Firefighter air respirator reserve prediction method and system based on dynamic pressure compensation

Abstract

The application relates to the technical field of fire rescue equipment monitoring, and discloses a firefighter air respirator residual amount prediction method and system based on dynamic pressure compensation. The method comprises the following steps: acquiring historical consumption time data of firefighters, using polynomial regression fitting to establish a theoretical pressure consumption rate function corresponding to an individual and establishing a theoretical prediction logic; receiving a combat organization instruction to obtain an initial full load pressure, starting timing and calculating and displaying a current theoretical prediction residual pressure; capturing an artificial interactive correction instruction, extracting a correction time node and an actual residual pressure, and solving to generate a dynamic compensation coefficient; applying the dynamic compensation coefficient to reconstruct and solve an actual prediction residual pressure and control and update display; comparing the actual prediction residual pressure with an alarm critical pressure value to trigger an alarm, and extracting actual combat data to iteratively update the theoretical function after the task is completed. The application realizes individualized benchmark prediction of air consumption and dynamic adaptive error correction of the working environment, and improves residual amount early warning accuracy.

Description

Technical Field

[0001] This invention relates to the field of fire and rescue equipment monitoring technology, specifically to a method and system for predicting the remaining capacity of firefighters' breathing apparatus based on dynamic pressure compensation. Background Technology

[0002] In fire rescue command and operation monitoring systems, self-contained breathing apparatus (SCBA) is an essential individual protective equipment for ensuring the safety of firefighters during interior assaults. Accurately predicting the remaining usable time of SCBAs is crucial for the rational allocation of fire rescue tasks and ensuring the safe evacuation of personnel. However, existing SCBA remaining capacity prediction and alarm systems generally use a uniform fixed consumption rate for theoretical estimation. This basic prediction method disregards the individual physiological characteristics and lung capacity differences of firefighters, failing to consider the inherent differences in air consumption among different personnel under normal conditions. This results in theoretical estimation errors in the prediction model from the initial task assignment stage.

[0003] In actual firefighting operations, firefighters face extreme environments such as scorching heat and strenuous physical exertion, causing their actual breathing rate and air consumption rate to fluctuate non-linearly. Existing monitoring systems rely solely on theoretical baselines for simulations, lacking a dynamic adaptive error correction mechanism based on real-world pressure drop feedback. This static monitoring model cannot eliminate the interference of the external working environment on individual physiological energy consumption. When firefighters experience a surge in air consumption due to stress or strenuous activity, the system cannot reconstruct the prediction curve in time, easily leading to severe delays in warning times.

[0004] Existing prediction systems mostly present data from single missions, lacking mechanisms for collecting historical operational data and long-term optimization. When firefighters' physical condition, work habits, and combat experience objectively change over time, the system cannot iteratively update its basic calculation model using long-term accumulated real-world mission data. This fixed computational architecture, lacking data feedback and benchmark evolution, results in the air respirator reserve prediction benchmark remaining static, making it difficult to maintain the accuracy and reliability of the monitoring system in long-term application. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method and system for predicting the remaining capacity of firefighters' breathing apparatus based on dynamic pressure compensation. This solves the technical problem in existing technologies where the prediction of breathing apparatus usage time is detached from the individual physiological characteristics of firefighters and the actual intensity of operations at the fire scene, leading to deviations in the prediction results.

[0006] To achieve the above objectives, the present invention provides the following technical solution: The first aspect of this invention provides a method for predicting the remaining capacity of a firefighter's self-contained breathing apparatus based on dynamic pressure compensation, comprising the following: Obtain basic information and historical consumption time data of firefighters. Extract the endpoints of discrete pressure drop intervals from the historical consumption time data and their corresponding specific time parameters to construct a discrete data point set containing time independent variables and pressure dependent variables. Extract and remove outlier data points from the discrete data point set. Use a multinomial regression fitting algorithm to perform curve fitting on the discrete data point set to establish a continuous theoretical pressure consumption rate function for the corresponding firefighters. Set the theoretical predicted residual pressure as the initial full-load pressure of the air respirator minus the integral value of the theoretical pressure consumption rate function over the duration of actual combat, forming the calculation logic for the theoretical predicted residual pressure.

[0007] The system listens for touch events of checkbox controls in the firefighter data list, extracts the unique identification code of the bound firefighter, and stores it in the assignment queue. It generates a personnel grouping instruction in response to touch signals from the assignment task button. Upon receiving the personnel grouping instruction, it retrieves the corresponding initial full-load pressure of the breathing apparatus using the unique identification code of the firefighter contained in the instruction as the data retrieval keyword. It activates the timer module to obtain the duration variable. Using the duration variable output by the timer module as the integration limit, it performs a definite integral on the theoretical pressure consumption rate function to obtain the cumulative air consumption value. It subtracts the cumulative air consumption value from the initial full-load pressure to obtain the theoretical predicted remaining pressure at the current moment. It converts the theoretical predicted remaining pressure at the current moment into text characters and maps and displays the text characters in the remaining air value box on the mobile terminal's personnel interface.

[0008] The system captures manual intervention correction commands and extracts the corresponding correction time points and actual remaining pressure values. It calculates the difference between the initial full-load pressure and the actual remaining pressure value, and divides this difference by the correction time point to obtain the actual average consumption rate. Using the correction time point as the upper limit of integration, it performs a definite integral on the theoretical pressure consumption rate function to obtain the theoretical cumulative gas consumption, and divides this theoretical cumulative gas consumption by the correction time point to obtain the theoretical average consumption rate. Finally, it calculates the ratio of the actual average consumption rate to the theoretical average consumption rate to generate a dynamic compensation coefficient.

[0009] The actual predicted remaining pressure is calculated by reconstructing the solution using dynamic compensation coefficients. During the monitoring phase where the duration variable output by the timekeeping module exceeds the correction time node, a definite integral is performed on the theoretical pressure consumption rate function using the correction time node as the lower limit of integration and the duration variable as the upper limit of integration to obtain the integral calculation value. The integral calculation value is multiplied by the dynamic compensation coefficient to obtain the reconstructed gas consumption. The actual predicted remaining pressure is obtained by subtracting the reconstructed gas consumption from the actual remaining pressure value. The mobile terminal is then controlled to stop displaying the theoretical predicted remaining pressure and instead display the actual predicted remaining pressure.

[0010] The system compares the actual predicted residual pressure with the alarm critical pressure value. When the actual predicted residual pressure is less than or equal to the alarm critical pressure value, an alarm trigger command is generated and sent to the mobile terminal. The system controls the background color of the corresponding personnel data row in the mobile terminal application interface to turn red and perform a highlighting flashing warning action, outputting a visual alarm signal. Simultaneously, the speaker module outputs a sound buzzer broadcast at a specified frequency and outputs an auditory alarm signal. After the fire-fighting operation is completed, the corrected time nodes recorded during the operation and the corresponding actual residual pressure values ​​are extracted and mapped to operational feature data points according to the data dimensions of the time independent variable and the pressure dependent variable. These operational feature data points are added as new sample nodes to the discrete data point set to integrate and generate an updated discrete data point set. A multinomial regression fitting algorithm is used to refit the updated discrete data point set, updating the multinomial weight coefficients in the theoretical pressure consumption rate function.

