CN116993050A - Intelligent building intensive management and control system and method - Google Patents
Intelligent building intensive management and control system and method Download PDFInfo
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Abstract
The invention provides an intelligent building intensive management and control system and method, comprising the following steps: the BIM model building module is used for obtaining building parameter information to perform building modeling, and the building after modeling is used for adjusting the display transparency of the building through instructions; the risk position positioning module is used for acquiring image data to perform risk position positioning operation, and performing risk position information positioning operation by acquiring facility data of each floor position of the building and combining fire-fighting facility data; and the risk treatment module is used for judging the building risk treatment threshold value according to the positioned risk position information and transmitting the risk treatment threshold value to the intelligent management terminal.
Description
Technical Field
The invention relates to the technical field of intelligent building management and control, in particular to an intelligent building intensive management and control system and method.
Background
Because of large-scale construction of cities in modern society, intelligent management is needed in the formed high-rise building, real-time analysis of monitoring video states in the building is needed, abnormal investigation of real-time monitoring pictures of a fire-fighting system and real-time monitoring of internal circuit systems and waterway pipe networks of the building are needed, image data acquired in the building are needed to be monitored in real time for management staff, intensive management and control are needed, high efficiency and safety of operation in the intelligent building are guaranteed, and the technical problems corresponding to the technical staff in the field are needed to be solved.
Disclosure of Invention
The invention aims at least solving the technical problems in the prior art, and particularly creatively provides an intelligent building intensive management and control system and method.
In order to achieve the above object of the present invention, the present invention provides an intelligent building intensive management and control system, comprising:
the BIM model building module is used for obtaining building parameter information to perform building modeling, and the building after modeling is used for adjusting the display transparency of the building through instructions;
the risk position positioning module is used for acquiring image data to perform risk position positioning operation, and performing risk position information positioning operation by acquiring facility data of each floor position of the building and combining fire-fighting facility data;
and the risk treatment module is used for judging the building risk treatment threshold value according to the positioned risk position information and transmitting the risk treatment threshold value to the intelligent management terminal.
Preferably, in the above technical solution, the BIM model building module further includes:
the two-dimensional and three-dimensional visual platform is used for controlling the building data of the intelligent building through the whole body, and has the data checking and counting functions; modeling operation is carried out according to intelligent building data, a semi-transparent BIM model is formed aiming at each floor of a building, building data are respectively extracted for each floor, distribution of fire-fighting facilities is displayed according to the formed BIM model, and running state data are extracted;
selecting any floor data, collecting positions of fire fighting facilities, temperature sensors and smoke sensors, establishing facility position coordinates according to corresponding positions to form a 3D facility map, forming a position list by the facility map, performing data interaction feedback, and screening the positions of the fire fighting facilities which are successfully bound and the fire fighting facilities which are not successfully bound; and forming a binding relation between the map position of the 3D facility and the fire-fighting facility.
Preferably, in the foregoing technical solution, the risk location positioning module includes:
determining the position coordinates of the fire-fighting equipment on the floor according to the acquired images, and forming the working area S=pi r of the radius r by taking the fire-fighting equipment as an origin 2 Acquiring temperature information and smoke information acquired by a temperature sensor and a smoke sensor at the intersection point position where the radius r of another fire-fighting facility and the adjacent fire-fighting facility form an intersection, judging the surrounding environment value of the fire-fighting facility, forming a fire-fighting intensive grid of the intelligent building, and forming all risk position positioning by any intersection point (x, y) in the fire-fighting intensive gridSum of added positioningn is a positive integer and the number of the intersection points.
Preferably, in the foregoing technical solution, the risk location positioning module includes:
the risk position positioning estimation is carried out on the acquired information of the adjacent temperature sensors and the smoke sensors around the fire-fighting facility, and an intelligent building risk position discovery function is established according to the risk position information at the acquisition time t;
wherein eta is a building environment loss threshold value, mu is a personnel heat effect threshold value,for the risk position location sum N fire loads of fire-fighting facilities e, C is the temperature anomaly value of the whole time period, C is the constant normalized by the objective function, dR t Differentiation of the smoke anomaly at time t, dt being the time differentiation, < >>Locating the heat capacity, P, of person P in the sum N for risk locations t For the person heat of the risk location area at time t,/->The average value of the heat quantity of the personnel in the risk position positioning area at the moment t is S, namely the fire protection coverage area of the fire protection facility, and the +.>Is the difference of the personnel heat quantity in unit area.
