High-rise building electrical fire hazard characteristic gas monitoring system, method and equipment

Abstract

The present invention belongs to the field of gas monitoring technology, specifically to a system, method and device for monitoring characteristic gases of electrical fire hazards in high-rise buildings. The monitoring system includes a sensor network module, a fault diagnosis module, a data processing center module and an alarm and notification module. The present invention receives ventilation system fault hazard data, generates a comprehensive index at the same time based on these data, monitors the change trend of the comprehensive index in real time, and uses a sliding window algorithm for continuous monitoring, so as to timely identify abnormal operation or failure of the ventilation system; through real-time monitoring, dynamic adjustment and fire hazard assessment, the safety management capability of the internal environment of high-rise buildings is significantly improved, the safety and stability of the equipment during operation are ensured, and at the same time, potential fire risks are effectively prevented and monitored, providing reliable safety protection for residents and operators in the building.

Description

Technical Field

[0001] The present invention belongs to the technical field of gas monitoring, and in particular relates to a system, method and equipment for monitoring gas characteristic of electrical fire hazards in high-rise buildings. Background Art

[0002] Fire monitoring refers to the real-time monitoring and analysis of environmental factors that may cause fires through the use of various sensors and monitoring equipment, so as to promptly discover fire hazards and take corresponding prevention and control measures; these environmental factors include but are not limited to smoke, temperature, carbon monoxide concentration, gas volatile concentration, etc.; fire monitoring systems are usually composed of sensors, control units, alarm devices and data processing units, etc., through which real-time monitoring and processing of fire hazards can be achieved.

[0003] In high-rise buildings, each floor or the corresponding high floors are usually equipped with the necessary electrical facilities, as well as ventilation systems, fire extinguishing systems and heat dissipation systems. For people working on high floors, the normal operation of the ventilation system is extremely critical. If the ventilation system between electrical equipment fails, heat and gas cannot be discharged in time, increasing the risk of fire. At present, the fire hazard monitoring of electrical equipment is usually only judged through gas monitoring. Some special electrical equipment may cause local overheating or produce abnormal gas due to long-term low-load operation, but this situation is relatively hidden and not easy to be detected, resulting in inaccurate monitoring results, which in turn affects the effectiveness of subsequent judgments on the degree of fire hazards.

[0004] Existing research often uses sensors to monitor the gas concentration of carbon monoxide to determine whether a fire has occurred. However, the alarm threshold corresponding to the sensor is usually fixed and cannot be dynamically adjusted according to historical data or the environment, resulting in the inability to further improve the detection accuracy, which also affects the subsequent accurate judgment of fire hazards. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a system, method and equipment for monitoring characteristic gases of electrical fire hazards in high-rise buildings. Through real-time monitoring, dynamic adjustment and fire hazard assessment, it significantly improves the safety management capability of the internal environment of high-rise buildings and ensures the safety and stability of the equipment during operation.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0007] High-rise building electrical fire hazard characteristic gas monitoring system, including:

[0008] The sensor network module collects hidden danger characteristic data in the corresponding electrical equipment, collects fault hidden danger data in the ventilation system pipeline in the building where the electrical equipment is located, and outputs the hidden danger characteristic data and the fault hidden danger data through the configured wireless communication unit;

[0009] The fault diagnosis module receives the fault potential data, generates the comprehensive index at the same time based on the fault potential data, and monitors the change trend of the comprehensive index at each time in real time without adjusting the ventilation system. It also uses the sliding window algorithm to monitor and choose whether to issue an early warning signal. If an early warning signal is issued, it triggers the alternative adjustment strategy.

[0010] The data processing center module receives the hidden danger characteristic data and issues a first-level alarm signal when it detects that the real-time carbon monoxide concentration exceeds the set standard range value; when it detects that there is a volatile organic compound concentration or the carbon monoxide concentration is within the standard range value, it issues a second-level alarm signal and executes the preset hidden danger assessment strategy; when it detects that the carbon monoxide concentration is lower than the standard range value, it does not respond;

[0011] The alarm and notification module, upon receiving a first-level alarm signal, immediately notifies the fire department through the Internet and activates the fire-fighting equipment in the corresponding electrical equipment.

