A fire-fighting cross-system event correlation verification method and system

Abstract

The present application relates to the field of fire safety management and Internet of Things data fusion, and provides a fire cross-system event correlation verification method and system. The method comprises: obtaining fire facility event stream data generated by an alarm host subsystem, identifying a target event of a target fire facility; determining a target monitoring object having a correlation relationship with the target fire facility; obtaining pressure time series data corresponding to the target monitoring object, dividing event-before baseline period pressure data and event-after verification period pressure data, and obtaining pressure fluctuation change characteristics; comparing the event duration with a preset event duration threshold, and matching the pressure fluctuation change characteristics with a preset pressure fluctuation determination condition, to obtain a cross-system correlation verification result of the target fire facility. Through cross-system correlation verification, high-confidence judgment of a fire control valve shielding event is realized, maintenance shielding and valve physical closing state are effectively distinguished, and single alarm signal misjudgment is avoided.

Description

Technical Field

[0001] This invention relates to the field of fire safety management and Internet of Things data fusion, and in particular to a method and system for cross-system event correlation verification in fire protection. Background Technology

[0002] With the digital development of building fire safety management, fire protection IoT systems have been widely applied in commercial complexes, office buildings, schools, factories, and other building scenarios. Existing fire protection IoT systems typically include several relatively independent subsystems, such as an automatic fire alarm subsystem, a water supply pressure monitoring subsystem, and a fire pump monitoring subsystem. The automatic fire alarm subsystem primarily collects information on detector alarms, linkage status, equipment shielding, faults, and feedback events; the water supply pressure monitoring subsystem primarily collects pressure time-series data from different locations in the fire protection pipeline network. While each of these subsystems can reflect some operational status of fire protection facilities, in actual operation, data from different subsystems is often stored and analyzed independently, and cross-system correlation and verification capabilities have not yet been fully established.

[0003] In existing technologies, the status assessment of critical fire protection facilities such as water supply control valves and signal valves typically relies primarily on equipment status information from the alarm control panel subsystem. For example, when the alarm control panel displays that a water supply control valve is in a disabled state, the system generally only knows that the valve's related signals are disabled, making it difficult to determine whether the disabled state is due to temporary management operations such as maintenance, testing, or corrosion prevention work, or whether the valve is actually closed and has been permanently disabled. These two scenarios differ significantly in terms of fire safety risks. The former is usually a traceable management operation, while the latter could lead to a loss of water supply to the corresponding fire protection pipeline section, representing a higher-risk situation. However, relying solely on a single event information from the alarm control panel subsystem makes it difficult to effectively distinguish between the two scenarios, easily leading to misjudgments or omissions.

[0004] Furthermore, existing fire protection IoT analysis methods mostly focus on data statistics and threshold judgments within a single subsystem. For example, they generate alerts based on shielding duration, alarm frequency, instantaneous pressure values, or the number of pressure exceedances. These methods lack cross-validation from other independent physical systems. When confirming high-risk events such as control valve closure, actual water usage, or abnormal pressure relief, the reliability of single-system signals is insufficient and easily affected by factors such as sensor malfunctions, manual operation, system shielding, and data delays. Summary of the Invention

[0005] To address the problems in existing fire protection IoT systems where the alarm control panel subsystem and pressure sensor subsystem are independent, making it difficult to distinguish between maintenance shielding and physical closure of water supply control valves based solely on alarm system shielding information, and lacking cross-system signal corroboration for high-risk states, this application provides a cross-system event correlation verification method and system for fire protection. This method performs high-confidence verification of the operational status of fire protection facilities by correlating and analyzing event stream data from the alarm control panel subsystem with pressure time-series data from the pressure sensor subsystem, particularly for reliably identifying the physical closure status of water supply control valves. The objective of this invention can be achieved through the following technical solutions: This invention provides a method for cross-system event correlation verification in fire protection, comprising the following steps: Step S1: Obtain the fire protection facility event stream data generated by the alarm host subsystem, and identify the target event of the target fire protection facility from the fire protection facility event stream data. The target event is used to trigger cross-system association verification of the target fire protection facility. Step S2: Based on the target event, determine the event occurrence time, event duration, and fire facility identification of the target fire protection facility. Based on the fire facility identification, determine the target monitoring objects that are related to the target fire protection facility, including at least one of the fire pipe section, fire area, or monitoring point corresponding to the target fire protection facility. Step S3: Based on the target monitoring object, obtain the pressure time series data corresponding to the target monitoring object from the pressure sensor subsystem, and divide the pressure time series data into pre-event baseline pressure data and post-event verification pressure data according to the event occurrence time; Step S4: Perform pressure fluctuation analysis on the pressure data of the baseline period before the event and the pressure data of the verification period after the event to obtain the baseline pressure fluctuation parameters and the verification pressure fluctuation parameters. Based on the relationship between the verification pressure fluctuation parameters and the baseline pressure fluctuation parameters, obtain the pressure fluctuation change characteristics. Step S5: Compare the duration of the event with the preset event duration threshold, and match the pressure fluctuation change characteristics with the preset pressure fluctuation judgment conditions to obtain the cross-system correlation verification results of the target fire protection facilities; Step S6: Output the operational status verification information of the target fire protection facilities based on the cross-system correlation verification results.

[0006] Further, step S1 includes, Acquire the fire protection facility event stream data generated or updated by the alarm host subsystem and perform field parsing to extract the fire protection facility identifier, event type, event occurrence time and event status corresponding to each fire protection facility event; Candidate events related to cross-system correlation verification are filtered from fire protection facility event flow data based on event type and event status; Match the event type of the candidate event with the preset target event type, which is the fire control valve shielding event; When the event type of a candidate event matches the preset target event type, the fire protection facility corresponding to the candidate event is identified as the target fire protection facility, and the candidate event is identified as the target event of the target fire protection facility.