Preferably, in the foregoing technical solution, the risk handling module includes:
in the risk position locating process, building environment loss coefficients are required to be adjusted, and calculation conditions for adjusting the building environment loss threshold are as follows:
wherein, the loss coefficient is calculated through, D is penalty factor, lambda is building environment influence weight, F t A fire protection facility response real-time value for the risk location area at time t,and T is a time index, and T is a time upper limit.
The above technical scheme is preferable, and the calculation process of the personnel heat effect threshold is as follows:
wherein B is self For the thermal coefficient of the risk location area, B p For the human heat release coefficient, T high For the highest indoor temperature of the risk location area, T low The lowest indoor temperature for the risk location area.
According to the technical scheme, risk judgment is preferably carried out by calculating the loss threshold value and the thermal effect threshold value, the risk judgment is substituted into a risk position issuing function for comprehensive evaluation, and whether a result meeting threshold value adjustment exists or not is searched from the acquired temperature sensor and smoke sensor information; when the threshold value adjusting result is met in all the information, determining a fire-fighting facility risk position positioning area corresponding to the threshold value adjusting result, determining the adjacent fire-fighting facility position according to the risk position positioning area, and determining whether the adjacent fire-fighting facility position is normal or not through information interaction; and forming a fire-fighting cluster for adjacent fire-fighting facilities in normal states, and when the fire-fighting facilities reach a fire-fighting disposal state, carrying out linkage work of the fire-fighting facilities and uploading the fire-fighting facilities to a remote terminal for alarm operation.
The invention also discloses an intelligent building intensive management and control method, which comprises the following steps:
s1, building parameter information is obtained to conduct building modeling, and the display transparency of the building is adjusted through instructions after building modeling is completed;
s2, acquiring image data to perform risk position locating operation, acquiring facility data of each floor position of the building, and performing risk position information locating operation by combining fire-fighting facility data;
and S3, setting building risk treatment thresholds according to the positioned risk position information, and transmitting the risk treatment thresholds to the intelligent management terminal.
In summary, due to the adoption of the technical scheme, the beneficial effects of the invention are as follows:
the intelligent building intelligent automatic judgment process is completed according to the corresponding limiting threshold value, and the safety and the comfort of the intelligent building are reflected. Aiming at the centralized evaluation of fire-fighting facilities, temperature sensors and smoke sensors, the intelligent building intensive management advantage is reflected, and the safety facilities of the building are subjected to overall management.
Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
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The foregoing and/or additional aspects and advantages of the invention will become apparent and may be better understood from the following description of embodiments taken in conjunction with the accompanying drawings in which:
FIG. 1 is a general schematic of the present invention;
FIGS. 2A and 2B are schematic illustrations of embodiments of the present invention;
FIG. 3 is a schematic view of another embodiment of the present invention;
FIG. 4 is a schematic view of another embodiment of the present invention;
fig. 5 is a schematic diagram of another embodiment of the present invention.
Detailed Description
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative only and are not to be construed as limiting the invention.
As shown in fig. 1, the invention discloses an intelligent building intensive management and control system, which comprises the following modules:
the BIM model building module is used for obtaining building parameter information to perform building modeling, and the building after modeling is used for adjusting the display transparency of the building through instructions;
the risk position positioning module is used for acquiring image data to perform risk position positioning operation, and performing risk position information positioning operation by acquiring facility data of each floor position of the building and combining fire-fighting facility data;
and the risk treatment module is used for judging the building risk treatment threshold value according to the positioned risk position information and transmitting the risk treatment threshold value to the intelligent management terminal.
