Fire extinguishing system based on multiple sensors

Abstract

The invention discloses a fire extinguishing system based on multiple sensors, and the system comprises a data collection module which is used for collecting temperature, humidity, flame and smoke data in a vehicle test room in real time, and transmitting the temperature, humidity, flame and smoke data to a data processing module; the data processing module is used for performing multi-data fusion fuzzy reasoning on the temperature, humidity, flame and smoke data, generating a fire extinguishing instruction according to a multi-data fusion fuzzy reasoning result, and transmitting the fire extinguishing instruction to the execution module; the execution module is used for executing a fire extinguishing action according to the fire extinguishing instruction; the transmission module is used for uploading the data fusion fuzzy reasoning result to the terminal module; and the terminal module is used for receiving and storing the data fusion fuzzy reasoning result, generating a remote fire extinguishing instruction according to the reasoning result and transmitting the remote fire extinguishing instruction to the execution module through the transmission module, and the execution module executes the fire extinguishing action according to the remote fire extinguishing instruction so as to improve the fire extinguishing efficiency of the vehicle laboratory.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle test fire extinguishing system, and particularly to a fire extinguishing system based on multiple sensors. BACKGROUND

[0002] With the continuous development and popularization of modern transportation tools, vehicle safety has always been one of the important concerns in the field of vehicle engineering, and the safety of vehicles is closely related to the life safety of passengers and traffic safety. Therefore, vehicle manufacturers and safety researchers have been working hard to improve vehicle design and safety technology to reduce the incidence of traffic accidents and reduce the harm caused by accidents. Therefore, safety detection experiments need to be conducted on each vehicle produced. Fire is a safety accident that frequently occurs in laboratories and vehicle test rooms, which has high risk and uncertainty, and becomes the top priority of safety accident prevention in laboratories and vehicle test rooms. During the production and manufacturing process of vehicles, a series of safety detection experiments need to be conducted, and the vehicle test room is a place specially used for vehicle safety detection experiments. In the traditional vehicle test room, fire can only be extinguished manually, and it is impossible to timely alarm and open the fire extinguishing device in the actual fire, which may cause more serious losses.

[0003] Therefore, the existing vehicle test room fire extinguishing system lacks real-time monitoring and timely automatic fire extinguishing functions, resulting in low fire prevention and extinguishing efficiency in the vehicle test room, which cannot meet the working needs of the vehicle test room. SUMMARY

[0004] The embodiments of the present application provide a fire extinguishing system based on multiple sensors to solve the technical problem that the existing vehicle test room fire extinguishing system lacks real-time monitoring and timely automatic fire extinguishing functions, resulting in low fire prevention and extinguishing efficiency in the vehicle test room, which cannot meet the working needs of the vehicle test room.

[0005] Therefore, the present application provides a fire extinguishing system based on multiple sensors, which comprises a data acquisition module, a data processing module, an execution module, a transmission module and a terminal module. The data acquisition module is used to acquire temperature, humidity, flame and smoke data in the vehicle test room in real time, and transmit the temperature, humidity, flame and smoke data to the data processing module. The data processing module is used to receive the temperature, humidity, flame and smoke data, perform multi-data fusion fuzzy reasoning on the temperature, humidity, flame and smoke data, generate a fire extinguishing instruction according to the multi-data fusion fuzzy reasoning result, and transmit the fire extinguishing instruction to the execution module. The execution module is used to execute a fire extinguishing action according to the fire extinguishing instruction. The transmission module is used to upload the data fusion fuzzy inference result to the terminal module; The terminal module is used to receive and store the data fusion fuzzy inference result, and generate a remote fire extinguishing command based on the inference result, which is then transmitted to the execution module through the transmission module. The execution module then performs the fire extinguishing action according to the remote fire extinguishing command.

[0006] Optionally, the data acquisition module includes a temperature sensor, a humidity sensor, a flame sensor, and a smoke sensor; the temperature sensor is used to acquire real-time temperature data in the vehicle test chamber; the humidity sensor is used to acquire real-time humidity data in the vehicle test chamber; the flame sensor is used to acquire real-time flame data in the vehicle test chamber; and the smoke sensor is used to acquire real-time smoke data in the vehicle test chamber.