[0012] Preferably, a plurality of electrical devices are arranged in the high-rise building, and the plurality of electrical devices together constitute a complete set of electrical facilities; the hidden danger characteristic data include:

[0013] Gas data sets, including carbon monoxide concentration and volatile organic compound concentration; air velocity data sets, including upper wind speed and lower wind speed; load data, including real-time output power;

[0014] Fault potential data include: real-time pipeline temperature value and pipeline air flow value.

[0015] Preferably, the comprehensive index at the same time is generated based on the potential fault data, and the formula used is:

[0016] ;

[0017] In the formula, represents the comprehensive index at the same time, t represents the time, , They represent the pipeline temperature value and pipeline air flow value at the same time respectively. , is the weight coefficient, , ,and .

[0018] Preferably, the process of monitoring using the sliding window algorithm is as follows:

[0019] The historical data is set as: the comprehensive index of the ventilation system in a high-rise building at each moment under normal working conditions within a preset time period T; based on the historical data, a sliding window algorithm is used to maintain the window of the fixed time period T, and the mean of the comprehensive index corresponding to each moment in the window is calculated, and then the current comprehensive index is compared with the mean in the window. If the difference between the two exceeds the preset deviation threshold, an early warning signal is issued.

[0020] Preferably, the alternative adjustment strategy is: disconnect the power supply of the original ventilation system and turn on the power supply of the backup ventilation system.

[0021] Preferably, the standard range value is set using a dynamic adjustment unit built into the data processing center module;

[0022] The historical test data is set as follows: the carbon monoxide concentration corresponding to each moment of the electrical equipment under normal operating conditions within a preset time period T; the dynamic adjustment unit summarizes the historical test data, extracts the maximum and minimum values ​​of the carbon monoxide concentration variation range in the historical test data, and generates the minimum value in the standard range value based on the maximum value of the carbon monoxide concentration variation range and the air flow rate data set. The maximum value in the standard range value is a fixed value.

[0023] Preferably, the process of generating the minimum value in the standard range is:

[0024] According to the air velocity data set, the wind speed average of the upper wind speed and the lower wind speed in the corresponding electrical equipment is calculated. According to the pre-processed wind speed average and the maximum value of the carbon monoxide concentration variation range, the minimum value in the standard range is generated. The formula is as follows:

[0025] ;

[0026] In the formula, Indicates the maximum value of the carbon monoxide concentration range. Indicates the upper wind speed, Indicates the lower wind speed, , are preset proportional coefficients, and ; Standard range values ​​are expressed as , Indicates the maximum value in the standard range. Indicates the minimum value in the standard range.

[0027] Preferably, the preset hidden danger assessment strategy is:

[0028] The carbon monoxide concentration, air velocity data set and load data in the hidden danger feature data are dimensionless processed, and the fire hazard estimated value Hug is generated based on the carbon monoxide concentration, wind speed average and load data at different times within the preset time period T. The fire hazard estimated value Hug corresponding to several electrical equipment is compared and analyzed, and the inspection priority is limited by the following methods:

[0029] ;

[0030] ;

[0031] In the formula, Indicates the maximum value of carbon monoxide concentration within the time period T, represents the maximum value of the mean wind speed within the time period T, represents the output power at each time i in the time period T, , n is a positive integer, and n=T, Indicates the time period T The average value of It indicates that the inspection priority is positively correlated with the fire hazard estimate Hug. , , are preset proportional coefficients respectively, and both are greater than 0.

[0032] The method for monitoring characteristic gases of electrical fire hazards in high-rise buildings, based on the above system, includes the following steps:

[0033] S1. Collect hidden danger feature data in the corresponding electrical equipment, collect fault hidden danger data in the ventilation system pipeline in the building where the electrical equipment is located, and output the hidden danger feature data and fault hidden danger data through the configured wireless communication unit;

[0034] S2. Receive fault potential data, generate a comprehensive index at the same time based on the fault potential data, and monitor the change trend of the comprehensive index at each time in real time without adjusting the ventilation system, and use a sliding window algorithm to monitor and choose whether to issue an early warning signal. Under the condition of issuing an early warning signal, trigger an alternative adjustment strategy;

[0035] S3. Receive hidden danger characteristic data, and when the real-time carbon monoxide concentration is detected to exceed the set standard range value, issue a first-level alarm signal; when the volatile organic compound concentration is detected or the carbon monoxide concentration is within the standard range value, issue a second-level alarm signal and execute the preset hidden danger assessment strategy; when the carbon monoxide concentration is detected to be lower than the standard range value, no response is made;

[0036] S4. Upon receiving a first-level alarm signal, immediately notify the fire department online and activate the fire-fighting equipment in the corresponding electrical equipment.

