Optimization reconstruction method and device of existing building fire fighting system based on internet of things state monitoring and intelligent linkage control

Abstract

The application discloses a method and device for optimizing and reforming an existing building fire-fighting system based on internet of things state monitoring and intelligent linkage control, and relates to the technical field of intelligent fire fighting. The method deploys internet of things terminals at fire-fighting pipe networks and electrical nodes, synchronously collects optical scattering maps, temperature rise gradients, steady-state micro-pressure fluctuation sequences and transient residual power supply loads to construct a characteristic matrix. The micro-pressure fluctuation sequences are analyzed and converted into optical distortion compensation factors to filter out the light intensity scattering interference caused by pipe network micro-leakage water vapor, and the temperature rise gradient is used to determine a fire and generate a fire source node coordinate and a hot air flow spreading vector. Then, the transient residual power supply load of the associated defense area is extracted, the power supply timing is adjusted within the safe bearing capacity, and a linkage control instruction set containing power-off load reduction and timing round start array is generated. The instructions are issued and the transient pressure building slope is collected at a high frequency during execution, non-linear pressure loss characteristics are identified through feature matching, valve sticking is determined and bypass compensation water supply is triggered.

Description

Technical Field

[0001] This invention relates to the field of intelligent fire protection technology, specifically to a method and device for optimizing and upgrading existing building fire protection systems based on Internet of Things (IoT) status monitoring and intelligent linkage control. Background Technology

[0002] Existing buildings commonly face issues such as aging pipe networks and declining electrical system capacity in their internal fire protection facilities during long-term operation. With the advancement of urban renewal, utilizing modern Internet of Things (IoT) technology to intelligently upgrade the fire protection systems of older buildings has become an important way to improve the overall fire safety level of buildings. Society's fire safety standards for residential and public commercial spaces are constantly increasing, requiring buildings to achieve digitalization and precision in fire early warning and coordinated response without altering the original main structure.

[0003] However, in actual operation and renovation scenarios, aging pipe networks often exhibit microscopic leaks. The resulting water droplet aerosols can easily cause scattering interference with conventional optical smoke detectors, leading to normal environmental fluctuations being misinterpreted as fire alarms. Simultaneously, existing linkage control methods typically activate all smoke exhaust fans and fire pumps in the corresponding fire zone concurrently after fire alarm confirmation. However, the transformer power supply capacity of existing aging buildings is often small, and the instantaneous concurrent inrush current can easily cause overload tripping of the power supply bus, resulting in a global power outage. Furthermore, aging mechanical valves are prone to jamming after years of inactivity. Existing technologies cannot dynamically monitor pressure buildup when executing linkage commands. Once mechanical valve jamming causes localized pipe network depressurization, the entire terminal will be unable to deliver water normally. Therefore, it is still necessary to provide a method for optimizing and renovating existing building fire protection systems based on IoT status monitoring and intelligent linkage control to improve the identification accuracy, power grid operation stability, and fire extinguishing pipe network water supply reliability after fire protection system renovation. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide a method and apparatus for optimizing and retrofitting existing building fire protection systems based on Internet of Things status monitoring and intelligent linkage control to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for optimizing and upgrading existing building fire protection systems based on IoT status monitoring and intelligent linkage control, comprising the following steps: S1, deploying IoT terminals in the existing building fire protection pipe network and electrical nodes, synchronously collecting optical scattering spectra, temperature rise gradients, steady-state micro-pressure fluctuation sequences of the pipe network, and transient remaining power supply load of the power supply bus in the monitoring area, aligning the data based on sampling time and node coordinates, and constructing a building infrastructure feature matrix; S2, extracting the steady-state micro-pressure fluctuation sequences from the building infrastructure feature matrix, analyzing the water vapor leakage frequency of the pipe network and converting it into an optical distortion compensation factor; mapping the optical distortion compensation factor to the optical scattering spectra, filtering out the light intensity scattering interference components caused by water vapor leakage in the pipe network, and combining the temperature rise gradient to analyze the fire situation. S3. Based on the fire source node coordinates, extract the transient remaining power supply load of the associated defense zone from the building infrastructure feature matrix; adjust the power supply sequence of the defense zone nodes within the safe carrying capacity of the transient remaining power supply load along the direction of the thermal airflow spread vector, and generate a linkage control command set including the power outage and load reduction command of the non-fire defense zone and the fire pump valve timing rotation array of the fire defense zone; S4. Issue the linkage control command set, and collect the transient pressure build-up slope of the pipeline network at high frequency during the execution of the timing rotation array; perform feature matching between the transient pressure build-up slope and the baseline pressure build-up response envelope, and determine that the associated valve has mechanically jammed in response to the nonlinear pressure loss characteristics that exceed the tolerance range of the transient pressure build-up slope, generate a valve isolation mark and trigger the bypass compensation water supply command of the adjacent pipeline network.

[0006] In a preferred embodiment, the specific process of deploying IoT terminals in existing building fire protection pipe networks and electrical nodes to synchronously collect optical scattering spectra, temperature rise gradients, steady-state micro-pressure fluctuation sequences of the pipe network, and transient residual power supply load of the power supply bus is as follows: Configure spatial sensing nodes containing multi-wavelength photoelectric emission and reception links and thermistor arrays to obtain the light intensity distribution characteristics under different scattering angles to generate optical scattering spectra; extract the absolute values ​​of ambient temperature at different time periods and convert them into spatial temperature change rates to generate temperature rise gradients; attach piezoelectric acoustic emission transducers to the outer wall of the fire protection pipe network to capture the acoustic envelope signals generated by the micro-oscillations of the fluid inside the pipe network to generate steady-state micro-pressure fluctuation sequences; connect non-intrusive Hall current transformers in series on the bus side of the floor distribution box to read the difference margin between the active power capacity extreme value and the real-time operating power load to extract the transient residual power supply load.

[0007] In a preferred embodiment, the specific process of constructing a building infrastructure feature matrix based on data alignment using sampling time and node coordinates is as follows: extracting the timestamps of optical scattering spectrum, temperature rise gradient, steady-state micro-pressure fluctuation sequence, and transient remaining power supply load; performing interpolation resampling processing to unify the sampling frequency and generating a synchronous feature data stream; obtaining the physical installation elevation and planar parameters of each acquisition node and converting them into node coordinates; and splicing the synchronous feature data stream and node coordinates to generate a building infrastructure feature matrix with node coordinates as row indexes, time reference as column indexes, and synchronous feature data streams as elements.

[0008] In a preferred embodiment, the specific process of extracting the steady-state micro-pressure fluctuation sequence from the feature matrix of building infrastructure, analyzing the water vapor leakage frequency of the pipeline network, and converting it into an optical distortion compensation factor is as follows: Perform discrete wavelet transform on the steady-state micro-pressure fluctuation sequence in the feature matrix of building infrastructure to separate the high-frequency micro-seismic feature band; extract the envelope peak amplitude and central oscillation frequency in the high-frequency micro-seismic feature band, map them to a preset water droplet size distribution table to retrieve the spatial water vapor retention density parameter; calculate the transmission attenuation coefficient and diffuse reflection increment of the beam under the spatial water vapor retention density parameter, and combine the transmission attenuation coefficient and diffuse reflection increment to form an optical distortion compensation factor.

[0009] In a preferred embodiment, the process of mapping the optical distortion compensation factor to the optical scattering spectrum, filtering out the light intensity scattering interference component caused by water vapor leakage in the pipeline network, and combining the temperature rise gradient to determine the fire event, and generating the fire source node coordinates and the thermal flow propagation vector is as follows: Based on the optical distortion compensation factor, the optical scattering spectrum is baseline-compensated and separated to obtain the smoke particle scattering component; the smoke particle scattering component and the temperature rise gradient are input into the joint threshold judgment condition, and the joint threshold judgment condition is triggered synchronously in response to the smoke particle scattering component and the temperature rise gradient, and it is judged as a fire event; the node coordinates of the maximum extreme point corresponding to the triggering joint threshold judgment condition are extracted and set as the fire source node coordinates; the spatial directional derivative is solved based on the temperature rise gradient set of the associated defense zones around the fire source node coordinates, and the thermal flow propagation vector along the direction of the maximum temperature change rate is output.