The BIM model building module further comprises:
the two-dimensional and three-dimensional visual platform is used for controlling the building data of the intelligent building through the whole body, and has the data checking and counting functions; modeling operation is carried out according to intelligent building data, a semi-transparent BIM model is formed aiming at each floor of a building, building data are respectively extracted for each floor, distribution of fire-fighting facilities is displayed according to the formed BIM model, and running state data are extracted;
selecting any floor data, collecting positions of fire fighting facilities, temperature sensors and smoke sensors, establishing facility position coordinates according to corresponding positions to form a 3D facility map, forming a position list by the facility map, performing data interaction feedback, and screening the positions of the fire fighting facilities which are successfully bound and the fire fighting facilities which are not successfully bound; forming a binding relation between the map position of the 3D facility and the fire-fighting facility,
when one bound position is selected, the bound device is fixed at the position of the 3D ground icon Huang Tuxian, the mouse is put on the upper suspension display device basic information, and the operations of detail viewing, editing information and unbinding can be performed on the device by clicking. The 3D facility map shows the building condition and the floor condition, and can rapidly switch floors through instruction guidance, and the facility map supports 2D and 3D random switching.
BIM models play an important role in building facility location positioning, helping facility managers to better understand and manage building systems and facilities.
As shown in fig. 3 to 5, the risk position location module includes:
determining the position coordinates of the fire-fighting equipment on the floor according to the acquired images, and forming the area S=pi r of the radius r by taking the fire-fighting equipment as an origin 2 Adding a temperature sensor and a smoke sensor at the intersection point of the radius r of another fire-fighting facility and the adjacent fire-fighting facility, collecting corresponding temperature information and smoke information, and setting the overlapping area of the two positions covered by the two fire-fighting facilities as a shared positioning position; the fire-fighting equipment is fire-fighting water mist spraying equipment;
the surrounding environment value of the fire-fighting facility is judged by collecting the temperature information and the smoke information of the intersection point positions to form a fire-fighting intensive grid of the intelligent building, and any intersection point (x, y) in the fire-fighting intensive grid forms a positioning sum of all risk position positioning additionn is a positive integer and the number of the intersection points.
Performing risk position location estimation according to acquired information of adjacent temperature sensors and smoke sensors around the fire-fighting facilities covered by extending the intersection points, and establishing an intelligent building risk position discovery function according to risk position information at the acquisition time t;
wherein eta is a building environment loss threshold value, mu is a personnel heat effect threshold value,for the risk position location sum N fire loads of fire-fighting facilities e, C is the temperature anomaly value of the whole time period, C is the constant normalized by the objective function, dR t Differentiation of smoke outliers at time t, dt being time differentiation, taking into account the environmental loss coefficient as an adjustment coefficient for the relevant risk location, requiring a numerical constraint on the surrounding environment, < >>Locating the heat capacity, P, of person P in the sum N for risk locations t For the person heat of the risk location area at time t,/->The average value of the heat quantity of the personnel in the risk position positioning area at the moment t is S, namely the fire protection coverage area of the fire protection facility, and the +.>The difference value of the personnel heat in unit area;
the risk position discovery function is to combine the information of fire-fighting facilities, temperature sensors and smoke sensors, and obtain comprehensive evaluation of distribution information of personnel and electrical equipment through image acquisition. The fire risk level for each floor risk location is calculated and high risk areas are identified. These high risk areas require targeted preventive measures such as strengthening the configuration of fire facilities, improving evacuation routes, strengthening inspection to ensure fire safety of the building, as a judgment condition for risk location.
In the sensor matching process, important factors of personnel density in building intensive management and control are needed to be considered, and comprehensive judgment is carried out on the fireproof coverage conditions of surrounding fire-fighting facilities.
The risk handling module includes:
in the risk position locating process, building environment loss coefficients are required to be adjusted, and calculation conditions for adjusting the building environment loss threshold are as follows:
wherein, the loss coefficient is calculated through, D is penalty factor, lambda is building environment influence weight, F t A fire protection facility response real-time value for the risk location area at time t,the response mean value of the fire-fighting equipment is represented by T, which is a time index, and T is a time upper limit;
the condition about the real-time value of the fire-fighting equipment response is F min ＜F t ＜F max ，F min To respond to the lower limit of the value, F max Is the upper limit of the response value.
