CN116704694A - Automatic fire prevention and control method for expressway tunnel and emergency disposal management system - Google Patents
Automatic fire prevention and control method for expressway tunnel and emergency disposal management system Download PDFInfo
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Abstract
The invention discloses an automatic fire prevention and control method for a highway tunnel and an emergency disposal management system, wherein the system comprises a fire detection system, a fire detection system and a fire control system; the system comprises a fire scene situation awareness subsystem, an awareness prediction model subsystem, an emergency treatment management subsystem and an intelligent management platform subsystem; on the basis of virtual dynamic display of fire information and temperature smoke fields in a tunnel, a fire identification and target positioning technology, an automatic fire extinguishing system and a smoke discharging system are combined, an automatic fire prevention and control technology and an emergency platform are built, the fire situation can be monitored in real time, automatic fire extinguishing and smoke discharging can be achieved, the real-time monitoring result is displayed in an image mode, in addition, the functions of knowledge driving and data driving are combined, the function of predicting the fire condition is added, and proper emergency rescue measures are matched in real time.
Description
Technical Field
The invention relates to the technical field of tunnel fire scene situation awareness technology, fire disaster awareness prediction model construction and correction and tunnel fire disaster intelligent emergency response, in particular to an automatic expressway tunnel fire disaster prevention and control method and an emergency treatment system.
Background
The construction of the tunnel plays an important role in reducing road congestion, shortening the running distance, improving the transportation capacity and the like.
The tunnel structure has the characteristics of long and narrow shape, tubular shape and airtight, when a fire accident happens in the tunnel structure, people evacuation and fire rescue are more difficult than other buildings, in addition, smoke discharging and heat dissipation conditions in the closed space are poor, when a truck, a tank truck or the like catches fire, the temperature is often more than 1000 ℃, the fire is quite difficult to put out, and serious fire accidents can cause a large amount of casualties and economic losses, so that serious negative effects are generated to society. Exploring the regular features of tunnel fire occurrence and fire prevention and control have become the hot spot and difficulty of current research.
With the continuous increase of the number of in-service tunnels and traffic flow, the tunnel operation environment is increasingly complex, and fires as main sudden disasters also frequently occur, and cause huge social influence and economic loss. The intelligent expressway tunnel fire active prevention and control and emergency treatment platform is developed and applied, so that disaster prevention and reduction working capacity and safety control level of tunnel risk situation awareness and the like are improved, emergency rescue and management are carried out on fire accidents which occur through scientific calculation and big data analysis and processing, effective processing such as ventilation and smoke discharge, people evacuation, fire scene data transmission and the like is carried out, real-time dynamic reproduction of fire scene conditions is comprehensively realized, and pertinence and effectiveness of fire emergency response plan execution are improved. The fire disaster prevention capability of the tunnel can be practically improved, and casualties and economic losses caused by fire disaster can be reduced to the maximum extent.
According to the summary analysis of the current situation of the highway tunnel fire emergency prevention and control technology, the present tunnel fire emergency prevention and control technology can be found that the following problems exist:
1) The research focus is mainly focused on the fields of a tunnel fire risk evaluation model, a tunnel fire risk evaluation research, a tunnel fire risk evaluation software design, a new physical device research of a highway tunnel safety system and the like, and the research direction is mainly to further improve the automation and real-time level of the tunnel fire risk evaluation software, ensure the accuracy of tunnel fire risk evaluation data and keep the safety traffic of the tunnel free of fire safety hidden trouble. The design for realizing the intelligent function of preventing and controlling the tunnel fire disaster and evacuating through the novel network platform technology is very few.
2) When a fire disaster occurs in a tunnel, under the prior emergency rescue technology, rescue workers are difficult to determine specific accident conditions in the tunnel, so that firefighters are difficult to determine which rescue measures to take to rescue the scene of the tunnel fire disaster more effectively, the fire disaster situation is changed along with the time development affected by the environment and the real-time state, the rescue workers cannot acquire corresponding information in time, and rescue difficulty and danger are relatively high.
