CN118230533A - Intelligent analysis system based on fire information - Google Patents
Intelligent analysis system based on fire information Download PDFInfo
- Publication number
- CN118230533A CN118230533A CN202410634182.1A CN202410634182A CN118230533A CN 118230533 A CN118230533 A CN 118230533A CN 202410634182 A CN202410634182 A CN 202410634182A CN 118230533 A CN118230533 A CN 118230533A
- Authority
- CN
- China
- Prior art keywords
- fire
- index
- area
- disaster
- scale
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000004458 analytical method Methods 0.000 title claims abstract description 49
- 238000011156 evaluation Methods 0.000 claims abstract description 79
- 238000000034 method Methods 0.000 claims abstract description 43
- 238000007405 data analysis Methods 0.000 claims abstract description 7
- 238000012545 processing Methods 0.000 claims abstract description 6
- 239000000779 smoke Substances 0.000 claims description 51
- 239000000126 substance Substances 0.000 claims description 49
- 238000012502 risk assessment Methods 0.000 claims description 47
- 238000012544 monitoring process Methods 0.000 claims description 43
- 230000007480 spreading Effects 0.000 claims description 42
- 230000005855 radiation Effects 0.000 claims description 31
- 230000008569 process Effects 0.000 claims description 21
- 230000007613 environmental effect Effects 0.000 claims description 15
- 230000014509 gene expression Effects 0.000 claims description 7
- 238000011158 quantitative evaluation Methods 0.000 claims description 6
- 238000011282 treatment Methods 0.000 claims description 5
- 230000009471 action Effects 0.000 abstract description 12
- 238000011161 development Methods 0.000 abstract description 11
- 230000009286 beneficial effect Effects 0.000 abstract description 7
- 238000002485 combustion reaction Methods 0.000 description 16
- 230000008859 change Effects 0.000 description 11
- 238000005516 engineering process Methods 0.000 description 10
- 239000000463 material Substances 0.000 description 9
- 230000000694 effects Effects 0.000 description 8
- 239000007789 gas Substances 0.000 description 5
- 238000004088 simulation Methods 0.000 description 5
- 239000002341 toxic gas Substances 0.000 description 5
- 239000003795 chemical substances by application Substances 0.000 description 4
- 238000001514 detection method Methods 0.000 description 4
- 238000009792 diffusion process Methods 0.000 description 4
- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 3
- 238000007726 management method Methods 0.000 description 3
- 238000009825 accumulation Methods 0.000 description 2
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 2
- 238000004422 calculation algorithm Methods 0.000 description 2
- 229910002091 carbon monoxide Inorganic materials 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 239000000446 fuel Substances 0.000 description 2
- LELOWRISYMNNSU-UHFFFAOYSA-N hydrogen cyanide Chemical compound N#C LELOWRISYMNNSU-UHFFFAOYSA-N 0.000 description 2
- 238000013507 mapping Methods 0.000 description 2
- 238000007254 oxidation reaction Methods 0.000 description 2
- 239000001301 oxygen Substances 0.000 description 2
- 229910052760 oxygen Inorganic materials 0.000 description 2
- 239000002245 particle Substances 0.000 description 2
- 238000005192 partition Methods 0.000 description 2
- 238000007781 pre-processing Methods 0.000 description 2
- 230000002265 prevention Effects 0.000 description 2
- 230000008786 sensory perception of smell Effects 0.000 description 2
- 238000005507 spraying Methods 0.000 description 2
- 238000009423 ventilation Methods 0.000 description 2
- 206010000369 Accident Diseases 0.000 description 1
- 206010003497 Asphyxia Diseases 0.000 description 1
- 208000021063 Respiratory fume inhalation disease Diseases 0.000 description 1
- 229910000831 Steel Inorganic materials 0.000 description 1
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000001133 acceleration Effects 0.000 description 1
- 238000007792 addition Methods 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 239000004566 building material Substances 0.000 description 1
- 239000006227 byproduct Substances 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000001066 destructive effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000005713 exacerbation Effects 0.000 description 1
- 239000000796 flavoring agent Substances 0.000 description 1
- 235000019634 flavors Nutrition 0.000 description 1
- 239000003546 flue gas Substances 0.000 description 1
- 238000009472 formulation Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 230000009474 immediate action Effects 0.000 description 1
- 230000001976 improved effect Effects 0.000 description 1
- 238000011221 initial treatment Methods 0.000 description 1
- 230000000977 initiatory effect Effects 0.000 description 1
- 238000009413 insulation Methods 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 238000002955 isolation Methods 0.000 description 1
- 238000012417 linear regression Methods 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000013021 overheating Methods 0.000 description 1
- 230000003647 oxidation Effects 0.000 description 1
- 238000012567 pattern recognition method Methods 0.000 description 1
- 231100000614 poison Toxicity 0.000 description 1
- 231100000572 poisoning Toxicity 0.000 description 1
- 230000000607 poisoning effect Effects 0.000 description 1
- 230000007096 poisonous effect Effects 0.000 description 1
- 231100000683 possible toxicity Toxicity 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 238000007637 random forest analysis Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000003014 reinforcing effect Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000000241 respiratory effect Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 230000000630 rising effect Effects 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 239000010959 steel Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000002195 synergetic effect Effects 0.000 description 1
- 238000005979 thermal decomposition reaction Methods 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B31/00—Predictive alarm systems characterised by extrapolation or other computation using updated historic data
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/06—Electric actuation of the alarm, e.g. using a thermally-operated switch
-
- 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
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Business, Economics & Management (AREA)
- Emergency Management (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Engineering & Computer Science (AREA)
- Computing Systems (AREA)
- Fire Alarms (AREA)
Abstract
The invention relates to the technical field of fire information analysis, and particularly discloses an intelligent analysis system based on fire information, which comprises the following components: the fire disaster data acquisition module, the fire disaster data analysis processing module, the fire disaster grade assessment module and the fire disaster database. According to the invention, the fire scale data monitored by the intelligent analysis system can be used for rapidly evaluating the fire intensity and the development trend, providing accurate field information for fire-extinguishing rescue actions, and automatically allocating corresponding rescue resources according to the fire scale, thereby being beneficial to improving the rescue efficiency. Meanwhile, the method helps to predict the development trend and potential influence area of fire, provides prospective information for fire-extinguishing rescue actions, and is beneficial to reducing rescue time and improving fire-extinguishing efficiency. According to the invention, more targeted fire extinguishing and rescue measures are formulated according to the evaluation result of the fire hazard level, so that the important areas and important hazard sources are fully protected, and the loss caused by the fire is reduced.
