CN115620477A - Fire engineering construction is with real-time fire prevention monitoring data transmission system - Google Patents
Fire engineering construction is with real-time fire prevention monitoring data transmission system Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/02—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP]
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/10—Actuation by presence of smoke or gases, e.g. automatic alarm devices for analysing flowing fluid materials by the use of optical means
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/12—Actuation by presence of radiation or particles, e.g. of infrared radiation or of ions
- G08B17/125—Actuation by presence of radiation or particles, e.g. of infrared radiation or of ions by using a video camera to detect fire or smoke
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/12—Alarms for ensuring the safety of persons responsive to undesired emission of substances, e.g. pollution alarms
- G08B21/16—Combustible gas alarms
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/182—Level alarms, e.g. alarms responsive to variables exceeding a threshold
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/185—Electrical failure alarms
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B25/00—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems
- G08B25/01—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium
- G08B25/08—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium using communication transmission lines
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B7/00—Signalling systems according to more than one of groups G08B3/00 - G08B6/00; Personal calling systems according to more than one of groups G08B3/00 - G08B6/00
- G08B7/06—Signalling systems according to more than one of groups G08B3/00 - G08B6/00; Personal calling systems according to more than one of groups G08B3/00 - G08B6/00 using electric transmission, e.g. involving audible and visible signalling through the use of sound and light sources
- G08B7/066—Signalling systems according to more than one of groups G08B3/00 - G08B6/00; Personal calling systems according to more than one of groups G08B3/00 - G08B6/00 using electric transmission, e.g. involving audible and visible signalling through the use of sound and light sources guiding along a path, e.g. evacuation path lighting strip
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
Abstract
The invention discloses a real-time fire prevention monitoring data transmission system for fire engineering construction, relates to the technical field of fire protection systems, and aims to solve the technical problems that in the prior art, the system only can play a role in fire monitoring data transmission, but cannot analyze data, perform early warning on fire and is low in safety. The system comprises a SaaS service platform, a PaaS service platform, an IaaS service model and a perception layer; the SaaS service platform comprises a Web end and an APP end, and the home page of the SaaS service platform comprises: role management, project profiles, equipment status, equipment classification, equipment alarm information, alarm classification, alarm statistics, and equipment ledger information. The system can inquire data through a Web end and an APP end, is more convenient to use, senses the front end data by utilizing a sensing layer, transmits fire monitoring data through a PaaS service platform and an IaaS service model, and carries out fire early warning, so that the possibility of fire occurrence is reduced, and the safety of the system is improved.
Description
Technical Field
The invention belongs to the technical field of fire-fighting systems, and particularly relates to a real-time fire prevention monitoring data transmission system for fire engineering construction.
Background
The fire threatens the life and property safety of people from ancient times to present, and the phenomenon of fire is constantly occurring in modern society today, and now the urbanization develops rapidly, and various buildings are more and more intensive, once a fire happens, the fire will produce the potential safety hazard to surrounding buildings, even arouse the associated reaction, produce the loss to social family.
Along with the development of internet technology, internet technology has begun to be applied to in many different fields, especially in recent years, along with the proposition of national proposition wisdom city construction theory, wisdom fire control has begun formally to enter into people's the field of vision also, can in time and high-efficiently find out the problem that fire safety control management work carries out the in-process and probably produces based on internet of things, when the conflagration breaks out, in time will transmit fire information, thereby can put out the conflagration fast, but current system only can play conflagration control data transmission's effect, and can not carry out the analysis to data, carry out the early warning to the conflagration, the security is lower.
Therefore, in order to solve the above problem that the fire alarm cannot be performed, it is necessary to improve the usage scenario of the system.
Disclosure of Invention
(1) Technical problem to be solved
Aiming at the defects of the prior art, the invention aims to provide a real-time fire prevention monitoring data transmission system for fire engineering construction, which aims to solve the technical problems that in the prior art, the system only can play a role in fire monitoring data transmission, but cannot analyze data, perform early warning on fire and has low safety.