[0007] Further, step S2 includes, Determine the time of occurrence and identification of the target fire protection facility based on the target event; Based on the event type and event status of the target event, determine whether the target event is a continuous event; When the target event is a continuous event, the start time of the target event is determined as the event start time, and it is determined whether there is an event end time corresponding to the target event; When there is an event end time corresponding to the target event, determine the duration of the event; When there is no event end time corresponding to the target event, the event duration is determined based on the event start time and the current system time. By querying the pre-set facility association table based on the fire protection facility identification, the target monitoring objects that are associated with the target fire protection facility are identified. The pre-set facility association table includes the correspondence between fire protection facility identification and fire protection pipe sections, fire protection zones, or monitoring points.

[0008] Further, step S3 includes, Based on the target monitoring object, determine the target pressure sensor in the pressure sensor subsystem that corresponds to the target monitoring object, and acquire the corresponding pressure time series data based on the target pressure sensor. The pressure time series data includes the sampling time and the corresponding pressure value. Using the time of the event as the time boundary, pressure data within a preset baseline time range before the time boundary is extracted from the pressure time series data as the pre-event baseline pressure data. At the same time, pressure data within a preset verification time range after the time boundary is used as the post-event verification pressure data. The baseline stress data before the event and the validation stress data after the event are sorted according to the sampling time to generate the baseline stress sequence and the validation stress sequence for fluctuation analysis.

[0009] Furthermore, the preset reference time range is the same as the preset verification time range, which is used to extract the pressure data of the pre-event reference period and the pressure data of the post-event verification period from the pressure time series data, and to calculate the reference pressure fluctuation parameter based on the extracted pre-event reference period pressure data and post-event verification period pressure data, which is used to determine whether the fire control valve is in a physically closed state.

[0010] Further, step S4 includes, Calculate the mean pressure of each pressure value in the baseline pressure series and the validation pressure series. Calculate the standard deviation of pressure based on the deviation between each pressure value and the corresponding mean pressure. Use the standard deviation of pressure corresponding to the baseline pressure series as the baseline pressure fluctuation parameter and the standard deviation of pressure corresponding to the validation pressure series as the validation pressure fluctuation parameter. The ratio between the verification pressure fluctuation parameter and the benchmark pressure fluctuation parameter is calculated to obtain the pressure fluctuation attenuation ratio, which is then used as a characteristic of pressure fluctuation change.

[0011] Further, step S5 includes, Determine whether the duration of the event exceeds a preset event duration threshold; When the duration of an event is less than or equal to a preset event duration threshold, no comparison of pressure fluctuations is performed, and the cross-system correlation verification result of the target fire protection facility is marked as not triggering the physical closure verification of the valve. When the duration of an event exceeds a preset event duration threshold, it is determined whether the pressure fluctuation change characteristic is greater than the preset pressure fluctuation. The pressure fluctuation change characteristic is the pressure fluctuation attenuation ratio, and the preset pressure fluctuation is the preset attenuation ratio threshold. When the pressure fluctuation attenuation ratio is less than the preset attenuation ratio threshold, the cross-system correlation verification result of the target fire protection facility is marked as the valve is physically closed. When the pressure fluctuation attenuation ratio is greater than or equal to the preset attenuation ratio threshold, the cross-system correlation verification result of the target fire protection facility is marked as the valve is not physically closed.

[0012] Further, step S6 includes generating operational status verification information for the target fire protection facility based on the cross-system correlation verification results, and sending the operational status verification information to at least one of the fire safety management terminal, property management terminal, or maintenance management terminal; wherein, When the cross-system correlation verification result is that the valve is physically closed, the operation status verification information includes the valve physical closure prompt information and the corresponding fire pipe section water supply risk prompt information; When the cross-system correlation verification result indicates that the valve is not physically closed, the operation status verification information includes a prompt message indicating that the valve is shielded but the pressure fluctuation is normal. When the cross-system correlation verification result is that the valve physical closure verification was not triggered, the operation status verification information includes a prompt message indicating that the event duration has not reached the verification trigger condition.

[0013] Based on the same inventive concept, this application also provides a fire protection cross-system event correlation verification system, employing the fire protection cross-system event correlation verification method as described above, including: The data acquisition module is used to acquire fire protection facility event stream data generated by the alarm host subsystem, and to identify target events of target fire protection facilities from the fire protection facility event stream data. The target events are used to trigger cross-system association verification of the target fire protection facilities. The data processing module is used to determine the event occurrence time, event duration, and fire facility identification of the target fire protection facility based on the target event. Based on the fire facility identification, it identifies target monitoring objects associated with the target fire protection facility, including at least one of the fire pipe section, fire zone, or monitoring point corresponding to the target fire protection facility. Based on the target monitoring object, it acquires pressure time-series data corresponding to the target monitoring object from the pressure sensor subsystem, and divides the pressure time-series data into pre-event baseline pressure data and post-event verification pressure data according to the event occurrence time. It performs pressure fluctuation analysis on the pre-event baseline pressure data and the post-event verification pressure data respectively to obtain baseline pressure fluctuation parameters and verification pressure fluctuation parameters. Based on the relationship between the verification pressure fluctuation parameters and the baseline pressure fluctuation parameters, it obtains the pressure fluctuation change characteristics. It compares the event duration with a preset event duration threshold and matches the pressure fluctuation change characteristics with preset pressure fluctuation judgment conditions to obtain the cross-system association verification results of the target fire protection facility. The results output module is used to output the operational status verification information of the target fire protection facilities based on the cross-system correlation verification results.