In the fire-fighting position positioning process, the loss threshold value is used for carrying out weighting treatment on fire-fighting risk degrees of different positions through evaluation of risk positions so as to help determine which positions need to take control and fire-fighting measures preferentially.
The loss threshold value weights risk positions to different degrees according to different situations and requirements. For example, if a location is at a higher risk of fire, but the location is not a critical facility or personnel intensive area, the penalty factor for the location may be appropriately reduced to balance and optimize the priority of the prevention and extinguishing measures.
By calculating the loss threshold value, the importance and the urgency of different positions are reflected more accurately in the risk position evaluation process, so that targeted prevention, control and fire extinguishing measures are formulated better, and the safety of buildings and personnel is ensured.
The fire-fighting equipment response real-time value refers to a value that the fire-fighting equipment automatically responds according to a fire situation monitored in real time. And (3) finding fire in time: the fire-fighting equipment responds to the real-time value to monitor the occurrence probability of fire and give out an alarm and start fire-extinguishing measures in time, thereby effectively controlling the spread of fire. The response real-time value of the fire-fighting equipment plays a key role in fire prevention, and can effectively reduce fire loss and casualties.
The personnel heat effect threshold value calculation process comprises the following steps:
wherein B is self For the thermal coefficient of the risk location area, B p For the human heat release coefficient, T high For the highest indoor temperature of the risk location area, T low The lowest indoor temperature for the risk location area. Thermal effect data is acquired by an infrared sensor.
The coefficient of personal heat release (also known as the coefficient of personal heat release) is used to estimate the impact of the heat dissipated by a person on the predicted development of a fire in the event of a fire. The personal heat release coefficient is a parameter that describes the amount of heat a person gives off in a fire. Typically derived from experimental data, represent the amount of heat each person gives off per unit time.
Personnel heat effect thresholds play an important role in intelligent building fire management. In intelligent building fire control management, the safety of personnel and facilities in a building can be ensured by monitoring and predicting fire risks, and the personnel heat effect threshold is the maximum heat load which can be tolerated by human bodies. For example, when the density of personnel is monitored to be too high, the temperature and humidity in the building can be reduced by adjusting an air conditioning system, increasing ventilation and the like, thereby reducing the thermal effect of the personnel. Meanwhile, a movement plan of a firefighter in the fire-extinguishing rescue process can be formulated according to the personnel thermal effect threshold value, so that body damage caused by overlarge thermal effect is avoided.
The personal heat release coefficient and the personal heat effect threshold value are obtained through conventional calculation, and basic data of the personal heat release coefficient and the personal heat effect threshold value are collected through a heat-sensitive sensor and are arranged around corresponding fire-fighting facilities according to actual conditions or are placed at positions of a temperature sensor and a smoke sensor.
For building risk position location, fire-fighting facilities, temperature sensors and smoke sensors are just sufficient conditions for location, and factors such as structures and systems of buildings, personnel flowing conditions, risk load density and the like need to be considered.
Judging risks by calculating a loss threshold value and a thermal effect threshold value, substituting the risk values into a risk position discovery function to perform comprehensive evaluation, and searching whether a result meeting threshold value adjustment exists in the acquired temperature sensor and smoke sensor information; when the threshold value adjusting result is met in all the information, determining a fire-fighting facility risk position positioning area corresponding to the threshold value adjusting result, determining the adjacent fire-fighting facility position according to the risk position positioning area, and determining whether the adjacent fire-fighting facility position is normal or not through information interaction; and forming a fire-fighting cluster for adjacent fire-fighting facilities in normal states, and when the fire-fighting facilities reach a fire-fighting disposal state, carrying out linkage work of the fire-fighting facilities and uploading the fire-fighting facilities to a remote terminal for alarm operation.