[0037] An electronic device includes a processor coupled to a memory;

[0038] The memory is used to store computer programs;

[0039] The processor is used to call the computer program stored in the memory to implement the above method.

[0040] The present invention has the following beneficial effects:

[0041] The present invention receives ventilation system fault hidden danger data, generates a comprehensive index at the same moment based on the data, monitors the changing trend of the comprehensive index in real time, and adopts a sliding window algorithm for continuous monitoring. It can promptly identify abnormal operation or failure of the ventilation system, and start the backup ventilation system under the condition of determining the failure, thereby effectively improving the reliability and safety of the ventilation system, ensuring continuous safe ventilation operation in high-rise buildings, and reducing the negative impact that may be caused by sudden failures.

[0042] After receiving real-time carbon monoxide concentration data, the present invention makes judgments and classifications based on the dynamically adjusted standard range value. When the carbon monoxide concentration exceeds or is within the set standard range value, a first-level or second-level alarm signal can be immediately issued to indicate possible electrical equipment combustion or fire hazards. A comprehensive evaluation is performed based on various parameters in the hazard characteristic data. The generated fire hazard estimate is not only used to reflect the severity of the fire hazard of the corresponding electrical equipment, but also can determine the inspection priority of the electrical equipment to ensure that high-risk equipment is inspected first, thereby minimizing the fire risk.

[0043] In the present invention, the dynamic adjustment of the standard range value can calculate the most suitable carbon monoxide concentration range according to historical test data and real-time environmental conditions, thereby ensuring the accuracy and timeliness of the alarm under different ventilation conditions.

[0044] In the present invention, after receiving the alarm signal, corresponding safety measures are immediately taken, such as alarm notification, evacuation of personnel or initiation of emergency measures, to effectively ensure the safety of personnel and equipment.

[0045] In summary, the present invention significantly improves the safety management capabilities of the internal environment of high-rise buildings through real-time monitoring, dynamic adjustment and fire hazard assessment, ensures the safety and stability of equipment operation, and effectively prevents and monitors potential fire risks, providing reliable safety protection for residents and operators in the building. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a schematic diagram of the module structure of the system of the present invention;

[0047] Figure 2 The figure is a flow chart of the overall steps of the method of the present invention. DETAILED DESCRIPTION

[0048] The technical solutions in the embodiments of the present invention are clearly and completely described below in conjunction with the accompanying drawings.

[0049] Example 1: Figure 1 As shown, this embodiment provides a high-rise building electrical fire hazard characteristic gas monitoring system, the main research and development ideas of the system are:

[0050] By combining various sensors to monitor and analyze gas, temperature and load of electrical equipment, it is possible to preliminarily determine whether combustion or thermal decomposition occurs in the corresponding electrical equipment. In the case of thermal decomposition, it means that there is a fire hazard in the electrical equipment, and the normal use of the electrical equipment can continue, but personnel still need to be dispatched in time for inspection and maintenance; in the case of combustion, it is necessary to immediately cut off the power supply to reduce losses, and when determining whether combustion or thermal decomposition occurs in the electrical equipment, the threshold setting is dynamically adjusted to ensure the accuracy of the determination result.

[0051] For high-rise buildings, the safety of personnel needs to be given priority consideration. Therefore, when monitoring electrical equipment, it is also necessary to diagnose the ventilation system in the building to ensure that the ventilation system can be used normally, thereby avoiding toxic and harmful gases produced by combustion or thermal decomposition that threaten the safety of personnel.