[0014] Furthermore, the data acquisition module includes, The event acquisition unit is used to acquire fire protection facility event stream data generated or updated by the alarm host subsystem and perform field parsing to extract the fire protection facility identifier, event type, event occurrence time and event status corresponding to each fire protection facility event; The candidate event filtering unit is used to filter candidate events related to cross-system correlation verification from the fire protection facility event flow data according to the event type and event status; and to match the event type of the candidate events with the preset target event type, which is the fire control valve shielding event. The target event determination unit is used to determine the fire protection facility corresponding to the candidate event as the target fire protection facility when the event type of the candidate event matches the preset target event type, and to determine the candidate event as the target event of the target fire protection facility.

[0015] Compared with the prior art, the present invention has at least one of the following technical advantages: This application achieves high-confidence judgment of fire control valve shielding events by cross-system correlation verification of alarm host event streams and pressure sensor data, effectively distinguishing between maintenance shielding and valve physical closure status, and avoiding misjudgment based on a single alarm signal; by combining event duration and pressure fluctuation attenuation ratio, it ensures that short-term operation does not trigger false verification, improves the reliability of operational status verification information, requires no additional sensors, and provides accurate and operable decision-making basis for fire management. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below: Figure 1 This is a flowchart illustrating the steps of the fire protection cross-system event correlation verification method in an embodiment of the present invention; Figure 2 This is a flowchart illustrating the cross-system event correlation verification method for fire protection in this embodiment of the invention. Detailed Implementation

[0017] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. It should be noted that the specific embodiments described herein are merely some embodiments of the present application, not all embodiments, and are only used to explain the present application and are not intended to limit the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present application.

[0018] First Embodiment In existing building fire protection IoT systems, the alarm control panel subsystem and the pressure sensor subsystem typically operate independently. The alarm control panel subsystem mainly collects event information such as detector alarms, equipment malfunctions, linkage feedback, and equipment shielding, while the pressure sensor subsystem mainly collects pressure time-series data from different pipe sections or areas in the fire protection network. Current technologies for analyzing the status of fire protection facilities usually perform judgments within each individual subsystem. For example, when the alarm control panel detects that a fire control valve is in a shielded state, the system generally only generates a shielding alarm based on the duration of the shielding; when a pressure sensor detects an abnormal pressure in a pipe section, the system generally only generates a pressure alarm based on whether the pressure value is below a threshold or whether a sudden change has occurred. While these methods can reflect local anomalies, the lack of effective data correlation between different subsystems makes it difficult to reliably verify signals from a single system.

[0019] For example, when a fire control valve is permanently disabled in the alarm control panel subsystem, existing systems typically only recognize the fact that "the valve signal is disabled," without being able to further distinguish whether the disablement is due to temporary management operations such as maintenance, construction, or testing, or whether the valve is actually closed but has been intentionally disabled. Directly assuming the valve is closed based solely on the disablement event recorded by the alarm control panel can easily lead to false alarms; treating it as a general disablement event may overlook high-risk situations where the fire pipeline has lost its water supply guarantee. Similarly, observing pressure sensor data alone makes it difficult to directly confirm a causal relationship between pressure fluctuations and specific valve disablement events. Therefore, while existing technologies can collect alarm events and pressure data separately, they have not yet solved the problem of how to mutually verify alarm events and pressure changes.

[0020] This application, through analysis of actual fire protection IoT operation data, discovered that if a fire control valve is physically closed, its corresponding pipe section will be hydraulically isolated from the main pipeline. Pressure fluctuations generated by the pressure stabilizing pump or the main pipeline are difficult to effectively transmit to this pipe section, resulting in a significant decrease in the fluctuation amplitude of the pressure time-series data for that pipe section. However, if the valve is only disabled in the alarm control panel due to maintenance or management reasons, but is actually still open, the corresponding pipe section will still be affected by pressure fluctuations in the main pipeline, and the pressure time-series data will maintain relatively normal fluctuation characteristics. Based on this understanding, this application proposes cross-system correlation verification between the fire control valve disabling event in the alarm control panel subsystem and the corresponding pipe section pressure time-series data in the pressure sensor subsystem. By jointly judging the event duration and pressure fluctuation attenuation characteristics, the application verifies whether the fire control valve is physically closed, thereby improving the reliability of the fire protection facility operation status verification results and reducing misjudgments caused by a single subsystem. Specific implementation methods are as follows: like Figure 1 As shown, this application provides a cross-system event correlation verification method for fire protection. By correlating and analyzing the event flow data of fire protection facilities generated by the alarm control panel subsystem with the pressure time-series data collected by the pressure sensor subsystem, it performs cross-system verification of the key operating status of fire protection facilities. It is particularly useful for reliably identifying whether a water supply control valve is in a physically closed state. The steps include... Step S1: Obtain the fire protection facility event stream data generated by the alarm host subsystem, and identify the target event of the target fire protection facility from the fire protection facility event stream data. The target event is used to trigger cross-system association verification of the target fire protection facility. Step S2: Based on the target event, determine the event occurrence time, event duration, and fire facility identification of the target fire protection facility. Based on the fire facility identification, determine the target monitoring objects that are related to the target fire protection facility, including at least one of the fire pipe section, fire area, or monitoring point corresponding to the target fire protection facility. Step S3: Based on the target monitoring object, obtain the pressure time series data corresponding to the target monitoring object from the pressure sensor subsystem, and divide the pressure time series data into pre-event baseline pressure data and post-event verification pressure data according to the event occurrence time; Step S4: Perform pressure fluctuation analysis on the pressure data of the baseline period before the event and the pressure data of the verification period after the event to obtain the baseline pressure fluctuation parameters and the verification pressure fluctuation parameters. Based on the relationship between the verification pressure fluctuation parameters and the baseline pressure fluctuation parameters, obtain the pressure fluctuation change characteristics. Step S5: Compare the event duration with a preset event duration threshold, and match the pressure fluctuation change characteristics with a preset pressure fluctuation judgment condition to obtain the cross-system correlation verification result of the target fire protection facility; the preset event duration threshold is used to distinguish between short-term management shielding and long-term shielding or valve physical closure status, and in one embodiment, it can be 30 days; the preset pressure fluctuation judgment condition can be set as a preset attenuation ratio threshold. When the pressure fluctuation amplitude during the verification period decreases significantly compared to the baseline period, it is determined whether the pressure fluctuation driven by the pressure stabilizing pump is no longer transmitted to the corresponding pipe section, thereby identifying the valve physical closure status. In one embodiment, the preset attenuation ratio threshold can be 0.3 (corresponding to a fluctuation amplitude decrease of approximately 70%). The above values ​​are only examples and do not constitute a limitation on the scope of protection of this invention.