Description
Technical Field
The invention relates to the technical field of fire information analysis, in particular to an intelligent analysis system based on fire information.
Background
With the acceleration of the urban process, complex environments such as high-rise buildings, underground spaces, large markets and the like are increasing, and the risk of fire is also increasing. In addition, the occurrence frequency and hazard of fire in public places and families are gradually increasing, so that the requirements for monitoring and early warning of fire are more and more urgent. Meanwhile, the rapid development of the sensor technology, the Internet of things technology, the data processing technology, the artificial intelligence algorithm and other technologies provides technical support for intelligent analysis of fire information. By the technology, the real-time monitoring, data acquisition, intelligent analysis and early warning of fire can be realized.
For example, bulletin numbers: the invention patent of CN117473274B discloses an intelligent early warning system for mine fire disaster multi-source information fusion, which comprises a multi-source information acquisition unit, an information preprocessing unit, a core analysis unit and a fire disaster early warning unit, wherein the multi-source information acquisition unit is used for monitoring fire disaster influence information of a mine tunnel, the information preprocessing unit is used for carrying out data conversion, the multi-source information is integrated into standard data which can be uniformly processed, the core analysis unit is used for carrying out deep analysis to obtain influence coefficients of multi-source parameter indexes, then the comprehensive fire disaster risk degree is fused and evaluated, the overall trend of the comprehensive fire disaster risk degree is monitored, the fire disaster prediction risk coefficient of a current fire disaster monitoring point in a certain future time period is obtained, the fire disaster risk degree of the fire disaster monitoring point is finely analyzed by the fire disaster early warning unit, a fire disaster prediction track is generated, the fire disaster is prevented in advance accordingly, and fine and reliable fire disaster monitoring early warning management is realized.
For example, bulletin numbers: the invention patent of CN112580749B discloses an intelligent fire detection method based on a machine olfaction technology, which utilizes a machine olfaction system to carry out nondestructive detection on smell information when a fire disaster occurs, acquires multidimensional characteristic data, analyzes and discusses feasibility of an electronic nose for detecting and classifying the fire disaster smell through a random forest algorithm, establishes a detection and pattern recognition method with the best effect, and classifies molecular element types by utilizing a flavor database obtained by arrangement so as to judge the type of the adopted fire extinguishing agent. Solves the difficult problems that which fire extinguishing agent can not be selected in time and the wrong fire extinguishing agent can not be selected when the fire disaster occurs.
Based on the above scheme, the prior fire information analysis has some defects, particularly in the aspect of incomplete fire information data analysis, can not provide accurate field information and prospective information for fire-extinguishing rescue actions, can not formulate more targeted fire-extinguishing and rescue measures, and can not effectively improve the rescue efficiency.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an intelligent analysis system based on fire information, which can effectively solve the problems related to the background art.
In order to achieve the above purpose, the invention is realized by the following technical scheme: the invention provides an intelligent analysis system based on fire information, which comprises: the fire disaster data acquisition module is used for monitoring fire disaster information data of a fire disaster area in real time, including fire disaster scale information data and fire disaster spread risk information data.
The fire data analysis processing module is used for analyzing the fire scale information data and the fire spreading risk information data to obtain a fire scale degree index and a fire spreading risk assessment index of the fire area, and comprehensively analyzing the fire scale degree index and the fire spreading risk assessment index of the fire area to obtain a fire risk degree assessment index of the fire area.
The fire disaster level evaluation module is used for evaluating the fire disaster level according to the fire disaster risk degree evaluation index of the fire disaster area and planning rescue measures of the fire disaster area according to the fire disaster level.
As a further method, the fire scale information data and the fire spread risk information data are analyzed to obtain a fire scale index and a fire spread risk assessment index of a fire area, and the specific analysis process is as follows: and deploying a plurality of environment monitoring points in the fire disaster area, collecting the temperature and the smoke concentration of each environment monitoring point, simultaneously obtaining the fire source area, extracting the critical fire source temperature, the critical fire source area and the critical smoke concentration from the fire disaster database, and comprehensively analyzing to obtain the fire disaster scale degree index of the fire disaster area.
As a further method, the fire scale information data and the fire spread risk information data are analyzed to obtain a fire scale index and a fire spread risk assessment index of a fire area, and the specific analysis process is as follows: according to the fire spread risk information data, including the wind speed and the wind direction of the fire area, the fire spread direction is obtained through treatment, the inflammable substance content in the fire spread direction is obtained, the critical wind speed and the critical inflammable substance content are extracted from a fire database, and the fire spread risk assessment index of the fire area is obtained through comprehensive analysis.
As a further method, the comprehensive analysis is used for obtaining a fire hazard degree evaluation index of the fire region, and the specific analysis process is as follows: and collecting the heat radiation intensity of the fire area, and comprehensively analyzing to obtain the fire hazard degree evaluation index of the fire area according to the fire scale degree index and the fire spreading risk evaluation index of the fire area.
As a further method, the fire scale index of the fire area is quantitative evaluation data obtained by comprehensively analyzing the temperature, the smoke concentration and the fire source area of the fire area, is used for quantitatively evaluating the scale of the fire and provides a basis for evaluating the fire hazard level.
As a further method, the fire spread risk assessment index of the fire area is quantitative assessment data obtained by analyzing the wind speed of the fire area and the content of inflammable substances in the fire spread direction, and is used for quantitatively assessing the spread degree of the fire, so that a basis is provided for assessing the risk degree of the fire.
As a further method, the fire hazard degree evaluation index of the fire region is quantitative evaluation data obtained by analyzing the fire scale degree index, the fire spreading risk evaluation index and the heat radiation intensity of the fire region, and is used for quantitatively evaluating the hazard degree of the fire, so that a basis is provided for planning rescue measures of the fire region.
As a further method, the fire level is evaluated according to the fire hazard degree evaluation index of the fire area, and the specific analysis process is as follows: and matching the fire hazard degree evaluation index of the fire region with fire grades corresponding to all fire hazard degree evaluation index intervals stored in the fire database to obtain the fire grade of the fire region, and feeding back the fire grade evaluation result.