3) Although the contact type fire detection technology in the present fire identification technology is still adopted in many engineering application occasions, the contact type fire detection is difficult to determine the alarm threshold value of a complex environment, and meanwhile, the real-time performance of the fire detection is difficult to ensure, so that the contact type fire detection technology is definitely fatal to the scene of a tunnel fire which is suddenly changed.
4) The fire disaster target positioning technology is widely applied nowadays, and the specific calculation process involves a large number of pixel point comparisons on the image, so that the complexity is extremely high. In addition, the matching process is also extremely susceptible to noise, shielding and other undesirable environments, so that errors in matching are caused, and as a rule, when the monitoring equipment is arranged more, the space information is restored more accurately, but the cost is quite huge.
Disclosure of Invention
The invention aims to solve the technical problem of providing an automatic fire prevention and control method for a highway tunnel and an emergency disposal management system, so as to solve the defects in the prior art.
The invention provides a highway tunnel fire emergency treatment management system, which comprises:
the fire scene situation awareness subsystem comprises a tunnel fire detector, acquires wind speed data, temperature data and image information of tunnel fire through the tunnel fire detector, and processes and analyzes the acquired wind speed data, temperature data and image information to acquire fire situation information, wherein the fire situation information comprises fire scale, fire position and fire type;
the perception prediction model subsystem comprises a tunnel fire scale prediction correction model applicable to longitudinal fire sources and transverse fire sources and is used for correcting fire situation information;
the emergency treatment management subsystem is used for establishing a fire disaster database, obtaining fire situation information according to the real-time information acquired by the fire scene situation sensing subsystem and the sensing model correcting subsystem, comparing similar scenes in the database, calling an emergency plan under the scene, updating the emergency plan in real time according to the fire situation information, and generating an emergency response auxiliary decision scheme for solving the target scene and an alternative plan;
and the intelligent management platform subsystem is used for displaying the flame state, the emergency response auxiliary decision scheme, the alternative scheme and the emergency scheme in the tunnel in real time.
As a preferable scheme of the invention, the fire situation information also comprises fire source power, temperature distribution, smoke diffusion range, smoke movement direction and natural wind speed.
As a preferable scheme of the invention, the tunnel fire detector comprises an anemometer, a grating fiber sensor, an infrared thermal imaging camera and a CCD camera.
As a preferable scheme of the invention, the fire disaster situation database is combined with big data prediction to support obtaining emergency countermeasures, emergency record and emergency plan; the big data prediction specifically comprises the following steps: traversing all plans of the fire disaster database, and deleting according to the data conditions obtained by the prediction perception prediction subsystem.
As a preferable mode of the present invention, the tunnel fire scale prediction correction model includes: a fire scale perception correction model and a fire position perception correction model,
the calculation formula of the fire scale perception correction model is as follows:
longitudinal fire source:
transverse fire source:
the calculation formula of the fire position perception correction model is as follows:
longitudinal fire source: l (L) 1 ＝3H ef u’ 0.6 ，u’＞0.19L 1 ＝H ef ，u’≤0.19
Transverse fire source: l (L) 1 ＝6.9H ef u’ 0.6 ，u’＞0.19L 1 ＝H ef ，u’≤0.19
Wherein Q is fire source power; delta T max The highest temperature difference of the ceiling; t (T) 0 Is at normal temperature; u' is wind speed; h ef Is the ceiling feature height; b f Is the diameter of the fire source; l1 is the linear distance of the fire source from the highest temperature.
As a preferable scheme of the invention, the intelligent management platform subsystem sends fire information in real time through the established network platform.