[0052] Hardware design:

[0053] The monitoring system includes:

[0054] The sensor network module collects hidden danger characteristic data in the corresponding electrical equipment, collects fault hidden danger data in the ventilation system pipeline in the building where the electrical equipment is located, and outputs the hidden danger characteristic data and the fault hidden danger data through the configured wireless communication unit;

[0055] Among them, a number of electrical equipment are installed in high-rise buildings, and the several electrical equipment together constitute a complete set of electrical facilities, and the electrical equipment includes but is not limited to: elevator control cabinets and building power distribution cabinets.

[0056] Hidden danger characteristic data include:

[0057] Gas data set: carbon monoxide concentration, volatile organic compound concentration (VOCs); air velocity data set: upper wind speed and lower wind speed; load data: represents real-time output power;

[0058] For gas data sets, a gas concentration sensor installed in the corresponding electrical equipment is required. The gas concentration sensor is integrated by a specific gas sensor group, including a carbon monoxide sensor and a VOCs sensor. Some models of single gas sensors are specifically used to detect carbon monoxide concentrations, such as the MQ-7 sensor; it can accurately measure carbon monoxide concentrations and is often used in environmental monitoring and safety applications; for the detection of volatile organic compounds, a dedicated VOCs sensor is usually used, such as the CCS811 sensor, which can quickly respond to a variety of volatile organic compounds and output corresponding concentration data for indoor air quality monitoring and industrial applications.

[0059] For the air velocity data set, an air velocity sensor installed in the corresponding electrical equipment is required. The space in the electrical equipment is divided into two parts, the upper and lower parts, and then the air velocity sensor is installed in the middle of the upper and lower parts. The TSI 9515 hot wire wind speed sensor is used. It uses hot wire technology to measure very low air velocity with high accuracy and fast response. It is often used in laboratory research, air conditioning system debugging and airflow dynamic analysis.

[0060] For load data, a power sensor installed on the output circuit end of the corresponding electrical equipment is required to detect the output power of the corresponding electrical equipment in real time.

[0061] The building where the electrical equipment is located is the corresponding high-rise building. It is not easy for people in the high-rise building to escape, so it is necessary to add a fault diagnosis module to ensure that the ventilation system in the building can be used normally, thereby reducing the danger of fire to people on high floors.

[0062] The ventilation system pipeline in the building where the electrical equipment is located represents the ventilation system installed in the building. The pipeline is the main ventilation duct, and all the branch pipes are connected to the main ventilation duct. The configuration of the ventilation system will not be described in detail here.

[0063] Fault potential data include:

[0064] Real-time pipeline temperature and pipeline air flow values;

[0065] For the pipe temperature value, an air temperature sensor installed in the center of the ventilation system pipe is needed to detect the temperature of the passing gas. The data obtained is the pipe temperature value;

[0066] For the pipeline air flow value, an air flow sensor installed in the center of the ventilation system pipeline is needed to detect the flow of gas passing through. The obtained data set is the pipeline air flow value; the air flow sensor uses an ultrasonic flow sensor: the propagation speed of ultrasound is used to measure the speed of the fluid, thereby calculating the flow rate. It can be installed in the center of the pipeline and indirectly calculate the air flow by measuring the air flow rate.

[0067] The wireless communication unit is configured in the sensor network module and uses wireless communication technology, such as 5G and WiFi technology, to wirelessly transmit hidden danger feature data and fault hidden danger data to the data processing center module to facilitate subsequent processing and analysis operations.

[0068] Software Design:

[0069] The monitoring system also includes:

[0070] The fault diagnosis module receives the fault potential data, generates the comprehensive index at the same time based on the fault potential data, and monitors the change trend of the comprehensive index at each time in real time without adjusting the ventilation system. It also uses the sliding window algorithm to monitor and choose whether to issue an early warning signal. If an early warning signal is issued, the alternative adjustment strategy is triggered. Otherwise, no response action is taken.

[0071] Among them, the formula used to generate the comprehensive index at the same time based on the fault hidden danger data is:

[0072] ;

[0073] In the formula, represents the comprehensive index at the same time, t represents the time, , They represent the pipeline temperature value and pipeline air flow value at the same time respectively. , is the weight coefficient, , ,and Before calculating the comprehensive index, the pipeline temperature value and pipeline air flow value need to be dimensionless to remove the units of the corresponding data.