As a further method, the fire spread risk assessment index of the fire area has a specific numerical expression:
；
In the method, in the process of the invention, A fire spread risk assessment index indicating a fire area, s indicating the number of each environmental monitoring point,H represents the total number of environmental monitoring points,/>Wind speed representing the s < th > environmental monitoring point,/>Representing the content of inflammable substances in the fire spreading direction of the s-th environmental monitoring point,/>Represents the critical wind speed,/>Representing the critical inflammable substance content,/>A fire spread risk assessment index influence factor corresponding to the set wind speed,/>And the fire spread risk assessment index influence factor corresponding to the set inflammable substance content is represented.
As a further method, the fire hazard level evaluation index of the fire area has a specific numerical expression:
；
In the method, in the process of the invention, Fire hazard degree evaluation index indicating fire region, e indicating natural constant,/>Index of fire scale indicating fire area,/>Index of fire spread risk assessment indicating fire area,/>Representing the intensity of heat radiation in a fire region,/>Indicating the set critical heat radiation intensity,/>A fire hazard level evaluation index influence factor corresponding to the set fire scale level index,/>Fire hazard degree evaluation index influence factor corresponding to set fire hazard spread risk evaluation index,/>, and method for evaluating fire hazard degreeAnd (3) representing a fire hazard degree evaluation index influence factor corresponding to the set heat radiation intensity.
Compared with the prior art, the embodiment of the invention has at least the following advantages or beneficial effects:
(1) According to the intelligent analysis system based on the fire information, fire resources and personnel can be reasonably allocated according to the evaluation result of the fire hazard level, more targeted fire extinguishing and rescue measures are formulated, and important areas and important hazard sources are ensured to be fully protected, so that the loss caused by the fire is reduced.
(2) According to the fire disaster monitoring system, the fire disaster scale data monitored by the intelligent analysis system can be used for rapidly evaluating the fire disaster and the development trend, providing accurate field information for fire extinguishment and rescue actions, automatically allocating corresponding rescue resources according to the fire disaster scale, and being beneficial to improving rescue efficiency and reducing casualties.
(3) The invention helps to predict the development trend and potential influence area of fire by analyzing the fire spreading risk data, provides prospective information for fire-extinguishing rescue actions, is beneficial to reducing rescue time and improves fire-extinguishing efficiency.
Drawings
The invention will be further described with reference to the accompanying drawings, in which embodiments do not constitute any limitation of the invention, and other drawings can be obtained by one of ordinary skill in the art without inventive effort from the following drawings.
Fig. 1 is a schematic diagram of a system module connection according to the present invention.
FIG. 2 is a graph showing the fire hazard level evaluation index as a function of the thermal amplitude intensity according to the embodiment of the present invention.
Detailed Description
The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, but not all embodiments, and all other embodiments obtained by those skilled in the art without making creative efforts based on the embodiments of the present invention are included in the protection scope of the present invention.
Referring to fig. 1, the present invention provides an intelligent analysis system based on fire information, comprising: the fire disaster data acquisition module is used for monitoring fire disaster information data of a fire disaster area in real time, including fire disaster scale information data and fire disaster spread risk information data.
In a specific embodiment, fire information data of a fire area is monitored in real time by deploying a plurality of environment monitoring points in the fire area, and monitoring fire conditions of the monitoring points in real time by utilizing sensors such as a smoke detector, a temperature sensor, a flame detector and the like and a satellite remote sensing technology, so that the monitored data are integrated into fire scale information data and fire spreading risk information data. The real-time fire monitoring data can help the fire department to respond quickly, arrive at the fire scene in time, and reduce the loss caused by the fire. By analyzing the historical fire data and the real-time fire data, the direction and speed of fire spreading can be predicted, and precious time is won for fire extinguishing actions. Accurate fire data is helpful for reasonably allocating fire resources such as manpower, vehicles and equipment, and improving fire extinguishing efficiency.
The fire data analysis processing module is used for analyzing the fire scale information data and the fire spreading risk information data to obtain a fire scale degree index and a fire spreading risk assessment index of the fire area, and comprehensively analyzing the fire scale degree index and the fire spreading risk assessment index of the fire area to obtain a fire risk degree assessment index of the fire area.
Specifically, the fire scale information data and the fire spreading risk information data are analyzed to obtain a fire scale degree index and a fire spreading risk assessment index of a fire area, and the specific analysis process is as follows: and deploying a plurality of environment monitoring points in the fire disaster area, collecting the temperature and the smoke concentration of each environment monitoring point, simultaneously obtaining the fire source area, extracting the critical fire source temperature, the critical fire source area and the critical smoke concentration from the fire disaster database, and comprehensively analyzing to obtain the fire disaster scale degree index of the fire disaster area.
In a specific embodiment, the fire scale index of the fire area is quantitative evaluation data obtained by comprehensively analyzing the temperature, the smoke concentration and the fire source area of the fire area, and is used for quantitatively evaluating the scale of the fire and providing a basis for evaluating the fire hazard level.
It should be noted that the fire database in this embodiment is used for collecting, storing and managing fire related data, and includes information about fire acquired from various sources, including, but not limited to, location, time, cause, loss condition, rescue action, etc. of fire occurrence. The acquisition path of the fire database mainly monitors fire information data of a fire area in real time by searching related fire data and various sensors in the field. By analyzing a large amount of fire data stored in the database, the occurrence rule, the fire cause, the combustion characteristics and the like of the fire can be deeply known, and basic data can be provided for fire-fighting scientific research. The data in the fire database may be used to identify and predict fire risk. By summarizing hot spot areas, high risk industries, places and the like where the fire occurs, related departments can take precautionary measures in time, and the probability of the fire is reduced. After a fire accident, the rapid acquisition of the data in the fire database can help the commander to know the situation of the accident scene, including the fire intensity, the fire source position, the surrounding environment and the like. Such information is critical to the formulation of rescue schemes and to the command of fire extinguishing actions.
In a specific embodiment, the fire scale index of the fire area has the following specific numerical expression:
；
In the method, in the process of the invention, A fire scale degree index indicating a fire area, s indicating the number of each environmental monitoring point,H represents the total number of environmental monitoring points,/>Representing the temperature of the s < th > environmental monitoring point,/>Represents the smoke concentration of the s-th environmental monitoring point,/>Representing the area of the fire source,/>Represents the critical temperature,/>Represents the critical smoke concentration,/>Representing the critical fire source area,/>Indicating the fire scale factor corresponding to the set temperature,/>Indicating a fire scale factor corresponding to the set smoke concentration,/>And the fire scale degree influence factor corresponding to the set fire source area is shown.