By comprehensively analyzing the risk treatment threshold, the building risk area can be accurately identified, and effective prevention and treatment measures can be taken. Aiming at the centralized evaluation of fire-fighting facilities, temperature sensors and smoke sensors, the intelligent building intensive management advantage is reflected, and the safety facilities of the building are subjected to overall management.
As shown in fig. 2, the invention discloses an intelligent building intensive management and control method, which comprises the following steps:
the user login state is stored in a server by default, a password page is entered according to a password setting instruction, the password page is divided into mobile phone number setting and mailbox setting, and a verification code is sent to a mobile phone short message through the mobile phone number setting; and sending the verification code into the mailbox through mailbox setting, and setting the effective time of the verification code.
S1, building parameter information is obtained to conduct building modeling, and the display transparency of the building is adjusted through instructions after building modeling is completed;
s2, acquiring image data to perform risk position locating operation, acquiring facility data of each floor position of the building, and performing risk position information locating operation by combining fire-fighting facility data;
and S3, setting building risk treatment thresholds according to the positioned risk position information, and transmitting the risk treatment thresholds to the intelligent management terminal.
Because the intelligent building intensive management and control is a system engineering, the factors to be considered are very many, if too many interference factors are introduced in the management and control process of the invention, more interference can be generated on the calculation result, and the result of the intensive effective management can not be completed, so that the main fire-fighting measures and fire-fighting means in the intelligent building management process are needed to be considered, and for the intensive management, the fire-fighting is a part of building management, and the system also comprises the effective management and control of energy sources, and the management of waterway pipe networks is the factors to be considered for the intensive management.
TABLE 1 optimization conditions for intensive management of the invention
The S1 further includes:
s1-1, a two-dimensional and three-dimensional visualization platform is used for overall controlling intelligent building construction data and has a data viewing and counting function; modeling operation is carried out according to intelligent building data, a semi-transparent BIM model is formed aiming at each floor of a building, building data are respectively extracted for each floor, distribution of fire-fighting facilities is displayed according to the formed BIM model, and running state data are extracted;
s1-2, selecting any floor data, collecting positions of fire fighting facilities, temperature sensors and smoke sensors, establishing facility position coordinates according to corresponding positions, forming a 3D facility map, forming a position list by the facility map, performing data interaction feedback, screening fire fighting facilities which are successfully bound and fire fighting facility positions which are not successfully bound; and forming a binding relation between the map position of the 3D facility and the fire-fighting facility.
The step S2 comprises the following steps:
s2-1, determining the position coordinates of the fire-fighting equipment on the floor according to the acquired image, and forming the area of radius r by taking the fire-fighting equipment as an origin pointS＝πr 2 Acquiring temperature information and smoke information acquired by a temperature sensor and a smoke sensor at an intersection point position where the radius r of another fire-fighting facility and an adjacent fire-fighting facility form an intersection, wherein the overlapping area of the two positions of the two fire-fighting facilities is set as a shared positioning position; the fire-fighting equipment can be fire-fighting water mist spraying equipment;
s2-2, judging surrounding environment values of the fire-fighting facilities by collecting temperature information and smoke information of intersection points to form a fire-fighting intensive grid of the intelligent building, wherein any intersection point (x, y) in the fire-fighting intensive grid forms a positioning sum of all risk position positioning additionn is a positive integer and the number of the intersection points. The implementation of the junction position in fig. 2A and 2B is just an example, and the acquired information of the corresponding sensor set according to the fire-fighting standard can also be acquired, because the building high-rise needs to set the corresponding fire-fighting facilities and sensor devices according to the national standard, which needs to form the defined fire-fighting intensive grid according to the actual situation.