[0021] Step S6: Output the operational status verification information of the target fire protection facilities based on the cross-system correlation verification results.

[0022] Specifically, such as Figure 2 As shown, the fire protection cross-system event correlation verification method provided in this embodiment further achieves high-confidence verification of the water supply control valve status through joint analysis of the alarm host subsystem and the pressure sensor subsystem. The left side of the figure shows the alarm host subsystem, and the right side shows the pressure sensor subsystem; both collect independent signals and upload them to the verification logic module.

[0023] In the alarm host subsystem, the control valve shielding event flow includes information such as shielding duration, shielding start time, and device identification. When the shielding lasts for more than a preset event duration threshold, the system triggers a cross-system verification process to determine whether the valve is physically closed. This threshold can be set based on engineering experience: normal maintenance or temporary shielding is usually completed within hours to days, and a shielding duration exceeding this threshold (30 days in one embodiment) can serve as one of the conditions for triggering cross-system verification, indicating that the shielding may have been caused by forgotten shielding or actual valve closure, and thus proceeding to the subsequent pressure fluctuation verification process.

[0024] In the pressure sensor subsystem, pressure time-series data for the corresponding pipe section is collected, and the pressure standard deviation (Std) between the baseline period before shielding and the verification period after shielding is calculated. The verification logic module comprehensively judges the pressure standard deviation ratio (Verification period Std / Base period Std) based on the shielding duration. When the shielding duration is >30 days and Ratio <0.3, the valve is determined to be physically closed; when Ratio ≥0.3, the valve is determined not to be physically closed; if the shielding duration is ≤30 days, no pressure fluctuation comparison is performed, only the shielding event is recorded, and physical closure verification is not triggered.

[0025] The verification results are divided into two categories: one is that the valve is confirmed to be closed, the corresponding pipe section may lose water supply guarantee, the system generates a high-priority alarm and notifies the property management terminal; the other is that the valve is not closed, it is only a shielding or temporary operation, the system generates a record or a medium-priority alarm, and does not trigger a serious defect alarm.

[0026] also, Figure 2 The expanded box in the lower right corner illustrates a scenario where three signals are jointly verified to identify real water usage events. When the water flow indicator activates, the pipeline pressure drops, and the pressure stabilizing pump starts simultaneously within a ±10-minute time window, the system outputs a high-confidence verification result for a real water usage event. If only one or two signals occur, a secondary verification is performed by combining historical records and time periods to improve the reliability of the judgment.

[0027] The entire illustrated process embodies the core logic of cross-subsystem dual-signal cross-verification. The duration of the shielding event exceeds the threshold and the pressure fluctuation significantly decreases as the basis for physical shutdown judgment. If the shielding duration is insufficient or the pressure fluctuation amplitude is not obvious, physical shutdown is excluded. Combined with the three-way signal expansion scenario, high-confidence fire event identification is achieved.

[0028] Further, step S1 includes, Acquire the fire protection facility event stream data generated or updated by the alarm host subsystem and perform field parsing to extract the fire protection facility identifier, event type, event occurrence time and event status corresponding to each fire protection facility event; Candidate events related to cross-system correlation verification are filtered from fire protection facility event flow data based on event type and event status; Match the event type of the candidate event with the preset target event type, which is the fire control valve shielding event; When the event type of a candidate event matches the preset target event type, the fire protection facility corresponding to the candidate event is identified as the target fire protection facility, and the candidate event is identified as the target event of the target fire protection facility.

[0029] Further, step S2 includes, Determine the time of occurrence and identification of the target fire protection facility based on the target event; Based on the event type and event status of the target event, determine whether the target event is a continuous event; When the target event is a continuous event, the start time of the target event is determined as the event start time, and it is determined whether there is an event end time corresponding to the target event; When there is an event end time corresponding to the target event, determine the duration of the event; When there is no event end time corresponding to the target event, the event duration is determined based on the event start time and the current system time. By querying the pre-set facility association table based on the fire protection facility identification, the target monitoring objects that are associated with the target fire protection facility are identified. The pre-set facility association table includes the correspondence between fire protection facility identification and fire protection pipe sections, fire protection zones, or monitoring points.