[0011] A second aspect of the present invention provides a firefighter's self-contained breathing apparatus reserve prediction system based on dynamic pressure compensation, comprising: The basic data acquisition and model building module is configured to acquire basic information and historical consumption time data of firefighters, use a fitting algorithm to establish the theoretical pressure consumption rate function of the corresponding firefighters based on the historical consumption time data, and establish the theoretical prediction of residual pressure calculation logic based on the theoretical pressure consumption rate function.

[0012] The combat mission initialization and monitoring startup module is configured to receive the personnel grouping instructions, obtain the initial full-load pressure of the corresponding air breathing apparatus of the personnel, start the timer module to obtain the duration variable, and calculate and display the theoretically predicted remaining pressure at the current moment based on the theoretically predicted remaining pressure calculation logic and the duration variable.

[0013] The dynamic adaptive compensation calculation module is configured to capture manual interaction correction commands and extract the corresponding correction time points and actual remaining pressure values. Based on the initial full-load pressure, actual remaining pressure values, correction time points, and the theoretical pressure consumption rate function, dynamic compensation coefficients are calculated and generated. These dynamic compensation coefficients are then applied to reconstruct and calculate the actual predicted remaining pressure, and the mobile terminal is controlled to stop displaying the theoretical predicted remaining pressure and instead display the actual predicted remaining pressure.

[0014] The critical value early warning and model optimization module is configured to compare the actual predicted residual pressure with the alarm critical pressure value. An alarm signal is output when the actual predicted residual pressure is less than or equal to the alarm critical pressure value. After the firefighting operation concludes, the theoretical pressure consumption rate function is iteratively updated using the correction time point and the actual residual pressure value.

[0015] This invention provides a method and system for predicting the remaining capacity of firefighters' self-contained breathing apparatus based on dynamic pressure compensation. It has the following beneficial effects: 1. This invention obtains historical air consumption data from firefighters and uses a multinomial regression fitting algorithm to establish a continuous theoretical pressure consumption rate function for each individual, overcoming the shortcomings of existing technologies that use a uniform fixed rate for estimation. A basic prediction model is constructed based on the historical air consumption characteristics of individual firefighters, enabling the theoretical prediction of remaining pressure to accurately match the physiological energy consumption benchmark of specific personnel, thus improving the objective accuracy of predicting the remaining air supply in the initial state.

[0016] 2. This invention extracts the actual remaining pressure value and corrects the time point, calculating the ratio of the actual average consumption rate to the theoretical average consumption rate to generate a dynamic compensation coefficient. The system uses the dynamic compensation coefficient combined with the integral value of the theoretical pressure consumption rate function to reconstruct and calculate the actual predicted remaining pressure. This allows the monitoring end to adaptively correct errors based on actual breathing changes caused by high temperatures and high-intensity operations at the fire site, effectively eliminating the interference of the external energy-consuming environment on the prediction results and ensuring the accuracy of dynamic gas volume monitoring during internal attack operations.

[0017] 3. After a firefighting operation concludes, this invention adds the corrected time points and corresponding actual remaining pressure values ​​recorded during the operation to the discrete data point set as new sample nodes. A fitting algorithm is then used to refit the curve to update the theoretical pressure consumption rate function. This data feedback mechanism allows the basic calculation logic to continuously absorb the energy consumption characteristics of real firefighting operations, prompting the air respirator remaining capacity prediction benchmark to be iteratively updated over a long period as firefighters' physical strength and experience change, thus improving the reliability of the prediction system during long-term operation. Attached Figure Description

[0018] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a system architecture diagram of the present invention. Detailed Implementation

[0019] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Please see the appendix Figure 1 -Appendix Figure 2 This invention provides a method and system for predicting the remaining capacity of firefighters' breathing apparatus based on dynamic pressure compensation.

[0021] The firefighter air respirator remaining capacity prediction system based on dynamic pressure compensation includes a mobile terminal, a data acquisition terminal, and a cloud server. The mobile terminal provides an interactive interface for fire safety officers; specifically, it is a portable tablet or smartphone. The data acquisition terminal is configured at the fire station for collecting and inputting data during daily safety inspections. The data acquisition terminal integrates a QR code scanning module and an RFID reading module. The cloud server establishes a communication connection with the mobile terminal and the data acquisition terminal. The cloud server achieves real-time data synchronization and backup through cloud platform technology. Based on the above architecture, the mobile terminal can receive management information in real time. For the wireless data transmission method between the mobile terminal, the data acquisition terminal, and the cloud server, those skilled in the art can use common communication protocols such as 4G, 5G, or wireless LAN. The specific communication mechanism and underlying handshake protocol of the wireless data transmission method are well-known technologies in the field and will not be elaborated here.

[0022] The method for predicting the remaining capacity of firefighters' self-contained breathing apparatus based on dynamic pressure compensation relies on the aforementioned cloud server and the hardware computing power of mobile terminals to perform calculations. The method for predicting the remaining capacity of firefighters' self-contained breathing apparatus based on dynamic pressure compensation includes steps S100 to S400.

[0023] Step S100 involves collecting basic data and establishing a theoretical consumption decay model. Step S100 specifically includes sub-steps S110 and S120.

[0024] In sub-step S110, basic information and historical consumption data of firefighters are acquired. The fire department sets fixed time slots daily, requiring firefighters to conduct comprehensive checks of their personal protective equipment and breathing apparatus (BPE). After the check, they must promptly scan a QR code to upload BPE air volume data, forming a closed-loop management system. The cloud server acquires the basic information database through the aforementioned scanning and data entry operations. The basic information database records individual firefighter characteristics including position, name, age, and blood type. The system simultaneously acquires historical consumption data, which specifically records the attenuation time for different operating pressure ranges, including the specific time parameters for consuming 5MPa, 10MPa, 15MPa, and 20MPa.

[0025] In sub-step S120, a theoretical pressure consumption rate function for each individual is established based on the acquired historical consumption data. The cloud server extracts discrete data point arrays from the pressure drop values ​​and corresponding time features acquired in each iteration. The cloud server runs a fitting algorithm module to perform curve fitting calculations on the discrete data point arrays, establishing the continuous theoretical pressure consumption rate function for the corresponding firefighter. Based on the calculated theoretical pressure consumption rate function, the system defines the theoretical predicted residual pressure under conditions unaffected by external high-energy-consuming environments. The theoretical predicted residual pressure is obtained by subtracting the integral value of the theoretical pressure consumption rate function from the initial full-load pressure of the air respirator over the duration of actual combat.