[0074] The monitoring process using the sliding window algorithm is as follows:

[0075] The historical data is set as: the comprehensive index of the ventilation system in the high-rise building at each moment under normal working conditions within the preset time period T; based on the historical data, the sliding window algorithm is used to maintain the window of the fixed time period T, and the mean of the comprehensive index corresponding to each moment in the window is calculated, and then the current comprehensive index is compared with the mean in the window. If the difference between the two exceeds the preset deviation threshold, an early warning signal is issued; the difference between the two here represents: the absolute value of the difference between the current comprehensive index and the mean in the window;

[0076] When the warning signal is issued, it means that there is a fault in the originally running ventilation system, so it is necessary to trigger an alternative adjustment strategy, which is: disconnect the power supply of the original ventilation system and turn on the power supply of the backup ventilation system; in order to ensure continuous ventilation operations in high-rise buildings, it is necessary to set up at least two ventilation systems in the building to deal with emergencies.

[0077] Receive ventilation system fault hidden danger data and generate a comprehensive index at the same time based on this data. By real-time monitoring of the changing trend of the comprehensive index and continuous monitoring using a sliding window algorithm, it can promptly identify abnormal operation or failure of the ventilation system and start the backup ventilation system when a failure is determined. This effectively improves the reliability and safety of the ventilation system, ensures continuous safe ventilation operation in high-rise buildings, and reduces the negative impact that may be caused by sudden failures.

[0078] The data processing center module receives the hidden danger characteristic data. When it is detected that the real-time carbon monoxide concentration exceeds the set standard range value, it indicates that the corresponding electrical equipment is burning and a first-level alarm signal is issued; when it is detected that there is a volatile organic compound concentration or the carbon monoxide concentration is within the standard range value, it indicates that the corresponding electrical equipment is thermally decomposed and has a fire hazard, a second-level alarm signal is issued, and a preset hidden danger assessment strategy is executed; when it is detected that the carbon monoxide concentration is lower than the standard range value, it indicates that the corresponding electrical equipment is normal;

[0079] The following table shows example data for each case:

[0080] Table 1 Example data of carbon monoxide concentration

[0081] Coincidence with the endpoint of the standard range value belongs to being within the standard range value;

[0082] Among them, the standard range value is set using a dynamic adjustment unit built into the data processing center module;

[0083] The historical test data is set as follows: the carbon monoxide concentration corresponding to each moment of the electrical equipment under normal operating conditions within a preset time period T; the dynamic adjustment unit summarizes the historical test data, extracts the maximum and minimum values ​​of the carbon monoxide concentration variation range in the historical test data, and generates the minimum value in the standard range value based on the maximum value of the carbon monoxide concentration variation range and the air flow rate data set. The maximum value in the standard range value is a fixed value and is set according to actual conditions.

[0084] For example, a scenario corresponding to this embodiment is:

[0085] In the indoor environment monitoring of high-rise buildings, the critical value of carbon monoxide concentration, that is, the fixed value, is: 100ppm; if the concentration of carbon monoxide exceeds 100ppm, it indicates that there is combustion; for example: suppose the carbon monoxide concentration is monitored in the electrical equipment of a high-rise building room, and the monitoring equipment detects that the carbon monoxide concentration in the electrical equipment reaches 150ppm, then it may indicate that there is combustion in the electrical equipment, which may be due to the accumulation of carbon monoxide caused by incomplete combustion; the system should immediately issue an alarm and take corresponding safety measures, such as evacuating personnel and notifying relevant departments to conduct inspection and handling;

[0086] Among them, the minimum value in the standard range needs to take ventilation conditions into consideration. If the ventilation conditions are good, the minimum value will continue to be dynamically adjusted to become smaller according to the ventilation conditions. Due to the indoor air flow and the effect of the cooling fan, the ventilation conditions change dynamically.