[0030] Further, step S3 includes, Based on the target monitoring object, determine the target pressure sensor in the pressure sensor subsystem that corresponds to the target monitoring object, and acquire the corresponding pressure time series data based on the target pressure sensor. The pressure time series data includes the sampling time and the corresponding pressure value. Using the time of the event as the time boundary, pressure data within a preset baseline time range before the time boundary is extracted from the pressure time series data as the pre-event baseline pressure data. At the same time, pressure data within a preset verification time range after the time boundary is used as the post-event verification pressure data. The baseline stress data before the event and the validation stress data after the event are sorted according to the sampling time to generate the baseline stress sequence and the validation stress sequence for fluctuation analysis.

[0031] Furthermore, the preset reference time range is the same as the preset verification time range, which is used to extract the pressure data of the pre-event reference period and the pressure data of the post-event verification period from the pressure time series data, and to calculate the reference pressure fluctuation parameter based on the extracted pre-event reference period pressure data and post-event verification period pressure data, which is used to determine whether the fire control valve is in a physically closed state.

[0032] Further, step S4 includes, Calculate the mean pressure of each pressure value in the baseline pressure series and the validation pressure series. Calculate the standard deviation of pressure based on the deviation between each pressure value and the corresponding mean pressure. Use the standard deviation of pressure corresponding to the baseline pressure series as the baseline pressure fluctuation parameter and the standard deviation of pressure corresponding to the validation pressure series as the validation pressure fluctuation parameter. The ratio between the verification pressure fluctuation parameter and the benchmark pressure fluctuation parameter is calculated to obtain the pressure fluctuation attenuation ratio, which is then used as a characteristic of pressure fluctuation change.

[0033] Further, step S5 includes, Determine whether the duration of the event exceeds a preset event duration threshold; When the duration of an event is less than or equal to a preset event duration threshold, no comparison of pressure fluctuations is performed, and the cross-system correlation verification result of the target fire protection facility is marked as not triggering the physical closure verification of the valve. When the duration of an event exceeds a preset event duration threshold, it is determined whether the pressure fluctuation change characteristic is greater than the preset pressure fluctuation. The pressure fluctuation change characteristic is the pressure fluctuation attenuation ratio, and the preset pressure fluctuation is the preset attenuation ratio threshold. When the pressure fluctuation attenuation ratio is less than the preset attenuation ratio threshold, the cross-system correlation verification result of the target fire protection facility is marked as the valve is physically closed. When the pressure fluctuation attenuation ratio is greater than or equal to the preset attenuation ratio threshold, the cross-system correlation verification result of the target fire protection facility is marked as the valve is not physically closed.

[0034] Further, step S6 includes generating operational status verification information for the target fire protection facility based on the cross-system correlation verification results, and sending the operational status verification information to at least one of the fire safety management terminal, property management terminal, or maintenance management terminal; wherein, When the cross-system correlation verification result is that the valve is physically closed, the operation status verification information includes the valve physical closure prompt information and the corresponding fire pipe section water supply risk prompt information; When the cross-system correlation verification result indicates that the valve is not physically closed, the operation status verification information includes a prompt message indicating that the valve is shielded but the pressure fluctuation is normal. When the cross-system correlation verification result is that the valve physical closure verification was not triggered, the operation status verification information includes a prompt message indicating that the event duration has not reached the verification trigger condition.

[0035] The following examples illustrate the verification of physical valve closure and joint verification of real water usage events in multiple scenarios: Application Example 1: Cross-system correlation verification of the physical closed state of water supply control valves.

[0036] In a building fire protection IoT system, the alarm control panel subsystem continuously receives event stream data from various fire protection facilities. When the system identifies a fire control valve blocking event corresponding to a water supply control valve from the event stream data, it identifies the water supply control valve as the target fire protection facility and the fire control valve blocking event as the target event. Based on the target event, it determines the blocking start time, event duration, and fire protection facility identifier. Then, based on the fire protection facility identifier, it queries a preset facility association table to determine the fire pipe section corresponding to the water supply control valve and the target pressure sensor on that fire pipe section.

[0037] In this application example, the water supply control valve is in a shielded state within the alarm host subsystem for 42 days, exceeding the preset event duration threshold of 30 days, thus triggering the verification of the valve's physical closure status. Using the shielding start time as the time boundary, pressure time-series data for the corresponding pipe section of the water supply control valve are read from the pressure sensor subsystem for 30 days before and 30 days after the shielding start, generating a baseline pressure sequence and a verification pressure sequence respectively. Subsequently, the pressure standard deviations of the baseline and verification pressure sequences are calculated to obtain the baseline pressure fluctuation parameter σbaseline and the verification pressure fluctuation parameter σverification, and the pressure fluctuation attenuation ratio Ratio = σverification / σbaseline is calculated.

[0038] For example, if the baseline pressure standard deviation σbaseline is 0.048 MPa and the verification pressure standard deviation σverification is 0.009 MPa, then the pressure fluctuation attenuation ratio Ratio = 0.009 / 0.048 = 0.1875. Since the shielding duration of this water supply control valve is greater than 30 days, and the pressure fluctuation attenuation ratio is less than the preset attenuation ratio threshold of 0.3, the system marks the cross-system correlation verification result of this water supply control valve as a physically closed state and generates operational status verification information. This operational status verification information includes a valve physical closure prompt and a corresponding fire-fighting pipeline section water supply risk prompt, and is sent to the fire safety management terminal, property management terminal, or maintenance management terminal. The principle is that when the water supply control valve is actually in a physically closed state, a hydraulic isolation is formed between the corresponding pipeline section and the main pipeline. Pressure fluctuations generated by the pressure stabilizing pump or the main pipeline are difficult to continue to be transmitted to this pipeline section, resulting in a significant reduction in the pressure standard deviation after shielding compared to before shielding. This allows for cross-system verification of the valve's physical closure state.