[0007] Optionally, the step of performing multi-data fusion fuzzy inference on the temperature, humidity, flame, and smoke data includes: extracting temperature feature information, humidity feature information, flame feature information, and smoke feature information from the real-time temperature data, real-time humidity data, real-time flame data, and real-time smoke data; then analyzing the credibility of the fire occurrence based on the extracted temperature feature information, humidity feature information, flame feature information, and smoke feature information; and then performing data fusion fuzzy inference based on the credibility.

[0008] Optionally, the step of extracting temperature feature information from the real-time temperature data includes: Obtain six consecutive real-time temperature data points and calculate the difference between the six real-time temperature data values. The calculation formula is as follows: ; Then, based on the preset temperature threshold The difference Temperature characteristic information is obtained through calculation. The calculation formula is as follows: .

[0009] Optionally, the step of extracting humidity feature information from the real-time humidity data includes: Obtain six consecutive real-time humidity data points and calculate the difference between the six real-time humidity data values. The calculation formula is as follows: ; Then, based on the preset temperature threshold The difference Temperature characteristic information is calculated. The calculation formula is as follows: .

[0010] Optionally, the step of extracting flame feature information from the real-time flame data includes: Let the flame characteristic information be When there is a flame The value is 1, when there is no flame. The value is 0, thus obtaining flame feature information. .

[0011] Optionally, the step of extracting smoke feature information from the real-time smoke data includes: Let the smoke characteristic information be When there is smoke The value is 1, indicating no smoke. The value is 0, and the smoke feature information is obtained. .

[0012] Optionally, the step of analyzing the credibility of the fire occurrence based on the extracted temperature feature information, humidity feature information, flame feature information, and smoke feature information includes: Assume the credibility of the fire occurrence is . Temperature reliability is The humidity confidence level is The credibility of the flame is The credibility of the smoke is To obtain the credibility of the fire occurrence .

[0013] Optionally, the step of performing data fusion fuzzy inference based on the credibility includes: assuming the output result of the data fusion fuzzy inference is... ,get ,in, To assess the credibility of the fire, For the degree of membership of information, ,in, For temperature membership, Humidity membership degree For the membership degree of the flame, The membership degree of the smoke.

[0014] Optionally, the terminal module is also used to allow users to query the historical data of temperature, humidity, flame, and smoke.

[0015] As can be seen from the above technical solutions, the embodiments of this application have the following advantages: This application provides a multi-sensor-based fire extinguishing system. Compared with existing technologies, this invention uses a data acquisition module to collect real-time temperature, humidity, flame, and smoke data within a vehicle testing chamber, and transmits this data to a data processing module. The data processing module receives the temperature, humidity, flame, and smoke data, performs multi-data fusion fuzzy inference on the data, generates a fire extinguishing command based on the fuzzy inference result, and transmits the fire extinguishing command to an execution module. The execution module executes the fire extinguishing action according to the fire extinguishing command. A transmission module uploads the data fusion fuzzy inference result to a terminal module. The terminal module receives and stores the data fusion fuzzy inference result, generates a remote fire extinguishing command based on the inference result, and transmits it to the execution module via the transmission module. The execution module executes the fire extinguishing action according to the remote fire extinguishing command, thereby achieving real-time monitoring of fires within the vehicle testing chamber, improving the accuracy of fire detection, and simultaneously supporting both remote and in-process fire extinguishing functions, thus enhancing the practicality of the fire extinguishing system within the vehicle testing chamber. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a system block diagram of a multi-sensor-based fire extinguishing system provided in the embodiments of this application. Detailed Implementation