It should be noted that the critical temperature is set to 50 ℃ in this embodiment, and this parameter represents the temperature threshold change associated with the development of fire or other thermodynamic processes. When the temperature of the monitoring point exceeds its normal range by 50 degrees celsius, it may mean that a safety hazard or abnormal condition exists. The critical smoke concentration was set to 0.05mg/m 3, and the change in smoke concentration was a key indicator for assessing the progress of fire or air quality. If the smoke concentration rises above this threshold, this indicates that the smoke released from combustion is increased and may pose a threat to environmental or personnel safety. The increase in the area of the fire source directly affects the spread rate and intensity of the fire. Setting the critical fire area to 10m 2 means that the fire expands to 10m 2 greater than the initial area is an important consideration for assessing the severity and potential hazards of the fire. The impact factors are used to adjust the contribution weights of the variables to the final result. In this embodiment, the fire scale level influence factor corresponding to the temperature: =2, indicating that the effect of monitoring point temperature changes on the overall risk assessment is strong. The magnitude of the influencing factor represents the relative importance of the variable. Fire scale factor for smoke concentration: /(I) =3, Meaning that smoke concentration changes are weighted higher than other factors, i.e. small changes in smoke concentration will affect the overall evaluation result more significantly. Fire scale degree influence factor corresponding to fire source area: /(I)=1, Meaning that in the current model, the direct impact of the expansion of the fire source area on the final evaluation result is considered minimal or as a baseline reference with respect to temperature and smoke concentration.
It should be explained that, in this embodiment, the fire scale factor corresponding to the temperature, smoke concentration and fire area is obtained by integrating detailed data of a fire simulation experiment with a deep experience of a field expert to construct a set of mapping rule system, reflecting the specific contribution of the temperature, smoke concentration and fire area to the fire hazard level evaluation index.
Table 1 fire scale index data example
It should be noted that the fire scale index in this embodiment is determined by the temperature, the smoke concentration and the fire source area, and the higher the temperature, the higher the smoke concentration, and the larger the fire source area, the larger the fire scale index.
It should be explained that, in this embodiment, the temperature is an important index for measuring the intensity and activity of fire, and the increase of the temperature accelerates the combustion reaction, so that the fire is more likely to spread. The high temperature can also lead more combustible substances to reach the ignition point, and the fire range is enlarged. High temperatures may also affect the structural stability of the building, and excessive temperatures may soften or lose strength of the building material, resulting in collapse of the building. The smoke concentration reflects the combustion state and possible toxicity level of the fire scene, and the smoke contains a large amount of harmful substances including carbon monoxide, hydrogen cyanide and other toxic gases and tiny combustion particles. High concentrations of smoke can cause inhalational damage, one of the major causes of casualties in fires. The smoke can also reduce visibility rapidly, influence personnel evacuation and fire rescue actions, and increase escape difficulty and rescue risk. The rising of smog can also carry the heat, forms hot flue gas layer, influences the inside temperature distribution of building, further aggravates the danger of conflagration. The area of a fire source refers to the size of the area where the fire actually burns, and expansion of the area of the fire source generally means spread of the fire and exacerbation of the fire. The area of the fire source directly determines the energy output of the fire. The larger the area of the fire source, the more heat is released, the more violent the fire is, and the difficulty of control and extinguishing is correspondingly increased. The larger area of the fire source can generate stronger heat radiation, so that a larger heat effect is caused to the surrounding environment, and the ignition process of the surrounding combustible is accelerated. Therefore, controlling temperature and heat source management, limiting fire area, and reducing smoke generation and controlling smoke spread are important in preventing the occurrence of fires. The specific measures include periodically checking and maintaining electrical circuits, heating equipment and kitchen appliances, ensuring no short circuit, overload or leakage phenomena, avoiding fires caused by local overheating. Heat insulation treatment is performed using high temperature resistant materials, particularly in the vicinity of kitchen and industrial heat sources, to limit heat diffusion in high temperature areas. A temperature monitoring system is implemented, particularly for areas where flammable substances are stored, ensuring that the ambient temperature remains within a safe range. The fire-proof areas are divided, and physical partitions such as a firewall and a fireproof door are adopted to limit the spreading path of potential fire sources. Inflammable articles are classified and stored, the storage amount is controlled, enough fireproof intervals are ensured, and the fire source area in case of fire is reduced. And installing an automatic water spraying fire extinguishing system or a gas fire extinguishing system, starting immediately once a fire source is detected, and controlling the area of the fire source as soon as possible. When the building is designed, a good ventilation system is considered, so that the smoke can be discharged rapidly, and the accumulation is reduced. The smoke detector and alarm system are installed and an alarm is raised immediately once the smoke concentration exceeds a threshold value for early detection and intervention. Smoke exhaust facilities such as a smoke exhaust fan and a smoke exhaust port and smoke prevention partitions used in emergency are installed in the necessary areas, so that smoke diffusion is effectively controlled. Fire exercises are performed to educate staff and residents about correct actions in the case of fire, such as low-posture movements to reduce smoke inhalation.
It should be understood that in this embodiment, the temperature, the area of the fire source, and the smoke concentration are related to each other in the fire dynamics, which affect the development and the hazard level of the fire together, and the area of the fire source directly affects the heat generated by the combustion, thereby affecting the temperature of the fire scene. The larger the area of the fire source, the more total heat generated by combustion, and the higher the temperature of the surrounding environment. The high temperature not only accelerates the thermal decomposition and oxidation of the surrounding combustibles, promoting the rapid spread of the fire, but also may reduce the strength of the structural materials and increase the risk of collapse of the building. The temperature rise accelerates incomplete combustion of the combustible material, producing more smoke and toxic gases. The particles and gases in the smoke diffuse faster at high temperatures, causing the smoke concentration to rise sharply in a short period of time. The high temperature may also change the physical state of the smoke, such as converting certain gases into steam, increasing the density and shielding effect of the smoke, affecting vision and respiratory safety. The expansion of the area of the fire source means an expansion of the combustion range, and more substances participate in combustion, naturally producing more smoke and combustion byproducts. The increase of the area of the fire source not only directly increases the generation amount of the smoke, but also promotes the accumulation and diffusion of the smoke by increasing the local temperature, thereby leading to the rapid increase of the smoke concentration, the reduction of the visibility and causing serious obstacle to personnel evacuation and rescue. The fire scale data monitored by the intelligent analysis system can be used for rapidly evaluating the fire intensity and the development trend, providing accurate field information for fire-extinguishing rescue actions, automatically allocating corresponding rescue resources according to the fire scale, and being beneficial to improving rescue efficiency and reducing casualties.