[0039] In another scenario, if a water supply control valve is also shielded for more than 30 days, but the pressure standard deviation before shielding is 0.051 MPa and the pressure standard deviation after shielding is 0.049 MPa, then the pressure fluctuation attenuation ratio Ratio = 0.049 / 0.051 = 0.96, which is greater than the preset attenuation ratio threshold of 0.3. This indicates that the fire-fighting pipeline section can still receive pressure fluctuations from the main pipeline or the pressure-stabilizing pump. The system marks the cross-system correlation verification result of this water supply control valve as a valve not physically closed and outputs a prompt message indicating that the valve is shielded but the pressure fluctuation is normal, thus avoiding misjudging maintenance or management shielding as a physically closed valve state.

[0040] Application Example 2: Joint verification of three signals from a real water usage event.

[0041] In a building fire protection IoT system, the system can also perform cross-system joint verification of water flow indicator activation signals, pipeline pressure drop events, and pressure-stabilizing pump start-up events to identify whether a real water usage event has occurred. Specifically, the system obtains water flow indicator activation signals from the alarm control panel subsystem, pipeline pressure drop events from the pressure sensor subsystem, and pressure-stabilizing pump start-up events from the fire pump monitoring subsystem or related equipment event streams. The system establishes a preset time window based on the occurrence time of any signal and determines whether all three signals fall within the same time window.

[0042] In this application example, a water flow indicator on a certain floor activated at 10:02, the pressure sensor subsystem detected a corresponding pressure drop in the pipe network at 10:05, and the pressure-stabilizing pump started at 10:08. Since the water flow indicator activation signal, the pipe network pressure drop event, and the pressure-stabilizing pump start event all fall within a ±10-minute time alignment window, the system determines that the three signals are time-consistent and outputs a verification result of the actual water usage event. The confidence level of this verification result is higher than that of judgment results formed by only a single signal or two signals.

[0043] In this scenario, the activation of the water flow indicator indicates a change in water flow within the pipe section, a drop in pipe network pressure indicates water usage or pressure relief in the fire protection pipe network, and the activation of the pressure-stabilizing pump indicates that the system is responding to the pressure drop by replenishing pressure. It should be noted that this application example addresses a non-fire condition where a slow drop in pipe network pressure due to low-flow water usage or minor leaks triggers the pressure-stabilizing pump for pressure replenishment. In this case, the pump that activates and participates in the aforementioned joint verification is the pressure-stabilizing pump. However, in actual fire water usage conditions, the pump activated by the water flow indicator is the main fire pump or sprinkler pump, while the pressure-stabilizing pump enters dormancy. These are different pump types under different conditions and should not be confused. When all three signals occur simultaneously within the same time window, it indicates a mutual corroboration relationship between the alarm host event, pressure timing changes, and pump operating status, thus identifying the event as a high-confidence, real water usage event. If only the water flow indicator signal is triggered, or only two signals from the pipeline pressure drop event and the pressure stabilizing pump start event are detected, the system will not directly output a high-confidence verification result of the real water use event. Instead, it will combine the event occurrence time, historical event records, maintenance operation records, or manual confirmation information for further verification, thereby reducing the risk of misjudgment.

[0044] Application Example 3: Verification that the valve physical closure is not triggered when the shielding duration does not reach the threshold. A fire protection ring control valve on the basement floor of a commercial complex was marked as disabled in the alarm control panel. The system identified this disabled event from the fire protection facility event stream data of the alarm control panel subsystem and extracted the corresponding disabled start time, fire protection facility identifier, and event status. Calculations showed that the disabled duration was 12 days, less than the preset event duration threshold of 30 days. Based on the judgment logic in step S5, the system marked this event as not triggering valve physical closure verification, stopped comparing the pressure fluctuation attenuation ratio of the corresponding pipe section, and output a prompt message indicating that the event duration did not meet the verification trigger condition. This approach avoids misjudging normal disabled events occurring during short-term maintenance, testing, or temporary construction as valve physical closure, reducing invalid alarms.

[0045] Application Example 4: Calculate and verify the duration of un-unblocked events based on the current system time. After a shielding event was generated in the alarm control panel for the fire branch pipe control valve on the third floor of a school building, no corresponding shielding release event was received. The platform calculated the event duration based on the start time of the shielding event and the current system time, determining that the control valve had been continuously shielded for 36 days, exceeding the preset event duration threshold of 30 days. The system then queried the preset facility association table based on the control valve's fire facility identification to determine the corresponding fire pipe section and target pressure sensor, and extracted pressure time-series data for the 30 days before and after the shielding began. Calculations showed that the baseline pressure standard deviation σbaseline = 0.046 MPa, the verification pressure standard deviation σverification = 0.012 MPa, and the pressure fluctuation attenuation ratio Ratio = 0.012 / 0.046 = 0.26, which is less than the preset attenuation ratio threshold of 0.3. Based on this, the system marked the cross-system association verification result of the control valve as a physically closed state and sent a valve physical closure prompt and a corresponding fire pipe section water supply risk prompt to the fire safety management and maintenance management terminals. After on-site verification, it was found that the valve had not been restored to the open state after previous maintenance, and the verification results were consistent with the on-site situation.

[0046] In summary, this application combines fire control valve blocking events from the alarm control panel subsystem with pressure time-series data from the pressure sensor subsystem through cross-subsystem dual signal correlation analysis, achieving high-confidence verification of the critical status of fire protection facilities. This method effectively distinguishes between administrative blocking and actual valve closure, avoiding misjudging maintenance operations as serious defects. It requires no additional hardware, relying solely on existing IoT data to complete cross-system verification, reducing system deployment costs. Furthermore, multiple valve closure events not recorded in maintenance logs have been discovered in actual building configurations, verifying the reliability and practical value of the method in engineering applications.

