operation of the system, and the other is the real-time fire scene data transmitted by the data acquisition module 21, including information such as smoke concentration, abnormal temperature, and flame status. These information reflect the dynamic situation and emergency degree of the fire scene. Subsequently, machine learning algorithms are used to deeply mine these data. The machine learning algorithms automatically identify and extract the characteristic variables related to power demand prediction, such as the trend of historical power consumption, the peak period of equipment energy consumption, the fire spread speed, and the relationship between power demand growth, and predict the power demand through the characteristic variables.

[0059] On the basis of feature extraction, the machine learning algorithm constructs a prediction model based on historical data and real-time data, learns the change law of the power demand of each area when a fire occurs, and predicts the power demand of each area in the next period of time according to the law. Through the ability to predict power, the intelligent prediction module 25 can learn in advance the change of power demand, enabling the power control system to adjust the power distribution strategy in advance according to the prediction result. In this way, in an emergency, the system can ensure stable power supply to key areas and important fire-fighting equipment, while avoiding power waste in non-critical areas, effectively balancing power supply and demand, and avoiding the situation of insufficient or excessive power supply in an emergency.

[0060] Finally, the emergency support module 26 is automatically activated when a fire or other emergency is detected. The emergency support module 26 immediately restricts the power supply to non-critical areas and non-essential fire-fighting equipment. Specifically, the emergency support module 26 gives priority to ensuring the power supply to critical areas and important fire-fighting equipment such as the fire control room, safety exits, evacuation routes, fire pumps, smoke exhaust fans, and fire elevators. At the same time, the emergency support module 26 also dynamically adjusts the power distribution strategy based on the real-time data at the fire scene and the prediction results of the intelligent prediction module 25. In the case of rapid fire spread and a sharp increase in power demand, the module further reduces the power supply to non-critical areas to ensure that critical areas and important fire-fighting equipment can continuously obtain stable and sufficient power support;

[0061] Through such emergency support measures, the reliability and stability of the fire power supply in an emergency can be improved, providing support for fire rescue work. Through intelligent prediction and dynamic adjustment of the power distribution strategy, the fire power supply control system can ensure that critical areas and important fire-fighting equipment can obtain power support during a fire;

[0062] Specifically, when a fire occurs, the data acquisition module 21 is activated, and fire data is comprehensively collected through smoke concentration sensors, temperature sensors, and flames. The collected data is transmitted to the fire power supply control module 22, and then the received data is processed and analyzed through real-time data analysis algorithms. When the fire is confirmed, the data processing unit 23 intervenes and determines the power supply strategy based on the critical areas of fire spread and the priority of fire-fighting equipment requirements;

[0063] Furthermore, the dynamic power distribution strategy module 24 dynamically adjusts the power supply to each area based on the output results of the data processing unit 23 to ensure stable power for critical fire-fighting equipment. At the same time, the intelligent prediction module 25 uses machine learning algorithms to integrate historical data and real-time data to predict the power demand in each area for a period of time in the future, enabling the power supply control system to pre-adjust the power distribution. Finally, the emergency support module 26 is activated to restrict the power supply to non-critical areas, prioritize the power demand of critical areas and important fire-fighting equipment, and dynamically adjust the strategy based on real-time data and prediction results to ensure that the system can provide efficient and stable power support in emergencies such as fires.