It should be explained that, in this embodiment, the fire scale index of the fire area may be obtained by not only providing a large-scale fire monitoring data analysis by using a satellite remote sensing technology, but also predicting and evaluating the fire scale by using historical fire data and an established fire spread model, and further by calculating a formula.
Specifically, the fire scale information data and the fire spreading risk information data are analyzed to obtain a fire scale index and a fire spreading risk assessment index of a fire area, and the specific analysis process is as follows: according to the fire spread risk information data, including the wind speed and the wind direction of the fire area, the fire spread direction is obtained through treatment, the inflammable substance content in the fire spread direction is obtained, the critical wind speed and the critical inflammable substance content are extracted from a fire database, and the fire spread risk assessment index of the fire area is obtained through comprehensive analysis.
In a specific embodiment, the fire spread risk assessment index of the fire area is quantitative assessment data obtained by analyzing the wind speed of the fire area and the content of inflammable substances in the fire spread direction, and is used for quantitatively assessing the fire spread degree and providing a basis for assessing the fire risk degree.
In a specific embodiment, the fire spread risk assessment index of the fire area has the following specific numerical expression:
；
In the method, in the process of the invention, Index of fire spread risk assessment indicating fire area,/>Wind speed representing the s < th > environmental monitoring point,/>Representing the content of inflammable substances in the fire spreading direction of the s-th environmental monitoring point,/>Represents the critical wind speed,/>Representing the critical inflammable substance content,/>A fire spread risk assessment index influence factor corresponding to the set wind speed,/>And the fire spread risk assessment index influence factor corresponding to the set inflammable substance content is represented.
It should be noted that, in this embodiment, the critical wind speed is set to 5m/s, and this parameter sets a threshold value of the wind speed beyond which the promotion effect of the wind speed on the fire spread is significantly enhanced. The relative influence of wind speed is quantified by calculating the ratio to the actual wind speed. The critical combustible substance content was set to 0.05mg/L, which is similarly a value defining the safety and hazard limits of the combustible substance content. When the flammable substance content of the monitoring point exceeds this value, the risk of fire spreading increases dramatically. The impact factor of the fire spread risk assessment index corresponding to the wind speed is 2, and the impact factor represents the importance degree of the wind speed in the fire spread risk assessment. A value of 2 means that the wind speed has twice the influence on the final evaluation result compared to the combustible substance content. The fire spread risk assessment index corresponding to the content of the inflammable substance has an influence factor of 3, representing the importance of the content of the inflammable substance. Although the value is 3, the influence factor is higher than the wind speed, the specific influence is considered by combining the wind speed and the actual content value. This means that in this embodiment, small variations in the content of inflammable substances may have a greater influence on the risk of fire spread than small variations in wind speed.
It should be explained that, in this embodiment, the fire spreading risk assessment index influence factor corresponding to the wind speed and the fire spreading risk assessment index influence factor corresponding to the combustible substance content are specifically obtained by collecting abundant fire simulation experiment data, taking the wind speed and the combustible substance content as input variables, simultaneously establishing a model with the fire spreading risk assessment index as target variables, and quantifying and extracting the specific influence of the wind speed and the combustible substance content on the fire spreading risk by adopting statistical analysis methods such as linear regression, etc.
Table 2 fire spread risk assessment index data example
It should be understood that the fire spread risk assessment index in this embodiment is determined by the wind speed and the combustible substance content, and the greater the wind speed, the higher the combustible substance content, and the greater the corresponding fire spread risk assessment index.
It should be explained that, in the present embodiment, wind speed is one of the key factors affecting the speed and direction of fire spread. The large wind speed can accelerate the spread of fire and improve the dangerous level of fire. The increased wind speed provides more oxygen, promotes the combustion reaction and accelerates the fire propagation. The fast flowing air can enhance the activity of the flame, making the fire more difficult to control. Strong winds can carry the heat radiation and sparks generated by combustion to a far distance, causing new fires, increasing the range and unpredictability of the fire. High wind speeds can accelerate the spread of smoke and toxic gases, while helping to reduce local smoke concentrations, while also potentially affecting larger areas, increasing the risk of personnel poisoning and asphyxiation. The content of combustible substances directly relates to the fuel supply of the fire, the higher the content, the greater the probability and speed of fire propagation. The higher the content of combustible materials in the environment, the less energy is required to reach the ignition point and the greater the likelihood of fire. The high content of inflammable substances means more energy is released in the combustion process, the fire is more violent, the temperature of the fire field is higher, and the damage to the surrounding environment is stronger. When some inflammable substances burn, toxic gases such as carbon monoxide are generated, and when the content is too high, personnel can be injured or killed by sucking the toxic gases even if the personnel do not directly contact with the flame. The high concentration of flammable substances makes the fire more difficult to control, requiring more extinguishing agent and longer time to extinguish completely. Thus by monitoring the combustible material content at various points, the potential risk of fire spread can be assessed.
It should be explained that in this embodiment, the wind speed accelerates the flow of air, provides more oxygen, promotes the oxidation reaction of inflammable substances, and accelerates the combustion rate. In environments with high levels of flammable substances, an increase in wind speed can significantly increase the severity and rate of spread of the fire. This is because more combustibles participate in the combustion reaction in a short time, releasing more heat and flame, making the fire more difficult to control. The direction of the wind determines the direction of the fire propagation. In areas where flammable materials are concentrated, if the wind direction blows the flame against these materials, the fire will be directed rapidly to a new fuel source, resulting in a rapid expansion of the fire scale. Therefore, the knowledge and prediction of wind direction are important for setting fire isolation belts in advance, planning evacuation routes and suppressing the early stage of fire. By combining the wind speed and the wind direction, the spreading path and the speed of the fire can be predicted. In addition, wind can also influence the diffusion mode of smog and poisonous gas, influences personnel's evacuation and fire control operation's safety. The synergistic effect of wind speed and direction, together with the content of inflammable substances, has a decisive influence on the initiation, development and final control of the fire. By analyzing the fire spreading risk data, the method helps to predict the development trend and potential influence area of fire, provides prospective information for fire-extinguishing rescue actions, and is beneficial to reducing rescue time and improving fire-extinguishing efficiency.