[0047] Second Embodiment Based on the same inventive concept, this application also provides a fire protection cross-system event correlation verification system, employing the fire protection cross-system event correlation verification method as described above, including: The data acquisition module is used to acquire fire protection facility event stream data generated by the alarm host subsystem, and to identify target events of target fire protection facilities from the fire protection facility event stream data. The target events are used to trigger cross-system association verification of the target fire protection facilities. The data processing module is used to determine the event occurrence time, event duration, and fire facility identification of the target fire protection facility based on the target event. Based on the fire facility identification, it identifies target monitoring objects associated with the target fire protection facility, including at least one of the fire pipe section, fire zone, or monitoring point corresponding to the target fire protection facility. Based on the target monitoring object, it acquires pressure time-series data corresponding to the target monitoring object from the pressure sensor subsystem, and divides the pressure time-series data into pre-event baseline pressure data and post-event verification pressure data according to the event occurrence time. It performs pressure fluctuation analysis on the pre-event baseline pressure data and the post-event verification pressure data respectively to obtain baseline pressure fluctuation parameters and verification pressure fluctuation parameters. Based on the relationship between the verification pressure fluctuation parameters and the baseline pressure fluctuation parameters, it obtains the pressure fluctuation change characteristics. It compares the event duration with a preset event duration threshold and matches the pressure fluctuation change characteristics with preset pressure fluctuation judgment conditions to obtain the cross-system association verification results of the target fire protection facility. The results output module is used to output the operational status verification information of the target fire protection facilities based on the cross-system correlation verification results.

[0048] Furthermore, the data acquisition module includes, The event acquisition unit is used to acquire fire protection facility event stream data generated or updated by the alarm host subsystem and perform field parsing to extract the fire protection facility identifier, event type, event occurrence time and event status corresponding to each fire protection facility event; The candidate event filtering unit is used to filter candidate events related to cross-system correlation verification from the fire protection facility event flow data according to the event type and event status; and to match the event type of the candidate events with the preset target event type, which is the fire control valve shielding event. The target event determination unit is used to determine the fire protection facility corresponding to the candidate event as the target fire protection facility when the event type of the candidate event matches the preset target event type, and to determine the candidate event as the target event of the target fire protection facility.

[0049] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the foregoing claims.

[0050] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

[0051] It should be understood that "multiple" as used in this article refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0052] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0053] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for verifying cross-system event correlation in fire protection, characterized in that, The steps include, Step S1: Obtain fire protection facility event stream data generated by the alarm host subsystem, and identify target events of target fire protection facilities from the fire protection facility event stream data. The target events are used to trigger cross-system association verification of the target fire protection facilities. Step S2: Based on the target event, determine the event occurrence time, event duration, and fire facility identification of the target fire protection facility; and determine the target monitoring object associated with the target fire protection facility based on the fire facility identification. The target monitoring object includes at least one of the fire pipe section, fire area, or monitoring point corresponding to the target fire protection facility. Step S3: Based on the target monitoring object, obtain the pressure time series data corresponding to the target monitoring object from the pressure sensor subsystem, and divide the pressure time series data into pre-event baseline pressure data and post-event verification pressure data according to the event occurrence time; Step S4: Perform pressure fluctuation analysis on the pre-event baseline pressure data and the post-event verification pressure data to obtain baseline pressure fluctuation parameters and verification pressure fluctuation parameters. Based on the relationship between the verification pressure fluctuation parameters and the baseline pressure fluctuation parameters, obtain the pressure fluctuation change characteristics. Step S5: Compare the duration of the event with a preset event duration threshold, and match the pressure fluctuation change characteristics with preset pressure fluctuation judgment conditions to obtain the cross-system correlation verification result of the target fire protection facility; Step S6: Output the operational status verification information of the target fire protection facility based on the cross-system correlation verification results.

2. The fire protection cross-system event correlation verification method according to claim 1, characterized in that, Step S1 includes, The alarm host subsystem generates or updates the fire protection facility event stream data and performs field parsing to extract the fire protection facility identifier, event type, event occurrence time, and event status corresponding to each fire protection facility event. Based on the event type and the event status, candidate events related to the cross-system association verification are filtered from the fire protection facility event stream data. The event type of the candidate event is matched with a preset target event type, wherein the preset target event type is a fire control valve shielding event; When the event type of the candidate event matches the preset target event type, the fire protection facility corresponding to the candidate event is determined as the target fire protection facility, and the candidate event is determined as the target event of the target fire protection facility.

3. The fire protection cross-system event correlation verification method according to claim 2, characterized in that, Step S2 includes, Based on the target event, determine the event occurrence time and the identification of the target fire protection facility; Based on the event type and event state of the target event, determine whether the target event is a continuous event; When the target event is a continuous event, the start time of the target event is determined as the event start time, and it is determined whether there is an event end time corresponding to the target event; When there is an event end time corresponding to the target event, the duration of the event is determined; When there is no event end time corresponding to the target event, the duration of the event is determined based on the event start time and the current system time. The target monitoring object that is associated with the target fire protection facility is determined by querying the preset facility association table based on the fire protection facility identification. The preset facility association table includes the correspondence between the fire protection facility identification and the fire protection pipe section, the fire protection area, or the monitoring point.