[0064] The specific embodiments described above further elaborate on the technical problems solved, technical solutions, and beneficial effects of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not used to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A fire power supply control system with power allocation function, characterized in that: The invention comprises a power supply (1) and a controller (2), wherein the controller (2) comprises: A data acquisition module (21), the data acquisition module (21) being used to collect power supply data and fire scene data; A fire power supply control module (22) is connected to the data acquisition module (21), and the fire power supply control module (22) is provided with a real-time data analysis algorithm for receiving data transmitted by the data acquisition module (21) and analyzing fire conditions in different areas; A data processing unit (23), the data processing unit (23) being electrically connected to the fire power supply control module (22), and being used to quickly process output results of a real-time data analysis algorithm, and identify key areas of fire spread and demand priorities for firefighting equipment; A dynamic power allocation strategy module (24), the dynamic power allocation strategy module (24) being electrically connected to the data processing unit (23) and used to dynamically adjust the power allocation strategy according to an output result of the data processing unit (23) to ensure power supply to key areas; An intelligent prediction module (25), the intelligent prediction module (25) being electrically connected to the dynamic power distribution strategy module (24), calculating the power demand of each area based on system big data and real-time data of the current fire scene, and adjusting the power distribution strategy in advance; An emergency protection module (26), the emergency protection module (26) being electrically connected to the intelligent prediction module (25) and used for giving priority to ensuring the power supply of key areas and important fire-fighting equipment; A data acquisition module (21), comprising a smoke concentration sensor, a temperature sensor and a flame detector, wherein the safety threshold of the smoke concentration sensor is 0.5 optical density units, and is used to trigger an alarm when the smoke concentration exceeds 0.5 OD; The safety threshold of smoke concentration is set at 0.5 optical density units. Once the smoke concentration exceeds 0.5 OD, that is, reaches or exceeds the critical level that may pose a threat to human body or indicates that the fire is spreading rapidly, the smoke concentration sensor will immediately send an alarm signal to the control system; A fire power supply control module (22) has a built-in fire spread trend prediction algorithm, wherein the algorithm predicts the direction and speed of fire spread based on the building structure, combustible material distribution and environmental parameters; The dynamic power distribution strategy module (24) is configured to: based on the critical area of ​​fire spread, increase the proportion of power supply to the automatic sprinkler fire extinguishing system in the area with the largest fire spread, and reduce the proportion of power supply to non-critical fire fighting equipment in the safe area; An emergency protection module (26) is used to cut off the power supply to non-firefighting equipment in case of fire, and allocate 80% of the power of the backup power supply to the automatic sprinkler fire extinguishing system and the smoke exhaust fan on a priority basis; Smoke concentration sensors, temperature sensors and flame detectors are installed in corridors, stairwells, machine rooms, warehouses and other places in buildings. These locations are usually key passages and areas for personnel evacuation and fire fighting equipment use when a fire occurs. The fire spread trend prediction algorithm analyzes the distribution of combustibles, the structure of the building, wind direction and wind speed, combines historical fire case data with real-time data from the current fire scene, and uses deep learning and other technical training and optimization to predict the direction and speed of fire spread; The dynamic power distribution strategy module 24 dynamically adjusts the power supply ratio of each fire-fighting equipment according to the key areas where the fire spreads and the demand priority of the fire-fighting equipment. For example, the power supply ratio of key fire-fighting equipment such as the sprinkler system and the smoke exhaust fan is increased preferentially in the area where the fire spreads the fastest or the fire is the largest, while reducing the power supply of the safe area or non-critical equipment; After being activated, the emergency support module 26 limits the power supply to non-critical areas and non-important fire-fighting equipment, such as cutting off the power supply to non-fire-fighting equipment, and preferentially allocating more than 80% of the backup power supply to the sprinkler system, fire pumps and smoke exhaust fans.

2. A fire power supply control system with power allocation function according to claim 1, characterized in that: The real-time data analysis algorithm includes a fire occurrence recognition algorithm, a fire spread trend prediction algorithm and a regional safety status assessment algorithm.

3. A fire power supply control system with power allocation function according to claim 2, characterized in that: The dynamic power distribution strategy module (24) dynamically adjusts the power supply ratio of each fire-fighting equipment according to the key areas where the fire spreads and the demand priority of the fire-fighting equipment.

4. A fire power supply control system with power allocation function according to claim 3, characterized in that: The intelligent prediction module (25) uses a machine learning algorithm to analyze the system big data and the real-time data of the current fire scene.

5. A fire power supply control system with power allocation function according to claim 4, characterized in that: After being activated, the emergency protection module (26) limits the power supply to non-critical areas and non-important fire-fighting equipment.

6. A fire power supply control method with power allocation function, used to implement a fire power supply control system with power allocation function as claimed in any one of claims 1 to 5, characterized in that: The method includes: Step S1: collecting power supply data and fire scene data through a data acquisition module (21); Step S2: transmitting the collected data to the fire power supply control module (22), and using a real-time data analysis algorithm to analyze the safety status of each area under fire emergency conditions; Step S3: The output result of the real-time data analysis algorithm is quickly processed by the data processing unit (23) to identify the key areas of fire spread and the priority of fire fighting equipment requirements; Step S4: dynamically adjust the power distribution strategy according to the identification results to ensure the power supply of key areas; Step S5: using the intelligent prediction module (25) to predict the power demand of each region in the future, and adjusting the power distribution strategy in advance; Step S6: When a fire or other emergency is detected, the emergency protection module (26) is automatically activated.

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