[0010] In a preferred embodiment, the specific process of extracting the transient remaining power supply load of the associated defense zone from the building infrastructure feature matrix based on the fire source node coordinates is as follows: extract the fire source node coordinates, delineate the physical boundary between the fire defense zone and the non-fire defense zone based on the node coordinates contained in the building infrastructure feature matrix; map the physical boundary between the fire defense zone and the non-fire defense zone to the electrical wiring topology, and locate the power supply bus node index of the associated defense zone; retrieve the operating power load and active power capacity extreme value under the corresponding time reference in the building infrastructure feature matrix through the power supply bus node index, and extract the difference margin between the operating power load and the active power capacity extreme value as the transient remaining power supply load.

[0011] In a preferred embodiment, the specific process of adjusting the power supply sequence of the zone nodes within the safe carrying capacity of the transient remaining power supply load along the direction of the hot airflow spread vector, and generating a linkage control instruction set including the power-off and load reduction command for non-fire zones and the timing rotation array of fire pump valves in the fire zone, is as follows: The hot airflow spread vector and node coordinates are subjected to spatial geometric projection to construct a fire spread hazard sequence for the surrounding associated zones; the rated starting inrush flow parameters of the fire pump valves in the fire zone are extracted; in response to the peak value of the rated starting inrush flow parameter envelope exceeding the transient remaining power supply load, the control route of the commercial electrical nodes in the non-fire zones is extracted to generate the power-off and load reduction command; the compensation power supply load margin released after the execution of the power-off and load reduction command is obtained; based on the fire spread hazard sequence of the associated zones, staggered start timestamps are allocated to the fire pump valves in the fire zone to construct a timing rotation array; and the power-off and load reduction command and the timing rotation array are combined to generate a linkage control instruction set.

[0012] In a preferred embodiment, a set of linkage control instructions is issued, and the transient pressure build-up slope of the pipeline network is collected at high frequency during the execution of the time-series start-up array. The transient pressure build-up slope is matched with the reference pressure build-up response envelope. In response to the transient pressure build-up slope exhibiting nonlinear pressure loss characteristics exceeding the tolerance range, it is determined that the associated valve has mechanically jammed, a valve isolation mark is generated, and a bypass compensation water supply command for the adjacent pipeline network is triggered. The specific process is as follows: A level trigger signal is issued to the corresponding electrical node according to the linkage control instruction set, and the high-frequency sampling mode of the pipeline network pressure monitoring node is activated synchronously. The transient pressure build-up slope is obtained by fitting the discrete points of the time-series pressure. The preset reference pressure build-up response envelope of the valve under normal opening is retrieved, and dynamic time warping matching of the transient pressure build-up slope and the reference pressure build-up response envelope is performed. In response to the matching trajectory deviating from the lower limit tolerance boundary of the reference pressure build-up response envelope and exhibiting nonlinear pressure loss characteristics with second derivative decay, the topological coordinates of the associated electrical node are locked to generate a valve isolation mark. The pipeline network connectivity topology map is retrieved to search for parallel water circuit control nodes that cross the valve isolation mark, and a bypass compensation water supply command is generated.

[0013] An optimization and renovation device for existing building fire protection systems based on IoT status monitoring and intelligent linkage control is used to execute the aforementioned optimization and renovation method for existing building fire protection systems based on IoT status monitoring and intelligent linkage control. The device includes: a matrix construction unit, used to deploy IoT terminals in the existing building's fire protection pipe network and electrical nodes, synchronously collecting optical scattering spectra, temperature rise gradients, steady-state micro-pressure fluctuation sequences of the pipe network, and transient remaining power supply load of the power supply bus in the monitoring area; data alignment based on sampling time and node coordinates to construct a building infrastructure feature matrix; a fire situation determination unit, used to extract the steady-state micro-pressure fluctuation sequence from the building infrastructure feature matrix, analyze the pipe network water vapor leakage frequency and convert it into an optical distortion compensation factor; mapping the optical distortion compensation factor to the optical scattering spectrum, filtering out light intensity scattering interference components caused by micro-leaking water vapor in the pipe network, and combining... The system uses a temperature rise gradient to determine fire events and generates fire source node coordinates and a hot air spread vector. An instruction generation unit extracts the transient remaining power supply load of associated defense zones from the building infrastructure feature matrix based on the fire source node coordinates. Along the hot air spread vector direction, it adjusts the power supply sequence of defense zone nodes within the safe carrying capacity of the transient remaining power supply load, generating a set of linkage control instructions including power outage and load reduction instructions for non-fire defense zones and a sequential start-up array for fire pumps and valves in the fire defense zone. A fault diagnosis unit issues the linkage control instruction set and collects the transient pressure build-up slope of the pipeline network at high frequency during the execution of the sequential start-up array. It performs feature matching between the transient pressure build-up slope and the baseline pressure build-up response envelope. If the transient pressure build-up slope exhibits nonlinear pressure loss characteristics exceeding the tolerance range, it determines that the associated valves are mechanically stuck, generates a valve isolation flag, and triggers a bypass compensation water supply instruction for the adjacent pipeline network.

[0014] The technical effects and advantages of this invention are as follows:

[0015] (1) An optimization and renovation method for existing building fire protection systems based on IoT status monitoring and intelligent linkage control. During the monitoring and sensing phase, optical scattering spectra, temperature rise gradients, steady-state micro-pressure fluctuation sequences of the pipeline network, and transient remaining power supply loads are collected simultaneously, and the data are aligned in the spatiotemporal dimensions to construct a feature matrix of building infrastructure. Subsequently, the frequency of water vapor leakage in the pipeline network is analyzed using the micro-pressure fluctuation sequence, converted into an optical distortion compensation factor and mapped onto the optical scattering spectra. The light intensity scattering interference component caused by water vapor leakage in the pipeline network is filtered out, and then combined with the temperature rise gradient to complete the determination of fire events and extraction of spread vectors. As a result, the problem of frequent false alarms of optical sensing devices caused by water vapor leakage in old pipeline networks in the existing technology can be improved, and the accuracy of fire identification and the accuracy of locating the real fire source in complex environments can be improved.

[0016] (2) An optimization and renovation device for existing building fire protection systems based on IoT status monitoring and intelligent linkage control adjusts the power supply sequence of the zone nodes within the safe carrying capacity limit during the linkage execution phase, according to the transient remaining power supply load of the surrounding defense zones based on the coordinates of the fire source node. This generates control commands that include power outage and load reduction in non-fire defense zones and sequential start-up of fire pumps and valves in fire defense zones. During the execution of the commands, the transient pressure build-up slope of the pipeline network is collected at high frequency and matched with the feature of the reference pressure build-up response envelope. The valve is judged to be stuck and the bypass compensation water supply is triggered when the nonlinear pressure loss characteristics are presented. Thus, the problem that existing full-scale concurrent linkage is prone to power supply overload tripping in old buildings can be solved, and dynamic fault-tolerant diagnosis and water supply route switching are implemented when mechanical failure occurs in the valve, ensuring the reliable operation of fire protection facilities under physical constraints.

[0017] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0018] Figure 1 This is a flowchart of the method for optimizing and retrofitting existing building fire protection systems based on Internet of Things status monitoring and intelligent linkage control, according to the present invention.

[0019] Figure 2 This is a schematic diagram comparing the trends of optical distortion filtering and fire situation determination in an embodiment of the present invention;

[0020] Figure 3 This is a timing diagram of asymmetric linkage control under transient load-limited conditions in an embodiment of the present invention;

[0021] Figure 4 This is a flowchart of the existing building fire protection system optimization and renovation device based on Internet of Things status monitoring and intelligent linkage control according to the present invention. Detailed Implementation

[0022] This application provides a method and device for optimizing and upgrading existing building fire protection systems based on IoT status monitoring and intelligent linkage control. This method and device solves the problems of frequent false alarms caused by environmental water vapor interference and failure of linkage water supply due to insufficient infrastructure carrying capacity during the renovation of existing building fire protection systems.