[0018] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0019] For easier understanding, please refer to Figure 1This application provides an embodiment of a multi-sensor-based fire extinguishing system, comprising a data acquisition module, a data processing module, an execution module, a transmission module, and a terminal module. The data acquisition module is used to collect temperature, humidity, flame, and smoke data in a vehicle testing chamber in real time, and transmit the temperature, humidity, flame, and smoke data to the data processing module. The data processing module is used to receive the temperature, humidity, flame, and smoke data, perform multi-data fusion fuzzy inference on the temperature, humidity, flame, and smoke data, generate a fire extinguishing command based on the multi-data fusion fuzzy inference result, and transmit the fire extinguishing command to the execution module. The execution module is used to execute fire extinguishing actions according to the fire extinguishing command. The transmission module is used to upload the data fusion fuzzy inference result to the terminal module. The terminal module is used to receive and store the data fusion fuzzy inference result, generate a remote fire extinguishing command based on the inference result, and transmit it to the execution module through the transmission module. The execution module executes fire extinguishing actions according to the remote fire extinguishing command. Through the above configuration, the data acquisition module collects temperature, humidity, flame, and smoke data in a vehicle testing chamber in real time, and transmits the temperature, humidity, flame, and smoke data to the execution module. The data, including temperature, humidity, flame, and smoke data, is transmitted to the data processing module. The data processing module receives temperature, humidity, flame, and smoke data, performs multi-data fusion fuzzy inference on these data, generates a fire extinguishing command based on the fuzzy inference results, and transmits the fire extinguishing command to the execution module. The execution module executes the fire extinguishing action according to the fire extinguishing command. The transmission module uploads the data fusion fuzzy inference results to the terminal module. The terminal module receives and stores the data fusion fuzzy inference results, generates a remote fire extinguishing command based on the inference results, and transmits it to the execution module via the transmission module. The execution module then executes the fire extinguishing action according to the remote fire extinguishing command. This system enables real-time monitoring of fires within the vehicle testing laboratory, improving the accuracy of fire detection. It also incorporates both remote and in-process fire suppression capabilities, enhancing the practicality of the fire suppression system. This addresses the shortcomings of traditional vehicle testing laboratories where fires can only be extinguished manually, lacking timely warnings and often resulting in significant losses due to delayed warnings and failure to activate fire suppression devices. The system improves fire prevention and suppression efficiency, as well as automation and remote control efficiency, ultimately meeting the operational needs of existing vehicle testing laboratories.

[0020] Specifically, the data processing module is a single-chip microcomputer minimum system circuit, and the transmission module is an NB-IoT wireless communication module, which consists of an M5311 circuit, a NanoSIM card circuit, a patch SIM card circuit, and a UART level conversion circuit. The NB-IoT wireless communication module is connected to the single-chip microcomputer minimum system circuit, and the terminal module is a OneNET cloud platform. For example, after the M5311 circuit receives the temperature, humidity, flame, and smoke data periodically sent from the serial port of the single-chip microcomputer minimum system circuit, it immediately forwards it to the OneNET cloud platform for storage. Then, through the mobile client APP designed with the open API interface of the OneNET cloud platform, users can not only query the monitoring data, but also send control alarm and sprinkler fire extinguishing commands. At this time, the M5311 circuit can immediately send the command to the single-chip microcomputer minimum system circuit through the serial port, and the single-chip microcomputer minimum system circuit then responds according to the command.

[0021] Specifically, the minimum system circuit of the microcontroller consists of a microcontroller, a crystal oscillator circuit, a reset circuit, and a debugging interface circuit. The microcontroller selected is the low-power STM32L151C8T6, the crystal oscillator circuit selects two crystal oscillators, 32.768 KHz and 8MHz, the reset circuit selects a button reset system, and the debugging interface circuit selects SWD serial debugging.

[0022] Specifically, the data acquisition module includes a temperature sensor, a humidity sensor, a flame sensor, and a smoke sensor. The temperature sensor is used to collect real-time temperature data inside the vehicle testing chamber; the humidity sensor is used to collect real-time humidity data inside the vehicle testing chamber; the flame sensor is used to collect real-time flame data inside the vehicle testing chamber; and the smoke sensor is used to collect real-time smoke data inside the vehicle testing chamber. This enables real-time monitoring of fires inside the vehicle testing chamber, improves the accuracy of fire detection, and enhances the practicality of the fire extinguishing system inside the vehicle testing chamber.