[0026] Step S200: Initialize the practical task and start predictive monitoring. Step S200 specifically includes sub-steps S210 to S230.

[0027] In sub-step S210, the system receives the personnel grouping instruction sent by the terminal device. During an emergency response or drill, the fire safety officer selects personnel on a mobile terminal. The system's main controller responds to the selection signal sent by the mobile terminal's touchscreen, assigns the corresponding personnel according to the configuration list of standby vehicles, and loads them into the data list of the interior attack monitoring interface.

[0028] In sub-step S220, the initial full-load pressure of the air respirator corresponding to the combat personnel is obtained. The system extracts the initial pressure data of each corresponding personnel before entering the field from the basic information database and renders the initial pressure data in the corresponding attribute column of the attack personnel interface.

[0029] In sub-step S230, a timer is started and the theoretically predicted remaining pressure value is output. The mobile terminal receives a physical or virtual trigger signal when the start button on the inside attack interface is pressed. The system processor starts the timer module based on the trigger signal and the clock frequency of the underlying chip. The system analyzes the data collected in the early stage and displays the remaining air volume of each inside attack personnel's breathing apparatus in real time. In the initial monitoring phase without human intervention, the remaining air volume of the breathing apparatus rendered by the system user interface is the theoretically predicted remaining pressure calculated and output based on historical data mentioned above.

[0030] Step S300 involves receiving manually queried data from the actual operation, performing dynamic adaptive compensation calculations, and reconstructing the predicted attenuation curve. Step S300 specifically includes sub-steps S310 to S340.

[0031] In sub-step S310, terminal correction commands are captured and operational characteristic parameters are extracted. The safety officer continuously inquires about the air respirator pressure of on-site personnel and synchronizes the data correction within the system. The system control process listens for changes in the remaining pressure input area on the attacker's interface. When a valid input action is detected, the system extracts the correction time point corresponding to the confirmation button's trigger action. Simultaneously, the system processing unit extracts and stores the actual remaining pressure value entered by the safety officer via the input device.

[0032] In sub-step S320, the system processing unit calculates the actual average consumption rate of the corresponding firefighter during the statistical interval from entry to the correction time node based on the stored actual remaining pressure value and correction time node. The actual average consumption rate is obtained by dividing the difference between the initial full load pressure and the actual remaining pressure value by the correction time node.

[0033] In sub-step S330, the system processing unit extracts the theoretical average consumption rate derived from the integral of the theoretical pressure consumption rate function within the time interval from entry to correction. The system processing unit calculates the ratio of the actual average consumption rate to the theoretical average consumption rate, generating a dimensionless dynamic compensation coefficient. The dynamic compensation coefficient is used to quantitatively characterize the deviation caused by the high temperature conditions at the fire scene on the physiological respiratory rate of on-site personnel.

[0034] In sub-step S340, nonlinear compensation reconstruction of the predicted attenuation curve is performed. During the process monitoring phase after the correction time node, the system applies dynamic compensation coefficients to nonlinearly scale and adjust the theoretical pressure consumption rate function, reconstructs and outputs the actual predicted residual pressure. The reconstructed actual predicted residual pressure is obtained by subtracting the integral value of the adjusted theoretical pressure consumption rate function from the actual residual pressure value. After completing the above reconstruction operation, the display driver layer of the mobile terminal switches the display data source channel, and the interface stops displaying the theoretical predicted residual pressure, seamlessly outputting the calculated actual predicted residual pressure.

[0035] Step S400 involves monitoring the actual predicted remaining pressure, triggering a critical value warning, and performing model data accumulation and optimization. Step S400 specifically includes sub-steps S410 and S420.

[0036] In sub-step S410, threshold monitoring and judgment are performed. The system processing unit logically compares the dynamically calculated actual predicted residual pressure with the preset alarm critical pressure value in the memory according to the set detection frequency. When the actual predicted residual pressure drops to the 8MPa critical value, the system will automatically trigger an alarm. The safety officer must immediately remind personnel to evacuate. The alarm triggering actions include the background color of the control terminal application interface turning red and flashing brightly as a warning, and sending an alarm signal to the speaker module for sound beeping.

[0037] In sub-step S420, practical application data feedback optimization is performed. After a single firefighting evacuation and mission completion record, the cloud server archives the corrected time node array and the corresponding actual remaining pressure value array generated by this mission in the storage medium. The system optimizes the algorithm model by continuously accumulating practical data. The system marks the archived data as the latest training samples and inputs them into the fitting algorithm module. Based on this, the cloud server adjusts the weight coefficient configuration in the theoretical pressure consumption rate function for the corresponding individual, thereby completing the closed-loop data flow.

[0038] The system executes sub-step S110 to obtain basic information and historical consumption data of firefighters, specifically including steps S111 to S114.

[0039] Step S111: Perform routine equipment inspection and air volume scanning and uploading. The fire department sets fixed time slots daily, explicitly requiring firefighters to conduct comprehensive inspections of personal protective equipment (PPE) and breathing apparatus (BPA). To achieve this comprehensive inspection, PPE specifically includes helmets and protective suits. Firefighters conduct the inspection by checking each item and confirming each step. After inspection, they must promptly scan the QR code to upload the BPA's air volume, forming a closed-loop management system for inspection, recording, and uploading. The process of scanning and parsing the QR code using a mobile terminal can be implemented using standard image acquisition modules and decoding algorithms by those skilled in the art. The process of scanning the QR code with a mobile terminal for QR code parsing and binding to the physical device is well-known technology in this field and will not be elaborated upon here.

[0040] Step S112: Acquire and input static characteristic data of firefighters. The system provides a data acquisition and input interface. After the safety officer enters the system, they select the acquisition and input module. The system receives the operation instruction to add a new row of data in the acquisition and input module. In response to the operation instruction to add a new row of data, the system adds a blank row to the data list on the interface and automatically generates the corresponding data sequence number. The system receives the firefighter characteristic attributes entered by the input device. The above characteristic attributes specifically include position, name, age, and blood type. The system uses the above position, name, age, and blood type as the physiological benchmark data for subsequent implementation of differentiated oxygen consumption warning.

[0041] Step S113: Acquire and input multi-stage air respirator consumption time data. The system receives the input air respirator pressure value in the corresponding row of the data acquisition interface. The system simultaneously receives and records the specific time taken by the corresponding firefighter in different pressure drop intervals during historical testing. The historical consumption time data acquired by the system specifically covers the time taken to consume 5 MPa, 10 MPa, 15 MPa, and 20 MPa. The data entered by the system also includes the remaining 8 MPa available time and the time from alarm onwards until the remaining pressure is exhausted. These time recording parameters are used to characterize the physical energy consumption characteristics of the corresponding individual firefighter.