4. The fire protection cross-system event correlation verification method according to claim 1, characterized in that, Step S3 includes, Based on the target monitoring object, a target pressure sensor corresponding to the target monitoring object is determined in the pressure sensor subsystem. Based on the target pressure sensor, the corresponding pressure time series data is obtained, and the pressure time series data includes the sampling time and the corresponding pressure value. Using the event occurrence time as a time boundary, pressure data within a preset baseline time range before the time boundary is extracted from the pressure time series data and used as the pre-event baseline pressure data. Simultaneously, pressure data within a preset verification time range after the time boundary is used as the post-event verification pressure data. The baseline pressure data before the event and the validation pressure data after the event are sorted according to the sampling time to generate the baseline pressure sequence and the validation pressure sequence for the fluctuation analysis.

5. The fire protection cross-system event correlation verification method according to claim 4, characterized in that, The preset reference time range is the same as the preset verification time range, and is used to extract the pre-event reference period pressure data and the post-event verification period pressure data from the pressure time series data, respectively, and calculate the reference pressure fluctuation parameter based on the extracted pre-event reference period pressure data and post-event verification period pressure data, which is used to determine whether the fire control valve is in a physically closed state.

6. The fire protection cross-system event correlation verification method according to claim 5, characterized in that, Step S4 includes, Calculate the mean pressure of each pressure value in the baseline pressure sequence and the validation pressure sequence, calculate the standard deviation of pressure based on the deviation between each pressure value and the corresponding mean pressure, and use the standard deviation of pressure corresponding to the baseline pressure sequence as the baseline pressure fluctuation parameter, and use the standard deviation of pressure corresponding to the validation pressure sequence as the validation pressure fluctuation parameter. The ratio between the verification pressure fluctuation parameter and the reference pressure fluctuation parameter is calculated to obtain the pressure fluctuation attenuation ratio, and the pressure fluctuation attenuation ratio is used as the pressure fluctuation change characteristic.

7. The fire protection cross-system event correlation verification method according to claim 6, characterized in that, Step S5 includes, Determine whether the duration of the event is greater than the preset event duration threshold; When the duration of the event is less than or equal to the preset event duration threshold, the comparison of the pressure fluctuation change is not performed, and the cross-system correlation verification result of the target fire protection facility is marked as not triggering the valve physical closure verification. When the duration of the event exceeds the preset event duration threshold, it is determined whether the pressure fluctuation change feature is greater than the preset pressure fluctuation, wherein the pressure fluctuation change feature is the pressure fluctuation attenuation ratio, and the preset pressure fluctuation is the preset attenuation ratio threshold. When the pressure fluctuation attenuation ratio is less than the preset attenuation ratio threshold, the cross-system correlation verification result of the target fire protection facility is marked as a valve physical closed state; When the pressure fluctuation attenuation ratio is greater than or equal to the preset attenuation ratio threshold, the cross-system correlation verification result of the target fire protection facility is marked as a valve not physically closed.

8. The fire protection cross-system event correlation verification method according to claim 7, characterized in that, Step S6 includes generating operational status verification information for the target fire protection facility based on the cross-system correlation verification results, and sending the operational status verification information to at least one of the fire safety management terminal, property management terminal, or maintenance management terminal; wherein, When the cross-system correlation verification result indicates that the valve is physically closed, the operation status verification information includes a valve physical closure prompt and a corresponding fire-fighting pipeline water supply risk prompt. When the cross-system correlation verification result indicates that the valve is not physically closed, the operating status verification information includes a prompt message indicating that the valve is shielded but the pressure fluctuation is normal. When the cross-system correlation verification result is that the valve physical closure verification has not been triggered, the operation status verification information includes a prompt message indicating that the duration of the event has not reached the verification triggering condition.

9. A fire protection cross-system event correlation verification system, employing the fire protection cross-system event correlation verification method as described in any one of claims 1 to 8, characterized in that, include, The data acquisition module is used to acquire fire protection facility event stream data generated by the alarm host subsystem, and to identify target events of target fire protection facilities from the fire protection facility event stream data. The target events are used to trigger cross-system association verification of the target fire protection facilities. The data processing module is used to determine the event occurrence time, event duration, and fire facility identification of the target fire protection facility based on the target event; determine the target monitoring object associated with the target fire protection facility based on the fire facility identification; the target monitoring object includes at least one of fire pipe section, fire area, or monitoring point corresponding to the target fire protection facility; and acquire pressure time series data corresponding to the target monitoring object from the pressure sensor subsystem based on the target monitoring object, and divide the pressure time series data into pre-event baseline pressure data and post-event verification pressure data according to the event occurrence time. Pressure fluctuation analysis was performed on the pressure data during the baseline period before the event and the pressure data during the verification period after the event to obtain the baseline pressure fluctuation parameters and the verification pressure fluctuation parameters. Based on the relationship between the verification pressure fluctuation parameters and the baseline pressure fluctuation parameters, the pressure fluctuation change characteristics were obtained. The duration of the event is compared with a preset event duration threshold, and the pressure fluctuation change characteristics are matched with preset pressure fluctuation judgment conditions to obtain the cross-system correlation verification results of the target fire protection facility. The result output module is used to output the operational status verification information of the target fire protection facility based on the cross-system correlation verification results.

10. The fire protection cross-system event correlation verification system according to claim 9, characterized in that, The data acquisition module includes, The event acquisition unit is used to acquire the fire protection facility event stream data generated or updated by the alarm host subsystem and perform field parsing to extract the fire protection facility identifier, event type, event occurrence time and event status corresponding to each fire protection facility event; The candidate event filtering unit is used to filter candidate events related to the cross-system association verification from the fire protection facility event flow data according to the event type and the event status; and to match the event type of the candidate events with a preset target event type, wherein the preset target event type is a fire control valve shielding event; The target event determination unit is used to determine the fire protection facility corresponding to the candidate event as the target fire protection facility when the event type of the candidate event matches the preset target event type, and to determine the candidate event as the target event of the target fire protection facility.

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