[0023] Specifically, the execution module includes an alarm and a sprinkler device. The alarm consists of a transistor, a capacitor, a resistor, and an active buzzer. The drive circuit of the sprinkler device consists of a diode, a transistor, an electromagnetic relay, a capacitor, and a resistor, enabling the alarm and the sprinkler device to operate normally.

[0024] Furthermore, the multi-data fusion fuzzy inference of the temperature, humidity, flame, and smoke data includes: extracting temperature feature information, humidity feature information, flame feature information, and smoke feature information from the real-time temperature data, real-time humidity data, real-time flame data, and real-time smoke data.

[0025] Specifically, the extraction of temperature feature information from the real-time temperature data includes: Obtain six consecutive real-time temperature data points and calculate the difference between the six real-time temperature data values. The calculation formula is as follows: ; Then, based on the preset temperature threshold The difference Temperature characteristic information is calculated. The calculation formula is as follows: .

[0026] Specifically, the extraction of humidity feature information from the real-time humidity data includes: Obtain six consecutive real-time humidity data points and calculate the difference between the six real-time humidity data values. The calculation formula is as follows: ; Then, based on the preset temperature threshold The difference Temperature characteristic information is calculated. The calculation formula is as follows: .

[0027] Optionally, the step of extracting flame feature information from the real-time flame data includes: Let the flame characteristic information be When there is a flame The value is 1, when there is no flame. The value is 0, thus obtaining flame feature information. .

[0028] Optionally, the step of extracting smoke feature information from the real-time smoke data includes: Let the smoke characteristic information be When there is smoke The value is 1, indicating no smoke. The value is 0, and the smoke feature information is obtained. .

[0029] Then, the credibility of the fire occurrence is analyzed based on the extracted temperature feature information, humidity feature information, flame feature information, and smoke feature information. Specifically, the step of analyzing the credibility of a fire occurrence based on the extracted temperature feature information, humidity feature information, flame feature information, and smoke feature information includes: Assume the credibility of the fire occurrence is . Temperature reliability is The humidity confidence level is The credibility of the flame is The credibility of the smoke is To obtain the credibility of the fire occurrence .

[0030] Then, based on the stated credibility, data fusion fuzzy reasoning is performed; Specifically, the step of performing data fusion fuzzy inference based on the credibility includes: assuming the output result of the data fusion fuzzy inference is... ,get ,in, To assess the credibility of the fire, For the degree of membership of information, ,in, For temperature membership, Humidity membership degree For the membership degree of the flame, The smoke membership is represented by the following columns: temperature, humidity, flame, and smoke information, respectively, from the first to the fourth row. The first column represents the membership degree for determining if there is a fire, and the second column represents the membership degree for determining if there is no fire. For example, for a certain piece of information in a certain row, the sum of the membership degree for "there is a fire" and the membership degree for "there is no fire" equals 1, thus enabling accurate judgment of fire occurrence and improving the accuracy of judging fire occurrence in vehicle testing laboratories.

[0031] Furthermore, the terminal module is also used to allow users to query historical data on temperature, humidity, flame, and smoke, thereby enabling users to interact with the vehicle testing laboratory fire extinguishing system. This allows users to query and understand the temperature, humidity, flame, and smoke data inside the vehicle testing laboratory in real time, so that when a fire occurs in the vehicle testing laboratory, users can receive a notification immediately, preventing users from accidentally entering or approaching the vehicle testing laboratory where a fire is taking place, thus protecting users' personal safety. Moreover, users who are in the vehicle testing laboratory where a fire is taking place can also receive a fire notification immediately, thereby quickly evacuating the fire area and further protecting user safety.