(2) Technical scheme
In order to solve the technical problem, the invention provides a real-time fire prevention monitoring data transmission system for fire engineering construction, which comprises a SaaS service platform, a PaaS service platform, an IaaS service model and a sensing layer;
the SaaS service platform comprises a Web end and an APP end, and the home page of the SaaS service platform comprises: role management, project overview, equipment state, equipment classification, equipment alarm information, alarm classification, alarm statistics and equipment ledger information;
the PaaS service platform comprises fire service management and data analysis and decision assistance, the fire service management comprises an intelligent power utilization subsystem, a fire alarm subsystem, a fire equipment management subsystem, a smoke prevention and discharge subsystem, a fire water subsystem, an emergency lighting and evacuation subsystem, a fire door subsystem, a fire equipment power subsystem and a video monitoring subsystem, the intelligent power utilization subsystem can be connected with an electric fire, an arc isolated, an electric fire host, an arc extinguishing type protector detector and a wireless temperature measurement detector, the fire alarm subsystem manages all fire equipment and assets of each building and project node, emphasizes address labeling of fire hydrants, fire extinguishers, spraying and fire fighting teams, brings daily inspection and maintenance into a plan, and the smoke prevention and discharge subsystem acquires smoke, harmful gas and fire extinguishing information data, detecting smog in real time second level, firstly, finding that the monitored number exceeds a risk threshold value, alarming by APP, short messages and telephones, and rapidly informing owners and property fire control units of the specific hidden fire situation based on the label and geographical position location of equipment, wherein the fire water subsystem can be connected with a fire hydrant, a fire water pressure and water level sensor and is used for monitoring the pressure and the liquid level of a fire water pipe network in real time so as to judge whether water leakage occurs or not, the water pressure threshold value and the liquid level threshold value are preset in the fire water subsystem, when the water leakage occurs in the pipe network, the real-time water pressure is smaller than the water pressure threshold value and/or the real-time liquid level is smaller than the liquid level threshold value, the fire water subsystem sends out an alarm in real time, the emergency lighting and evacuation subsystem is used for monitoring and controlling each emergency lamp in real time, and when a fire occurs, a safe evacuation path indication can be accurately given, the fire fighting equipment power supply subsystem monitors the power supply working state of each part of a fire fighting system in real time and gives alarm prompts to overvoltage, undervoltage, overcurrent, short circuit and open circuit faults generated by power supplies of each part, the video monitoring subsystem can adjust a monitoring camera image related to an alarm position after receiving alarm information of each subsystem, and checks video assistance of an alarm site to confirm fire conditions, and the data analysis and decision assistance comprises report statistics, three-color early warning and multi-dimensional data display;
the system comprises an IaaS service model, a remote monitoring system and a remote monitoring system, wherein the IaaS service model comprises a fire safety index model and hidden danger and early warning intelligent analysis, the database type of the IaaS service model comprises MySQL, mongoDB and Redis, the functions of the hidden danger and early warning intelligent analysis comprise hidden danger query, hidden danger distribution, hidden danger processing and hidden danger analysis, the hidden danger analysis analyzes the safety state of equipment based on the fire safety index model and calculates a comprehensive score, five safety level states are preset in the hidden danger and early warning intelligent analysis, and the five states are respectively unsafe, relatively unsafe, general safety, relatively safe and very safe according to the comprehensive score from low to high;
the sensing layer comprises fire-fighting front-end equipment and a fire alarm control host which are deployed at each data acquisition point, and the acquired data are uploaded to a PaaS service platform.