[0087] The process of generating the minimum value in the standard range is:

[0088] According to the air velocity data set, the average wind speed of the upper wind speed and the lower wind speed of the corresponding electrical equipment is calculated. The higher the average wind speed, the better the ventilation effect. According to the pre-processed average wind speed and the maximum value of the carbon monoxide concentration range, the minimum value in the standard range is generated. The formula is as follows:

[0089] ;

[0090] In the formula, Indicates the minimum value in the standard range. Indicates the maximum value of the carbon monoxide concentration range. Indicates the upper wind speed, Indicates the lower wind speed, , are preset proportional coefficients, and ; The preprocessing process of the mean wind speed and the maximum value of the carbon monoxide concentration range is: normalization processing;

[0091] The standard range values ​​are expressed as , Indicates the maximum value in the standard range. Indicates the minimum value in the standard range;

[0092] The preset hidden danger assessment strategy is:

[0093] The carbon monoxide concentration, air velocity data set and load data in the hidden danger feature data are dimensionless processed, and the carbon monoxide concentration, wind speed average and load data at different times within the preset time period T are obtained and the fire hazard estimated value Hug reflecting the degree of fire hazard of the corresponding electrical equipment is generated. The fire hazard estimated value Hug corresponding to several electrical equipment is compared and analyzed, and the inspection priority is limited by the following methods:

[0094] ;

[0095] ;

[0096] In the formula, Indicates the maximum value of carbon monoxide concentration within the time period T, represents the maximum value of the mean wind speed within the time period T, represents the output power at each time i in the time period T, , n is a positive integer, and n=T, Indicates the time period T The average value of , , They are preset proportional coefficients, and both are greater than 0; It indicates that the inspection priority is positively correlated with the fire hazard estimated value Hug. Therefore, the larger the fire hazard estimated value Hug of the corresponding electrical equipment is, the higher the inspection priority is. For the corresponding electrical equipment with the largest fire hazard estimated value Hug, the first priority inspection is required.

[0097] After receiving real-time carbon monoxide concentration data, judgment and classification are performed based on the dynamically adjusted standard range value. When the carbon monoxide concentration exceeds or is within the set standard range value, a level 1 or level 2 alarm signal can be immediately issued to indicate possible electrical equipment combustion or fire hazards. A comprehensive assessment is performed based on the various parameters in the hazard characteristic data. The generated fire hazard estimate is not only used to reflect the severity of the fire hazard of the corresponding electrical equipment, but also to determine the inspection priority of the electrical equipment, ensuring that high-risk equipment is inspected first, thereby minimizing the fire risk.

[0098] Dynamic adjustment of the standard range value can calculate the most suitable carbon monoxide concentration range based on historical test data and real-time environmental conditions, thereby ensuring the accuracy and timeliness of the alarm under different ventilation conditions;

[0099] The alarm and notification module, upon receiving a first-level alarm signal, immediately notifies the fire department through the Internet and starts the fire-fighting equipment in the corresponding electrical equipment. The fire-fighting equipment includes a vacuum control device and a dry powder fire extinguisher, and the vacuum control device includes a plurality of port sealing gates and a vacuum generator. The plurality of port sealing gates are arranged on the surface of the corresponding equipment near the port, and the port therein includes a heat dissipation port, an equipment interface, and any passage connecting the outside world with the inner cavity of the corresponding electrical equipment. The plurality of port sealing gates are used to block the corresponding port after closing, and the vacuum generator is installed in the corresponding electrical equipment. The specific equipment structure will not be elaborated here.

[0100] The process of activating fire extinguishing equipment is:

[0101] Issue a command to close each port closing gate, and then the port closing gate will complete the closing action about 1~2s after closing the corresponding port, and finally start the vacuum generator to form a vacuum environment for the corresponding electrical equipment, isolating oxygen to achieve the effect of fire extinguishing. This type of fire extinguishing equipment is driven by a separate power supply; the fire extinguishing equipment mentioned here is also part of the hardware design;

[0102] The purpose of notifying the fire department is to ensure that firefighters can rush to the address where the notification is issued as soon as possible after receiving the alarm, so as to achieve the purpose of fire extinguishing and disaster relief.