It should be explained that an increase in wind speed and an increase in the content of combustible substances both significantly increase the risk of fire. In the prevention and management of fire, the wind speed change in weather forecast is needed to be closely concerned, inflammable substances are reasonably stored and managed, effective measures are taken to reduce risks in the two aspects, and the specific measures are that, when building design and urban planning are carried out, the influence of wind direction and wind speed on the fire is considered, the building is reasonably laid, a wind-proof forest or a wind-proof wall is arranged, and the combustion-supporting effect of wind speed on the fire is reduced. Reinforcing monitoring and early warning: and the weather station data and the local wind speed monitoring equipment are utilized to monitor the wind speed change in real time, particularly in forests and open areas, and once the wind speed reaches the early warning standard, the fire hazard early warning is issued in time to prepare for emergency. The inflammable substances are classified and stored in a limited amount, and are far away from a fire source and a heat source, and explosion-proof electrical equipment is used, so that good ventilation of a storage area is ensured, and fire hazards are reduced. Periodically checking flammable substance stock to ensure that the flammable substance stock meets the safe storage standard; professional training is performed on personnel handling inflammable substances, so that the safety awareness and emergency processing capacity of the personnel are improved. The automatic spraying system, the gas fire extinguishing system and the fire alarm system are arranged in the inflammable substance storage and treatment area, and can be started immediately and responded quickly once a fire is detected. The detailed fire emergency plan is formulated, which comprises the steps of combustible material leakage and initial treatment of fire, emergency exercises are organized regularly, and rapid and effective response in emergency situations is ensured.
It should be explained that, in this embodiment, the fire spread risk assessment index of the fire area may be obtained by not only providing a large-scale analysis of fire monitoring data by using satellite remote sensing technology, but also by using a fire risk assessment tool and model, and by combining the collected fire data and the selected fire risk index, and performing calculation and assessment, and may also be obtained by calculation through a formula.
Further, comprehensive analysis is carried out to obtain a fire hazard degree evaluation index of the fire region, and the specific analysis process is as follows: and acquiring the heat radiation intensity of the fire area, and comprehensively analyzing the heat radiation intensity of the fire area according to the fire scale degree index of the fire area, the fire spreading risk assessment index of the fire area and the heat radiation intensity of the fire area to obtain the fire hazard degree assessment index of the fire area.
In a specific embodiment, the fire hazard level evaluation index of the fire region is quantitative evaluation data obtained by analyzing the fire scale level index, the fire spreading risk evaluation index and the heat radiation intensity of the fire region, and is used for quantitatively evaluating the hazard level of the fire, so as to provide a basis for planning rescue measures of the fire region.
It should be explained that, in this embodiment, the fire hazard level evaluation index of the fire region may be obtained by not only providing some types of fire hazard level information data analysis by satellite remote sensing technology, but also determining the fire hazard level by performing field investigation and expert evaluation, and may also be obtained by calculation through a formula.
In a specific embodiment, the fire hazard level evaluation index of the fire area has the following specific numerical expression:
；
In the method, in the process of the invention, Fire hazard degree evaluation index indicating fire region, e indicating natural constant,/>Index of fire scale indicating fire area,/>Index of fire spread risk assessment indicating fire area,/>Representing the intensity of heat radiation in a fire region,/>Indicating the set critical heat radiation intensity,/>A fire hazard level evaluation index influence factor corresponding to the set fire scale level index,/>Fire hazard degree evaluation index influence factor corresponding to set fire hazard spread risk evaluation index,/>, and method for evaluating fire hazard degreeAnd (3) representing a fire hazard degree evaluation index influence factor corresponding to the set heat radiation intensity.
It should be explained that in the present embodiment, the critical heat amplitude intensity is set to 10kW/m 2, which means that when the heat radiation intensity exceeds this value, it is considered that the critical point of emergency or immediate action is required is reached. The fire hazard level assessment index corresponding to the fire scale level index has an impact factor of 0.4, which means that a larger fire directly correlates with a higher destructive potential, and the fire scale is usually the primary factor in fire hazard level assessment and can be set to a higher weight. The fire hazard level evaluation index corresponding to the fire spread risk evaluation index has an influence factor of 0.3, which indicates that it is also an extremely critical factor. The risk of spread is critical to controlling the fire. The fire hazard level evaluation index corresponding to the heat radiation intensity has an influence factor of 0.3, and the heat radiation affects the safety of personnel and the stability of surrounding structures, so that the fire hazard level evaluation index is also an important index. In fig. 2, curve a shows the change of the fire hazard level evaluation index with the change of the heat amplitude intensity in the case where the fire scale level index is 2.54 and the fire spread risk evaluation index is 2.44, curve b shows the change of the fire hazard level evaluation index with the change of the heat amplitude intensity in the case where the fire scale level index is 3.05 and the fire spread risk evaluation index is 2.69, and curve c shows the change of the fire hazard level evaluation index with the change of the heat amplitude intensity in the case where the fire scale level index is 3.56 and the fire spread risk evaluation index is 2.99. Wherein, the abscissa is the intensity of the thermal amplitude, and the ordinate is the fire hazard degree evaluation index.
It should be explained that, in this embodiment, the fire hazard level evaluation index influence factor corresponding to the fire scale level index and the fire hazard level evaluation index influence factor corresponding to the fire spread risk evaluation index are obtained by performing a fire simulation experiment, and computer simulation software (such as FDS, FIRE DYNAMICS simuator) is used to simulate the fire development under different conditions, and the influence factors are adjusted and verified by the simulation results. The fire hazard degree assessment index influence factor corresponding to the heat radiation intensity is obtained by establishing a set of mapping rule system according to detailed data of fire simulation experiments and integrating rich experience of field experts, and accurately quantifying the influence of the heat radiation intensity on the fire hazard degree.