When the system of the technical scheme is used, the system logs in through a Web end or an APP end, and the following operations can be performed through the home page of the SaaS service platform: role management, project general inquiry, equipment state inquiry, equipment classification inquiry, equipment alarm information inquiry, alarm classification inquiry, alarm statistics inquiry and equipment account information inquiry, fire-fighting front-end equipment deployed at each data acquisition point acquires data and uploads the acquired data to a PaaS service platform, wherein the PaaS service platform comprises fire-fighting service management and data analysis and decision assistance, the fire-fighting service management comprises an intelligent power utilization subsystem, a fire alarm subsystem, a fire-fighting equipment management subsystem, a smoke-proof subsystem, a fire-fighting water subsystem, an emergency lighting and evacuation subsystem, a fire door subsystem, a fire-fighting equipment power subsystem and a video monitoring subsystem, the intelligent power utilization subsystem can be connected with an electric fire, an arc, an electric fire host, an arc-extinguishing type protector detector, a wireless temperature measurement detector and a fire alarm subsystem, the fire-fighting equipment management subsystem brings all fire-fighting equipment and assets of each building and project node into management, addresses of fire hydrants, fire extinguishers, spraying and fire fighting teams are highlighted, daily routing inspection and maintenance are brought into a plan, the smoke-preventing and exhausting subsystem acquires smoke, harmful gas and gas fire-extinguishing information data, detects smoke in real time and second level, and firstly, finds that monitoring times exceed risk threshold values, gives an alarm through APP, short messages and telephones, and quickly informs owners and property fire-fighting units of specific positions of fire hidden situations based on labels and geographical position positioning of the equipment, the fire-fighting water subsystem can be connected with a fire hydrant, a fire-fighting water pressure sensor and a water level sensor and is used for monitoring the pressure and the liquid level of a fire-fighting water pipe network in real time so as to judge whether water leakage exists or not, a water pressure threshold value and a liquid level threshold value are preset in the fire-fighting water subsystem, and when the pipe network leaks water, the real-time water pressure is smaller than the water pressure threshold value and/or the real-time liquid level is smaller than the liquid level threshold value, the fire-fighting water subsystem sends out an alarm in real time, the emergency lighting and evacuation subsystem is used for monitoring and controlling each emergency lamp in real time, when a fire disaster occurs, safe evacuation path indication can be accurately given, the indication direction and the emergency lighting lamp of the fire-fighting emergency indicator lamp are intelligently turned on, the fire-fighting subsystem is in association with gate inhibition alarm and video identification, a fire passage, a safety exit and a life passage are monitored in real time, the opening and closing of a fire door and the stacking condition of the fire passage are realized, the opening and closing control function under the emergency condition is realized, the fire-fighting equipment power subsystem monitors the power working state of each part of the fire-fighting system in real time, and the alarm prompt of overvoltage, undervoltage, overcurrent, short circuit and open circuit faults generated by each part of a power supply is given out, after the video monitoring subsystem receives alarm information of each subsystem, a monitoring camera image related to the alarm position can be given out, the video assistance on the alarm site is checked to confirm the fire condition, the data analysis and decision assistance comprises a report form, three-color early warning and multi-dimensional data display, meanwhile, the IaaS service model comprises a fire safety index model and an intelligent analysis, and an early warning index model, and the construction flow of the fire safety index model comprises: identifying a danger source, determining an initial node of a Bayesian network, establishing a risk Bayesian network structure diagram according to the Bayesian network initial node formed in the process of identifying the danger source and combining expert knowledge because no historical case exists in an inference case library, storing a corresponding Bayesian network structure diagram formed, adopting a Bayesian network structure based on structure learning after inference cases are accumulated in the inference case library, extracting similar historical cases from the Bayesian network inference case library, performing pruning and recombination operations to form a new Bayesian network structure meeting requirements, storing the new Bayesian network structure into a case list after assessment, gradually forming a case library of a multi-inference structure, setting states of each network node, setting conditional probability and prior probability by using expert knowledge, then determining weights by using a hierarchical analysis method, obtaining a comprehensive score, analyzing the safety state of equipment based on a fire fighting safety index model, calculating the comprehensive state of the equipment, calculating the comprehensive score and pre-setting safety state, and comparing five safety grades according to a high safety state, a safety early warning, and five safety grades.