The invention also provides a fire prevention and control method based on the management system, which comprises the following steps:
1) The tunnel fire detector of the fire scene situation awareness subsystem acquires wind speed data, temperature data and image information of a fire scene; analyzing and processing the acquired wind speed data, temperature data and image information through a fire scene situation awareness subsystem, determining the fire scale, the fire position and the fire type, and integrating the fire scale, the fire position and the fire type into fire situation information;
2) The perception prediction model subsystem corrects the fire situation information through a tunnel fire scale prediction correction model suitable for the longitudinal fire source and the transverse fire source to obtain corrected fire situation information;
3) The fire scene situation information is obtained through the real-time information acquired by the fire scene situation sensing subsystem and the sensing model correcting subsystem, the fire scene information is combined with a fire rescue method and a strategy on site and a fire emergency command, the quality and the effectiveness of internal and external emergency resources are evaluated, the matching comparison is carried out on the internal and external emergency resources and the similar scenes in a database, and an emergency treatment plan under the scene is called;
4) The intelligent management platform subsystem displays the flame state in the tunnel, the adopted emergency countermeasures, the adopted emergency record and the adopted emergency plan in real time;
5) After the scheme is implemented, the emergency treatment management subsystem forms feedback on the implementation effect of the emergency decision method in the fire disaster database; and judging whether to add the current fire case scene into the fire disaster database or whether to update, correct or delete the scene in the fire disaster database and the emergency plan according to the condition of the fire disaster database, thereby generating an emergency response auxiliary decision scheme and an alternative plan for solving the current fire scene.
Compared with the prior art, the invention has the following beneficial effects:
the invention adopts the knowledge of fire dynamics, has simple formula, reduces the operation workload, greatly improves the recognition speed by using knowledge drive, and saves a great amount of time for eliminating the fire danger.
Besides the grating fiber optic sensor, the invention combines the infrared thermal imaging technology with the camera, adopts the infrared thermal imaging camera to draw the thermal vector diagram of the fire scene, and greatly increases the efficiency and the accuracy.
The linkage early warning of the tunnel fire protection system is helpful for quickly eliminating tunnel fires; on the basis of virtual dynamic display of fire information and temperature smoke fields in a tunnel, a fire identification and target positioning technology, an automatic fire extinguishing system and a smoke discharging system are combined, an automatic fire prevention and control technology and an emergency platform are built, the fire situation can be monitored automatically, fire is extinguished timely, smoke is discharged, a real-time monitoring result is displayed in an image form, in addition, a function of combining knowledge driving with data driving is added, a function of predicting the fire is added, proper emergency rescue measures are matched in real time, and an alternative emergency plan is also arranged to comprehensively realize informatization and automation of tunnel fire prevention and control aiming at emergency, so that rescue safety and scientificity are greatly improved.
Drawings
FIG. 1 is a schematic diagram of a tunnel fire emergency flow;
FIG. 2 is a schematic illustration of an evacuation stage plan emergency flow;
FIG. 3 is a schematic illustration of an emergency flow during a fire suppression phase;
FIG. 4 is a schematic diagram of a color gamut segmentation and region localization process using an infrared thermal imaging technique;
fig. 5 is a schematic view of the installation of the device.
Detailed Description
The invention is further illustrated and described below in connection with specific embodiments. The described embodiments are merely exemplary of the present disclosure and do not limit the scope. The technical features of the embodiments of the invention can be combined correspondingly on the premise of no mutual conflict.
As shown in fig. 5, the automatic fire prevention and control emergency treatment system for the expressway tunnel of the present invention comprises:
1) Fire scene situation sensing subsystem
a) Tunnel temperature sensing technology research under fire scene: and by utilizing a scale tunnel fire test model, respectively installing distributed temperature sensing optical fibers and thermocouples in the tunnel vault and the longitudinal direction, determining the fire source power and the smoke discharge speed of the fire test by a similar theory, analyzing the longitudinal attenuation of the temperature of the tunnel vault and the vertical attenuation of the temperature of a smoke layer under different fire source powers and smoke discharge speeds, and comparing the temperature measurement differences of the temperature sensing optical fibers and the thermocouples under different working conditions.
b) The technology for sensing the situation of the fire scene of the tunnel fire disaster comprises the following steps: the tunnel fire scene information components are analyzed from the existing research and expert-based depth interviews by a summary method, and the tunnel fire scene basic information is extracted based on root taking theory. And establishing a corresponding relation between a fire situation prediction model and basic information of a fire scene (fire factor, fire level, fire source position, nearby gradient, flame burning speed, temperature and smoke concentration).
c) Infrared thermal imaging system: if the flame is not reasonably controlled after the fire occurs, the flame will lose control and start to spread in a limited range, thereby leading to an increase in the area of the fire. The area of the bright color area is increased, f (x, y) can be obtained after the thermal imaging image is binarized, the number of pixel points with the pixel value of 0 in the binarized image is counted, and the area of the flame suspicious area is calculated.