[0023] The overall approach of the scheme in this application embodiment is as follows: First, IoT terminals are deployed at existing building fire protection pipe networks and electrical nodes to collect optical scattering spectra, temperature rise gradients, steady-state micro-pressure fluctuation sequences, and transient remaining power supply loads for data alignment, thereby constructing a building infrastructure feature matrix. Second, the micro-pressure fluctuation sequences are analyzed to extract pipe network leakage characteristics, and compensation factors are generated to filter out interference from the optical scattering spectra. The coordinates of the fire source node and the thermal flow propagation vector are confirmed by combining the temperature rise gradient. Next, the remaining power supply load of the associated defense zone is extracted, and within the carrying capacity, the power outage and load reduction of non-fire defense zones and the timing wheel start-up of fire pumps and valves are planned to generate a linkage control command set. Finally, the control command set is issued, and the transient pressure build-up slope of the pipe network is collected at high frequency. By matching the features of the baseline pressure build-up response envelope, the nonlinear pressure loss characteristics caused by valve mechanical jamming are identified, and isolation markers and bypass compensation water supply commands are triggered.

[0024] Example 1; please refer to Figure 1 This invention provides a technical solution: a method for optimizing and upgrading existing building fire protection systems based on IoT status monitoring and intelligent linkage control, comprising the following steps: S1, deploying IoT terminals in the existing building fire protection pipe network and electrical nodes, synchronously collecting optical scattering spectra, temperature rise gradients, steady-state micro-pressure fluctuation sequences of the pipe network, and transient remaining power supply load of the power supply bus in the monitoring area, aligning the data based on sampling time and node coordinates, and constructing a building infrastructure feature matrix; S2, extracting the steady-state micro-pressure fluctuation sequences from the building infrastructure feature matrix, analyzing the water vapor leakage frequency of the pipe network and converting it into an optical distortion compensation factor; mapping the optical distortion compensation factor to the optical scattering spectra, filtering out the light intensity scattering interference components caused by water vapor leakage in the pipe network, and combining the temperature rise gradient to determine fire events. S3. Based on the fire source node coordinates, extract the transient remaining power supply load of the associated defense zone from the building infrastructure feature matrix; adjust the power supply sequence of the defense zone nodes within the safe carrying capacity of the transient remaining power supply load along the direction of the thermal airflow spread vector, and generate a linkage control command set including the power outage and load reduction command of the non-fire defense zone and the fire pump valve timing rotation array of the fire defense zone; S4. Issue the linkage control command set, and collect the transient pressure build-up slope of the pipeline network at high frequency during the execution of the timing rotation array; perform feature matching between the transient pressure build-up slope and the reference pressure build-up response envelope, and determine that the associated valve has mechanically jammed in response to the transient pressure build-up slope showing a nonlinear pressure loss characteristic exceeding the tolerance range, generate a valve isolation mark and trigger the bypass compensation water supply command of the adjacent pipeline network.

[0025] In this implementation plan, step S1 is used to complete the multi-dimensional perception and spatiotemporal synchronous integration of underlying physical operation data. After installing sensors on the pipes and electrical circuits of the existing building, the system will simultaneously acquire optical scattering spectra reflecting the concentration of air particles, temperature rise gradient reflecting the rate of change of ambient temperature, steady-state micro-pressure fluctuation sequence reflecting the small pressure changes inside the water pipes under normal conditions, and transient remaining power load reflecting how much equipment the power grid can still support. After collecting these parameters, the system uses the timestamp of the acquisition and the three-dimensional spatial coordinates of the sensors to align and fuse the scattered physical data to construct a feature matrix of the building infrastructure. Among them, the optical scattering spectra refer to the spatial distribution mapping of the intensity of light beam scattering by airborne suspended particles at different angles; the steady-state micro-pressure fluctuation sequence refers to the continuous discrete pressure values ​​of the internal fluid of the fire water pipe network under non-spraying conditions due to small disturbances; and the transient remaining power load refers to the safe power reserve that can be immediately used after subtracting the real-time operating load from the current total rated capacity of the distribution box.

[0026] Step S2 is used to remove physical interference from existing old building environments and to achieve spatial location and trend prediction of fire sources. The system extracts water pipe pressure change data from the building infrastructure feature matrix, calculates the frequency of water vapor leakage reflecting leaks in hidden parts of the pipe network, and converts it into an optical distortion compensation factor. This parameter is superimposed on the data collected by the optical sensor to remove false smoke concentration values ​​caused by the refraction of tiny water droplets in the air. Then, it is combined with the temperature rise gradient to confirm whether a fire has occurred and calculate the precise location of the ignition point and the direction of fire spread. The optical distortion compensation factor is a numerical calibration parameter set to eliminate the abnormal refraction and attenuation of light of a specific wavelength caused by water droplet aerosols; the heat flow spread vector is a three-dimensional spatial direction vector reflecting the highest dimension of heat diffusion, which is solved by using the difference in temperature rise gradients of multiple temperature measurement points in space.

[0027] Step S3 is used to formulate an asymmetric fire-fighting linkage strategy to prevent overload under the objective physical condition of limited power supply capacity in old buildings. The system extracts the available power reserves of surrounding fire compartments based on the calculated fire source coordinates, and calculates how much starting current the power grid can still withstand along the direction of fire spread. To prevent the tripping of old transformers due to the simultaneous start-up of all pumps and fans, the system plans to cut off non-essential commercial power to non-fired areas to release power, and schedules the sequential start-up of fire-fighting equipment in the fire area, combining these into a complete set of linkage control instructions. The safe carrying capacity refers to the maximum power load that the power grid can provide without triggering a short circuit or overload protection switch tripping in the power supply circuit; the time-sequential start-up array refers to a scheduling data structure that staggers the start-up trigger commands of multiple high-power fire-fighting devices on the time axis to avoid the superposition of surge currents generated by concurrent device start-up.

[0028] Step S4 is used to perform physical-level closed-loop verification of the fire linkage command execution process and water circuit fault-tolerant switching under mechanical failure conditions. The system issues pre-arranged commands to the equipment, and during the sequential startup of the equipment, it measures the rate of pressure rise inside the fire water pipe at high frequency and compares it with the theoretical pressure rise range that the equipment should have under normal operation. When it is found that the pressure rise trajectory deviates from the theoretical range and shows an abnormal drop trend, the system determines that the corresponding mechanical valve is rusted and stuck, and then isolates the faulty valve in the topology diagram and starts the backup pipeline control node to supply water. The transient pressure build-up slope refers to the rate of increase of the fluid pressure inside the pipeline network per unit time after the fire pump starts or the valve is opened; the reference pressure build-up response envelope refers to the set of upper and lower limit tolerance boundaries of the pipeline network pressure change over time under normal operating conditions, which is pre-set according to the fluid dynamics characteristics; the nonlinear pressure loss characteristic refers to the irregular pressure drop pattern in which the pipeline network pressure deviates from the normal rise curve and shows a second derivative decay during the pressure build-up stage.

[0029] Specifically, the process of deploying IoT terminals in existing building fire protection pipe networks and electrical nodes to synchronously collect optical scattering spectra, temperature rise gradients, steady-state micro-pressure fluctuation sequences of the pipe network, and transient remaining power supply load of the power supply bus is as follows: Configure spatial sensing nodes containing multi-wavelength photoelectric emission and reception links and thermistor arrays to obtain the light intensity distribution characteristics under different scattering angles to generate optical scattering spectra; extract the absolute values ​​of ambient temperature at different time periods and convert them into spatial temperature change rates to generate temperature rise gradients; attach piezoelectric acoustic emission transducers to the outer wall of the fire protection pipe network to capture the acoustic envelope signals generated by the micro-oscillations of the fluid inside the pipe network to generate steady-state micro-pressure fluctuation sequences; connect non-intrusive Hall current transformers in series on the bus side of the floor distribution box to read the difference margin between the active power capacity extreme value and the real-time operating power load to extract the transient remaining power supply load.