Further, the APP side supports Android and IOS operating systems, and login conditions of the SaaS service platform include a user name and a password.
Further, the role management can be performed by customizing the operation authority owned by the user by an administrator according to the identity of the user.
Further, the three-color early warning is divided into the following levels from high to low: red early warning, yellow early warning and green early warning.
Further, the fire fighting front end equipment includes, but is not limited to: the fire-fighting emergency lighting and evacuation system comprises a camera, a smoke sensor, a combustible gas detector, a fire-fighting emergency lighting and evacuation indication host, a fire door monitoring host, a fire-fighting equipment power supply monitoring host and an electric fire monitoring host.
Furthermore, the data in the database comprises service data and map data, wherein the service data comprises equipment point location information, detector detection data, fire alarm information, video data and equipment operation state data, and the map data is a GIS electronic map.
Further, the fire fighting system components monitored by the fire fighting equipment power subsystem in real time include, but are not limited to: fire alarm host computer, floor display, water pump, spray pump and elevator.
Further, the construction process of the fire safety index model comprises the following steps: identifying a danger source, determining initial nodes of a Bayesian network, establishing a risk Bayesian network structure diagram according to Bayesian network initial nodes formed in the danger source identification process by combining expert knowledge as a historical case does not exist in an inference case library, storing corresponding Bayesian network files formed, adopting a Bayesian network construction based on structure learning after inference cases are accumulated in the inference case library, extracting similar historical cases from the Bayesian network inference case library, performing pruning and recombination operations to form a new Bayesian network structure meeting requirements, storing the new Bayesian network structure into a case list after evaluation, gradually forming a case library with multiple inference structures, setting states of each network node, setting conditional probability and prior probability by using expert knowledge, determining weights by using a hierarchical analysis method, and obtaining comprehensive scores.
(3) Advantageous effects
Compared with the prior art, the invention has the beneficial effects that: the system can inquire data through the Web end and the APP end, is more convenient to use, senses front-end data through the sensing layer, transmits fire monitoring data through the PaaS service platform and the IaaS service model, analyzes the data, and carries out fire early warning before a fire happens, so that the possibility of fire occurrence is reduced, and the safety of the system is improved.
Drawings
FIG. 1 is an overall architecture diagram of one embodiment of the system of the present invention;
FIG. 2 is a block diagram of a fire safety index model in one embodiment of the system of the present invention;
FIG. 3 is a schematic diagram of a defense business management architecture in one embodiment of the system of the present invention;
FIG. 4 is a schematic diagram of a data analysis and decision support architecture in accordance with an embodiment of the present invention.
Detailed Description
The specific embodiment is a real-time fire prevention monitoring data transmission system for fire engineering construction, the overall architecture diagram of which is shown in fig. 1, wherein the structure diagram of a fire safety index model is shown in fig. 2, and the system comprises a SaaS service platform, a PaaS service platform, an IaaS service model and a sensing layer;
the SaaS service platform comprises a Web end and an APP end, and the home page of the SaaS service platform comprises: role management, project overview, equipment state, equipment classification, equipment alarm information, alarm classification, alarm statistics and equipment ledger information;
the PaaS service platform comprises fire service management and data analysis and decision assistance, the fire service management comprises an intelligent power utilization subsystem, a fire alarm subsystem, a fire equipment management subsystem, a smoke prevention and discharge subsystem, a fire water subsystem, an emergency lighting and evacuation subsystem, a fire door subsystem, a fire equipment power subsystem and a video monitoring subsystem, the intelligent power utilization subsystem can be connected with an electric fire, an arc isolated, an electric fire host, an arc extinguishing type protector detector and a wireless temperature measurement detector, the fire alarm subsystem manages all fire equipment and assets of each building and project node, emphasizes address labeling of fire hydrants, fire extinguishers, spraying and fire fighting teams, brings daily inspection and maintenance into a plan, and the smoke prevention and discharge subsystem acquires smoke, harmful gas and fire extinguishing information data, detecting smog in real time second level, firstly, finding that the monitored number exceeds a risk threshold value, alarming by APP, short messages and telephones, and rapidly informing owners and property fire control units of the specific hidden fire situation based on the label and geographical position