[0042] Step S114: Save and synchronize basic multidimensional data. After completing the full entry of personnel information and test time data for the corresponding team / station, the system receives the operation instruction to save this table. The system's underlying data processing module performs a structured binding between the static feature data obtained in step S112 and the multi-stage consumption time data obtained in step S113. To achieve the above structured binding, the system uses the data sequence number automatically generated in step S112 as a unique identifier primary key to associate the corresponding firefighter static feature data with the multi-stage consumption time data of the air respirator. The system uploads the above structured bound dataset to a relational database on the cloud server for persistent storage via a network communication interface.

[0043] The system executes sub-step S120 to establish the theoretical stress consumption rate function at the individual level. Establishing the theoretical stress consumption rate function at the individual level specifically includes steps S121 to S123.

[0044] Step S121: Extract and preprocess discrete consumption data. The cloud server retrieves historical consumption time data for the corresponding firefighters from a relational database. The system maps and extracts the endpoints of discrete pressure drop intervals (5MPa, 10MPa, 15MPa, and 20MPa) to the corresponding specific time parameters. The cloud server extracts the above mapping relationship and constructs a discrete data point set containing time independent variables and pressure dependent variables. To improve model accuracy, the system removes anomalous jump data from the discrete data point set. For the specific algorithms for data outlier removal and cleaning, those skilled in the art can use the Laida criterion or the isolated forest algorithm. Outlier data processing is a well-known technology in this field and will not be elaborated here.

[0045] Step S122: Perform curve fitting calculations to establish a continuous theoretical pressure consumption rate function. The fitting algorithm module on the cloud server receives the preprocessed discrete data point set. The system calls the mathematical operation library and uses the least squares method to perform polynomial regression fitting on the discrete data point set, thereby constructing the continuous theoretical pressure consumption rate function corresponding to the individual firefighter. In the theoretical pressure consumption rate function, For continuous-time variables used in integral calculations, the units of these variables must be consistent with the units of the time parameters acquired during the data acquisition and input phase. Theoretical pressure consumption rate function. It reflects the instantaneous rate of change of the pressure of a firefighter's breathing apparatus as it continuously decreases over time under normal test conditions.

[0046] Step S123: Construct the theoretical prediction logic for calculating residual pressure. The system is based on the established theoretical pressure consumption rate function. Defined as the theoretically predicted residual pressure under conditions unaffected by external high temperatures and high-intensity operations in a fire scene. The system acquires the initial full-load pressure of the air respirator worn by firefighters. The system sets the duration variable recorded by the timer after the start of the practical mission to [value]. Theoretical prediction of residual pressure The pressure is calculated by integrating the initial full-load pressure of the breathing apparatus over the duration of combat, minus the theoretical pressure consumption rate function. The formula for calculating the theoretically predicted residual pressure is as follows: In the above calculation formula, The baseline gas volume state characterizing the starting point of a combat mission, the integral term Used for quantification calculations over time The total gas consumption is based on historical benchmarks. The theoretical pressure consumption rate function is obtained by fitting a polynomial regression equation to the cloud server. Find the definite integral to obtain the duration. The corresponding integral calculation value. The system will calculate and output the theoretically predicted residual pressure. Write it into the running memory as the initial baseline parameter for triggering dynamic adaptive compensation calculation during the subsequent dispatch process.

[0047] The system executes sub-step S210 to receive the personnel grouping instructions sent by the terminal device, specifically including steps S211 to S213.

[0048] Step S211: The mobile terminal loads and displays the team / station personnel information list. The mobile terminal receives data filtering or sorting instructions input by the user. Specifically, the data filtering instructions are generated by capturing text keywords entered by the user through the search input box on the mobile terminal interface, while the data sorting instructions are generated by capturing the user's touch clicks on the header of the data list. Based on the aforementioned data filtering or sorting instructions, the system main controller outputs a list of firefighter data containing standby vehicles, positions, and names on the team / station personnel management interface. The data processing logic for sorting and filtering list items on the mobile terminal interface can be implemented using standard query statements from relational databases by those skilled in the art. The data processing logic for conditional filtering is well-known in the field and will not be elaborated upon here.

[0049] Step S212: Capture the checkmark operation signal of the participating personnel. The mobile terminal receives the checkmark operation signal input by the user through the touch screen. The mobile terminal's processor listens for touch events of the checkmark controls configured at the front of each data row in the firefighter data list. When the checkmark control is active and selected, the mobile terminal's processor extracts the firefighter's unique identification code bound to the corresponding data row of the checkmark control and stores the extracted unique identification code in the pending allocation queue of the mobile terminal's running memory. Data association is established by extracting the unique identification code to avoid data overlap and confusion caused by searching based on text names.

[0050] Step S213: Trigger and issue the personnel grouping instruction. The mobile terminal responds to the touch signal of the task allocation trigger control configured in the user interface. The task allocation trigger control is specifically the task allocation button control configured in the mobile terminal interface. The mobile terminal encapsulates the unique identification codes of all firefighters in the queue to be assigned, generates the personnel grouping instruction, and sends the personnel grouping instruction to the system main controller. Based on the personnel grouping instruction, the system main controller creates an independent interior attack monitoring task process in memory and loads the corresponding firefighter attribute data in the queue to be assigned into the data list of the independently generated interior attack personnel interface.

[0051] The system executes sub-step S220 to obtain the initial full-load pressure of the air respirator corresponding to the combat personnel, specifically including steps S221 to S222.

[0052] Step S221: Extract operational initialization environment parameters. The system main controller parses the personnel grouping instructions, using the firefighter's unique identification code contained in the instructions as the data retrieval keyword. The system main controller queries and extracts the initial air respirator pressure data entered and bound to the corresponding firefighter before entry from the relational database on the cloud server by calling a preset data interface. The system main controller assigns the extracted initial air respirator pressure data to the initial full-load pressure variable in the memory space of the current task process, recording it as the initial full-load pressure. .

[0053] Step S222: Display the initial full-load pressure value. The mobile terminal's display driver module reads the initial full-load pressure from the system's main controller memory space. The display driver module will initially be under full load pressure. The system environment data initialization for the internal attack monitoring task is now complete, and the corresponding personnel data row in the internal attack personnel interface is displayed in the attribute column.

[0054] The system executes sub-step S230 to start the timer and output the theoretically predicted remaining pressure value, specifically including steps S231 to S233.

[0055] Step S231: Capture the trigger signal and start the underlying timekeeping module. The mobile terminal receives the trigger signal from the timing control control in the interface of the attacker. The timing control control is specifically the start button control configured in the data row of the mobile terminal interface. The processor of the mobile terminal captures the touch press event of the start button control and generates a timing trigger command. The processor of the mobile terminal responds to the timing trigger command and calls the system clock interface of the underlying operating system to start the local timekeeping module. The timekeeping module accumulates the count in seconds, generating and outputting the duration variable of the combat mission in real time. The specific implementation method for time synchronization and process timing by calling the system clock interface of the underlying operating system can be achieved by those skilled in the art using standard system application programming interface function calls. System clock calls are well-known technologies in this field and will not be elaborated here.