[0030] In this implementation scheme, for the multidimensional physical data acquired by the spatial sensing nodes, the underlying microprocessor reads the electrical signals of the thermistor array cycle by cycle, and uses the formula... Calculate the temperature gradient, where Indicates the temperature gradient; Indicates a time period; This indicates the total number of resistive elements in the thermistor array; The counting designation indicating the resistor element; Indicates the first Attenuation coefficient of spatial distance between resistive elements; Indicates the current sampling time; Indicates the first A resistive element at time... The absolute value of the collected ambient temperature. The formula is used for the spatial distance attenuation coefficient mentioned above. Confirmed, among which Indicates the first The physical Euclidean distance from each resistive element to the geometric center of the array; This represents the thermal diffusion reference constant for the monitored area. For the transient residual power supply load on the distribution box side, the system controls a non-intrusive Hall current transformer to sample at high frequency and integrate at the underlying hardware level, according to the formula... Extract the specific values, among which Indicates the transient remaining power supply load; This indicates the extreme value of the active power capacity of the distribution busbar; Represent the integral infinitesimal variable; Integral infinitesimal variable The real-time operating loop current obtained below; Integral infinitesimal variable The real-time operating phase voltage is obtained. As for the optical scattering spectrum and steady-state micro-voltage fluctuation sequence, the conversion from analog physical signals to discrete numerical characteristics and local buffering are directly completed by the modulation and demodulation module of the photoelectric transmitter-receiver link and the analog-to-digital converter array of the piezoelectric acoustic emission transducer, respectively.

[0031] Specifically, the process of constructing a building infrastructure feature matrix based on data alignment using sampling time and node coordinates is as follows: extract timestamps from optical scattering spectra, temperature rise gradients, steady-state micro-pressure fluctuation sequences, and transient remaining power supply loads; perform interpolation and resampling to unify the sampling frequency and generate a synchronous feature data stream; obtain the physical installation elevation and planar parameters of each acquisition node and convert them into node coordinates; and concatenate the synchronous feature data stream and node coordinates to generate a building infrastructure feature matrix with node coordinates as row indices, time reference as column indices, and synchronous feature data streams as elements.

[0032] In this implementation scheme, due to the asynchronous sampling characteristics of various heterogeneous sensors in terminals, data alignment requires first extracting timestamps and then performing interpolation resampling processing. The central processing unit uses a formula... Unified sampling frequency, where Indicates a unified time base Synchronous characteristic data stream; This represents the total number of original sampling points within the truncation window; m represents the step index of the original sampling points. Indicates the original timestamp The corresponding sensor reads the original value; This represents the time step interval corresponding to the target resampling frequency. Subsequently, the absolute spatial coordinates of each acquisition node are analyzed, a tensor space is dynamically allocated in the pre-allocated memory stack, and fixed-point concatenation of the data streams is performed. This matrix concatenation process follows the formula... Construct multidimensional feature elements, where The feature matrix of building infrastructure is represented in the first... Row node coordinate index and the first Feature fusion value at the column time base index; This indicates the modal category identifier covering optics, temperature, pressure, and electricity; This represents the normalized weight coefficients for the corresponding modal sequence; Indicates the first The mode in the th ... Line and number The actual arrangement value of the synchronization feature data stream at the column intersection. The above normalized weight coefficients are calculated using the formula... Confirmed, among which Indicates the first time within the historical sliding time window Information entropy evaluation index obtained by calculating the discreteness of numerical fluctuations in each modality; This represents the accumulated loop variable used to iterate through the feature modes.

[0033] Specifically, the process of extracting the steady-state micro-pressure fluctuation sequence from the feature matrix of building infrastructure, analyzing the water vapor leakage frequency of the pipeline network, and converting it into an optical distortion compensation factor is as follows: Perform discrete wavelet transform on the steady-state micro-pressure fluctuation sequence in the feature matrix of building infrastructure to separate the high-frequency micro-seismic feature band; extract the envelope peak amplitude and central oscillation frequency in the high-frequency micro-seismic feature band, map them to a preset water droplet size distribution table to retrieve the spatial water vapor retention density parameter; calculate the transmission attenuation coefficient and diffuse reflection increment of the beam under the spatial water vapor retention density parameter, and combine the transmission attenuation coefficient and diffuse reflection increment to form the optical distortion compensation factor.

[0034] In this implementation scheme, the central processing unit performs discrete wavelet transform on the collected steady-state micro-pressure fluctuation sequence to separate low-frequency background interference and extract the envelope peak amplitude and central oscillation frequency within the high-frequency micro-seismic characteristic band. Using a preset fluid mapping model, the formula... Solve for the space water vapor residence density parameter, where This represents the space water vapor residence density parameter; The empirical coefficient representing the acoustic attenuation of the pipe material; This represents the peak envelope amplitude within the characteristic band of high-frequency microseismic activity. Indicates the central oscillation frequency; This represents the reference frequency of the fluid at standard atmospheric pressure. Subsequently, based on the physical mechanism of particle scattering, it is expressed using the formula... Calculate the transmission attenuation coefficient and use the formula Calculate the diffuse reflection increment, where Indicates the transmission attenuation coefficient; The extinction cross-sectional area constant represents the area of ​​light emitted during a specific measurement wavelength range; This indicates the effective penetration test distance of the light beam inside the sensing node; Indicates the diffuse reflection increment; The scattering constant is related to the refractive index of the surrounding air; x represents the nonlinear volume scattering distribution index. Finally, the two are combined using the formula... The optical distortion compensation factor is constituted, among which Indicates the optical distortion compensation factor; This represents the transmission attenuation compensation constant; This represents the diffuse reflection increment compensation constant; the above two compensation constants are determined through a dynamic normalization method, and the calculation process is as follows: and .

[0035] Specifically, the process of mapping the optical distortion compensation factor to the optical scattering spectrum, filtering out the light intensity scattering interference components caused by water vapor leakage in the pipeline network, and combining the temperature rise gradient to determine the fire event, and generating the coordinates of the fire source node and the thermal flow spread vector is as follows: Based on the optical distortion compensation factor, the optical scattering spectrum is baseline-compensated and separated to obtain the smoke particle scattering component; the smoke particle scattering component and the temperature rise gradient are input into the joint threshold judgment condition, and the joint threshold judgment condition is triggered synchronously in response to the smoke particle scattering component and the temperature rise gradient, and it is judged as a fire event; the node coordinates of the maximum extreme point corresponding to the triggering joint threshold judgment condition are extracted and set as the fire source node coordinates; the spatial directional derivative is solved based on the temperature rise gradient set of the associated defense zones around the fire source node coordinates, and the thermal flow spread vector along the direction of the maximum temperature change rate is output.