[0032] Specifically, establishing a communication connection between the M5311 circuit and the OneNET platform requires operations on both the OneNET platform side and the M5311 circuit device side. Operations on the OneNET platform side include logging into the OneNET platform, creating products, and creating devices. Operations on the M5311 circuit device side include the M5311 circuit accessing the OneNET platform and transmitting and receiving data on the OneNET platform, enabling remote data reception and transmission, and improving the efficiency of remote data transmission and reception. Specifically, initial use of the OneNET platform requires registration. After successful registration, log in to the OneNET platform using your account. Once logged in, enter the console, select NB-IoT IoT Kit, then add a product, fill in the product information and technical parameters, and complete product creation. After successful product creation, select the product information from the product list to enter the product overview page. Through the device list, enter the device management page to add a device, select the device type, and fill in the device name to complete device creation. After successful operation on the OneNET platform, operate the M5311 circuit device. The M5311 circuit access to the OneNET platform process is as follows: the M5311 circuit sends relevant requests to the OneNET platform via AT commands. After receiving the request, the OneNET platform provides corresponding feedback and completes request authentication. After successful authentication, the M5311 circuit can be connected to the OneNET platform. The M5311 circuit can connect to the OneNET platform. After connecting to the cloud platform, it can perform data transmission and reception operations. This includes reporting temperature, humidity, flame, and smoke data, as well as issuing control commands to the OneNET platform. When reporting temperature, humidity, flame, and smoke data, the microcontroller sends the "AT+MIPLNOTIFY" command to the M5311 circuit via the serial port. The M5311 circuit then uploads the temperature, humidity, flame, and smoke data to the OneNET platform via the NB network. When the OneNET platform issues control commands, the microcontroller receives a command starting with "+MIPLWRITE". The microcontroller then issues corresponding action commands to the alarm and sprinkler system based on the value following the command, realizing remote control of the vehicle laboratory fire extinguishing system and improving fire extinguishing efficiency.

[0033] Furthermore, the terminal module also includes a mobile client APP. This APP fully utilizes the portability of mobile phones to facilitate user monitoring of vehicle laboratory fire information. Developed using Android Studio and Java, the APP uses the open API interfaces provided by the OneNET platform (HTTP / HTTPS calls) to query temperature, humidity, flame, and smoke data stored on the OneNET platform or to issue control commands. The APP has five pages: a function selection homepage, a subpage displaying the latest temperature, humidity, flame, and smoke data, a subpage displaying historical temperature, humidity, flame, and smoke data, a subpage controlling alarms and sprinkler devices, and a vehicle laboratory fire suppression monitoring overview page. Opening the APP and entering the homepage (function selection page), clicking the "Vehicle Laboratory Fire Suppression Monitoring Overview" option on the homepage, displays the current vehicle laboratory fire suppression monitoring information. In the event of a fire, the phone will vibrate for one minute to notify the user to take immediate action. Clicking the "Latest Monitoring Data" option on the homepage displays 4... The system displays the latest temperature, humidity, flame, and smoke data from various sensors. Clicking the "Historical Monitoring Data" option on the homepage allows users to query the last five monitoring data sets for a specific sensor. For example, querying the last five monitoring data sets for the temperature sensor will display the temperature data from those five sets. Clicking the "Control Alarm and Sprinkler Devices" option on the homepage displays that the alarms and sprinklers are currently off. Users can manually control the alarms and sprinklers to turn on or off as needed. This allows users to interact with the vehicle testing laboratory fire suppression system, facilitating real-time monitoring of temperature, humidity, flame, and smoke data within the testing laboratory, and remotely controlling the alarms and sprinklers to improve the efficiency of remote operation.