S2-3, performing risk position location estimation on acquired information of adjacent temperature sensors and smoke sensors around the fire-fighting facilities, and establishing an intelligent building risk position discovery function according to the risk position information at the acquisition time t;
wherein eta is a building environment loss threshold value, mu is a personnel heat effect threshold value,for the risk position location sum N fire loads of fire-fighting facilities e, C is the temperature anomaly value of the whole time period, C is the constant normalized by the objective function, dR t Differentiation of smoke outliers at time t, dt being time differentiation, taking into account the environmental loss coefficient as an adjustment coefficient for the relevant risk location, requiring a numerical constraint on the surrounding environment, < >>Locating the heat capacity, P, of person P in the sum N for risk locations t For the person heat of the risk location area at time t,/->The average value of the heat quantity of the personnel in the risk position positioning area at the moment t is S, namely the fire protection coverage area of the fire protection facility, and the +.>The difference value of the personnel heat in unit area;
the step S3 comprises the following steps:
s3-1, in the risk position positioning process, building environment loss coefficients are required to be adjusted, and the calculation conditions for adjusting the building environment loss threshold are as follows:
wherein, the loss coefficient is calculated through, D is penalty factor, lambda is building environment influence weight, F t A fire protection facility response real-time value for the risk location area at time t,the response mean value of the fire-fighting equipment is represented by T, which is a time index, and T is a time upper limit;
in the fire-fighting position positioning process, the loss threshold value is used for carrying out weighting treatment on fire-fighting risk degrees of different positions through evaluation of risk positions so as to help determine which positions need to take control and fire-fighting measures preferentially.
The loss threshold value weights risk positions to different degrees according to different situations and requirements. For example, if a location is at a higher risk of fire, but the location is not a critical facility or personnel intensive area, the penalty factor for the location may be appropriately reduced to balance and optimize the priority of the prevention and extinguishing measures.
By calculating the loss threshold value, the importance and the urgency of different positions are reflected more accurately in the risk position evaluation process, so that targeted prevention, control and fire extinguishing measures are formulated better, and the safety of buildings and personnel is ensured.
The fire-fighting equipment response real-time value refers to a value that the fire-fighting equipment automatically responds according to a fire situation monitored in real time. And (3) finding fire in time: the fire-fighting equipment responds to the real-time value to monitor the occurrence probability of fire and give out an alarm and start fire-extinguishing measures in time, thereby effectively controlling the spread of fire. The response real-time value of the fire-fighting equipment plays a key role in fire prevention, and can effectively reduce fire loss and casualties.
S3-2, the personnel heat effect threshold value calculation process is as follows:
wherein B is self For the thermal coefficient of the risk location area, B p For the human heat release coefficient, T high For the highest indoor temperature of the risk location area, T low The lowest indoor temperature for the risk location area.
Personnel heat effect thresholds play an important role in intelligent building fire management. In intelligent building fire control management, the safety of personnel and facilities in a building can be ensured by monitoring and predicting fire risks, and the personnel heat effect threshold is the maximum heat load which can be tolerated by human bodies. For example, when the density of personnel is monitored to be too high, the temperature and humidity in the building can be reduced by adjusting an air conditioning system, increasing ventilation and the like, thereby reducing the thermal effect of the personnel. Meanwhile, a movement plan of a firefighter in the fire-extinguishing rescue process can be formulated according to the personnel thermal effect threshold value, so that body damage caused by overlarge thermal effect is avoided.
While embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that: many changes, modifications, substitutions and variations may be made to the embodiments without departing from the spirit and principles of the invention, the scope of which is defined by the claims and their equivalents.
Claims (8)
1. An intelligent building intensive management and control system, comprising:
the BIM model building module is used for obtaining building parameter information to perform building modeling, and the building after modeling is used for adjusting the display transparency of the building through instructions;
the risk position positioning module is used for acquiring image data to perform risk position positioning operation, and performing risk position information positioning operation by acquiring facility data of each floor position of the building and combining fire-fighting facility data;
and the risk treatment module is used for judging the building risk treatment threshold value according to the positioned risk position information and transmitting the risk treatment threshold value to the intelligent management terminal.
2. The intelligent building intensive management and control system of claim 1, wherein the BIM model building module further comprises:
the two-dimensional and three-dimensional visual platform is used for controlling the building data of the intelligent building through the whole body, and has the data checking and counting functions; modeling operation is carried out according to intelligent building data, a semi-transparent BIM model is formed aiming at each floor of a building, building data are respectively extracted for each floor, distribution of fire-fighting facilities is displayed according to the formed BIM model, and running state data are extracted;
selecting any floor data, collecting positions of fire fighting facilities, temperature sensors and smoke sensors, establishing facility position coordinates according to corresponding positions, forming a 3D facility map, forming a position list by the facility map, performing data interaction feedback, screening the successfully bound fire fighting facilities and the unsubscribed fire fighting facilities; and forming a binding relation between the map position of the 3D facility and the fire-fighting facility.