[0036] In this implementation scheme, to address environmental moisture interference in the optical scattering spectrum, the underlying logic controller performs baseline compensation based on an optical distortion compensation factor, using the formula... The scattering component of smoke particles was separated, among which Indicates the scattering component of smoke particles; This represents the raw light intensity scattering measurement value received by the sensor; This represents the optical distortion compensation factor generated in the previous step; This represents the pre-calibrated baseline light intensity value under an ideal environment with no smoke or water vapor. Subsequently, the smoke particle scattering component and the temperature rise gradient are simultaneously input into the joint judgment logic, and the result is determined using the formula... Assess the extreme values ​​of fire detection characteristics in the current space, among which This represents the feature value used to determine the joint threshold. This represents the scattering gain coefficient that matches the volume of the building's defense zone. This represents the thermodynamic gain coefficient that matches the thermal capacity properties of the environment. This represents the temperature rise gradient input extracted from the monitoring area. When the characteristic value continuously exceeds the critical lower limit and reaches its maximum extreme value, the corresponding absolute coordinates are locked and set as the coordinates of the fire source node; this critical lower limit is determined by the formula... Confirmed, among which This indicates the lower limit of the joint threshold; The safety margin coefficient represents the degree of hardware sensitivity; This represents the background statistical variance of light intensity fluctuations during historically safe periods. After confirming the fire source coordinates, spatial directional derivative analysis is performed based on the temperature distribution array of the surrounding defense zones, using the formula... Output hot airflow spread vector, where The vector represents the spread of hot air currents; g represents the traversal increment of the surrounding associated defense zones. This indicates the total number of surrounding associated defense zones involved in the calculation; This represents the local temperature rise gradient parameter of the g-th surrounding defense zone; This represents the extreme temperature rise gradient measured at the coordinates of the fire source node; This represents the three-dimensional spatial displacement vector from the center of the fire source node to the geometric center of the g-th surrounding defense zone; This represents the Euclidean physical distance of the three-dimensional spatial displacement vector. For example... Figure 2 As shown in the figure, the original light intensity measurement value is affected by water droplet aerosols generated by micro-leakage in the pipeline network, exhibiting high-frequency and irregular fluctuations; based on the optical distortion compensation factor obtained from the aforementioned steady-state micro-pressure fluctuation sequence, the system performs baseline separation on the original light intensity, and obtains the smoke particle scattering component ( Figure 2 The smooth curve remained stable in the initial stage, eliminating spurious peak interference caused by water vapor. In response to the occurrence of a fire event, the smoke particle scattering component showed a step-up trend in sync with the temperature rise gradient, eventually exceeding the preset joint threshold lower limit (…). Figure 2 The threshold line in the middle reflects the technical logic of this solution to correct conventional optical sensing and suppress false fire alarms in complex environments by using acoustic features.

[0037] Specifically, the process of extracting the transient remaining power supply load of the associated defense zone from the building infrastructure feature matrix based on the coordinates of the fire source node is as follows: extract the coordinates of the fire source node, delineate the physical boundary between the fire defense zone and the non-fire defense zone based on the node coordinates contained in the building infrastructure feature matrix; map the physical boundary between the fire defense zone and the non-fire defense zone to the electrical wiring topology, and locate the power supply bus node index of the associated defense zone; retrieve the operating power load and active power capacity extreme value under the corresponding time reference in the building infrastructure feature matrix through the power supply bus node index, and extract the difference margin between the operating power load and the active power capacity extreme value as the transient remaining power supply load.

[0038] In this implementation scheme, after obtaining the coordinates of the fire source node, the system's main control unit compares them within a pre-stored 3D building model space to delineate the physical isolation boundary between the fire zone and adjacent non-fire zones. Subsequently, based on the hard-wired connections of the existing building's electrical distribution circuits, this physical boundary is mapped across domains to the electrical topology data table, accurately locating the end transformer and power supply bus node indexes responsible for supplying power to the associated zones. Using this index, power characteristic parameters are retrieved from the building infrastructure feature matrix. Considering the dynamic fluctuation and hysteresis effects of aging equipment in actual operation, the system uses formulas... To perform precise quantification, among which Indicates the transient remaining power supply load; This indicates the extreme value of active power capacity recorded in the transformer file; This indicates the total number of branch circuits connected to the power supply bus; j represents the cycle index of the branch circuit. This represents the real-time operating power load of the j-th branch loop; This represents the load fluctuation compensation coefficient; This represents the load change rate of the j-th branch loop within the current sampling window. For the crucial load fluctuation compensation coefficient in the above calculation, an exponential nonlinear mapping method is adopted, using the formula... Confirmed, among which This represents the load sensitivity adjustment constant, which reflects the impedance attenuation characteristics of old cables, and thus calculates the actual available power margin that the current power grid can directly draw upon without overload tripping.

[0039] Specifically, the process of adjusting the power supply sequence of the defense zone nodes within the safe carrying capacity of the transient remaining power supply load along the direction of the hot air spread vector, and generating a linkage control instruction set including the power-off and load reduction command for non-fire defense zones and the timed rotation array of fire pump valves in the fire defense zone, is as follows: The hot air spread vector and node coordinates are subjected to spatial geometric projection to construct a fire spread hazard sequence for the surrounding associated defense zones; the rated starting inrush flow parameters of the fire pump valves in the fire defense zone are extracted; in response to the peak value of the rated starting inrush flow parameter envelope exceeding the transient remaining power supply load, the control route of the commercial electrical nodes in the non-fire defense zone is extracted to generate the power-off and load reduction command; the compensation power supply load margin released after the execution of the power-off and load reduction command is obtained; based on the fire spread hazard sequence of the associated defense zones, staggered start timestamps are allocated to the fire pump valves in the fire defense zone to construct a timed rotation array; and the power-off and load reduction command and the timed rotation array are combined to generate a linkage control instruction set.

[0040] In this implementation scheme, the scheduling logic unit performs spatial geometric projection of the hot airflow propagation vector and the coordinates of surrounding nodes, using the formula... Construct a fire spread hazard sequence for surrounding related defense zones, among which This indicates the fire spread risk level of the z-th associated defense zone; z represents the logical label of the associated defense zone. Indicates the vector of thermal gas spread; This represents the projected displacement vector from the fire source node to the centroid of the z-th associated defense zone. This represents the absolute Euclidean distance of the projected displacement vector; This represents the spatial barrier attenuation constant. The method for determining the aforementioned spatial barrier attenuation constant is as follows: ,in This indicates the average thickness of the physical partition walls in the associated defense zones. This represents the standard thermal resistance coefficient of the building material. When the rated starting inrush current envelope peak of the fire pump valve in the fire zone exceeds the transient remaining power supply load, the controller immediately issues a power-off and load-reducing command to the commercial lighting and air conditioning distribution boxes in non-fire zones according to the electrical control route. After the power-off action is completed, the system reads the actual released compensation power supply load margin and arranges the fire-fighting equipment in descending order of hazard level, using a formula... Assign staggered start timestamps to fire pump valves within the fire zone, among which This indicates the staggered start-up timestamp of the f-th fire pump valve; f represents the execution sequence number of the fire pump valves after being sorted by hazard level. This indicates the baseline start time for triggering the linkage command; 'a' represents the accumulated step variable. This represents the rated starting inrush envelope peak value of the a-th activated fire pump valve; This represents the transient remaining power supply load calculated in the previous step; This indicates the margin of compensated power supply load released after the power outage and load reduction command is executed; This indicates the allowable baseline surge recovery time interval for existing building electrical busbars; This represents the normalized fire spread hazard level of the zone where the f-th fire pump valve is located. Finally, the power-off and load-reduction commands are combined with the calculated timestamp array to generate a complete set of linkage control commands. For example... Figure 3 As shown in the figure, the horizontal dashed line defines the maximum safe carrying capacity of the target power supply bus. Upon fire alarm triggering and detection of a rated inrush current exceeding the grid load, the system first issues a power-off and load-reduction command, causing a step-down of commercial load in non-fire zones to release compensating power supply load margin. Subsequently, the fire pump and valve arrays in the fire zone are activated sequentially according to the timestamps allocated by the aforementioned time-sequenced array activation. The figure shows that the peak activation values ​​of each pump and valve array are staggered along the time axis. Through this timing control process, the superimposed total system power load is strictly suppressed below the safe carrying capacity dashed line, physically preventing bus overload tripping defects caused by a surge in concurrent inrush current in the aging power grid.

