Fire-fighting power supply control system with electric quantity allocation function and control method thereof

Abstract

The invention discloses a fire-fighting power supply control system with an electric quantity allocation function and a control method thereof, and belongs to the technical field of electric quantity allocation of fire-fighting power supplies, the fire-fighting power supply control system comprises a power supply and a controller, the controller comprises a data acquisition module used for collecting power supply data and fire scene data; the fire-fighting power supply control module is connected with the data acquisition module, is internally provided with a real-time data analysis algorithm, and is used for receiving the data transmitted by the data acquisition module and analyzing the condition of each region under the fire emergency condition; the data processing unit is electrically connected with the fire-fighting power supply control module and is used for quickly processing an output result of a real-time data analysis algorithm and identifying a key area where fire spreads and a demand priority of fire-fighting equipment; and the dynamic power distribution strategy module dynamically adjusts the power distribution strategy according to the output result of the data processing unit, thereby achieving the effects of flexibly distributing the electric quantity and improving the reliability of the fire-fighting power supply.

Description

Technical Field

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

[0002] The fire power supply control system is a management system that acts on the fire power supply. Its purpose is to comprehensively monitor the charging and discharging status and stability of the fire power supply, and to monitor the key parameters such as the voltage and current of the fire power supply in real time to ensure that the fire power supply works stably within the normal range. In the event of a mains failure or abnormality, the control system immediately starts the fire 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 an abnormality or insufficient stability of the fire power supply is detected, the control system will promptly issue an alarm to remind maintenance personnel to handle it.

[0003] For example, the patent with announcement number CN106056827A specifically discloses a fire power supply control system. 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, it can quickly cut off the power supply when a fire signal is detected, and use the backup power supply to power the lighting, sensors and communication units 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 emergency areas and important fire-fighting equipment are given priority power supply. The lack of flexibility may affect the effective operation of fire-fighting equipment at critical moments.

[0004] It should be noted that the above information disclosed in this background technology section is only for understanding the background technology of the present application concept, and therefore, it may contain 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 power supply control system with power allocation function and a control method thereof, so as to achieve the effect of flexible power allocation and improve the reliability of the fire power supply.

[0006] In order to solve the above technical problems, the technical solution of the present invention is: a fire power supply control system with power allocation function and a control method thereof, including a power supply and a controller, wherein the controller includes: A data acquisition module, which includes a smoke concentration sensor, a temperature sensor and a flame detector, and is used to collect data at the fire scene; A fire power supply control module is connected to the data acquisition module, and the fire power supply control module is provided with a real-time data analysis algorithm for receiving data transmitted by the data acquisition module and analyzing the fire conditions in different areas; A data processing unit, the data processing unit is electrically connected to the fire power supply control module, and is used to quickly process the output results of the real-time data analysis algorithm, identify the key areas of fire spread and the demand priority of fire fighting equipment; A dynamic power allocation strategy module, the dynamic power allocation strategy module is electrically connected to the data processing unit, and is used to dynamically adjust the power allocation strategy according to the output result of the data processing unit to ensure the power supply of key areas; An intelligent prediction module, which is electrically connected to the dynamic power distribution strategy module, 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; An emergency support module is electrically connected to the intelligent prediction module and is used to give priority to ensuring the power supply to key areas and important fire-fighting equipment.

[0007] Furthermore, the real-time data analysis algorithm includes a fire occurrence identification algorithm, a fire spread trend prediction algorithm and a regional safety status assessment algorithm.

[0008] Furthermore, the dynamic power distribution strategy module 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.

[0009] Furthermore, the intelligent prediction module uses machine learning algorithms to analyze system big data and real-time data of the current fire scene.

[0010] Furthermore, after being activated, the emergency protection module limits the power supply to non-critical areas and non-important fire-fighting equipment.

[0011] A fire power supply control method with power allocation function, the method comprising: Step S1: Collecting fire scene data in real time through a data acquisition module; Step S2: The collected data is transmitted to the fire power supply control module, and the safety status of each area in the fire emergency situation is analyzed using a real-time data analysis algorithm; 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 demand priorities of fire fighting equipment; 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 to predict the power demand of each region in the future and adjust the power distribution strategy in advance; Step S6: When a fire or other emergency situation is detected, the emergency protection module is automatically started.

[0012] The beneficial effects of the present application are: by integrating the data acquisition module and the fire equipment power supply 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 to provide information for power allocation. The fire equipment power supply control module has a built-in real-time data analysis algorithm to quickly evaluate the regional safety status and personnel safety in fire emergencies. The data processing unit further processes these data to identify the key areas where the fire spreads, the demand priority of fire equipment, and the densely populated areas. The dynamic power distribution strategy module uses the above information to dynamically adjust the power distribution, ensure the power supply of key areas, ensure the safety of personnel and the effective operation of fire equipment, and the intelligent prediction module predicts future power demand based on system 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 power supply in fire response is improved, and the flexible allocation of the fire power supply is realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0014] Figure 1 It is a schematic diagram of the module structure of a fire power supply control system with power allocation function in the present invention; Figure 2 It is a flow chart of a fire power supply control method with power allocation function in the present invention.