location of equipment, wherein the fire water subsystem can be connected with a fire hydrant, a fire water pressure and water level sensor and is used for monitoring the pressure and the liquid level of a fire water pipe network in real time so as to judge whether water leakage occurs or not, the water pressure threshold value and the liquid level threshold value are preset in the fire water subsystem, when the water leakage occurs in the pipe network, the real-time water pressure is smaller than the water pressure threshold value and/or the real-time liquid level is smaller than the liquid level threshold value, the fire water subsystem sends out an alarm in real time, the emergency lighting and evacuation subsystem is used for monitoring and controlling each emergency lamp in real time, and when a fire occurs, a safe evacuation path indication can be accurately given, the fire fighting emergency indicator lamp is turned on intelligently, the fire door subsystem monitors the opening and closing of a fire fighting channel, a safety exit and a life channel fire door and the stacking situation of the fire fighting channel in real time through the association of door access alarm and video identification, the opening and closing control function under the emergency situation is realized, the fire fighting equipment power subsystem monitors the power supply working state of each component of the fire fighting system in real time and gives alarm prompts to the overvoltage, undervoltage, overcurrent, short circuit and open circuit faults generated by the power supply of each component, after the video monitoring subsystem receives alarm information of each subsystem, a monitoring camera image related to the alarm position can be obtained, the video assistance of the alarm site is checked to confirm the fire, and the data analysis and decision assistance comprises report statistics, three-color early warning and multi-dimensional data display;
the system comprises an IaaS service model, a remote monitoring system and a remote monitoring system, wherein the IaaS service model comprises a fire safety index model and hidden danger and early warning intelligent analysis, the database type of the IaaS service model comprises MySQL, mongoDB and Redis, the functions of the hidden danger and early warning intelligent analysis comprise hidden danger query, hidden danger distribution, hidden danger processing and hidden danger analysis, the hidden danger analysis analyzes the safety state of equipment based on the fire safety index model and calculates a comprehensive score, five safety level states are preset in the hidden danger and early warning intelligent analysis, and the five states are respectively unsafe, relatively unsafe, general safety, relatively safe and very safe according to the comprehensive score from low to high;
the sensing layer comprises fire-fighting front-end equipment and a fire alarm control host which are deployed at each data acquisition point, and the acquired data are uploaded to the PaaS service platform.
The application side supports Android and IOS operating systems, the login conditions of the SaaS service platform comprise a user name and a password, and the role management can be realized by customizing the operation permission of a user by an administrator according to the identity of the user.
Meanwhile, the three-color early warning is divided into the following parts according to the degree from high to low: red early warning, yellow early warning and green early warning, fire control front end equipment includes but not limited to: the fire-fighting emergency lighting and evacuation system comprises a camera, a smoke sensor, a combustible gas detector, a fire-fighting emergency lighting and evacuation indication host, a fire door monitoring host, a fire-fighting equipment power supply monitoring host and an electric fire monitoring host.
In addition, the data in the database comprises service data and map data, wherein the service data comprises equipment point location information, detector detection data, fire alarm information, video data and equipment running state data, the map data is a GIS electronic map, and the fire-fighting system components monitored by the fire-fighting equipment power subsystem in real time include but are not limited to: fire alarm host computer, floor display, water pump, spray pump and elevator.
In addition, the construction process of the fire safety index model comprises the following steps: identifying a danger source, determining initial nodes of a Bayesian network, establishing a risk Bayesian network structure diagram according to Bayesian network initial nodes formed in the danger source identification process by combining expert knowledge as a historical case does not exist in an inference case library, storing corresponding Bayesian network files formed, adopting a Bayesian network construction based on structure learning after inference cases are accumulated in the inference case library, extracting similar historical cases from the Bayesian network inference case library, performing pruning and recombination operations to form a new Bayesian network structure meeting requirements, storing the new Bayesian network structure into a case list after evaluation, gradually forming a case library with multiple inference structures, setting states of each network node, setting conditional probability and prior probability by using expert knowledge, determining weights by using a hierarchical analysis method, and obtaining comprehensive scores.