[0041] Specifically, the following process is involved: A linkage control command set is issued, and during the execution of the time-series start-up array, the transient pressure build-up slope of the pipeline network is collected at high frequency. The transient pressure build-up slope is then matched with the baseline pressure build-up response envelope. If the transient pressure build-up slope exhibits nonlinear pressure loss characteristics exceeding the tolerance range, it is determined that the associated valve is mechanically stuck. A valve isolation flag is generated, and a bypass compensation water supply command for the adjacent pipeline network is triggered. The specific process is as follows: A level trigger signal is issued to the corresponding electrical node according to the linkage control command set, simultaneously activating the high-frequency sampling mode of the pipeline network pressure monitoring node. The transient pressure build-up slope is obtained by fitting the discrete points of the time-series pressure. A preset baseline pressure build-up response envelope for normal valve opening is retrieved, and dynamic time warping matching of the transient pressure build-up slope and the baseline pressure build-up response envelope is performed. If the matching trajectory deviates from the lower limit tolerance boundary of the baseline pressure build-up response envelope and exhibits nonlinear pressure loss characteristics with second-order derivative decay, the topological coordinates of the associated electrical node are locked to generate a valve isolation flag. The pipeline network connectivity topology map is retrieved to find parallel water circuit control nodes that cross the valve isolation flag, and a bypass compensation water supply command is generated.

[0042] In this implementation scheme, the system's main control unit sends relay closing level trigger signals to the corresponding electrical nodes according to the linkage control instruction set, and simultaneously controls the pipeline pressure monitoring nodes to enter millisecond-level high-frequency sampling mode. For the extracted time-series pressure discrete points, the system uses the least squares method based on the formula... The transient pressure build-up slope is obtained by fitting, where Indicates the transient pressure build-up slope; This represents the total number of discrete pressure points within a high-frequency sliding time window. A sequence index representing discrete pressure points; Indicates the first The sampling timestamps corresponding to each discrete pressure point; Indicates the first The system obtains real-time pressure values ​​of the pipeline network from discrete pressure points. After acquiring this slope sequence, the system retrieves the preset valve normal opening baseline pressure build-up response envelope and executes a dynamic time warping algorithm to nonlinearly and elastically align the transient pressure build-up slope sequence with the envelope on the time axis to eliminate random phase shifts caused by water hammer effects in aging pipelines. After alignment, the system continuously monitors and compares the trajectory. When the matching result satisfies the formula... When determining the criteria, nonlinear underpressure characteristics are identified, among which... Indicator indicating the result of mechanical jamming of the valve; This represents the real-time transient pressure build-up slope sequence after dynamic time warping and alignment. This represents the lower tolerance boundary of the baseline build-up response envelope; The real-time second derivative of the transient pressure build-up slope represents the characteristic of pipeline pressure build-up acceleration. This represents the critical threshold for second-order derivative decay in determining a mechanical jamming state. Regarding this crucial critical threshold for second-order derivative decay, the system uses the formula... To determine dynamically, where This represents the physical aging correction factor obtained by converting the actual service life of existing building pipe networks with water corrosion levels. Indicates the rated static water pressure of the fire protection design at the end of the pipeline network; This represents the standard operating cycle of a valve of the corresponding diameter from receiving an electrical signal to fully opening mechanically. Once mechanical jamming is detected, indicating that the valve is obstructed by internal corrosion and the pressure rise trend shows physical attenuation, the system immediately locks the topological coordinates of the associated electrical node and generates a valve isolation marker. Subsequently, in the pre-loaded pipeline connectivity topology data structure in memory, a path retrieval algorithm is used to find the upstream parallel water circuit control node that can bypass the isolation marker node, generate the corresponding bypass compensation water supply command and issue the drive to ensure the fire water circuit connectivity in the event of partial valve failure.

[0043] Example 2; please refer to Figure 4 An optimization and renovation device for existing building fire protection systems based on IoT status monitoring and intelligent linkage control is used to execute the optimization and renovation method for existing building fire protection systems based on IoT status monitoring and intelligent linkage control described in the embodiments. The device includes: a matrix construction unit, used to deploy IoT terminals in the existing building fire protection pipe network and electrical nodes, synchronously collecting optical scattering spectra, temperature rise gradients, steady-state micro-pressure fluctuation sequences of the pipe network, and transient remaining power supply load of the power supply bus in the monitoring area; aligning the data based on sampling time and node coordinates to construct a building infrastructure feature matrix; and a fire determination unit, used to extract the steady-state micro-pressure fluctuation sequence from the building infrastructure feature matrix, analyze the water vapor leakage frequency of the pipe network and convert it into an optical distortion compensation factor; mapping the optical distortion compensation factor to the optical scattering spectrum, and filtering out the light intensity scattering interference components caused by water vapor leakage from the pipe network. The system combines temperature rise gradient to determine fire events, generating fire source node coordinates and hot air spread vectors. An instruction generation unit extracts the transient remaining power supply load of associated defense zones from the building infrastructure feature matrix based on the fire source node coordinates. Along the hot air spread vector direction, within the safe carrying capacity of the transient remaining power supply load, it adjusts the power supply sequence of defense zone nodes, generating a set of linkage control instructions including power outage and load reduction instructions for non-fire defense zones and a sequential start-up array for fire pumps and valves in the fire defense zone. A fault diagnosis unit issues the linkage control instruction set and, during the execution of the sequential start-up array, frequently collects the transient pressure build-up slope of the pipeline network. It performs feature matching between the transient pressure build-up slope and the baseline pressure build-up response envelope. Responding to the nonlinear pressure loss characteristics exceeding the tolerance range in response to the transient pressure build-up slope, it determines that the associated valves are mechanically stuck, generates a valve isolation flag, and triggers a bypass compensation water supply instruction for the adjacent pipeline network.

[0044] In this implementation scheme, the matrix construction unit serves as the central hub for acquiring and synchronizing underlying physical data, driving various IoT sensor terminals deployed on existing building pipe networks and electrical nodes. During operation, this unit synchronously receives raw sensing data streams of optical scattering spectra, temperature rise gradients, steady-state micro-pressure fluctuation sequences, and transient remaining power supply loads. Through its built-in central processing unit, it extracts the acquisition timestamps and physical coordinates of the hardware nodes for each input parameter, performs interpolation alignment and spatial topology mapping calculations, and integrates the originally heterogeneous and asynchronous discrete physical sensing signals in the memory stack, outputting a building infrastructure feature matrix with a unified spatiotemporal reference.

[0045] The fire situation determination unit is primarily responsible for the mathematical stripping of environmental interference characteristics and the computational execution of the spatial location of the actual fire source. After acquiring the feature matrix of the building infrastructure, the unit extracts the steady-state micro-pressure fluctuation sequence for frequency domain analysis to lock the frequency of water vapor leakage in the pipeline network, and quantizes it into an optical distortion compensation factor. Subsequently, the unit substitutes the compensation factor into the data sequence of the optical scattering spectrum to perform reverse baseline correction, directly filtering out the interference light intensity component caused by water vapor condensation. Then, the corrected scattering component and the temperature rise gradient are synchronously imported into the joint threshold determination logic matrix to complete the status confirmation and output the absolute coordinates of the fire source node and the thermal gas spread vector.

[0046] The instruction generation unit is responsible for the underlying logic scheduling of the overload prevention asymmetric linkage scheduling strategy under the limited physical power supply capacity of existing old buildings. This unit uses the coordinates of the fire source node output by the fire situation determination unit as a spatial retrieval pointer to retrieve the real-time transient remaining power supply load of the associated defense zone from the feature matrix. During the control logic allocation process, this unit performs calculations along the hazard gradient direction indicated by the thermal airflow spread vector, under the constraint of not exceeding the current rated load limit of the power grid. Finally, it compiles and generates and outputs a set of linkage control instructions that includes instructions to cut off commercial power supply to non-fire defense zones and staggered timestamps for the start-up of fire pumps and valves in the fire defense zone.

[0047] The fault diagnosis unit is a physical control execution module that realizes closed-loop verification of end-point mechanical actions and waterway fault tolerance self-rescue. While issuing linkage control commands to the underlying relays and electrical nodes, this unit forcibly activates the millisecond-level high-frequency sampling mode of the pipeline pressure sensor to continuously record the actual transient pressure build-up slope of the pipeline. Throughout the entire cycle of the time-sequenced array execution, this unit performs dynamic feature matching calculations between the real-time calculated pressure build-up slope and the system's preset benchmark pressure build-up response envelope. Once the calculation result shows that the real-time trajectory deviates from the lower tolerance range and exhibits second-order nonlinear drop decay, the unit immediately determines that the corresponding physical valve has a mechanical jamming fault, generates an isolation flag in the system, and simultaneously invokes the waterway topology to trigger the bypass control node of the adjacent unobstructed pipeline to execute a compensating water supply action.