[0034] For example, a field test was conducted on the fire suppression system in the vehicle testing laboratory. Simulated temperature, humidity, fire, and smoke scenarios were used, including a hair dryer, burning waste wood, and smoke, as shown in Table 1. After four tests, six consecutive real-time temperature data points were acquired, and the results were analyzed using a formula. Calculate the difference between the six real-time temperature data values. Then, based on the preset temperature threshold The difference Through formula Calculate and obtain temperature characteristic information ; Then, by acquiring six consecutive real-time humidity data points, and using the formula... Calculate the difference between the six real-time humidity data values. Then, based on the preset temperature threshold The difference Through formula Calculate and obtain temperature characteristic information ; Then, by setting the flame characteristic information as When there is a flame The value is 1, when there is no flame. The value is 0, thus obtaining flame feature information. ; Then, by setting the smoke characteristic information as When there is smoke The value is 1, indicating no smoke. The value is 0, and the smoke feature information is obtained. ; Then, based on the extracted temperature feature information Humidity characteristics information Flame characteristic information and smoke characteristic information Analyzing the credibility of the fire occurrence includes: assuming the credibility of the fire occurrence is... Temperature reliability is The humidity confidence level is The credibility of the flame is The credibility of the smoke is To obtain the credibility of the fire occurrence ; Therefore, the confidence level for determining a fire based on temperature is 0.35, and the membership degree is 0.45; the confidence level for determining a fire based on humidity is 0.15, and the membership degree is 0.65; the confidence level for determining a fire based on flame is 0.4, and the membership degree is 1; and the confidence level for determining a fire based on smoke from the information source is 0.1, and the membership degree is 1. According to the formula... ,get The calculation yielded a probability of 0.755 for the occurrence of a fire and a probability of 0.245 for the absence of a fire. Based on the calculated probability of a fire, the threshold for the vehicle laboratory fire suppression system to determine the occurrence of a fire was set at 0.755. Tests showed that the vehicle laboratory fire suppression system operated stably, and the accuracy of determining the occurrence of a fire through multi-sensor fusion and fuzzy inference was significantly better than that of determining the occurrence of a fire from a single information source.

[0035] Table 1 Test Results

[0036] Working Principle: The data acquisition module, including temperature, humidity, flame, and smoke sensors, collects real-time data on temperature, humidity, flame, and smoke within the vehicle testing chamber and transmits this data to the data processing module. The microcontroller in the data processing module receives the temperature, humidity, flame, and smoke data, performs multi-data fusion fuzzy inference on the data, generates a fire extinguishing command based on the fuzzy inference result, and transmits the fire extinguishing command to the execution module. The alarm and sprinkler system in the execution module execute the fire alarm and fire extinguishing actions according to the fire extinguishing command. The NB-IoT wireless communication module in the transmission module uploads the data fusion fuzzy inference result and the temperature, humidity, flame, and smoke data to the terminal module. The OneNET platform in the terminal module receives and stores the data fusion fuzzy inference result and the temperature, humidity, flame, and smoke data, and generates a remote fire extinguishing command based on the inference result, which is then transmitted through the transmission module. The NB-IoT wireless communication module transmits data to the execution module, which then executes fire alarm and fire extinguishing actions according to the remote fire extinguishing command. Next, through the mobile client APP included in the terminal module, the mobile client APP fully utilizes the portability of mobile phones to facilitate real-time monitoring of fire information in the vehicle testing laboratory, thereby achieving real-time monitoring of fires in the vehicle testing laboratory. Furthermore, fuzzy inference calculations using multi-sensor fusion improve the accuracy of fire detection. The cooperation between the terminal module and the transmission module enables remote fire extinguishing operation, enhancing the practicality of the fire extinguishing system in the vehicle testing laboratory. The fire extinguishing system in the vehicle testing laboratory is based on multi-sensor fusion and adopts a "cloud-pipe-terminal" architecture NB-IoT wireless transmission technology and multi-sensor fusion fuzzy inference for fire detection. Combined with the OneNET platform, it realizes data interaction between the vehicle testing laboratory fire extinguishing monitoring and control device and the mobile client APP. Test results demonstrate that this fire extinguishing system has a high accuracy rate in fire detection, strong practicality, and stable operation, effectively preventing fires in the vehicle testing laboratory.