The schematic diagram of the fire service management structure in the system is shown in fig. 3, and the schematic diagram of the data analysis and decision assistance structure is shown in fig. 4.
When the system of the technical scheme is used, the system logs in through a Web end or an APP end, and the following operations can be performed through the home page of the SaaS service platform: role management, project general inquiry, equipment state inquiry, equipment classification inquiry, equipment alarm information inquiry, alarm classification inquiry, alarm statistics inquiry and equipment account information inquiry, fire-fighting front-end equipment deployed at each data acquisition point acquires data and uploads the acquired data to a PaaS service platform, wherein the PaaS service platform comprises fire-fighting service management and data analysis and decision assistance, the fire-fighting service management comprises an intelligent power utilization subsystem, a fire alarm subsystem, a fire-fighting equipment management subsystem, a smoke-proof subsystem, a fire-fighting water subsystem, an emergency lighting and evacuation subsystem, a fire door subsystem, a fire-fighting equipment power subsystem and a video monitoring subsystem, the intelligent power utilization subsystem can be connected with an electric fire, an arc, an electric fire host, an arc-extinguishing type protector detector, a wireless temperature measurement detector and a fire alarm subsystem, the fire-fighting equipment management subsystem manages all fire-fighting equipment and assets of each building and project node, marks addresses of fire hydrants, fire extinguishers, spraying and fire-fighting teams heavily, brings daily routing inspection and maintenance into a plan, acquires fire extinguishing information data of smoke, harmful gas and gas, detects the smoke in real time and second level, quickly informs owners and property fire-fighting units of the specific fire hidden situation by finding that monitoring numbers exceed a risk threshold value through APP, short messages and telephone alarm, positions the fire-fighting equipment based on labels and geographic positions, can be connected to fire hydrants, fire-fighting water pressure and water level sensors, and is used for monitoring the pressure and the liquid level of a fire-fighting water pipe network in real time so as to judge whether water leakage exists or not, a water pressure threshold value and a liquid level threshold value are preset in the fire-fighting water subsystem, and when the water leakage occurs, the real-time water pressure is smaller than the water pressure threshold value and/or the real-time liquid level is smaller than the liquid level threshold value, the fire-fighting water subsystem sends out an alarm in real time, the emergency lighting and evacuation subsystem is used for monitoring and controlling each emergency lamp in real time, when a fire disaster occurs, safe evacuation path indication can be accurately given, the indication direction and the emergency lighting lamp of the fire-fighting emergency indicator lamp are intelligently turned on, the fire-fighting subsystem gives an alarm through entrance guard and video identification, the fire-fighting channel is monitored in real time, a safety outlet, the opening and closing of a life channel fire door and the stacking condition of the fire-fighting channel are realized, the power working state of each part of the fire-fighting system is monitored in real time by the fire-fighting equipment power subsystem, and the overvoltage, the undervoltage, the overcurrent, the short circuit and the open circuit fault alarm prompt are generated for each part of a power supply, after the video monitoring subsystem receives alarm information of each subsystem, a monitoring camera image related to the alarm position can be obtained, the video assistance of the alarm site is checked to confirm the fire situation, the data analysis and decision assistance comprises report statistics, three-color early warning and multi-dimensional data display, meanwhile, the IaaS service model comprises a fire safety index model and early warning intelligent analysis, and a construction flow of the fire safety index model is as follows: identifying a danger source, determining an initial node of a Bayesian network, establishing a risk Bayesian network structure diagram according to the Bayesian network initial node formed in the process of identifying the danger source and combining expert knowledge because no historical case exists in an inference case library, storing a corresponding Bayesian network structure diagram formed, adopting a Bayesian network structure based on structure learning after inference cases are accumulated in the inference case library, extracting similar historical cases from the Bayesian network inference case library, performing pruning and recombination operations to form a new Bayesian network structure meeting requirements, storing the new Bayesian network structure into a case list after assessment, gradually forming a case library of a multi-inference structure, setting states of each network node, setting conditional probability and prior probability by using expert knowledge, then determining weights by using a hierarchical analysis method, obtaining a comprehensive score, analyzing the safety state of equipment based on a fire fighting safety index model, calculating the comprehensive state of the equipment, calculating the comprehensive score and pre-setting safety state, and comparing five safety grades according to a high safety state, a safety early warning, and five safety grades.