[0015] In the figure: 1. power supply; 2. controller; 21. data acquisition module; 22. fire power supply control module; 23. data processing unit; 24. dynamic power supply allocation strategy module; 25. intelligent prediction module; 26. emergency support module. DETAILED DESCRIPTION

[0016] In order to make the contents of the present invention more clearly understood, the present invention is further described in detail below based on specific embodiments in conjunction with the accompanying drawings.

[0017] like Figure 1 As shown, the present application provides a fire power supply control system with power allocation function, including a power supply 1 and a controller 2, and the controller 2 includes: 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; The fire power supply control module 22 is connected to the data acquisition module 21. 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 the fire conditions in different areas; A data processing unit 23, which is electrically connected to the fire power supply control module 22, and is used to quickly process the output results of the real-time data analysis algorithm, identify the key areas where the fire spreads and the demand priority of the fire equipment; A dynamic power distribution strategy module 24, which is 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 of key areas; Intelligent prediction module 25, which is electrically connected to dynamic power distribution strategy module 24, calculates the power demand of each area based on system big data and real-time data of the current fire scene, and adjusts the power distribution strategy in advance; The emergency protection module 26 is electrically connected to the intelligent prediction module 25 and is used to give priority to the power supply to key areas and important fire-fighting equipment.

[0018] like Figure 1-2 As shown, 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.

[0019] like Figure 1-2 As 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 demand priority of the 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 being started, the emergency guarantee module 26 limits the power supply to non-critical areas and non-important fire-fighting equipment.

[0020] The present invention also provides a method for implementing the above system, such as Figure 2 It is a flow chart of a fire power supply control method with power allocation function in the present invention, and the system includes: Step S1: Collecting fire scene data in real time through the data acquisition module 21; Step S2: The collected data is transmitted to the fire equipment power control module, and the safety status of each area in the fire emergency situation is analyzed using a real-time data analysis algorithm; Step S3: The output results of the real-time data analysis algorithm are quickly processed by the data processing unit 23 to identify the key areas of fire spread and the demand priorities of fire fighting equipment; 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 situation is detected, the emergency protection module 26 is automatically started.