[0056] Step S232: Synchronously calculate the theoretically predicted residual pressure. The system main controller calculates the duration variable in real time based on the timing module. The numerical calculation process for theoretically predicted remaining pressure is executed in the running memory. The system's main controller retrieves the initial full-load pressure recorded in the memory space. And call the corresponding theoretical pressure consumption rate function. The system processor, through its built-in arithmetic logic unit, uses the duration variable output by the timing module. The upper limit of integration is given by the theoretical pressure consumption rate function. The cumulative gas consumption is obtained by performing a definite integral. The system processor uses the initial full-load pressure. Subtracting the cumulative gas consumption, the theoretically predicted remaining pressure at the current moment is obtained. The calculated theoretical prediction of residual pressure will be used. Write it to the dynamic cache.

[0057] Step S233: Map and display the remaining air volume of the air respirator. The display driver module of the mobile terminal establishes a data reading channel with the dynamic buffer of the system main controller. The display driver module periodically reads the updated theoretically predicted remaining pressure from the dynamic buffer according to a preset screen refresh rate. The display driver module formats the read values ​​into text characters with a specified number of decimal places and maps these text characters to the corresponding remaining air volume value box on the internal personnel's interface. In the initial monitoring phase, before receiving external manual intervention to correct data, the system interface dynamically outputs the remaining air volume value of the breathing apparatus, which is equivalent to the theoretically predicted remaining pressure. .

[0058] The system executes sub-step S310 to capture terminal correction instructions and extract practical feature parameters, specifically including steps S311 to S313.

[0059] Step S311: Capture manual interaction correction instructions. During the inside attack operation, the safety officer inquires about the actual pressure of the on-site firefighters' breathing apparatus via communication equipment. The safety officer enters the actual pressure value into the remaining pressure input box in the corresponding data row of the inside attack personnel interface on the mobile terminal. The mobile terminal's processor listens for changes in the remaining pressure input box value and confirmation trigger events. Confirmation trigger events specifically include the input box losing focus or a click event on the virtual keyboard's Enter key. When the mobile terminal's processor detects a confirmation trigger event, it determines that a manual interaction correction instruction has been received.

[0060] Step S312: Extract the correction time node. The mobile terminal's processor responds to the manual interaction correction command by calling the data interface of the timekeeping module. The mobile terminal's processor obtains the cumulative running time from the start of the timekeeping module to the moment the manual interaction correction command is received. The mobile terminal's processor assigns the cumulative running time to the time parameter variable in memory, recording it as the correction time node. Correcting time nodes A time parameter used to characterize the time of status confirmation during actual operation.

[0061] Step S313: Extract the actual remaining pressure value. The mobile terminal's processor reads the text string data from the corresponding remaining pressure input box. The mobile terminal's processor calls a data type conversion function to convert the text string data into a floating-point number format. The mobile terminal's processor assigns the converted floating-point number format data to the pressure parameter variable and records it as the actual remaining pressure value. The mobile terminal's processor will correct the timing. Compared with the actual residual pressure value Practical feature parameter data pairs are formed and written into the dynamic buffer of the system's main controller to provide input parameters for subsequent dynamic compensation calculations. The logic for listening to mobile terminal interface control events and handling data type conversions can be implemented using standard front-end development frameworks and system functions by those skilled in the art. Interface event listening and data type conversion are well-known technologies in this field and will not be elaborated upon here.

[0062] The system executes sub-step S320 to calculate the actual average consumption rate for the corresponding firefighter. The system main controller reads the initial full-load pressure stored in the dynamic buffer. Actual residual pressure value and the timeline for correction The system's main controller calculates the initial full-load pressure using its built-in arithmetic logic unit. Compared with the actual residual pressure value The difference between the values ​​indicates the time elapsed from the firefighters' arrival to the corrected time point. The actual total gas consumption within the interval. The system main controller divides the actual total gas consumption by the correction time point. To obtain the actual average consumption rate Actual average consumption rate The calculation formula is: In the above calculation formula, This parameter is used to characterize the actual gas consumption rate of firefighters in current combat environments.

[0063] The system executes sub-step S330 to extract the theoretical average consumption rate and generate dynamic compensation coefficients, specifically including steps S331 and S332.

[0064] Step S331: Calculate the theoretical average consumption rate. The system's main controller extracts the theoretical pressure consumption rate function for the corresponding individual firefighter. The system's main controller invokes a numerical integration algorithm to correct the timing points. The upper limit of integration is given by the theoretical pressure consumption rate function. By performing definite integrals, the time from entry to correction can be obtained. The theoretical cumulative gas consumption within the interval. The system main controller divides the theoretical cumulative gas consumption by the correction time node. The theoretical average consumption rate was obtained. Theoretical average consumption rate The calculation formula is: In the above calculation formula, A parameter used to characterize the expected average gas consumption rate under conditions unaffected by external fire environment.

[0065] Step S332: Calculate and generate dynamic compensation coefficients. The system main controller extracts the actual average consumption rate from the dynamic buffer. Compared with the theoretical average consumption rate The system's main controller calculates the actual average consumption rate using a division operation unit. Compared with the theoretical average consumption rate The ratio of the two values ​​is used to generate dynamic compensation coefficients. Dynamic compensation coefficient The calculation formula is: Dynamic compensation coefficient This is used to quantify the deviation caused by actual high temperature and high-intensity working conditions on firefighters' physiological breathing rate. The system's main controller will generate dynamic compensation coefficients. The data is written into the running memory as a control variable to trigger the nonlinear reconstruction of the predicted decay curve, and provides basic parameters for the reconstruction of the predicted decay curve.

[0066] The system executes sub-step S340 to perform nonlinear compensation reconstruction of the predicted attenuation curve, specifically including steps S341 to S343.

[0067] Step S341: Extract nonlinear reconstruction parameters. The system main controller reads the dynamic compensation coefficients from the running memory. and theoretical pressure consumption rate function The system's main controller synchronously extracts the correction time nodes recorded in the dynamic buffer. Compared with the actual residual pressure value The system's main controller will use the extracted parameters as the basis for subsequent dynamic cumulative gas consumption reconstruction.

[0068] Step S342, reconstruct the actual predicted residual pressure. In the duration variable... Greater than the correction time node During the monitoring phase, the system's main controller invokes a numerical integration algorithm to correct the time points. As the lower limit of integration, with duration as the variable The upper limit of integration is given by the theoretical pressure consumption rate function. Perform definite integral calculation. The system's main controller will then compare the calculated integral value with the dynamic compensation coefficients. Multiplying, we get the result at... to Reconfiguration gas consumption within the interval. The system main controller uses the actual remaining pressure value. Subtracting the gas consumption for reconfiguration, the actual predicted remaining pressure at the current moment is obtained. Actual forecast of remaining pressure The calculation formula is: In the above calculation formula, Used to characterize the expected remaining air volume of an air respirator after calibration with real-world data.