Claims (8)
1. A real-time fire prevention monitoring data transmission system for fire engineering construction comprises a SaaS service platform, a PaaS service platform, an IaaS service model and a sensing layer; it is characterized in that the preparation method is characterized in that,
the SaaS service platform comprises a Web end and an APP end, and the home page of the SaaS service platform comprises: role management, project overview, equipment state, equipment classification, equipment alarm information, alarm classification, alarm statistics and equipment ledger information;
the PaaS service platform comprises fire service management and data analysis and decision assistance, the fire service management comprises an intelligent power utilization subsystem, a fire alarm subsystem, a fire equipment management subsystem, a smoke prevention and discharge subsystem, a fire water subsystem, an emergency lighting and evacuation subsystem, a fire door subsystem, a fire equipment power subsystem and a video monitoring subsystem, the intelligent power utilization subsystem can be connected with an electric fire, an arc isolated, an electric fire host, an arc extinguishing type protector detector and a wireless temperature measurement detector, the fire alarm subsystem manages all fire equipment and assets of each building and project node, emphasizes address labeling of fire hydrants, fire extinguishers, spraying and fire fighting teams, brings daily inspection and maintenance into a plan, and the smoke prevention and discharge subsystem acquires smoke, harmful gas and fire extinguishing information data, detecting smog in real time second level, firstly, finding that the monitored number exceeds a risk threshold value, alarming by APP, short messages and telephones, and rapidly informing owners and property fire control units of the specific hidden fire situation based on the label and geographical position location of equipment, wherein the fire water subsystem can be connected with a fire hydrant, a fire water pressure and water level sensor and is used for monitoring the pressure and the liquid level of a fire water pipe network in real time so as to judge whether water leakage occurs or not, the water pressure threshold value and the liquid level threshold value are preset in the fire water subsystem, when the water leakage occurs in the pipe network, the real-time water pressure is smaller than the water pressure threshold value and/or the real-time liquid level is smaller than the liquid level threshold value, the fire water subsystem sends out an alarm in real time, the emergency lighting and evacuation subsystem is used for monitoring and controlling each emergency lamp in real time, and when a fire occurs, a safe evacuation path indication can be accurately given, the fire fighting emergency indicator lamp is turned on intelligently, the fire door subsystem monitors the opening and closing of a fire fighting channel, a safety exit and a life channel fire door and the stacking situation of the fire fighting channel in real time through the association of door access alarm and video identification, the opening and closing control function under the emergency situation is realized, the fire fighting equipment power subsystem monitors the power supply working state of each component of the fire fighting system in real time and gives alarm prompts to the overvoltage, undervoltage, overcurrent, short circuit and open circuit faults generated by the power supply of each component, after the video monitoring subsystem receives alarm information of each subsystem, a monitoring camera image related to the alarm position can be obtained, the video assistance of the alarm site is checked to confirm the fire, and the data analysis and decision assistance comprises report statistics, three-color early warning and multi-dimensional data display;
the method comprises the following steps that an IaaS service model comprises a fire safety index model and hidden danger and early warning intelligent analysis, the database type of the IaaS service model comprises MySQL, mongoDB and Redis, the functions of the hidden danger and early warning intelligent analysis comprise hidden danger query, hidden danger distribution, hidden danger processing and hidden danger analysis, the hidden danger analysis analyzes the safety state of equipment based on the fire safety index model and calculates a comprehensive score, five safety level states are preset in the hidden danger and early warning intelligent analysis, and the states are respectively very unsafe, relatively unsafe, common safety, relatively safe and very safe according to the comprehensive score from low to high;
the sensing layer comprises fire-fighting front-end equipment and a fire alarm control host which are deployed at each data acquisition point, and the acquired data are uploaded to the PaaS service platform.