2) Perception prediction model correction subsystem
As shown in fig. 4, the integration of the classical tunnel fire dynamics model and the infrared thermal imaging system are combined, and the vertical attenuation model of the smoke layer is supplemented. And aiming at a typical tunnel fire scene, adopting FDS numerical simulation software to establish a three-dimensional full-size model. And analyzing the influence rules of parameters such as a tunnel structure, a fire type, a fire source power, a fire source position, a longitudinal wind speed and the like on the change of temperature, the reflux length of smoke, the thickness of the smoke layer and visibility on the longitudinal surface at the central line of the tunnel by combining with a scale model test, establishing a theoretical model of smoke reflux length, longitudinal attenuation of the temperature of a tunnel vault and vertical attenuation of the temperature of the smoke layer, and constructing a theoretical prediction model of tunnel fire perception.
3) Emergency handling management subsystem
As shown in fig. 1, the fire smoke evacuation schedule control mode: according to a ventilation and smoke discharge control principle, in a personnel evacuation stage, longitudinal airflow should keep smoke layering as far as possible, so as to avoid smoke layer disturbance, fire disaster is generated near an outlet, tiny wind speed is provided to promote smoke discharge of the fire disaster, fire disaster is generated in the middle of a gradient tunnel, and tiny wind speed in a downhill direction is provided to slow down the speed and distance of spreading of the smoke to two sides; as shown in fig. 3, during the fire extinguishing phase, a critical wind speed is provided to the tunnel, preventing the reverse flow of fire smoke to one side. Based on the principle, the smoke flow resistance, the parking resistance, the buoyancy effect and the influence of fire smoke flow on a fan during highway tunnel fire are considered, and based on a multiphase turbulence reaction fluid dynamic model, the influence rules of a smoke discharging mode, a ventilation wind speed, a fire source position and heat release power on the motion characteristics of tunnel fire smoke are analyzed in the tunnel fire development process, so that a fire smoke discharging time interval control mode is constructed.
As shown in fig. 2, a dynamic plan for evacuation and rescue of a tunnel: when the evacuation rescue dynamic plan is formulated, the basic information elements of the extracted tunnel fire scene are combined, a plurality of scenes are selected as source scenes of the project plan library through the classification analysis of the past road tunnel fire accident cases, the corresponding relation between the emergency plan and the source scenes is determined through the methods of case analysis, numerical simulation, model test and the like, and the origin scene emergency plan library is initially established. The emergency corresponding measures in the plan library relate to ventilation lighting, fire protection and disaster relief, personnel evacuation and personnel relief, traffic control, alarm fire protection system linkage and the like, the plans of the systems are coordinated and orderly organized, real-time and effective fire information is timely obtained, and the emergency plans are adjusted in real time according to the change of conditions such as fire scene, rescue and the like. By combining the intelligent evacuation induction system of the project, the emergency working mode is started at the first time when the occurrence of a fire disaster is detected, so that the arrows of the evacuation indication graphic panel are stroboscopic, and the indication effect is enhanced. The escape system can realize linkage with a fan smoke discharging mode, dynamically adjust the arrow indication direction according to a preset evacuation plan, so that evacuees can safely, accurately and rapidly select a safety channel for escape, and the evacuees are guided to escape in the mode, so that the selection of the escape channel of the whole tunnel can be circulated, and the evacuees are prevented from entering a fire area.