[0048] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0049] This invention is described with reference to flowchart illustrations and / or block diagrams of systems, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0050] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0051] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0052] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0053] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for optimizing and retrofitting existing building fire protection systems based on Internet of Things (IoT) status monitoring and intelligent linkage control, characterized in that: Includes the following steps: S1. Deploy IoT terminals in existing building fire protection pipe networks and electrical nodes to synchronously collect optical scattering spectra, temperature rise gradients, steady-state micro-pressure fluctuation sequences of the pipe network and transient remaining power supply load of the power supply bus in the monitoring area. Based on sampling time and node coordinates, align the data to construct a feature matrix of building infrastructure. S2. Extract the steady-state micro-pressure fluctuation sequence from the feature matrix of building infrastructure, analyze the frequency of water vapor leakage in the pipeline network and convert it into an optical distortion compensation factor; map the optical distortion compensation factor to the optical scattering spectrum, filter out the light intensity scattering interference component caused by water vapor leakage in the pipeline network, combine the temperature rise gradient to determine the fire event, and generate the coordinates of the fire source node and the thermal airflow spread vector. Using a pre-defined fluid mapping model, through formulas Solve for the space water vapor residence density parameter, where This represents the space water vapor residence density parameter; The empirical coefficient representing the acoustic attenuation of the pipe material; This represents the peak envelope amplitude within the characteristic band of high-frequency microseismic activity. } represents the central oscillation frequency; This represents the reference frequency of the fluid at standard atmospheric pressure; subsequently, based on the physical mechanism of particle scattering, it is expressed by the formula... Calculate the transmission attenuation coefficient and use the formula Calculate the diffuse reflection increment, where Indicates the transmission attenuation coefficient; The extinction cross-sectional area constant represents the area of ​​light emitted during a specific measurement wavelength range; This indicates the effective penetration test distance of the light beam inside the sensing node; Indicates the diffuse reflection increment; The scattering constant is related to the refractive index of the surrounding air; x represents the nonlinear volume scattering distribution index; finally, the two are combined using the formula... The optical distortion compensation factor is constituted, among which Indicates the optical distortion compensation factor; This represents the transmission attenuation compensation constant; This represents the diffuse reflection increment compensation constant; the above two compensation constants are determined through a dynamic normalization method, and the calculation process is as follows: and ; S3. Based on the coordinates of the fire source node, extract the transient remaining power supply load of the associated defense zone from the feature matrix of the building infrastructure; along the direction of the thermal airflow propagation vector, adjust the power supply sequence of the defense zone node within the safe carrying capacity of the transient remaining power supply load, and generate a set of linkage control instructions that includes power off and load reduction instructions for non-fire defense zones and the timing wheel array of fire pump valves in fire defense zones. When the rated starting inrush current envelope peak of the fire pump valve in the fire zone exceeds the transient remaining power supply load, the controller immediately issues a power-off and load-reducing command to the commercial lighting and air conditioning distribution boxes in non-fire zones according to the electrical control route; after the power-off action is completed, the system reads the actual released compensation power supply load margin and arranges the fire-fighting equipment in descending order of hazard level, using a formula... Assign staggered start timestamps to fire pump valves within the fire zone, among which This indicates the staggered start-up timestamp of the f-th fire pump valve; f represents the execution sequence number of the fire pump valves after being sorted by hazard level. This indicates the baseline start time for triggering the linkage command; 'a' represents the accumulated step variable. This represents the rated starting inrush envelope peak value of the a-th activated fire pump valve; This represents the transient remaining power supply load calculated in the previous step; This indicates the margin of compensated power supply load released after the power outage and load reduction command is executed; This indicates the allowable baseline surge recovery time interval for existing building electrical busbars; This represents the normalized fire spread hazard level of the zone where the f-th fire pump valve is located; finally, the power-off and load-reduction command is combined with the calculated timestamp array to generate a complete set of linkage control commands; S4. Issue a set of linkage control instructions and collect the transient pressure build-up slope of the pipeline network at high frequency during the execution of the timing wheel start array; perform feature matching between the transient pressure build-up slope and the reference pressure build-up response envelope; if the transient pressure build-up slope shows nonlinear pressure loss characteristics that exceed the tolerance range, determine that the associated valve has mechanically stuck, generate a valve isolation mark, and trigger the bypass compensation water supply instruction of the adjacent pipeline network. The system's main control unit sends relay closing level trigger signals to the corresponding electrical nodes according to the linkage control instruction set, and simultaneously controls the pipeline pressure monitoring nodes to enter millisecond-level high-frequency sampling mode; for the extracted time-series pressure discrete points, the system uses the least squares method based on the formula The transient pressure build-up slope was obtained through fitting, where... Indicates the transient pressure build-up slope; This represents the total number of discrete pressure points within a high-frequency sliding time window. A sequence index representing discrete pressure points; Indicates the first The sampling timestamps corresponding to each discrete pressure point; Indicates the first The system obtains real-time pressure values ​​of the pipeline network measured at discrete pressure points. After acquiring the slope sequence, the system retrieves the preset valve normal opening baseline pressure build-up response envelope and executes a dynamic time warping algorithm to nonlinearly and elastically align the transient pressure build-up slope sequence with the envelope on the time axis to eliminate random phase shifts caused by water hammer effects in aging pipelines. After alignment, the system continuously monitors and compares the trajectory. When the matching result satisfies the formula... When determining the criteria, nonlinear underpressure characteristics are identified, among which... Indicator indicating the result of mechanical jamming of the valve; This represents the real-time transient pressure build-up slope sequence after dynamic time warping and alignment. This represents the lower tolerance boundary of the baseline build-up response envelope; The real-time second derivative of the transient pressure build-up slope represents the characteristic of pipeline pressure build-up acceleration. This represents the critical threshold for second-order derivative decay in determining a mechanical jamming state; regarding the aforementioned critical threshold for second-order derivative decay, the system uses the formula... To determine dynamically, where This represents the physical aging correction factor obtained by converting the actual service life of existing building pipe networks with water corrosion levels. Indicates the rated static water pressure of the fire protection design at the end of the pipeline network; This indicates the standard operating cycle of a valve of the corresponding diameter from receiving an electrical signal to fully opening mechanically.

2. The method for optimizing and retrofitting existing building fire protection systems based on IoT status monitoring and intelligent linkage control as described in claim 1, characterized in that: The specific process of deploying IoT terminals in existing building fire protection pipe networks and electrical nodes to simultaneously collect optical scattering spectra, temperature rise gradients, steady-state micro-pressure fluctuation sequences of the pipe network, and transient residual power supply load of the power supply bus is as follows: Configure a space sensing node that includes a multi-wavelength photoelectric transmission and reception link and a thermistor array to obtain the light intensity distribution characteristics under different scattering angles to generate an optical scattering spectrum, extract the absolute value of the ambient temperature at different time periods and convert it into the spatial temperature change rate to generate a temperature rise gradient. A piezoelectric acoustic emission transducer is attached to the outer wall of the fire protection pipeline network to capture the acoustic envelope signal generated by the micro-oscillation of the fluid inside the pipeline network and generate a steady-state micro-pressure fluctuation sequence. A non-intrusive Hall current transformer is connected in series on the bus side of the floor distribution box to extract the transient remaining power supply load by reading the difference margin between the extreme value of active power capacity and the real-time operating power load.