[0103] After receiving the alarm signal, immediately take corresponding safety measures, such as alarm notification, evacuation of personnel or initiation of emergency measures, to effectively ensure the safety of personnel and equipment;

[0104] In summary, this embodiment significantly improves the safety management capabilities of the internal environment of high-rise buildings through real-time monitoring, dynamic adjustment and fire hazard assessment, ensures the safety and stability of equipment operation, and effectively prevents and monitors potential fire risks, providing reliable safety protection for residents and operators in the building.

[0105] Example 2: Figure 2 As shown, based on the system of Example 1, the method for monitoring characteristic gases of electrical fire hazards in high-rise buildings includes the following specific steps:

[0106] S1. Collect hidden danger feature data in the corresponding electrical equipment, collect fault hidden danger data in the ventilation system pipeline in the building where the electrical equipment is located, and output the hidden danger feature data and fault hidden danger data through the configured wireless communication unit;

[0107] S2. Receive fault potential data, generate a comprehensive index at the same time based on the fault potential data, and monitor the change trend of the comprehensive index at each time in real time without adjusting the ventilation system, and use a sliding window algorithm to monitor and choose whether to issue an early warning signal. Under the condition of issuing an early warning signal, trigger an alternative adjustment strategy;

[0108] S3. Receive hidden danger characteristic data, and when the real-time carbon monoxide concentration is detected to exceed the set standard range value, issue a first-level alarm signal; when the volatile organic compound concentration is detected or the carbon monoxide concentration is within the standard range value, issue a second-level alarm signal and execute the preset hidden danger assessment strategy; when the carbon monoxide concentration is detected to be lower than the standard range value, no response is made;

[0109] S4. Upon receiving a first-level alarm signal, immediately notify the fire department online and activate the fire-fighting equipment in the corresponding electrical equipment.

[0110] Embodiment 3: An electronic device includes a processor, wherein the processor is coupled to a memory;

[0111] The memory is used to store computer programs;

[0112] The processor is used to call the computer program stored in the memory to implement the method described in Example 2.

[0113] In the above embodiments, the several formulas involved are all calculated by taking the numerical values ​​after removing the dimension, and the formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation, and the formula is set by technicians in this field according to the actual situation. The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product.

Claims

1. High-rise building electrical fire hazard characteristic gas monitoring system, characterized by: include: The sensor network module collects hidden danger characteristic data in the corresponding electrical equipment, collects fault hidden danger data in the ventilation system pipeline in the building where the electrical equipment is located, and outputs the hidden danger characteristic data and the fault hidden danger data through the configured wireless communication unit; The fault diagnosis module receives the fault potential data, generates the comprehensive index at the same time based on the fault potential data, and monitors the change trend of the comprehensive index at each time in real time without adjusting the ventilation system. It also uses the sliding window algorithm to monitor and choose whether to issue an early warning signal. If an early warning signal is issued, it triggers the alternative adjustment strategy. The data processing center module receives the hidden danger characteristic data and issues a first-level alarm signal when it detects that the real-time carbon monoxide concentration exceeds the set standard range value; when it detects that there is a volatile organic compound concentration or the carbon monoxide concentration is within the standard range value, it issues a second-level alarm signal and executes the preset hidden danger assessment strategy; when it detects that the carbon monoxide concentration is lower than the standard range value, it does not respond; The standard range value is set using the dynamic adjustment unit built into the data processing center module; The historical test data is set as: the carbon monoxide concentration corresponding to each moment of the electrical equipment under normal operating conditions within a preset time period T; the dynamic adjustment unit summarizes the historical test data, extracts the maximum and minimum values ​​of the carbon monoxide concentration variation range in the historical test data, and generates the minimum value in the standard range value based on the maximum value of the carbon monoxide concentration variation range and the air flow rate data set, and the maximum value in the standard range value is a fixed value; The process of generating the minimum value in the standard range is: According to the air velocity data set, the wind speed average of the upper wind speed and the lower wind speed in the corresponding electrical equipment is calculated. According to the pre-processed wind speed average and the maximum value of the carbon monoxide concentration variation range, the minimum value in the standard range is generated. The formula is as follows: ； In the formula, Indicates the maximum value of the carbon monoxide concentration range. Indicates the upper wind speed, Indicates the lower wind speed, , are preset proportional coefficients, and ; The standard range values ​​are expressed as , Indicates the maximum value in the standard range. Indicates the minimum value in the standard range; The alarm and notification module, upon receiving a first-level alarm signal, immediately notifies the fire department through the Internet and activates the fire-fighting equipment in the corresponding electrical equipment.