[0069] Step S343: Switch the display data source. The mobile terminal's display driver module establishes communication with the system main controller's dynamic buffer. The mobile terminal's display driver module responds to the reconstruction completion control signal and terminates the reading operation of the theoretical predicted remaining pressure. The display driver module then establishes communication with the actual predicted remaining pressure. The memory address read channel. The display driver module will read the actual predicted remaining pressure. The data is converted to text characters and mapped to the corresponding remaining air volume value box on the internal attack personnel's interface. When a manual correction command is received again during subsequent operations, the system's main controller extracts the latest actual remaining pressure value and correction time point, overwriting the data in the dynamic cache. and The process then cycles through steps S341 to S343. For the update and rendering mechanism of data displayed on the mobile terminal interface, those skilled in the art can implement it using standard front-end development frameworks and data binding logic. Two-way data binding and refresh rendering are well-known technologies in this field and will not be elaborated upon here.

[0070] The system executes sub-step S410 to perform threshold monitoring and determination, specifically including steps S411 and S412.

[0071] Step S411: Perform a threshold comparison between the actual predicted remaining pressure and the actual pressure. The system main controller acquires the preset alarm critical pressure value stored in the memory. According to fire safety regulations, the alarm critical pressure value is... The pressure is set to 8 MPa. The system's main controller, according to the set clock detection frequency, extracts the dynamically calculated actual predicted residual pressure from the running memory at the current moment. The system's main controller invokes a comparison command to compare the actual predicted remaining pressure. alarm critical pressure value A logical comparison of the numerical values ​​is performed. The system's main controller determines the actual predicted remaining pressure through this logical comparison. Is it less than or equal to the alarm critical pressure value? .

[0072] Step S412: Trigger an alarm and issue an evacuation prompt. When the system main controller determines the actual predicted remaining pressure... Less than or equal to the alarm critical pressure value At that time, the system's main controller generates an alarm trigger command and sends it to the mobile terminal. The mobile terminal's display driver module receives the alarm trigger command, calls operating system instructions to control the background color of the corresponding personnel data row in the mobile terminal's application interface to turn red, and executes a highlighting and flashing warning action, outputting a visual alarm signal. The mobile terminal's processor synchronously sends a level signal to the speaker module, controlling the speaker module to output a buzzer broadcast at a specified frequency, outputting an auditory alarm signal. The safety officer receives the aforementioned visual and auditory alarm prompts through the mobile terminal and issues a voice command to evacuate the fire scene to the corresponding personnel via communication equipment. The processing logic for the mobile terminal interface color rendering control and speaker audio driving can be implemented by those skilled in the art using standard front-end user interface component libraries and system audio interface functions. Interface color rendering and audio driving are well-known technologies in the field and will not be elaborated upon here.

[0073] The system executes sub-step S420 to perform practical application data feedback optimization, specifically including steps S421 to S423.

[0074] Step S421: Pack and archive the practical correction data. After a single fire drill mission concludes, the mobile terminal's processor receives the mission completion command input from the user interface. The mobile terminal's processor then extracts all correction time nodes recorded in the dynamic cache during the mission process. Corresponding actual residual pressure value The mobile terminal's processor will use the extracted correction time points. Compared with the actual residual pressure value The data is packaged into a live-fire data array. The mobile terminal sends the live-fire data array to the cloud server via a communication interface. The cloud server receives the live-fire data array and stores it in the storage area of ​​the relational database corresponding to the firefighter's unique identification code.

[0075] Step S422: Construct an updated set of discrete data points containing real-world feedback features. The fitting algorithm module on the cloud server receives the data update trigger signal. The cloud server retrieves the initial set of discrete data points from the relational database, consisting of the original historical consumption time data of the corresponding firefighters. The cloud server extracts the corrected time nodes from the latest archived real-world data array. Compared with the actual residual pressure value The cloud server will extract the actual remaining pressure value. and the corresponding correction time points Mapping the data to real-world feature data points according to the same data dimension, and adding the real-world feature data points as new sample nodes to the initial discrete data point set, and integrating them to generate an updated discrete data point set.

[0076] Step S423: Iteratively calculate and update the theoretical stress consumption rate function. The cloud server calls the fitting algorithm module and uses the least squares method to re-fit the updated discrete data point set with polynomial regression. Based on the refitted calculation results, the cloud server adjusts the theoretical stress consumption rate function for the corresponding individual firefighter. The polynomial weighting coefficients in the equation. The cloud server will update the theoretical pressure consumption rate function with the updated weighting coefficients. The data is overwritten to the relational database. In subsequent real-world task processes, the system's main controller reads and calls the updated theoretical pressure consumption rate function. The calculation of the theoretically predicted residual pressure is performed. For the data appending to the database and the iterative calculation logic of the least squares method, those skilled in the art can implement it using standard database operation statements and mathematical calculation libraries. Incremental database writing and polynomial regression iterative calculations are well-known techniques in this field and will not be elaborated upon here.

[0077] The firefighter breathing apparatus (BBA) capacity prediction system based on dynamic pressure compensation operates on a hardware architecture that includes mobile terminals and cloud servers. The system comprises: a basic data acquisition and model building module, a combat mission initialization and monitoring startup module, a dynamic adaptive compensation calculation module, and a critical value early warning and model optimization module.

[0078] The basic data acquisition and model building module is used to execute step S100 of the above method. This module acquires basic information and historical consumption time data of firefighters. It extracts the historical consumption time data to construct a discrete data point set. Finally, it uses the least squares method to perform polynomial regression fitting on the discrete data point set to establish a continuous theoretical pressure consumption rate function for each individual firefighter. The basic data acquisition and model building module is based on the theoretical pressure consumption rate function. Establish the calculation logic for theoretically predicted residual pressure under conditions unaffected by external environment. To avoid redundancy in the formulas in the instruction manual, the theoretically predicted residual pressure... For specific calculation formulas, please refer to the above method implementation examples. The theoretical prediction of residual pressure... The initial full load pressure of the air respirator Subtracting the theoretical pressure consumption rate function variable with duration The integral value is calculated.

[0079] The combat mission initialization and monitoring startup module is used to execute step S200 of the above method. The combat mission initialization and monitoring startup module receives the personnel grouping instruction sent by the mobile terminal and retrieves the initial full-load pressure of the corresponding air respirator for each personnel from the relational database. The practical task initialization and monitoring startup module responds to the trigger signal of the timing control control to start the timer module. The practical task initialization and monitoring startup module is based on the duration variable output by the timer module. , with duration variable The upper limit of integration is a function of the theoretical pressure consumption rate. By performing definite integrals, the theoretically predicted residual pressure at the current moment can be obtained. The practical task initialization and monitoring startup module controls the display driver module of the mobile terminal to theoretically predict the remaining pressure. The mapping is displayed on the interface for internal attackers.