The fire scene simulation analysis and the fire rescue method are combined with the strategy and the fire emergency command to evaluate the quality and the effectiveness of internal and external emergency resources, and the fire situation sensing system and the intelligent evacuation guiding system are combined to quantify the vehicle situation, the environmental information, the personnel action, the fire development and the rescue situation unfolding time/space when the accident happens, so that a tunnel evacuation rescue dynamic plan database comprising tunnels of different types, different fire forms, different disaster groups, different external environments and taking the emergency into consideration is established.
c) Tunnel fire emergency response aid decision: by combining the scene similarity calculation method, the scene similarity of the source scene and the target fire scene in the emergency plan library can be obtained, a similarity threshold can be determined by consulting documents and expert discussions, when the similarity exceeds the threshold, the target scene is considered to be similar to the source scene, and the emergency plan corresponding to the source scene can be used as a reference for target scene solution. The retrieved case scenario solution and the method for solving the accidents are further required to be corrected according to actual conditions, so that the case scenario solution is suitable for the current case scenario, and an emergency decision scheme for solving the current case is formed. After the scheme is implemented, feedback about the implementation effect of the emergency decision method is formed. And judging whether to add the current fire case scene into the case scene library or whether to update, correct or delete the scene in the scene library and the emergency plan according to the situation of the case scene library, thereby generating an emergency response auxiliary decision scheme for solving the target scene and an alternative plan. And the fire extinguishing gun in the tunnel is controlled in a linkage way to accelerate the fire extinguishing speed, so that the fire extinguishing speed is faster. The high-efficiency fire extinguishment can protect the life and property safety of people.
The above model and data processing formula:
fire scale perception model based on ceiling temperature:
wherein: q is fire source power (kW); delta T max Is the highest temperature difference (K) of the vault; t (T) 0 Is at normal temperature (K); u is wind speed (m/s); h ef Is the tunnel feature height (m); b f Is the diameter of the fire source; ρ 0 Is air density (kg/m) 3 ) The method comprises the steps of carrying out a first treatment on the surface of the The method comprises the steps of carrying out a first treatment on the surface of the g gravity acceleration (m/s) 2 )。
Theoretical predictive correction model:
longitudinal fire source:
transverse fire source:
and when ventilation is performed longitudinally, predicting a highest temperature position of smoke under the ceiling:
the tunnel ceiling maximum temperature theoretical prediction correction model is suitable for longitudinal fire sources and transverse fire sources:
longitudinal fire source:
transverse fire source:
flame area and its change formula:
a) Flame suspicious area: a= Σf (x, y)
b) Area change rate:
wherein A is the area of the flame suspicious region; the f-function is the pixel value of the thermographic image binarized. After the area of the flame suspicious region is obtained, the area change rate of the flame suspicious region can be calculated by combining the time difference, lambda is the area change rate of the flame suspicious region, A 1 For the area of the flame suspicious region at the later moment, A 0 Area available for flame at the previous moment, t 1 For the time stamp of the latter moment, t 0 Is the time stamp of the previous moment.
The foregoing examples illustrate only a few embodiments of the invention and are described in detail herein without thereby limiting the scope of the invention. It will be apparent to those skilled in the art that various modifications and improvements can be made without departing from the spirit of the invention.
Claims (7)
1. An expressway tunnel fire emergency treatment management system, comprising:
the fire scene situation awareness subsystem comprises a tunnel fire detector, acquires wind speed data, temperature data and image information of tunnel fire through the tunnel fire detector, and processes and analyzes the acquired wind speed data, temperature data and image information to acquire fire situation information, wherein the fire situation information comprises fire scale, fire position and fire type;
the perception prediction model subsystem comprises a tunnel fire scale prediction correction model applicable to longitudinal fire sources and transverse fire sources and is used for correcting fire situation information;
the emergency treatment management subsystem is used for establishing a fire disaster database, obtaining fire situation information according to the real-time information acquired by the fire scene situation sensing subsystem and the sensing model correcting subsystem, comparing similar scenes in the database, calling an emergency plan under the scene, updating the emergency plan in real time according to the fire situation information, and generating an emergency response auxiliary decision scheme for solving the target scene and an alternative plan;
and the intelligent management platform subsystem is used for displaying the flame state, the emergency response auxiliary decision scheme, the alternative scheme and the emergency scheme in the tunnel in real time.
2. The highway tunnel fire emergency treatment management system according to claim 1, wherein: the fire situation information also comprises fire source power, temperature distribution, smoke diffusion range, smoke movement direction and natural wind speed.