3. The intelligent building intensive care system of claim 1, wherein the risk location module comprises:
determining the position coordinates of the fire-fighting equipment on the floor according to the acquired images, and forming the working area S=pi r of the radius r by taking the fire-fighting equipment as an origin 2 Acquiring temperature information and smoke information acquired by a temperature sensor and a smoke sensor at the intersection point of the radius r of another fire-fighting facility and the adjacent fire-fighting facility, judging the surrounding environment value of the fire-fighting facility, forming a fire-fighting intensive grid of the intelligent building, wherein any intersection point (x, y) in the fire-fighting intensive grid forms a positioning sum of all risk position positioning additionn is a positive integer and the number of the intersection points.
4. The intelligent building intensive care system of claim 1, wherein the risk location module comprises:
the risk position positioning estimation is carried out on the acquired information of the adjacent temperature sensors and the smoke sensors around the fire-fighting facility, and an intelligent building risk position discovery function is established according to the risk position information at the acquisition time t;
wherein eta is a building environment loss threshold value, mu is a personnel heat effect threshold value,for the risk position location sum N fire loads of fire-fighting facilities e, C is the temperature anomaly value of the whole time period, C is the constant normalized by the objective function, dR t Differentiation of the smoke anomaly at time t, dt being the time differentiation, < >>Locating the heat capacity, P, of person P in the sum N for risk locations t For the person heat of the risk location area at time t,/->The average value of the heat quantity of the personnel in the risk position positioning area at the moment t is S, namely the fire protection coverage area of the fire protection facility, and the +.>Is the difference of the personnel heat quantity in unit area.
5. The intelligent building intensive care system of claim 1, wherein the risk handling module comprises:
in the risk position locating process, building environment loss coefficients are required to be adjusted, and calculation conditions for adjusting the building environment loss threshold are as follows:
wherein, the loss coefficient is calculated through, D is penalty factor, lambda is building environment influence weight, F t A fire protection facility response real-time value for the risk location area at time t,and T is a time index, and T is a time upper limit.
6. The intelligent building intensive management and control system according to claim 3, wherein the personnel heat effect threshold calculation process is as follows:
wherein B is self For the thermal coefficient of the risk location area, B p For the human heat release coefficient, T high For the highest indoor temperature of the risk location area, T low The lowest indoor temperature for the risk location area.
7. The intelligent building intensive management and control system according to claim 6, wherein risk judgment is performed by calculating a loss threshold and a thermal effect threshold, the risk judgment is substituted into a risk position issuing function to perform comprehensive evaluation, and whether a result meeting threshold adjustment exists is searched from the acquired temperature sensor and smoke sensor information; when the threshold value adjusting result is met in all the information, determining a fire-fighting facility risk position positioning area corresponding to the threshold value adjusting result, determining the adjacent fire-fighting facility position according to the risk position positioning area, and determining whether the adjacent fire-fighting facility position is normal or not through information interaction; and forming a fire-fighting cluster for adjacent fire-fighting facilities in normal states, and when the fire-fighting facilities reach a fire-fighting disposal state, carrying out linkage work of the fire-fighting facilities and uploading the fire-fighting facilities to a remote terminal for alarm operation.
8. An intelligent building intensive management and control method is characterized by comprising the following steps:
s1, building parameter information is obtained to conduct building modeling, and the display transparency of the building is adjusted through instructions after building modeling is completed;
s2, acquiring image data to perform risk position locating operation, acquiring facility data of each floor position of the building, and performing risk position information locating operation by combining fire-fighting facility data;
and S3, setting building risk treatment thresholds according to the positioned risk position information, and transmitting the risk treatment thresholds to the intelligent management terminal.
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