2. The real-time fire protection monitoring data transmission system for fire engineering construction according to claim 1, wherein the APP supports Android and IOS operating systems, and the SaaS service platform login conditions include a user name and a password.
3. The real-time fire protection monitoring data transmission system for fire engineering construction according to claim 1, wherein the role management enables an administrator to customize the operation authority owned by a user according to the identity of the user.
4. The real-time fire protection monitoring data transmission system for fire protection engineering construction according to claim 1, wherein the three-color pre-warning is divided into, from high to low: red early warning, yellow early warning and green early warning.
5. The real-time fire protection monitoring data transmission system for fire protection engineering construction according to claim 1, wherein the fire protection front-end equipment includes but is not limited to: the fire-fighting emergency lighting and evacuation system comprises a camera, a smoke sensor, a combustible gas detector, a fire-fighting emergency lighting and evacuation indication host, a fire door monitoring host, a fire-fighting equipment power supply monitoring host and an electric fire monitoring host.
6. The real-time fire prevention monitoring data transmission system for fire engineering construction as claimed in claim 1, wherein the data in the database includes service data and map data, wherein the service data includes equipment point location information, detector detection data, fire alarm information, video data and equipment operation state data, and the map data is a GIS electronic map.
7. The real-time fire protection monitoring data transmission system for fire protection engineering construction according to claim 1, wherein the fire protection system components monitored by the fire protection equipment power subsystem in real time include but are not limited to: fire alarm host computer, floor display, water pump, spray pump and elevator.
8. The real-time fire protection monitoring data transmission system for fire engineering construction according to claim 1, wherein the construction process of the fire protection safety index model is as follows: identifying a danger source and determining initial nodes of the Bayesian network, wherein a historical case does not exist in an inference case library, the modeling selects a Bayesian network component mode based on expert knowledge, a risk Bayesian network structure diagram is established according to the Bayesian network initial nodes formed in the danger source identification process and in combination with the expert knowledge, corresponding Bayesian network files are stored, after the inference cases are accumulated in the inference case library, a Bayesian network construction based on structure learning is adopted, similar historical cases are extracted from the Bayesian network case library, pruning and recombination operations are carried out, a new Bayesian network structure meeting requirements is formed, the new Bayesian network structure is stored in a case list after evaluation is finished, a case library with a multi-structure inference structure is gradually formed, conditions of each network node are set, conditional probabilities and prior probabilities are set by using the expert knowledge, weights are determined by using an analytic hierarchy process, and comprehensive scores are obtained.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117152906A (en) * | 2023-11-01 | 2023-12-01 | 福建阿古电务数据科技有限公司 | Video image fire alarm system based on artificial intelligence |
| CN117436532A (en) * | 2023-12-21 | 2024-01-23 | 中用科技有限公司 | Root cause analysis method for gaseous molecular pollutants in clean room |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117152906A (en) * | 2023-11-01 | 2023-12-01 | 福建阿古电务数据科技有限公司 | Video image fire alarm system based on artificial intelligence |
| CN117152906B (en) * | 2023-11-01 | 2024-01-23 | 福建阿古电务数据科技有限公司 | Video image fire alarm system based on artificial intelligence |
| CN117436532A (en) * | 2023-12-21 | 2024-01-23 | 中用科技有限公司 | Root cause analysis method for gaseous molecular pollutants in clean room |
| CN117436532B (en) * | 2023-12-21 | 2024-03-22 | 中用科技有限公司 | Root cause analysis method for gaseous molecular pollutants in clean room |
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