3. The highway tunnel fire emergency treatment management system according to claim 1, wherein: the tunnel fire detector comprises an anemometer, a grating fiber optic sensor, an infrared thermal imaging camera and a CCD camera.
4. The highway tunnel fire emergency treatment management system according to claim 1, wherein: the fire disaster situation database combines big data prediction to support obtaining emergency countermeasures, emergency record and emergency plan; the big data prediction specifically comprises the following steps: traversing all plans of the fire disaster database, and deleting according to the data conditions obtained by the prediction perception prediction subsystem.
5. The highway tunnel fire emergency treatment management system according to claim 1, wherein: the tunnel fire scale prediction correction model comprises the following steps: a fire scale perception correction model and a fire position perception correction model,
the calculation formula of the fire scale perception correction model is as follows:
longitudinal fire source:
transverse fire source:
the calculation formula of the fire position perception correction model is as follows:
longitudinal fire source: l (L) 1 ＝3H ef u’ 0.6 ，u’＞0.19L 1 ＝H ef ，u’≤0.19
Transverse fire source: l (L) 1 ＝6.9H ef u’ 0.6 ，u’＞0.19L 1 ＝H ef ，u’≤0.19
Wherein Q is fire source power; delta T max The highest temperature difference of the ceiling; u' is wind speed; h ef Is the ceiling feature height; b f Is the diameter of the fire source; l1 is the linear distance of the fire source from the highest temperature.
6. The highway tunnel fire emergency treatment management system according to claim 1, wherein: and the intelligent management platform subsystem transmits fire information in real time through the established network platform.
7. A fire prevention and control method based on the highway tunnel fire emergency treatment management system according to claim 1, comprising the steps of:
1) The tunnel fire detector of the fire scene situation awareness subsystem acquires wind speed data, temperature data and image information of a fire scene; analyzing and processing the acquired wind speed data, temperature data and image information through a fire scene situation awareness subsystem, determining the fire scale, the fire position and the fire type, and integrating the fire scale, the fire position and the fire type into fire situation information;
2) The perception prediction model subsystem corrects the fire situation information through a tunnel fire scale prediction correction model suitable for the longitudinal fire source and the transverse fire source to obtain corrected fire situation information;
3) The fire scene situation information is obtained through the real-time information acquired by the fire scene situation sensing subsystem and the sensing model correcting subsystem, the fire scene information is combined with a fire rescue method and a strategy on site and a fire emergency command, the quality and the effectiveness of internal and external emergency resources are evaluated, the matching comparison is carried out on the internal and external emergency resources and the similar scenes in a database, and an emergency treatment plan under the scene is called;
4) The intelligent management platform subsystem displays the flame state in the tunnel, the adopted emergency countermeasures, the adopted emergency record and the adopted emergency plan in real time;
5) After the scheme is implemented, the emergency treatment management subsystem forms feedback on the implementation effect of the emergency decision method in the fire disaster database; and judging whether to add the current fire case scene into the fire disaster database or whether to update, correct or delete the scene in the fire disaster database and the emergency plan according to the condition of the fire disaster database, thereby generating an emergency response auxiliary decision scheme and an alternative plan for solving the current fire scene.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117282054A (en) * | 2023-11-16 | 2023-12-26 | 四川智慧高速科技有限公司 | Tunnel fire-fighting linkage system based on edge calculation |
| CN117764162A (en) * | 2023-12-26 | 2024-03-26 | 迪爱斯信息技术股份有限公司 | Multi-agent model system and method for emergency decision assistance |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117282054A (en) * | 2023-11-16 | 2023-12-26 | 四川智慧高速科技有限公司 | Tunnel fire-fighting linkage system based on edge calculation |
| CN117282054B (en) * | 2023-11-16 | 2024-01-30 | 四川智慧高速科技有限公司 | Tunnel fire-fighting linkage system based on edge calculation |
| CN117764162A (en) * | 2023-12-26 | 2024-03-26 | 迪爱斯信息技术股份有限公司 | Multi-agent model system and method for emergency decision assistance |
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