[0080] The dynamic adaptive compensation calculation module is used to execute step S300 of the above method. The dynamic adaptive compensation calculation module listens for numerical change events from the mobile terminal to capture manual interaction correction commands. The dynamic adaptive compensation calculation module extracts the corresponding correction time node triggered by the confirmation action. Compared with the actual residual pressure value input The dynamic adaptive compensation solution module calculates the initial full-load pressure. Compared with the actual residual pressure value The difference is divided by the correction time point. The actual average consumption rate is then obtained. The dynamic adaptive compensation solution module calls a numerical integration algorithm to calculate the theoretical pressure consumption rate function. Perform definite integral calculation and divide by the corrected time node. The theoretical average consumption rate is then derived. The dynamic adaptive compensation solution module calculates the ratio of the actual average consumption rate to the theoretical average consumption rate, generating a dynamic compensation coefficient. The dynamic adaptive compensation solution module applies dynamic compensation coefficients. Combined with actual residual pressure values Perform integral reconstruction calculations and output the actual predicted residual pressure. Actual forecast of remaining pressure The reconstruction calculation formula is described in the above method embodiment. The actual predicted residual pressure... Based on actual residual pressure values Deducting dynamic compensation coefficient With respect to the theoretical pressure consumption rate function The product of the integral values ​​is used for calculation. The dynamic adaptive compensation solution module generates a display data source switching command, controlling the mobile terminal to stop displaying the theoretical predicted residual pressure and instead display the actual predicted residual pressure calculated by the reconstructed solution. .

[0081] The critical value early warning and model optimization module is used to execute step S400 of the above method. The critical value early warning and model optimization module extracts the preset alarm critical pressure value. The critical value early warning and model optimization module will actually predict the remaining pressure. alarm critical pressure value Perform a logical comparison. When the actual predicted remaining pressure... Less than or equal to the alarm critical pressure value At that time, the critical value early warning and model optimization module generates an alarm trigger command, controlling the mobile terminal to output visual and auditory alarm signals. The critical value early warning and model optimization module extracts the correction time points generated from a single firefighting operation. Compared with the actual residual pressure value The timeline will be corrected. Compared with the actual residual pressure value The mapping is encapsulated into practical feature data points. The critical value warning and model optimization module adds the practical feature data points to the initial discrete data point set and calls the fitting algorithm module to iteratively recalculate the theoretical pressure consumption rate function. The polynomial weighting coefficients in the text. For the encapsulation of program code for each functional module and the system call logic, those skilled in the art can use object-oriented programming languages ​​and standard software engineering layered architectures to implement them. The encapsulation of software functional modules and object interface calls are well-known technologies in this field and will not be elaborated upon here.

[0082] Embodiments of the present invention also provide an electronic device and a computer-readable storage medium for implementing the above-described method for predicting the remaining capacity of firefighters' breathing apparatus based on dynamic pressure compensation.

[0083] The electronic device is specifically the mobile terminal or cloud server described in the preceding embodiments. The electronic device includes a processor, a memory, a communication interface, and a communication bus. The processor, memory, and communication interface are electrically connected and transmit data through the communication bus.

[0084] Memory is used to store at least one computer program. Memory specifically includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and the computer program. Internal memory provides a data caching environment for the operation of the operating system and computer program stored in the non-volatile storage media. Memory may specifically be random access memory, read-only memory, flash memory, or solid-state drive.

[0085] The processor is used to call and execute computer programs stored in memory. Specifically, the processor may be a central processing unit, microprocessor, digital signal processor, or application-specific integrated circuit (ASIC). When the processor executes the aforementioned computer program, it implements steps S100 to S400 in the aforementioned method for predicting the remaining capacity of firefighters' breathing apparatus based on dynamic pressure compensation. By executing the logical instructions contained in the computer program, the processor calls the arithmetic logic unit and memory to complete the calculation and control operations of acquiring basic data, establishing a theoretical consumption attenuation model, initializing the practical task, calculating the dynamic compensation coefficient, reconstructing the predicted attenuation curve, and monitoring the actual predicted remaining pressure to trigger an early warning.

[0086] The communication interface is used to establish a data interaction channel with an external data acquisition terminal or external server. The communication interface receives the air volume data of the air respirator uploaded by the data acquisition terminal and sends alarm signals to the external speaker module. For the data transmission protocol of the communication bus and the communication protocol of the communication interface, those skilled in the art can use standard peripheral component interconnect bus standards and transmission control protocols. Bus data transmission and interface network control are well-known technologies in the field and will not be elaborated further here.

[0087] Embodiments of the present invention also provide a computer-readable storage medium. The computer-readable storage medium stores computer-executable program instructions. When the computer-executable program instructions are read and executed by the processor, they implement the steps in the above-described method for predicting the remaining capacity of a firefighter's self-contained breathing apparatus based on dynamic pressure compensation. Specifically, the computer-readable storage medium may be a non-volatile medium such as a USB flash drive, portable hard drive, read-only optical disc, or magnetic disk.

[0088] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for predicting the remaining capacity of firefighters' self-contained breathing apparatus based on dynamic pressure compensation, characterized in that, Includes the following steps: Obtain basic information and historical consumption time data of firefighters, establish the theoretical pressure consumption rate function of the corresponding firefighters based on the historical consumption time data, and establish the calculation logic of theoretical predicted residual pressure based on the theoretical pressure consumption rate function. Receive the command to organize the combat personnel, obtain the initial full load pressure of the corresponding air breathing apparatus of the combat personnel, start the time timing module to obtain the duration variable, and calculate and display the theoretically predicted remaining pressure at the current moment based on the theoretically predicted remaining pressure calculation logic and the duration variable. Capture human interaction correction commands, extract the correction time node and actual remaining pressure value corresponding to the human interaction correction commands, calculate and generate dynamic compensation coefficients based on the initial full load pressure, actual remaining pressure value, correction time node and theoretical pressure consumption rate function, and apply the dynamic compensation coefficients to reconstruct and calculate the actual predicted remaining pressure, control the mobile terminal to stop displaying the theoretical predicted remaining pressure and display the actual predicted remaining pressure. The system performs a comparison between the actual predicted residual pressure and the alarm critical pressure value. When the actual predicted residual pressure is less than or equal to the alarm critical pressure value, an alarm signal is output. After the fire-fighting mission is completed, the system extracts the correction time point and the actual residual pressure value to update the theoretical pressure consumption rate function.