[0021] 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, wherein the power supply part is the mains power and the backup power supply. When the mains power is interrupted, the fire power supply control system can automatically switch to the backup power supply to supply power to the fire fighting equipment. When a fire occurs, the control system responds, firstly collecting power supply data and fire data through the data acquisition module 21, and the fire data is collected collaboratively through the smoke concentration sensor, the temperature sensor and the flame detector; The function of the smoke density sensor is to capture the change of smoke density in the air. Once the smoke density exceeds the preset safety threshold, an alarm will be issued immediately. According to the fire safety standards, the safety threshold of smoke density is set at 0.5 optical density units. Specifically, once the smoke density exceeds 0.5 OD, that is, it reaches or exceeds the critical level that may pose a threat to the human body or indicates that the fire is spreading rapidly, the smoke density sensor will immediately send an alarm signal to the control system; In addition, the role of the temperature sensor is to monitor the temperature changes inside the building and continuously monitor the ambient temperature. Once the temperature is detected to be abnormally high, exceeding the normal range and reaching 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 flames. Once the flame detector detects a flame, it will also transmit the alarm information to the control system to ensure that the system can respond in the first time; The smoke concentration sensor, temperature sensor and flame detector together constitute the data acquisition module 21, which provides comprehensive and real-time fire monitoring data for the fire power supply from three aspects: smoke concentration, temperature anomaly and flame, so that the control system can respond and make decisions quickly in the early stage of the fire; It should be noted that 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. 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 equipped with a real-time data analysis algorithm, including a fire occurrence identification algorithm, a fire spread trend prediction algorithm, and a regional safety status assessment algorithm. These algorithms process the data from the data acquisition module 21 to identify whether a fire has actually occurred, predict the direction of fire spread, and analyze the safety status of each area in the building. Specifically, the fire occurrence recognition algorithm is based on the characteristics of flames and smoke. When the smoke concentration sensor, temperature sensor and flame detector capture that the smoke concentration exceeds the preset threshold, the temperature rises abnormally and the flame is detected, these data are transmitted to the fire power supply control module 22. The fire occurrence recognition algorithm processes and analyzes these data and determines whether there is a possibility of fire occurrence by comparing the preset flame and smoke characteristic models. If the algorithm determines that a fire has occurred, the system will immediately trigger an alarm. The fire spread trend prediction algorithm will analyze the distribution of combustibles, the structure of the building, wind direction and wind speed, etc., and use historical fire data and real-time fire data, and deep learning and other technologies for training and optimization. When a fire occurs, it will predict the direction and speed of fire spread based on the current fire scale and location, as well as the structure and environment of the building, which will help to formulate fire extinguishing and evacuation plans in advance; The regional safety assessment algorithm conducts safety assessments on each area based on the location of the fire, the spread of the fire, and the distribution of firefighting equipment. Through calculation and analysis, it identifies safe and dangerous areas, including areas that need to be evacuated first. Once a fire is confirmed, the data processing unit 23 immediately intervenes. The data processing unit 23 is set in the power control module. According to the output results of the real-time data analysis algorithm, the data processing unit 23 identifies the key areas where the fire spreads, including the areas with the largest fire and the areas that are about to be threatened, so as to determine the demand priority of the fire fighting equipment and ensure the power supply according to the priority level; In addition, based on the output result of the data processing unit 23, the dynamic power allocation strategy module 24 is started. According to the key areas where the fire spreads and the demand priority of the fire-fighting equipment, the dynamic power allocation strategy module 24 will increase the power supply of the automatic sprinkler fire extinguishing system in the area with the largest fire to ensure that it can continue to work effectively. In the safe area with less threat, the power supply of some non-critical fire-fighting equipment will be reduced, thereby ensuring the power resources of the fire-fighting power supply, ensuring that the key equipment can obtain a stable power supply for a long time, and realizing the dynamic supply of the fire-fighting power supply; At the same time, 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 to predict the power demand of each region in the future. The intelligent prediction module 25 first integrates two types of data: one is the historical power consumption data accumulated during the long-term operation of the system, the equipment energy consumption pattern and the power demand change data in the previous fire response; the other is the fire scene data transmitted in real time by the data acquisition module 21, including information such as smoke concentration, temperature anomaly, and flame state. This information reflects the dynamic situation and urgency of the fire scene. Subsequently, the machine learning algorithm is used to deeply mine these data. The machine learning algorithm automatically identifies and extracts characteristic variables related to power demand prediction, such as the trend of historical power consumption, the peak period of equipment energy consumption, the speed of fire spread, and the relationship between power demand growth, and predicts power demand through characteristic variables; On the basis of feature extraction, the machine learning algorithm builds a prediction model based on historical data and real-time data, learns the changing rules of power demand in each area when a fire occurs, and predicts the power demand in each area in the future based on the rules. Through the ability to predict power, the intelligent prediction module 25 can learn about the changes in power demand in advance, so that the power control system can pre-adjust the power distribution strategy according to the prediction results. In this way, in an emergency, the system can ensure that key areas and important fire-fighting equipment have a stable power supply, while avoiding power waste in non-key areas, effectively balancing power supply and demand, and avoiding insufficient or excessive power supply in an emergency. Finally, the emergency support module 26 is automatically activated when a fire or other emergency is detected. The emergency support module 26 will immediately limit the power supply to non-critical areas and non-important fire-fighting equipment. Specifically, the emergency support module 26 will give priority to the power supply to key areas and important fire-fighting equipment such as the fire control room, emergency exits, evacuation passages, fire pumps, smoke exhaust fans, and fire elevators. At the same time, the emergency support module 26 will dynamically adjust the power distribution strategy based on the real-time data of the fire scene and the prediction results of the intelligent prediction module 25. In the case of rapid spread of fire and surge in power demand, the module will further compress the power supply to non-critical areas to ensure that key areas and important fire-fighting equipment can continue to obtain stable and sufficient power support; This emergency protection measure can improve the reliability and stability of fire power supply in emergency situations and provide support for fire rescue work. Through intelligent prediction and dynamic adjustment of power distribution strategy, the fire power supply control system can ensure that key areas and important fire fighting equipment can be powered when a fire occurs. Specifically, when a fire occurs, the data acquisition module 21 is started, and the fire data is comprehensively collected through the smoke density sensor, temperature sensor and flame, and the collected data is transmitted to the fire power control module 22, and then the received data is processed and analyzed through the real-time data analysis algorithm. When the fire is confirmed, the data processing unit 23 intervenes to determine the power supply strategy according to the key areas where the fire spreads and the priority of the fire equipment demand; Furthermore, the dynamic power distribution strategy module 24 dynamically adjusts the power supply of each area according to the output results of the data processing unit 23 to ensure that key fire-fighting equipment obtains stable power. 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 of each area in the future, so that the power control system can adjust the power distribution in advance. Finally, the emergency guarantee module 26 is activated to restrict the power supply of non-critical areas, give priority to the power demand of key areas and important fire-fighting equipment, and dynamically adjust the strategy according to real-time data and prediction results to ensure that in emergency situations such as fire, the system can provide power support efficiently and stably.

[0022] The specific embodiments described above further illustrate the technical problems, technical solutions and beneficial effects solved by the present invention. It should be understood that the above are only specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in 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 to key areas and important firefighting equipment.

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 control method for a fire power supply control system with power allocation function according to 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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