[0037] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented, for example, in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0038] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A fire extinguishing system based on multiple sensors, characterized in that, It includes a data acquisition module, a data processing module, an execution module, a transmission module, and a terminal module; The data acquisition module is used to collect temperature, humidity, flame and smoke data in the vehicle test chamber in real time, and transmit the temperature, humidity, flame and smoke data to the data processing module. The data processing module is used to receive the temperature, humidity, flame and smoke data, perform multi-data fusion fuzzy inference on the temperature, humidity, flame and smoke data, generate a fire extinguishing command based on the multi-data fusion fuzzy inference result, and transmit the fire extinguishing command to the execution module. The execution module is used to perform fire extinguishing actions according to the fire extinguishing command; The transmission module is used to upload the data fusion fuzzy inference result to the terminal module; The terminal module is used to receive and store the data fusion fuzzy inference result, and generate a remote fire extinguishing command based on the inference result, which is then transmitted to the execution module through the transmission module. The execution module then performs the fire extinguishing action according to the remote fire extinguishing command.

2. The fire extinguishing system based on multiple sensors according to claim 1, characterized in that, The data acquisition module includes a temperature sensor, a humidity sensor, a flame sensor, and a smoke sensor; the temperature sensor is used to collect real-time temperature data in the vehicle test chamber; the humidity sensor is used to collect real-time humidity data in the vehicle test chamber; and the flame sensor is used to collect real-time flame data in the vehicle test chamber. The smoke sensor is used to collect real-time smoke data in the vehicle test chamber.

3. A fire extinguishing system based on multiple sensors according to claim 2, characterized in that, The multi-data fusion fuzzy inference of the temperature, humidity, flame, and smoke data includes: extracting temperature feature information, humidity feature information, flame feature information, and smoke feature information from the real-time temperature data, real-time humidity data, real-time flame data, and real-time smoke data; then analyzing the credibility of the fire occurrence based on the extracted temperature feature information, humidity feature information, flame feature information, and smoke feature information; and then performing data fusion fuzzy inference based on the credibility.

4. A fire extinguishing system based on multiple sensors according to claim 3, characterized in that, The extraction of temperature feature information from the real-time temperature data includes: Obtain six consecutive real-time temperature data points and calculate the difference between the six real-time temperature data values. The calculation formula is as follows: ; Then, based on the preset temperature threshold The difference Temperature characteristic information is calculated. The calculation formula is as follows: .

5. A fire extinguishing system based on multiple sensors according to claim 4, characterized in that, The extraction of humidity feature information from the real-time humidity data includes: Obtain six consecutive real-time humidity data points and calculate the difference between the six real-time humidity data values. The calculation formula is as follows: ; Then, based on the preset temperature threshold The difference Temperature characteristic information is calculated. The calculation formula is as follows: .

6. A fire extinguishing system based on multiple sensors according to claim 5, characterized in that, The extraction of flame feature information from the real-time flame data includes: Let the flame characteristic information be When there is a flame The value is 1, when there is no flame. The value is 0, thus obtaining flame feature information. .

7. A fire extinguishing system based on multiple sensors according to claim 6, characterized in that, The step of extracting smoke feature information from the real-time smoke data includes: Let the smoke characteristic information be When there is smoke The value is 1, indicating no smoke. The value is 0, and the smoke feature information is obtained. .

8. A fire extinguishing system based on multiple sensors according to claim 7, characterized in that, The analysis of the credibility of a fire occurrence based on the extracted temperature, humidity, flame, and smoke characteristics includes: Assume the credibility of the fire occurrence is . Temperature reliability is The humidity confidence level is The credibility of the flame is The credibility of the smoke is To obtain the credibility of the fire occurrence .

9. A fire extinguishing system based on multiple sensors according to claim 8, characterized in that, The step of performing data fusion fuzzy inference based on the credibility includes: assuming the output result of the data fusion fuzzy inference is... ,get ,in, To assess the credibility of the fire, For the degree of membership of information, ,in, For temperature membership, Humidity membership degree For the membership degree of the flame, The membership degree of the smoke.

10. A fire extinguishing system based on multiple sensors according to claim 1, characterized in that, The terminal module is also used to allow users to query historical data on temperature, humidity, flame, and smoke.

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