It should be explained that, as can be seen from fig. 2, the greater the heat amplitude intensity, the fire scale level index, and the fire spread risk assessment index, the higher the fire risk level assessment index, and when the heat amplitude intensity is lower than 40kW/m 2, the fire risk level assessment index is very low, but when the heat amplitude intensity is higher than 80kW/m 2, the fire risk level assessment index is abruptly increased. The heat radiation heats the surrounding combustibles and when the temperature of these substances reaches their ignition point, new fires may be initiated, thereby accelerating the spread of the fire and expanding the range of the fire. High intensity heat radiation can rapidly raise the temperature of human skin, leading to burns and even in extreme cases, death. In addition, intense heat radiation can also prevent firefighters from accessing the fire source for rescue and fire extinguishing operations. The long-time heat radiation also reduces the strength of structural materials (such as steel, concrete and the like) of the building, which can cause the building to collapse, increase the difficulty of fire control and endanger personnel safety. Meanwhile, the high-temperature environment formed by heat radiation can obstruct people from being evacuated, the visibility is reduced, and the efficiency of rescue equipment is also challenged. Therefore, the intensity of heat radiation is an important factor in determining the fire spacing between buildings when planning the layout of the buildings. The setting of the fire-proof distance aims at preventing a fire from igniting adjacent buildings by thermal radiation, ensuring a sufficient safety distance to reduce the risk of fire spreading.
The fire disaster level evaluation module is used for evaluating the fire disaster level according to the fire disaster risk degree evaluation index of the fire disaster area and planning rescue measures of the fire disaster area according to the fire disaster level.
Specifically, the fire hazard level is evaluated according to the fire hazard level evaluation index of the fire hazard area, and the specific analysis process is as follows: and matching the fire hazard degree evaluation index of the fire region with fire grades corresponding to all fire hazard degree evaluation index intervals stored in the fire database to obtain the fire grade of the fire region, and feeding back the fire grade evaluation result.
In a specific embodiment, the fire hazard level evaluation index of the fire region is matched with fire hazard levels corresponding to each fire hazard level evaluation index interval stored in the fire database to obtain the fire hazard level of the fire region, specifically, the fire hazard level is classified into three levels of low, medium and high, the fire hazard level evaluation index is compared with the fire hazard level evaluation index interval of the corresponding level for analysis, if the fire hazard level evaluation index is higher than the lowest value of the fire hazard level evaluation index interval and lower than the highest value of the fire hazard level evaluation index interval, the fire hazard is indicated to be in the corresponding fire hazard level, and finally fire rescue measures are planned according to the fire hazard level.
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art can be made to the described embodiments without departing from the scope of the invention or from the scope of the invention as defined in the accompanying claims.
Claims (10)
1. An intelligent analysis system based on fire information, comprising:
the fire disaster data acquisition module is used for monitoring fire disaster information data of a fire disaster area in real time, including fire disaster scale information data and fire disaster spread risk information data;
The fire data analysis processing module is used for analyzing the fire scale information data and the fire spreading risk information data to obtain a fire scale degree index and a fire spreading risk assessment index of the fire area, and comprehensively analyzing the fire scale degree index and the fire spreading risk assessment index of the fire area to obtain a fire risk degree assessment index of the fire area;
the fire disaster level evaluation module is used for evaluating the fire disaster level according to the fire disaster risk degree evaluation index of the fire disaster area and planning rescue measures of the fire disaster area according to the fire disaster level.
2. The intelligent analysis system based on fire information of claim 1, wherein: the fire scale information data and the fire spreading risk information data are analyzed to obtain a fire scale degree index and a fire spreading risk assessment index of a fire area, and the specific analysis process is as follows:
And deploying a plurality of environment monitoring points in the fire disaster area, collecting the temperature and the smoke concentration of each environment monitoring point, simultaneously obtaining the fire source area, extracting the critical fire source temperature, the critical fire source area and the critical smoke concentration from the fire disaster database, and comprehensively analyzing to obtain the fire disaster scale degree index of the fire disaster area.
3. The intelligent analysis system based on fire information of claim 1, wherein: the analysis of the fire scale information data and the fire spreading risk information data to obtain a fire scale index and a fire spreading risk assessment index of a fire area further comprises:
According to the fire spread risk information data, including the wind speed and the wind direction of the fire area, the fire spread direction is obtained through treatment, the inflammable substance content in the fire spread direction is obtained, the critical wind speed and the critical inflammable substance content are extracted from a fire database, and the fire spread risk assessment index of the fire area is obtained through comprehensive analysis.
4. An intelligent analysis system based on fire information as claimed in claim 3, wherein: the comprehensive analysis obtains a fire hazard degree evaluation index of a fire region, and the specific analysis process comprises the following steps:
And collecting the heat radiation intensity of the fire area, and comprehensively analyzing to obtain the fire hazard degree evaluation index of the fire area according to the fire scale degree index and the fire spreading risk evaluation index of the fire area.
5. An intelligent analysis system based on fire information as claimed in claim 2, wherein: the fire scale degree index of the fire area is quantitative evaluation data obtained by comprehensively analyzing the temperature, the smoke concentration and the fire source area of the fire area, is used for quantitatively evaluating the scale degree of the fire and provides a basis for evaluating the fire hazard degree.
6. An intelligent analysis system based on fire information as claimed in claim 3, wherein: the fire spreading risk assessment index of the fire area is quantitative assessment data obtained by analyzing the wind speed of the fire area and the content of inflammable substances in the fire spreading direction, is used for quantitatively assessing the spreading degree of the fire, and provides a basis for assessing the risk degree of the fire.
7. The intelligent analysis system based on fire information of claim 4, wherein: the fire hazard degree evaluation index of the fire region is quantitative evaluation data obtained by analyzing the fire scale degree index, the fire spreading risk evaluation index and the heat radiation intensity of the fire region, is used for quantitatively evaluating the fire hazard degree and provides a basis for planning rescue measures of the fire region.
8. The intelligent analysis system based on fire information of claim 1, wherein: the fire disaster grade is evaluated according to the fire disaster risk degree evaluation index of the fire disaster area, and the specific analysis process is as follows:
and matching the fire hazard degree evaluation index of the fire region with fire grades corresponding to all fire hazard degree evaluation index intervals stored in the fire database to obtain the fire grade of the fire region, and feeding back the fire grade evaluation result.
9. An intelligent analysis system based on fire information as claimed in claim 3, wherein: the fire spreading risk assessment index of the fire area has the following specific numerical expression:
；
In the method, in the process of the invention, A fire spread risk assessment index indicating a fire area, s indicating the number of each environmental monitoring point,H represents the total number of environmental monitoring points,/>Wind speed representing the s < th > environmental monitoring point,/>Representing the content of inflammable substances in the fire spreading direction of the s-th environmental monitoring point,/>Represents the critical wind speed,/>Representing the critical inflammable substance content,/>A fire spread risk assessment index influence factor corresponding to the set wind speed,/>And the fire spread risk assessment index influence factor corresponding to the set inflammable substance content is represented.