2. The method for predicting the remaining capacity of firefighters' self-contained breathing apparatus based on dynamic pressure compensation according to claim 1, characterized in that, Obtain basic information and historical consumption time data of firefighters, establish a theoretical pressure consumption rate function for each firefighter based on the historical consumption time data, and establish the calculation logic for theoretically predicted residual pressure based on the theoretical pressure consumption rate function, including: Extract the discrete pressure drop interval endpoints and corresponding specific time parameters from the historical consumption time data to construct a discrete data point set containing time independent variables and pressure dependent variables; A multinomial regression fitting algorithm was used to fit the discrete data point set to establish a function of the theoretical pressure consumption rate corresponding to the firefighter's continuous data. The theoretically predicted residual pressure is set as the initial full-load pressure of the air respirator minus the integral value of the theoretical pressure consumption rate function over the duration of actual combat, forming the calculation logic for the theoretically predicted residual pressure.

3. The method for predicting the remaining capacity of firefighters' self-contained breathing apparatus based on dynamic pressure compensation according to claim 1, characterized in that, The theoretically predicted residual pressure is calculated and displayed at the current moment based on the calculation logic of theoretically predicted residual pressure and the duration variable, including: Using the duration variable output by the timer module as the upper limit of integration, the theoretical pressure consumption rate function is solved by definite integral to obtain the cumulative gas consumption value. By subtracting the cumulative gas consumption from the initial full-load pressure, the theoretical predicted remaining pressure at the current moment is obtained; The theoretically predicted remaining pressure at the current moment is converted into text characters, and the text characters are mapped and displayed in the remaining gas volume value box on the mobile terminal's internal personnel interface.

4. The method for predicting the remaining capacity of firefighters' self-contained breathing apparatus based on dynamic pressure compensation according to claim 1, characterized in that, Dynamic compensation coefficients are generated based on the initial full-load pressure, actual remaining pressure values, correction time points, and the theoretical pressure consumption rate function, including: Calculate the difference between the initial full-load pressure and the actual remaining pressure, and divide the difference by the correction time point to obtain the actual average consumption rate. Using the correction time node as the upper limit of integration, the theoretical pressure consumption rate function is solved by definite integral to obtain the theoretical cumulative gas consumption. The theoretical cumulative gas consumption is then divided by the correction time node to obtain the theoretical average consumption rate. Calculate the ratio of the actual average consumption rate to the theoretical average consumption rate to generate a dynamic compensation coefficient.

5. The method for predicting the remaining capacity of a firefighter's self-contained breathing apparatus based on dynamic pressure compensation according to claim 4, characterized in that, The actual predicted residual pressure is reconstructed and calculated using dynamic compensation coefficients, including: During the monitoring phase when the duration variable output by the time timing module is greater than the correction time node, the theoretical pressure consumption rate function is solved by definite integral with the correction time node as the lower limit of integration and the duration variable as the upper limit of integration to obtain the integral calculation value. Multiply the integral calculation value by the dynamic compensation coefficient to obtain the reconstructed gas consumption; The actual predicted remaining pressure is obtained by subtracting the reconstructed gas consumption from the actual remaining pressure value.

6. The method for predicting the remaining capacity of firefighters' self-contained breathing apparatus based on dynamic pressure compensation according to claim 1, characterized in that, When the actual predicted residual pressure is less than or equal to the alarm critical pressure value, an alarm signal is output, including: Generate an alarm trigger command and send it to the mobile terminal; The background color of the corresponding personnel data row in the mobile terminal application interface is turned red and a highlighting and flashing warning action is performed, outputting a visual alarm signal; The speaker module is controlled to output a sound beeping announcement in a specified frequency band, and an auditory alarm signal is output.

7. The method for predicting the remaining capacity of a firefighter's self-contained breathing apparatus based on dynamic pressure compensation according to claim 1, characterized in that, After the firefighting operation is completed, the theoretical pressure consumption rate function is updated by extracting the corrected time points and the actual remaining pressure values, including: Extract the correction time points and corresponding actual remaining pressure values ​​recorded in fire-fighting operations, and map the actual remaining pressure values ​​and corresponding correction time points into operational feature data points according to the data dimensions of time independent variable and pressure dependent variable. Add the actual feature data points as new sample nodes to the discrete data point set, and integrate them to generate an updated discrete data point set; The polynomial regression fitting algorithm is used to refit the curve of the updated discrete data point set, and the polynomial weight coefficients in the theoretical pressure consumption rate function are updated.

8. The method for predicting the remaining capacity of a firefighter's self-contained breathing apparatus based on dynamic pressure compensation according to claim 1, characterized in that, Receive personnel grouping instructions and obtain the initial full-load pressure of the corresponding air respirator for each personnel, including: Listen for touch events of checkboxes in the firefighter data list, extract the unique identification code of the firefighter bound to the corresponding data row of the checkbox and store it in the queue to be assigned; In response to the touch signal of the task assignment button control, the unique identification code of the firefighter in the queue to be assigned is encapsulated into data to generate the personnel grouping instruction; Using the unique identification code of the firefighters contained in the personnel grouping instructions as the data retrieval keyword, the initial full load pressure of the air breathing apparatus bound to the corresponding firefighter is queried and extracted.

9. The method for predicting the remaining capacity of a firefighter's self-contained breathing apparatus based on dynamic pressure compensation according to claim 2, characterized in that, Before applying the multinomial regression fitting algorithm to fit the discrete data point set to a curve, the process also includes: extracting and removing abnormal jump data from the discrete data point set.

10. The firefighter breathing apparatus reserve prediction system based on dynamic pressure compensation according to any one of claims 1-9, characterized in that, include: The basic data acquisition and model building module is configured to acquire basic information and historical consumption time data of firefighters, establish the theoretical pressure consumption rate function of the corresponding firefighters based on the historical consumption time data, and establish the theoretical prediction of residual pressure calculation logic based on the theoretical pressure consumption rate function. The combat mission initialization and monitoring startup module is configured to receive the personnel grouping instruction, obtain the initial full load pressure of the corresponding air breathing apparatus of the personnel, start the time timing module to obtain the duration variable, and calculate and display the theoretically predicted remaining pressure at the current moment based on the theoretically predicted remaining pressure calculation logic and the duration variable. The dynamic adaptive compensation calculation module is configured to capture manual interaction correction commands, extract the correction time node and actual remaining pressure value corresponding to the manual interaction correction commands, calculate and generate dynamic compensation coefficients based on the initial full load pressure, actual remaining pressure value, correction time node and theoretical pressure consumption rate function, and apply the dynamic compensation coefficients to reconstruct and calculate the actual predicted remaining pressure, and control the mobile terminal to stop displaying the theoretical predicted remaining pressure and display the actual predicted remaining pressure. The critical value early warning and model optimization module is configured to perform a comparison operation between the actual predicted residual pressure and the alarm critical pressure value. When the actual predicted residual pressure is less than or equal to the alarm critical pressure value, an alarm signal is output. After the fire-fighting mission is completed, the module extracts the correction time node and the actual residual pressure value to update the theoretical pressure consumption rate function.

Images