2. The high-rise building electrical fire hazard characteristic gas monitoring system according to claim 1 is characterized in that: Several electrical equipment are installed in high-rise buildings, and several electrical equipment together constitute a complete set of electrical facilities; Hidden danger characteristic data include: Gas data sets, including carbon monoxide concentration and volatile organic compound concentration; air velocity data sets, including upper wind speed and lower wind speed; load data, including real-time output power; Fault potential data include: real-time pipeline temperature value and pipeline air flow value.

3. The high-rise building electrical fire hazard characteristic gas monitoring system according to claim 2 is characterized in that: The comprehensive index at the same time is generated based on the fault potential data. The formula used is: ； In the formula, represents the comprehensive index at the same time, t represents the time, , They represent the pipeline temperature value and pipeline air flow value at the same time respectively. , is the weight coefficient, , ,and .

4. The high-rise building electrical fire hazard characteristic gas monitoring system according to claim 3 is characterized in that: The monitoring process using the sliding window algorithm is as follows: The historical data is set as: the comprehensive index of the ventilation system in a high-rise building at each moment under normal working conditions within a preset time period T; based on the historical data, a sliding window algorithm is used to maintain the window of the fixed time period T, and the mean of the comprehensive index corresponding to each moment in the window is calculated, and then the current comprehensive index is compared with the mean in the window. If the difference between the two exceeds the preset deviation threshold, an early warning signal is issued.

5. The high-rise building electrical fire hazard characteristic gas monitoring system according to claim 4 is characterized in that: The alternative adjustment strategy is to disconnect the power supply of the original ventilation system and turn on the power supply of the backup ventilation system.

6. The high-rise building electrical fire hazard characteristic gas monitoring system according to claim 1 is characterized in that: The preset hidden danger assessment strategy is: The carbon monoxide concentration, air velocity data set and load data in the hidden danger feature data are dimensionless processed, and the fire hazard estimated value Hug is generated based on the carbon monoxide concentration, wind speed average and load data at different times within the preset time period T. The fire hazard estimated value Hug corresponding to several electrical equipment is compared and analyzed, and the inspection priority is limited by the following methods: ； ； In the formula, Indicates the maximum value of carbon monoxide concentration within the time period T, represents the maximum value of the mean wind speed within the time period T, represents the output power at each time i in the time period T, , n is a positive integer, and n=T, Indicates the time period T The average value of It indicates that the inspection priority is positively correlated with the fire hazard estimate Hug. , , are preset proportional coefficients respectively, and both are greater than 0.

7. A method for monitoring characteristic gases of electrical fire hazards in high-rise buildings, based on the system according to any one of claims 1 to 6, characterized in that The steps include: S1. Collect hidden danger feature data in the corresponding electrical equipment, collect fault hidden danger data in the ventilation system pipeline in the building where the electrical equipment is located, and output the hidden danger feature data and fault hidden danger data through the configured wireless communication unit; S2. Receive fault potential data, generate a comprehensive index at the same time based on the fault potential data, and monitor the change trend of the comprehensive index at each time in real time without adjusting the ventilation system, and use a sliding window algorithm to monitor and choose whether to issue an early warning signal. Under the condition of issuing an early warning signal, trigger an alternative adjustment strategy; S3. Receive hidden danger characteristic data, and when the real-time carbon monoxide concentration is detected to exceed the set standard range value, issue a first-level alarm signal; when the volatile organic compound concentration is detected or the carbon monoxide concentration is within the standard range value, issue a second-level alarm signal and execute the preset hidden danger assessment strategy; when the carbon monoxide concentration is detected to be lower than the standard range value, no response is made; S4. Upon receiving a first-level alarm signal, immediately notify the fire department online and activate the fire-fighting equipment in the corresponding electrical equipment.

8. An electronic device, characterized in that: comprising a processor coupled to a memory; The memory is used to store computer programs; The processor is used to call the computer program stored in the memory to implement the method described in claim 7.

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