3. The method for optimizing and retrofitting existing building fire protection systems based on IoT status monitoring and intelligent linkage control as described in claim 1 or 2, characterized in that: The specific process of constructing the feature matrix of building infrastructure based on data alignment with sampling time and node coordinates is as follows: Extract the timestamps of optical scattering spectrum, temperature rise gradient, steady-state micro-pressure fluctuation sequence and transient remaining power supply load, perform interpolation and resampling processing to unify the sampling frequency, and generate a synchronous feature data stream; Obtain the physical installation elevation and planar parameters of each acquisition node, and convert them into node coordinates; By concatenating the synchronous feature data stream and node coordinates, a building infrastructure feature matrix is ​​generated, with node coordinates as row indices, time base as column indices, and synchronous feature data streams as elements.

4. The method for optimizing and retrofitting existing building fire protection systems based on IoT status monitoring and intelligent linkage control as described in claim 1, characterized in that: The specific process of extracting the steady-state micro-pressure fluctuation sequence from the feature matrix of building infrastructure, analyzing the water vapor leakage frequency of the pipeline network, and converting it into an optical distortion compensation factor is as follows: Perform discrete wavelet transform on the steady-state micro-pressure fluctuation sequence within the characteristic matrix of building infrastructure to separate the high-frequency microseismic characteristic bands; Extract the envelope peak amplitude and central oscillation frequency within the high-frequency microseismic feature band, and map them to a preset water droplet size distribution table to retrieve the spatial water vapor residence density parameter. The transmission attenuation coefficient and diffuse reflection increment of the beam under the spatial water vapor residence density parameter are calculated, and the transmission attenuation coefficient and diffuse reflection increment are combined to form the optical distortion compensation factor.

5. The method for optimizing and retrofitting existing building fire protection systems based on IoT status monitoring and intelligent linkage control as described in claim 1 or 4, characterized in that: The specific process of mapping the optical distortion compensation factor to the optical scattering spectrum, filtering out the light intensity scattering interference component caused by water vapor from micro-leaks in the pipeline network, and combining it with the temperature rise gradient to determine the fire event, and generating the coordinates of the fire source node and the thermal gas spread vector, is as follows: Baseline compensation and separation of optical scattering patterns are performed based on optical distortion compensation factors to obtain the scattering components of smoke particles. The smoke particle scattering component and the temperature rise gradient are input into the joint threshold judgment condition. When the smoke particle scattering component and the temperature rise gradient are simultaneously triggered, the joint threshold judgment condition is determined to be a fire event. The node coordinates of the maximum extreme point corresponding to the trigger joint threshold judgment condition are set as the fire source node coordinates; The spatial directional derivative is solved based on the set of temperature rise gradients of the associated defense zones around the fire source node coordinates, and the thermal airflow spread vector along the direction of the maximum temperature change rate is output.

6. The method for optimizing and retrofitting existing building fire protection systems based on IoT status monitoring and intelligent linkage control as described in claim 1, characterized in that: The specific process for extracting the transient remaining power supply load of the associated defense zone from the building infrastructure feature matrix based on the fire source node coordinates is as follows: Extract the coordinates of the fire source nodes, and delineate the physical boundaries between the fire prevention zone and the non-fire prevention zone based on the node coordinates contained in the feature matrix of the building infrastructure. Map the physical boundaries of fire zones and non-fire zones to the electrical wiring topology, and locate the power supply bus node index of the associated zones; By retrieving the extreme values ​​of operating power load and active power capacity under the corresponding time reference in the building infrastructure feature matrix through the power supply bus node index, the difference margin between the operating power load and the extreme values ​​of active power capacity is extracted and output as the transient remaining power supply load.

7. The method for optimizing and retrofitting existing building fire protection systems based on IoT status monitoring and intelligent linkage control according to claim 1, characterized in that: The specific process of adjusting the power supply sequence of the zone nodes along the direction of the hot airflow propagation vector, within the safe carrying capacity of the transient remaining power supply load, and generating a set of linkage control instructions that includes power outage and load reduction commands for non-fire zones and the timing rotation array of fire pump valves in fire zones, is as follows: By performing spatial geometric projection on the hot airflow spread vector and node coordinates, a fire spread hazard sequence of surrounding associated defense zones is constructed. Extract the rated start-up inrush flow parameters of fire pump valves in the fire zone. In response to the peak value of the rated start-up inrush flow parameter envelope exceeding the transient remaining power supply load, extract the control routes of commercial electrical nodes in non-fire zones to generate power-off and load-reducing commands. The compensation power supply load margin released after the power outage and load reduction command is obtained. Based on the fire spread hazard sequence of the associated defense zone, staggered start timestamps are allocated to the fire pumps and valves in the fire zone to construct a time-series start array. The power outage and load reduction command and the time-series start array are combined to generate a linkage control command set.

8. The method for optimizing and retrofitting existing building fire protection systems based on IoT status monitoring and intelligent linkage control as described in claim 1, characterized in that: The process of issuing a set of linkage control commands, collecting the transient pressure build-up slope of the pipeline network at high frequency during the execution of the time-sequenced start-up array, performing feature matching between the transient pressure build-up slope and the baseline pressure build-up response envelope, determining that the transient pressure build-up slope exhibits nonlinear pressure loss characteristics exceeding the tolerance range, identifying mechanical jamming of the associated valve, generating a valve isolation flag, and triggering a bypass compensation water supply command for the adjacent pipeline network is as follows: According to the linkage control instruction set, a level trigger signal is sent to the corresponding electrical node to synchronously activate the high-frequency sampling mode of the pipeline pressure monitoring node, and the transient pressure build-up slope is obtained by extracting the discrete points of time-series pressure and fitting them. Retrieve the preset valve normal opening reference pressure build-up response envelope, and perform dynamic time warping matching between the transient pressure build-up slope and the reference pressure build-up response envelope; In response to the nonlinear underpressure characteristics of the matching trajectory deviating from the lower limit tolerance boundary of the baseline pressure build-up response envelope and exhibiting second derivative decay, the topological coordinates of the associated electrical nodes are locked to generate valve isolation identifiers. Retrieve the pipeline network topology map to find parallel water circuit control nodes that cross valve isolation markers, and generate bypass compensation water supply instructions.

9. An optimization and renovation device for existing building fire protection systems based on Internet of Things (IoT) status monitoring and intelligent linkage control, used to execute the optimization and renovation method for existing building fire protection systems based on IoT status monitoring and intelligent linkage control as described in any one of claims 1-8, characterized in that, include: The matrix construction unit is used to deploy IoT terminals in the fire protection pipe network and electrical nodes of existing buildings, and synchronously collect optical scattering spectrum, temperature rise gradient, steady-state micro-pressure fluctuation sequence of the pipe network and transient residual power supply load of the power supply bus in the monitoring area. Based on the sampling time and node coordinates, the data is aligned to construct the feature matrix of building infrastructure. The fire incident determination unit is used to extract the steady-state micro-pressure fluctuation sequence from the feature matrix of building infrastructure, analyze the frequency of water vapor leakage in the pipeline network and convert it into an optical distortion compensation factor; map the optical distortion compensation factor to the optical scattering spectrum, filter out the light intensity scattering interference component caused by water vapor leakage in the pipeline network, combine the temperature rise gradient to determine the fire incident, and generate the coordinates of the fire source node and the thermal airflow spread vector. The instruction generation unit is used to extract the transient remaining power supply load of the associated defense zone from the building infrastructure feature matrix based on the coordinates of the fire source node; Along the direction of the hot airflow propagation vector, within the safe carrying capacity of the transient remaining power supply load, the power supply sequence of the zone nodes is adjusted to generate a set of linkage control instructions that includes power outage and load reduction commands for non-fire zones and the timing rotation array of fire pump valves in fire zones. The fault diagnosis unit is used to issue a set of linkage control commands. During the execution of the timing wheel start array, it collects the transient pressure build-up slope of the pipeline network at high frequency. It performs feature matching between the transient pressure build-up slope and the baseline pressure build-up response envelope. In response to the nonlinear pressure loss characteristics of the transient pressure build-up slope exceeding the tolerance range, it determines that the associated valve has mechanically jammed, generates a valve isolation mark, and triggers the bypass compensation water supply command of the adjacent pipeline network.

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