10. The intelligent analysis system based on fire information of claim 4, wherein: the fire hazard degree evaluation index of the fire region comprises the following specific numerical expressions:
；
In the method, in the process of the invention, Fire hazard degree evaluation index indicating fire region, e indicating natural constant,/>Index of fire scale indicating fire area,/>Index of fire spread risk assessment indicating fire area,/>Representing the intensity of heat radiation in a fire region,/>Indicating the set critical heat radiation intensity,/>A fire hazard level evaluation index influence factor corresponding to the set fire scale level index,/>Fire hazard degree evaluation index influence factor corresponding to set fire hazard spread risk evaluation index,/>, and method for evaluating fire hazard degreeAnd (3) representing a fire hazard degree evaluation index influence factor corresponding to the set heat radiation intensity.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410634182.1A CN118230533B (en) | 2024-05-22 | 2024-05-22 | Intelligent analysis system based on fire information |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410634182.1A CN118230533B (en) | 2024-05-22 | 2024-05-22 | Intelligent analysis system based on fire information |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN118230533A true CN118230533A (en) | 2024-06-21 |
| CN118230533B CN118230533B (en) | 2024-08-06 |
Family
ID=91504261
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410634182.1A Active CN118230533B (en) | 2024-05-22 | 2024-05-22 | Intelligent analysis system based on fire information |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN118230533B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118379841A (en) * | 2024-06-24 | 2024-07-23 | 民航成都电子技术有限责任公司 | Integrated fire-fighting linkage alarm method and system |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20200066140A1 (en) * | 2017-03-15 | 2020-02-27 | Carrier Corporation | System and method for indicating building fire danger ratings |
| CN113034833A (en) * | 2021-03-02 | 2021-06-25 | 梅州市悦思智能科技有限公司 | Artificial intelligence information management system based on multisensor fuses |
| CN116189372A (en) * | 2023-03-02 | 2023-05-30 | 南京林业大学 | Forest fire prevention multilayer early warning and monitoring system and method applying big data technology |
| CN116307739A (en) * | 2023-05-15 | 2023-06-23 | 安徽省赛达科技有限责任公司 | Forest fire prevention intelligent monitoring early warning system |
| CN116524666A (en) * | 2023-05-06 | 2023-08-01 | 江西赣鄱云新型智慧城市技术研究有限公司 | Fire monitoring and early warning system based on data analysis |
| CN117392798A (en) * | 2023-09-25 | 2024-01-12 | 中国消防救援学院 | Forest fire early warning method |
-
2024
- 2024-05-22 CN CN202410634182.1A patent/CN118230533B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20200066140A1 (en) * | 2017-03-15 | 2020-02-27 | Carrier Corporation | System and method for indicating building fire danger ratings |
| CN113034833A (en) * | 2021-03-02 | 2021-06-25 | 梅州市悦思智能科技有限公司 | Artificial intelligence information management system based on multisensor fuses |
| CN116189372A (en) * | 2023-03-02 | 2023-05-30 | 南京林业大学 | Forest fire prevention multilayer early warning and monitoring system and method applying big data technology |
| CN116524666A (en) * | 2023-05-06 | 2023-08-01 | 江西赣鄱云新型智慧城市技术研究有限公司 | Fire monitoring and early warning system based on data analysis |
| CN116307739A (en) * | 2023-05-15 | 2023-06-23 | 安徽省赛达科技有限责任公司 | Forest fire prevention intelligent monitoring early warning system |
| CN117392798A (en) * | 2023-09-25 | 2024-01-12 | 中国消防救援学院 | Forest fire early warning method |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118379841A (en) * | 2024-06-24 | 2024-07-23 | 民航成都电子技术有限责任公司 | Integrated fire-fighting linkage alarm method and system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN118230533B (en) | 2024-08-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN118230533B (en) | Intelligent analysis system based on fire information | |
| Kodur et al. | Fire hazard in buildings: review, assessment and strategies for improving fire safety | |
| CN108295407A (en) | Robot cable piping lane scene fire alarm and extinguishing method, device, system | |
| CN116645775A (en) | Cloud platform fire alarm information response system | |
| Chen et al. | Fire risk assessment in cotton storage based on fuzzy comprehensive evaluation and Bayesian network | |
| Khan et al. | Machine learning driven smart fire safety design of false ceiling and emergency response | |
| Raja et al. | Investigating the impact of oxygen concentration on fire dynamics using numerical simulation with FDS | |
| CN116205085B (en) | Research and development type building multi-combustible fire coupling result evaluation method | |
| Salami et al. | Enhancing fire safety in underground mines: Experimental and large eddy simulation of temperature attenuation, gas evolution, and bifurcation influence for improved emergency response | |
| Thakkar et al. | Environmental fire hazard detection and prediction using random forest algorithm | |
| Jiang et al. | Numerical simulation of cruise ship cabin fire based on FDS | |
| Hu | Research on the Fire of High-rise Residential Building Based on Pyrosim Numerical Simulation | |
| CN118521168B (en) | Fire safety risk assessment method and system for thermal power plant | |
| Andersson | Evaluation and mitigation of industrial fire hazards | |
| Muller et al. | SCHEMA-SI: A hybrid fire safety engineering tool Part II: Case study | |
| Lee et al. | Indication System in Fire Accident & IAQ of Building with Central Controlling System | |
| Leiras et al. | A performance-based fire risk analysis for buildings | |
| Aziz et al. | Dwelling Fire Safety Evacuation (DFSE): A Conceptual Approach | |
| CN118521168A (en) | Fire safety risk assessment method and system for thermal power plant | |
| Hume | Firefighting in under-ventilated compartments: Literature review | |
| Ou et al. | Fire Characteristics of Light Steel Structure Building and Suggestions for Fire Alarm System | |
| Wang et al. | Fire simulation at the end of cable tunnel based on high voltage cable burning experiment | |
| Carboni et al. | On the use of Fire Safety Engineering to Evaluate the Performance of Heat Detectors in High Ceiling Application | |
| Barros Daza | Advanced Computing and Sensing to Improve Mine Fire Characterization and Response | |
| Tharima et al. | Application of response surface methodology for optimizing evacuation time in enclosed car park |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |