CN113390171B - Underground station ventilation air conditioner control method through visual monitoring - Google Patents

Underground station ventilation air conditioner control method through visual monitoring Download PDF

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CN113390171B
CN113390171B CN202110625855.3A CN202110625855A CN113390171B CN 113390171 B CN113390171 B CN 113390171B CN 202110625855 A CN202110625855 A CN 202110625855A CN 113390171 B CN113390171 B CN 113390171B
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CN113390171A (en
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唐超
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Beijing Urban Construction Design and Development Group Co Ltd
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/70—Control systems characterised by their outputs; Constructional details thereof
    • F24F11/72—Control systems characterised by their outputs; Constructional details thereof for controlling the supply of treated air, e.g. its pressure
    • F24F11/74—Control systems characterised by their outputs; Constructional details thereof for controlling the supply of treated air, e.g. its pressure for controlling air flow rate or air velocity
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/50—Control or safety arrangements characterised by user interfaces or communication
    • F24F11/61—Control or safety arrangements characterised by user interfaces or communication using timers
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F2110/00—Control inputs relating to air properties
    • F24F2110/50—Air quality properties
    • F24F2110/65—Concentration of specific substances or contaminants
    • F24F2110/70—Carbon dioxide
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F2120/00—Control inputs relating to users or occupants
    • F24F2120/10—Occupancy

Abstract

A ventilation air-conditioning control method for an underground station through visual monitoring comprises a video computing module, a thermal imaging instrument computing module and a piston wind module, wherein the video computing module is divided into two parts, namely a station hall, an entrance and an exit, a transfer channel camera, and a platform waiting area camera; a fresh air quantity real-time analysis unit is also arranged, and the fresh air quantity value is determined by the number of staff at the station and the air exchange quantity inside and outside the station; the system is also provided with a frozen water flow real-time analysis unit, a piston wind speed, wind volume and wind temperature real-time analysis unit, a personnel body temperature real-time analysis unit, a fresh air volume real-time analysis unit and a frozen water flow real-time analysis unit; the system is also provided with a historical data learning unit, and the historical data learning unit is used for analyzing and feeding back data such as a real-time personnel number analyzing unit and the like; therefore, the invention can overcome the defects of the prior art, can accurately and quickly reflect the real thermal comfort degree of the dynamic personnel in the piston wind, and provides better control and intellectualization.

Description

Underground station ventilation air conditioner control method through visual monitoring
Technical Field
The invention relates to the technical field of ventilation control of underground stations, in particular to a method for controlling a ventilation air conditioner of an underground station through visual monitoring comprising the steps of collecting the number of people by a camera and collecting the surface temperature of the skin of a human body by an infrared thermal imaging instrument.
Background
In the existing ventilation air-conditioning control of the rail transit station, the room temperature control of the ventilation air-conditioning system generally transmits the air state and the cold water state in the air-conditioning system to a processor by an air temperature and humidity sensor and a water temperature sensor, so as to control the air-conditioning system. The carbon dioxide sensor transmits the carbon dioxide concentration to the processor as one of the parameters for adjusting the fresh air quantity and the return air quantity. The state of the air comprises temperature, humidity and carbon dioxide concentration, and the monitoring and the regulation of the operation effect of the air conditioning system are completed through the parameters of the temperature, the humidity and the carbon dioxide concentration of the indoor air and the outdoor air. And the determination of the design parameters of the indoor air temperature and humidity needs to consider the comfort conditions under the comprehensive action of the indoor parameters. In the aspect of thermal comfort of a ventilation air conditioner human body, areas containing waiting vehicles, such as large railway stations, station buildings and the like in traffic buildings, belong to areas where people stay for a long time. Subway passengers enter the station to leave the station for about 3 to 5 minutes, which is a short-term stay area. The GB50736-2012 standard mentions that the design parameters of the air conditioner in the region where people stay for a long time are 24-28 ℃ under the cooling working condition, the relative humidity is 40% -70%, and the wind speed is less than 0.3 m/s. For short term sojourn areas, it is mentioned in GB50157-2013 that when the station employs a ventilation system, the indoor calculated temperature is not easily 5 degrees above the outdoor temperature and should not exceed 30 degrees. When an air conditioning system is adopted, the calculated temperature of the station hall is 2-3 ℃ lower than the calculated temperature of the air conditioning outdoor and should not exceed 30 ℃, the platform is 1-2 ℃ lower than the station hall, and the relative humidity is 40-70%. The instantaneous wind speed is not easily larger than 5 m/s. The difference between the energy metabolism rate of the human body and the individual work is caused by the difference between the traveling mode, clothing, sex and age of passengers entering the traffic building. Meanwhile, in recent years, the instantaneous wind speed difference is large due to differences in building forms and corresponding equipment such as platform doors. These all lead to the difference of human comfort level, consequently rely on the air condition index to regulate and control central air conditioning alone, hardly embody human comfort level accurately.
Two common control methods for rail transit are currently used. One is to adjust the fan frequency, the water pump frequency, the opening of the two-way valve, etc. according to the values of the air and the water temperature which are monitored in real time. One is a control system with load prediction, including feedforward and feedback. According to the above contents, when the human body is in different metabolic rates and individual working states, the comfortable feeling of the temperature and humidity interval is different. According to the related research surface, in a certain area, the temperature of the body surface of a human body can directly reflect the comfort level of the human body. Relevant studies show that human skin temperature and heat sensation response and thermal comfort are positively correlated over a range of temperatures.
The current control method comprises a wind-water linkage system, namely a control system with load prediction and feed-forward and feedback, and the indoor load is predicted according to the number of personnel, meteorological conditions and the like.
However, the prior art has the following disadvantages:
(1) the real thermal comfort of dynamic personnel can not be accurately reflected by collecting indexes such as indoor temperature and humidity.
(2) At present, most of fresh air is constant frequency and cannot be adjusted according to actual conditions
(3) The existing air conditioning system control method adjusts in real time according to field parameters, has hysteresis and is not intelligent.
Therefore, in view of the above-mentioned drawbacks, the present inventor has studied and designed a method for controlling ventilation and air conditioning of an underground station through visual monitoring by taking into account experience and results of related industries for many years through careful research and design to overcome the above-mentioned drawbacks.
Disclosure of Invention
The invention aims to provide a control method of an underground station ventilation air conditioner through visual monitoring, which can overcome the defects of the prior art, can accurately and quickly reflect the real thermal comfort degree of dynamic personnel under piston wind, and provides better control and intellectualization.
In order to achieve the aim, the invention discloses a control method of an underground station ventilation air conditioner through visual monitoring, which comprises a video computing module, a thermal imaging instrument computing module and a piston wind module, and is characterized in that:
the video calculation module is divided into two parts, namely a station hall, an entrance and an exit, and a transfer channel camera, which are arranged in the station hall, the entrance and the exit and the transfer channel to calculate the people flow difference value, judge whether the station is in the people inrush or inrush period and calculate the number of people in the area; secondly, the camera of the waiting area of the platform calculates the total number of people in the area and obtains the total number of people through the sum of the number of people in the two areas;
the thermal imaging instrument calculation module is divided into two parts, namely a station hall thermal imaging instrument and a station thermal imaging instrument to calculate the average body temperature of the human body in the area, and a gateway thermal imaging instrument, a transfer passage thermal imaging instrument and a vehicle body internal thermal imaging instrument to calculate the average body temperature of the human body in the area and the average value of body temperature change values caused by the change of the thermal environment of a calculator in a short time when the calculator enters the other area from one area;
and the piston wind module is used for testing the wind speed and the wind temperature of the piston wind and calculating the air quantity exchanged between the interior of the station and the outside of the station.
Wherein: also provided with a fresh air volume real-time analysis unitThe value is determined by the number of the station staff and the exchange quantity of the air inside and outside the station, namely L1 (fresh air) is S M + L2 (exchange quantity of the air inside and outside), wherein L1 is the fresh air quantity required by the station, S is the number of the staff, M is the fresh air quantity required by a single person, L2 is the exchange quantity of the air inside and outside the room, and delta LReal-time analysisΔ S + Δ L2 (internal and external air exchange amount), where Δ LReal-time analysisThe fresh air volume is the fresh air volume which needs to be increased or decreased relative to a certain moment at a station, the delta S is the number of people which need to be increased or decreased relative to the certain moment at the station, the delta L2 is the amount of increase or decrease of indoor and outdoor air exchange relative to the certain moment at the station, the M is the fresh air volume which needs to be needed by a single person, and the L2 is the indoor and outdoor air exchange volume.
Wherein: a freezing water flow real-time analysis unit is also arranged, wherein for a constant temperature difference system, the freezing water flow is determined by station cold load, new air cold load and reheating quantity, namely
Figure BDA0003101072380000041
Wherein VReal-time analysisIs water flow, Q is system cooling capacity, CPρ is the density of water at a temperature, Δ T is the temperature difference of water, and Q ═ Q1+Q2+Q3Wherein Q is the system cold quantity, Q1For indoor cooling load, Q2Is a new air cooling load, Q3Is reheat;
thus, it is possible to provide
Figure BDA0003101072380000042
Wherein Δ VReal-time analysisFor the water flow, Δ Q, to be increased or decreased at a station relative to a certain time1For increasing or decreasing indoor cooling load, Δ Q, of the station at a certain time2The station increases or decreases fresh air cooling load at a certain moment, CPThe specific heat capacity at constant pressure is defined as rho, which corresponds to the density of water at temperature, and Δ T is the temperature difference of water.
Wherein: the device is also provided with a historical data learning unit, and a real-time analysis unit for the number of the personnel is arranged through the historical data learning unit; a piston wind speed, wind volume and wind temperature real-time analysis unit; a real-time body temperature analysis unit of a person; a fresh air volume real-time analysis unit; a real-time analysis unit for the flow rate of the chilled water; and constructing a machine learning algorithm by using the fan air volume and the chilled water flow controller to obtain a training value.
Wherein: for the air conditioning mode, the air volume of the new air blower is determined by the fresh air volume, the real-time value and the learning value are jointly determined, the air volume of the air blower is also jointly determined by the real-time value and the learning value, and for the primary air return system, the air volume of the air blower is
Figure BDA0003101072380000051
Wherein G isReal-time analysisFor the amount of air supply, Q1For residual heat in the room iNIs the enthalpy value of indoor air, i0Is the enthalpy value of the air supply point, and
Figure BDA0003101072380000052
wherein Δ GReal-time analysisFor the amount of air supply required to be increased or decreased relative to a certain moment, Δ Q1For increasing or decreasing the residual heat in the room relative to the need at a certain moment, iNIs the enthalpy value of indoor air, i0Is the enthalpy value of the air supply point.
Wherein: for the ventilation mode, the air volume of the air feeder is jointly decided by a real-time value and a learning value,
Figure BDA0003101072380000053
wherein G isReal-time analysisFor the amount of air supply, QDisplay deviceIs residual heat in the room, tPIs the outdoor air temperature, tSIs the temperature of the air in the room,
Figure BDA0003101072380000054
wherein Δ GReal-time analysisFor the amount of air supply required to be increased or decreased relative to a certain moment, Δ QDisplay deviceFor increasing or decreasing the residual heat in the room relative to a certain moment, tPIs the outdoor air temperature, tSIs the indoor air temperature.
Wherein: the method comprises the following steps that firstly, a station hall, an entrance and an exit in a video calculation module and a transfer channel camera calculate the number of people in the area, the difference of the flow of people is calculated to judge whether a station is in a people inrush or inrush time period, a camera in a station waiting area calculates the total number of people in the area, the sum of the number of people in the two areas is calculated, then a fresh air quantity real-time analysis unit receives data of the video calculation module and a piston air calculation module, analysis and calculation are carried out, when the personnel belong to the inrush time period, the fresh air quantity is increased, when the personnel are in the inrush time period, the fresh air quantity is considered to be reduced or kept in combination with the total number of people in the station, the piston air module data participate in calculation as influence factors, and further a fresh air quantity real-time analysis unit makes analysis and calculation:
ΔLreal-time analysisΔ S + Δ L2 (internal and external air exchange amount) ═ f (a, Δ S)
Wherein Δ LReal-time analysisThe air volume is the new air volume which needs to be increased or decreased relative to a certain moment in a station, delta S is the number of people which need to be increased or decreased relative to the certain moment in the station, M is the new air volume which needs to be increased or decreased relative to indoor and outdoor air exchange of the station at a certain moment, delta L2 is the piston air influence factor a;
the air volume of the new fan is a base number plus variable:
L＝f(Llearned value，ΔLReal time)
Analyzing and calculating the week rule by the previous time nodes of each day and the previous week data to obtain a base number LLearned valueAnd deriving the variable value DeltaL from the real-time dataReal-time analysisAnd from the analysis results of the radix plus the variables, the present and future control logic f (L) is obtainedLearned value，ΔLReal time)；
Meanwhile, the calculation module of the thermal imaging instrument calculates the average body temperature of personnel in the station through the station hall and the station thermal imaging instrument, and the meter is TAverage of the population；
Through the data of the entrance, the transfer passage and the thermal imaging instrument in the vehicle body, the average value of the body temperature change values caused by the change of the thermal environment of a person entering from one area to the other area in a short time is calculated as delta TAverage of the populationWhen T isAverage of the population、ΔTAverage of the populationWhen increasing or decreasing, the freezing water flow is correspondingly increased or decreased, and further the real-time freezing water flow analysis unit simultaneously considers the personnel burdenLoad and fresh air load, namely:
Figure BDA0003101072380000061
wherein, is Δ VReal-time analysisFor the water flow, Δ Q, to be increased or decreased at a station relative to a certain time1For increasing or decreasing indoor cooling load, Δ Q, of the station at a certain time2The station increases or decreases fresh air cooling load at a certain moment, CPFor specific heat capacity at constant pressure, ρ is the density of water at the temperature corresponding to ρ, Δ T is the temperature difference of water, TAverage of the populationIs the average temperature of human body, delta T, in the stationAverage of the populationThe average value of body temperature change values caused by the change of the thermal environment of a person in a short time when the person enters another area from one area, wherein delta L is the new air volume required to be increased or reduced relative to a certain moment at a station, and delta L is the change value of the air volume of a fan instead of delta LReal time，
The final blower has an air volume of
Figure BDA0003101072380000071
Wherein the content of the first and second substances,
Figure BDA0003101072380000072
the chilled water flow value is a base plus variable:
Figure BDA0003101072380000073
wherein: the method comprises the following steps that firstly, a station hall, an entrance and an exit in a video calculation module and a transfer channel camera calculate the number of people in the area, the difference of the flow of people is calculated to judge whether a station is in a station inrush or inrush time period, a camera in a station waiting area calculates the total number of people in the area, the sum of the number of people in the two areas is calculated, then a fresh air quantity real-time analysis unit receives data of the video calculation module and a piston air calculation module, analysis and calculation are carried out, when a person belongs to the inrush time period, the fresh air quantity is increased, when the person is in the inrush time period, the fresh air quantity is considered to be reduced or kept, the piston air module data is taken as an influence factor to participate in calculation, and further, a fresh air quantity real-time analysis unit carries out analysis and calculation:
ΔLreal-time analysisΔ S + Δ L2 (internal and external air exchange amount) ═ f (a, Δ S)
Wherein, DeltaL is the fresh air quantity which needs to be increased or decreased relative to a certain moment in a station, DeltaS is the number of people which needs to be increased or decreased relative to a certain moment in the station, M is the fresh air quantity which needs to be increased or decreased relative to a certain moment in the station, DeltaL 2 is the indoor and outdoor air exchange increase or decrease relative to a certain moment in the station, a is a piston air influence factor,
the fresh air volume is a base number plus variable:
L＝f(Llearned value，ΔL)
Analyzing and calculating the week rule by the previous time nodes of each day and the previous week data to obtain a base number LLearned valueAnd deriving the variable value DeltaL from the real-time dataReal-time analysisAnd from the analysis results of the radix plus the variables, the present and future control logic f (L) is obtainedLearned value，ΔL)，
Meanwhile, the calculation module of the thermal imaging instrument calculates the average body temperature of personnel in the station through the station hall and the station thermal imaging instrument and records the average body temperature as TAverage of the population，
Through the data of the entrance, the transfer passage and the thermal imaging instrument in the vehicle body, the average value of the body temperature change values caused by the change of the thermal environment in a short time when a computer enters from one area to the other area is recorded as delta TAverage of the populationWhen T isAverage of the population、ΔTAverage of the populationIncreasing or decreasing the blower or exhaust air volume, Q, when increasing or decreasing, respectivelyDisplay device＝S×QShow everyone+QE+QL，ΔQDisplay device＝ΔS×QShow everyone+QL＝f(TAverage of the population、ΔTAverage of the populationΔ S, Δ L), wherein QDisplay deviceShowing heat quantity for station, S is number of station people, QShow everyoneIs the sensible heat of a single person, QEFor the apparatus to develop heat, QLFor giving out heat of fresh air, Delta QDisplay deviceIs a vehicleThe station is the sensible heat that needs increase or reduce at a certain moment relatively, and Δ S is the quantity that the station increases or reduces personnel at a certain moment relatively, and last forced draught blower amount of wind is:
Figure BDA0003101072380000081
Figure BDA0003101072380000082
as can be seen from the above, the method for controlling ventilation and air conditioning of an underground station through visual monitoring according to the present invention has the following effects:
(1) the real thermal comfort of dynamic personnel can not be accurately reflected by collecting indexes such as indoor temperature and humidity. The invention can accurately and quickly reflect the real thermal comfort degree of dynamic personnel under the piston wind by collecting the skin temperature of a human body as an index.
(2) At present, most of the fresh air meets the requirement of carbon dioxide concentration, so that the fresh air is constant frequency, or the fresh air is added according to the upper limit of the carbon dioxide concentration, and cannot be adjusted according to actual conditions. The fresh air quantity is judged according to the number of the collected personnel of the camera, the difference value and the like, and the frequency conversion control is carried out on the fresh air fan.
(3) The existing air conditioning system control method adjusts in real time according to field parameters, has hysteresis and is not intelligent. The final fan and cold water control of the invention are both composed of a base number plus a variable, and the base number part is a machine learning data result.
(4) Compared with the traditional temperature and humidity and carbon dioxide sensor, the stability of the air volume calculated through shooting and the service life of the sensor are superior to those of the carbon dioxide sensor, and the maintenance frequency and period are reduced. The details of the present invention can be obtained from the following description and the attached drawings.
Drawings
FIG. 1 shows a schematic diagram of a video computing module of the present invention.
FIG. 2 shows a schematic diagram of the thermal imaging instrument computing module of the present invention.
FIG. 3 shows a schematic diagram of the piston wind calculation module of the present invention.
Fig. 4 shows a schematic diagram of the underground station ventilation and air conditioning control method through visual monitoring according to the present invention.
Fig. 5 shows a schematic view of another embodiment of the present invention.
Detailed Description
Referring to fig. 1 to 5, a method for controlling ventilation and air conditioning of an underground station through visual monitoring according to the present invention is shown.
The underground station ventilation air-conditioning control method through visual monitoring comprises a video computing module, a thermal imaging instrument computing module and a piston wind module. Referring to fig. 1, because the number of people in the station waiting area is relatively stable, the ground personnel in the station hall, the entrance and exit, the transfer passage and the like are in a fast flowing state, the video calculation module is divided into two parts, namely, a camera in the station waiting area is arranged in the station waiting area to calculate the total number of people in the area, the more the number of people is, the higher the air volume is, a camera in the station hall, the entrance and exit and the transfer passage is arranged in the station hall, the entrance and exit and the transfer passage to calculate the people flow difference value to judge that the station is in the people inrush or inrush period, the new air volume is increased in the inrush period, the new air volume is maintained or reduced in the inrush period, the air volume is reduced while considering whether the number of people in the station hall is reduced, so as to calculate the total number of people in the area, and finally, the total number of people is calculated by the camera in the station waiting area, the station hall and the camera in the transfer passage, The sum of the number of the entrances and exits and the number of the transfer channels and the number of people calculated by the cameras in the waiting area of the platform are gathered, and the total number of people in the station is calculated.
Referring to fig. 2, the thermal imaging instrument calculation module is in a dynamic state due to passengers in a station, and there are differences in thermal environments of the outside, the entrance, the transfer passage, the station hall, the platform, and the inside of the vehicle. The thermal imaging instrument calculation module is also divided into two parts, namely a station hall thermal imaging instrument and a station thermal imaging instrument to calculate the average body temperature of the human body in the area, and a gateway thermal imaging instrument, a transfer passage thermal imaging instrument and a vehicle body internal thermal imaging instrument to calculate the average body temperature of the human body in the area and calculate the average value of body temperature change values caused by the change of the thermal environment of a person entering the other area from one area in a short time.
Referring to fig. 3, the piston air module directly affects the fresh air volume and the thermal comfort of the human body due to the disturbance of the air exchange between the subway and the outdoor environment caused by the piston air and the thermal environment of the subway station. Thus, a piston wind module is added. The piston wind module collects and calculates piston wind speed and wind temperature, and calculates data such as air volume exchanged between the interior of the station and the outside of the station.
The system is also provided with a fresh air volume real-time analysis unit, wherein the fresh air volume value is determined by the number of the station personnel and the exchange quantity of the inside and outside air of the station, namely L1 (fresh air) is S M + L2 (exchange quantity of the inside and outside air), wherein L1 is the fresh air volume required by the station, S is the personnel number, M is the fresh air volume required by a single person, L2 is the exchange quantity of the inside and outside air, and delta LReal-time analysisΔ S + Δ L2 (internal and external air exchange amount), where Δ LReal-time analysisDelta is the fresh air volume which needs to be increased or decreased relative to a certain moment in the station, delta S is the number of people which need to be increased or decreased relative to a certain moment in the station, M is the fresh air volume which needs to be increased or decreased by a single person, and delta L2 is the indoor and outdoor air exchange increase or decrease amount relative to a certain moment in the station.
A freezing water flow real-time analysis unit is also arranged, wherein for a constant temperature difference system, the freezing water flow is determined by station cold load, new air cold load and reheating quantity, namely
Figure BDA0003101072380000111
Wherein V is water flow, Q is system cold quantity, CPThe specific heat capacity at constant pressure is defined as rho, which corresponds to the density of water at temperature, and Δ T is the temperature difference of water. And Q ═ Q1+Q2+Q3Wherein Q is the cooling capacity of the refrigerating system, Q1For indoor cooling load, Q2Is a new air cooling load, Q3Is reheat.
Thus, it is possible to provide
Figure BDA0003101072380000112
Wherein, DeltaV is the water flow which needs to be increased or decreased at a certain moment relative to a station, DeltaQ1For increasing or decreasing indoor cooling load, Δ Q, of the station at a certain time2Relative to a certain stationIncreasing or decreasing fresh air cooling load at a moment, CPThe specific heat capacity at constant pressure is defined as rho, which corresponds to the density of water at temperature, and Δ T is the temperature difference of water.
A real-time human body temperature analysis unit is also arranged; the device is also provided with a historical data learning unit, and a real-time analysis unit for the number of the personnel is arranged through the historical data learning unit; a piston wind speed, wind volume and wind temperature real-time analysis unit; a real-time body temperature analysis unit of a person; a fresh air volume real-time analysis unit; a real-time analysis unit for the flow rate of the chilled water; and constructing a machine learning algorithm by using the data of the fan air volume and the chilled water flow controller. Obtaining the average body temperature TAverage of the populationAverage value of body temperature change, Δ TAverage of the population、VLearned value、QLearned value、LLearned value、GLearned value、ΔLLearned value、ΔQ1 learning value、ΔQ2 learning value、ΔVLearned value、ΔGLearned value、SLearned value、ΔSLearned valueAnd (4) equivalence.
Wherein:
Taverage of the population: average body temperature of personnel in station
ΔTAverage of the population: average value of body temperature change values caused by change of thermal environment of person in short time from one area to another area
VLearned value: chilled water flow value obtained by machine learning
QLearned value: refrigerating system cold quantity value obtained through machine learning
LLearned value: new fan air volume value obtained through machine learning
GLearned value: fan air volume value obtained through machine learning
ΔLLearned value: fresh air fan air volume value increased or decreased relatively to a certain moment obtained through machine learning
ΔQ1 learning value: increased or decreased indoor cooling load at a certain time through machine learning
ΔQ2 learning value: obtained by machine learningThe fresh air cooling load increased or decreased relatively to a certain moment
ΔVLearned value: chilled water flow value increased or decreased at a certain time through machine learning
ΔGLearned value: the fan air volume value which is obtained through machine learning and is increased or reduced relatively to a certain moment
SLearned value: number of persons obtained by machine learning
ΔSLearned value: the number of people gained or lost relatively to a certain moment through machine learning.
The fan air quantity and chilled water flow controller is also arranged, and the air quantity control of the fan comprises a fresh air fan, an air feeder, a return air fan and the like.
For the air-conditioning mode, the fresh air machine is independently provided with an air-conditioning system, some fresh air machines are arranged in the subway station at present, and the fresh air machines in the combined air conditioner operate together.
The air volume of the new air fan is determined by the fresh air volume and is determined by a real-time value and a learning value together. The air volume of the blower is jointly decided by the real-time value and the learning value. For a primary air return system, the air quantity of the blower is
Figure BDA0003101072380000131
Wherein G is the amount of air supply, Q1For residual heat in the room iNIs the enthalpy value of indoor air, i0Is the enthalpy value of the air supply point, and
Figure BDA0003101072380000132
wherein Δ GReal-time analysisΔ is the amount of air supply that needs to be increased or decreased relative to a certain moment, Δ Q1For increasing or decreasing the residual heat in the room relative to the need at a certain moment, iNIs the enthalpy value of indoor air, i0Is the enthalpy value of the air supply point.
For the ventilation mode, the air volume of the blower is jointly decided by the real-time value and the learning value.
Figure BDA0003101072380000133
Wherein G is the amount of air supply, QDisplay deviceIs residual heat in the room, tPIs the outdoor air temperature, tSIs the indoor air temperature.
Figure BDA0003101072380000134
Wherein Δ GReal-time analysisΔ is the amount of air supply that needs to be increased or decreased relative to a certain moment, Δ QDisplay deviceFor increasing or decreasing the residual heat in the room relative to a certain moment, tPIs the outdoor air temperature, tSIs the indoor air temperature.
The air volume value of the fan is as follows: the base plus the variable.
Radix part: the corresponding time period learning value is machine-learned by the previous weeks.
Variable part: and determining the weight of the variable according to the real-time human flow, the difference value of the real-time human flow and the previous weeks and the like.
The wind quantity of the fan is analyzed and calculated by the previous time node every day through the data of the previous weeks, and the current and future control logics are obtained by the analysis result of the cardinal number plus the variable.
Flow value of chilled water:
radix plus variable
Radix part: learning the corresponding time period learning value by the machine in the previous weeks
Variable part: and determining the weight of the variable according to the real-time average body temperature, the average value of the body temperature change value, the difference value of the real-time average body temperature and the body temperature change value with the previous weeks and the like.
The flow value of the chilled water is analyzed and calculated by the previous time node of each day through the data of the previous weeks, and the current and future control logics are obtained by the analysis result of the base number plus the variable.
Firstly, a video computing module, a piston air module and a thermal imaging instrument module respectively extract respective parameters from the environment and respectively transmit the parameters to corresponding real-time analysis units (a personnel quantity real-time analysis unit, a fresh air quantity real-time analysis unit, a piston air quantity, air temperature real-time analysis unit, a human body temperature real-time analysis unit and a chilled water flow real-time analysis unit), and the real-time analysis units calculate real-time values and transmit the real-time values to a history learning unit and a fan air quantity and chilled water flow controller. And furthermore, the fan air quantity and chilled water flow controller receives data of the historical learning unit and the real-time analysis and analysis unit, makes a decision according to the calculation result of the real-time analysis unit and the data of the historical data learning unit, and controls the fan air quantity and the chilled water flow. As shown in fig. 4, in an embodiment of the present invention, a flow chart of a control method of a station air conditioning mode of a chilled water temperature difference setting system is provided. Referring to fig. 4, the control method of the present invention specifically includes:
firstly, the number of people in the area is calculated by cameras such as station halls, entrances and exits, transfer channels and the like in a video calculation module, a people flow difference value is calculated, the station is judged to be in a people inrush or inrush time period, and the total number of people in the area is calculated by a camera in a station waiting area. And calculates the sum of the number of people in both areas. And then the fresh air volume real-time analysis unit receives the data of the video calculation module and the piston air calculation module for analysis and calculation. When the personnel belong to the inrush time interval, the fresh air volume is increased, and when the personnel belong to the inrush time interval, the fresh air volume is reduced or kept in combination with the total number of the stations. And the piston wind module data is used as an influence factor to participate in calculation. And further, the fresh air volume real-time analysis unit performs analysis and calculation, namely:
ΔLreal-time analysisΔ S + Δ L2 (internal and external air exchange amount) ═ f (a, Δ S)
Wherein Δ LReal-time analysisThe air volume is the new air volume which needs to be increased or decreased relative to a certain moment at a station, the delta S is the number of people which need to be increased or decreased relative to the certain moment at the station, the M is the new air volume which needs to be increased or decreased relative to a single person at the station, the delta L2 is the amount of increase or decrease of indoor and outdoor air exchange relative to the certain moment at the station, and the a is a piston wind influence factor.
The air volume of the new fan is a base number plus variable:
L＝f(Llearned value，ΔLReal time)
Analyzing and calculating the previous data of several weeks from the previous time nodes of each day to obtain a base number LLearned valueAnd deriving the variable value DeltaL from the real-time dataReal-time analysisAnd from the analysis results of the radix plus the variables, the present and future control logic f (L) is obtainedLearned value，ΔLReal time)。
Meanwhile, the calculation module of the thermal imaging instrument calculates the average body temperature of personnel in the station through the station hall and the station thermal imaging instrument, and the meter is TAverage of the population。
Through the data of the entrance, the transfer passage and the thermal imaging instrument in the vehicle body, the average value of the body temperature change values caused by the change of the thermal environment of a person entering from one area to the other area in a short time is calculated as delta TAverage of the population. When T isAverage of the population、ΔTAverage of the populationIncreasing or decreasing the chilled water flow rate is considered accordingly. And further, a real-time analysis unit for the flow of the chilled water considers the personnel load and the fresh air load at the same time. Namely:
Figure BDA0003101072380000151
wherein, is Δ VReal-time analysisFor the water flow, Δ Q, to be increased or decreased at a station relative to a certain time1For increasing or decreasing indoor cooling load, Δ Q, of the station at a certain time2The station increases or decreases fresh air cooling load at a certain moment, CPRho is the density of water at a temperature corresponding to the specific heat capacity at constant pressure, and DeltaT is the temperature difference of water, TAverage of the populationIs the average temperature of human body, delta T, in the stationAverage of the populationThe delta L is the average value of body temperature change values caused by the change of the thermal environment of a person in a short time when the person enters another area from one area, and is the new air volume required to be increased or reduced relative to a certain moment at a station.
Meanwhile, the piston wind calculation module calculates the piston wind speed, the wind quantity and the wind temperature, and provides a data basis for the calculation of other modules.
In the whole calculation process, the personnel number real-time analysis unit, the piston wind speed, the wind volume, the wind temperature real-time analysis unit, the personnel body temperature real-time analysis unit, the fresh wind volume real-time analysis unit, the chilled water flow real-time analysis unit, the fan wind volume and chilled water flow controller module and the like continuously transmit data to the historical data learning unit. Derived by machine learningMean body temperature TAverage of the populationAverage value of body temperature change value Δ TAverage of the population、VLearned value、QLearned value、LLearned value、GLearned value、ΔLLearned value、ΔQ1 learning value、ΔQ2 learning value、ΔVLearned value、ΔGLearned value、SLearned value、ΔSLearned valueAnd (4) equivalence. And finally, the fan air volume and chilled water flow controller makes a decision according to the calculation result of the real-time analysis unit and the historical data learning unit data to control the fan air volume and the chilled water flow.
The air volume value of the fan is as follows: radix plus variable
Air volume of an air blower:
Figure BDA0003101072380000161
Figure BDA0003101072380000162
beta is the external influence factor of the air supply
For example, the base G is obtained by taking the week as a time calculation unit and analyzing and calculating the previous week data by the previous time node of each dayLearned valueAnd deriving the variable value Δ G from the real-time dataReal timeAnd from the results of the analysis of the radix plus the variables, the present and future control logic f (G) is derivedLearned value，ΔGReal time)。
Flow value of chilled water: radix plus variable
Figure BDA0003101072380000171
For example, the base V is obtained by taking the week as a time calculation unit and analyzing and calculating the previous week data by the previous time node of each dayLearned valueAnd deriving the value of the variable Δ V from the real-time dataReal timeAnd the analysis result of the base number plus the variable is used for obtaining the present and future control logicf(VLearned value，ΔVReal time)。
As shown in fig. 5, in another embodiment of the present invention, a flow chart of a station ventilation mode control method is provided. Referring to fig. 5, the control method of the present invention specifically includes:
firstly, the number of people in the area is calculated by cameras such as station halls, entrances and exits, transfer channels and the like in a video calculation module, a people flow difference value is calculated, the station is judged to be in a people inrush or inrush time period, and the total number of people in the area is calculated by a camera in a station waiting area. And calculates the sum of the number of people in both areas. And then the fresh air volume real-time analysis unit receives the data of the video calculation module and the piston air calculation module for analysis and calculation. When the personnel belong to the inrush time interval, the fresh air volume is increased, and when the personnel belong to the inrush time interval, the fresh air volume is reduced or kept in combination with the total number of the stations. And the piston wind module data is used as an influence factor to participate in calculation. And further, the fresh air volume real-time analysis unit performs analysis and calculation, namely:
ΔLreal-time analysisΔ S × M + Δ L2) internal and external air exchange amount ═ f (a, Δ S)
Wherein, Δ L is the fresh air volume which needs to be increased or decreased relative to a certain moment in a station, Δ S is the number of people which needs to be increased or decreased relative to a certain moment in the station, M is the fresh air volume which needs to be decreased by a single person, Δ L2 is the amount of air exchange increase or decrease relative to indoor and outdoor air at a certain moment in the station, and a is a piston air influence factor.
The fresh air volume is a base number plus variable:
L＝f(Llearned value，ΔLReal time)
Analyzing and calculating the previous data of several weeks from the previous time nodes of each day to obtain a base number LLearned valueAnd deriving the variable value DeltaL from the real-time dataReal-time analysisAnd from the analysis results of the radix plus the variables, the present and future control logic f (L) is obtainedLearned value，ΔLReal time)
Meanwhile, the calculation module of the thermal imaging instrument calculates the average body temperature of personnel in the station through the station hall and the station thermal imaging instrument and records the average body temperature as TAverage of the population。
Through the data of the entrance, the transfer passage and the thermal imaging instrument in the vehicle body, the average value of the body temperature change values caused by the change of the thermal environment in a short time when a computer enters from one area to the other area is recorded as delta TAverage of the population. When T isAverage of the population、ΔTAverage of the populationWhen increasing or decreasing, the air volume of the blower or the exhaust fan is increased or decreased accordingly.
QDisplay device＝S×QShow everyone+QE+QL
ΔQDisplay device＝ΔS×QShow everyone+QL＝f(TAverage of the population、ΔTAverage of the population，ΔS，ΔL)
Wherein Q isDisplay deviceShowing heat quantity for station, S is number of station people, QShow everyoneIs the sensible heat of a single person, QEFor sensible heat of the plant, QLFor giving out heat of fresh air, Delta QDisplay deviceThe quantity of the added or reduced sensible heat quantity of the station relative to a certain moment is deltaS.
Meanwhile, the piston wind calculation module calculates the piston wind speed, the wind quantity and the wind temperature, and provides a data basis for the calculation of other modules.
And in the whole calculation process, the personnel number real-time analysis unit, the piston wind speed, the wind volume, the wind temperature real-time analysis unit, the personnel body temperature real-time analysis unit, the fresh wind volume real-time analysis unit, the fan wind volume controller module and the like continuously transmit data to the historical data learning unit. Obtaining the average body temperature T through machine learningAverage of the populationAverage value of body temperature change value Δ TAverage of the population、QLearned value、LLearned value、GLearned value、ΔLLearned value、ΔGLearned value、SLearned value、ΔSLearned valueAnd (4) equivalence. And finally, the fan air volume controller makes a decision according to the calculation result of the real-time analysis unit and the historical data learning unit data to control the fan air volume.
The air volume value of the fan is as follows: the base plus the variable.
The air volume of the air blower is as follows:
Figure BDA0003101072380000191
Figure BDA0003101072380000192
gamma is the external influence factor of air supply
For example, the base G is obtained by taking the week as a time calculation unit and analyzing and calculating the previous week data by the previous time node of each dayLearned valueAnd deriving the variable value Δ G from the real-time dataReal timeAnd from the results of the analysis of the radix plus the variables, the present and future control logic f (G) is derivedLearned value，ΔGReal time)。
Therefore, the method and the device have the advantages that the number of people, the number of people and the flow are comprehensively applied and judged through the video AI, the method and the device are more accurate and practical, the real-time air volume and the real-time air temperature are controlled through historical learning and real-time flow weight distribution, the function of forecasting in advance is achieved, and the effects of energy conservation and environmental protection are achieved.
And through station hall, platform camera use mode, to the relatively stable platform of stream of people waiting the district calculation number of people, to station hall, access & exit, transfer passage flow variation is great, through calculating inrush period and inrush period, again with the amount of wind correlated with. And calculating and predicting the flow rate of the station freezing water according to the body temperature of the human body and the difference value of the body temperatures passing through different areas, and comparing the flow rate with the predicted flow rate.
Therefore, the invention has the advantages that:
1. compared with the traditional temperature and humidity and carbon dioxide sensor, the stability of the air volume calculated through shooting and the service life of the sensor are superior to those of the carbon dioxide sensor, and the maintenance frequency and period are reduced.
2. Compared with the traditional temperature and humidity sensor, the human body surface temperature can reflect the human body comfort degree more directly and accurately in a certain range.
It should be apparent that the foregoing description and illustrations are by way of example only and are not intended to limit the present disclosure, application or uses. While embodiments have been described in the embodiments and depicted in the drawings, the present invention is not limited to the particular examples illustrated by the drawings and described in the embodiments as the best mode presently contemplated for carrying out the teachings of the present invention, and the scope of the present invention will include any embodiments falling within the foregoing description and the appended claims.

Claims (7)

1. The utility model provides a through visual monitoring's underground station ventilation air conditioner control method, contains video calculation module, thermal imaging appearance calculation module and piston wind module, its characterized in that:
the video calculation module is divided into two parts, namely a station hall, an entrance and an exit, and a transfer channel camera, which are arranged in the station hall, the entrance and the exit and the transfer channel to calculate the people flow difference value, judge whether the station is in the people inrush or inrush period and calculate the number of people in the area; secondly, the camera of the waiting area of the platform calculates the total number of people in the area and obtains the total number of people through the sum of the number of people in the two areas;
the thermal imaging instrument calculation module is divided into two parts, namely a station hall thermal imaging instrument and a station thermal imaging instrument to calculate the average body temperature of the human body in the area, and a gateway thermal imaging instrument, a transfer passage thermal imaging instrument and a vehicle body internal thermal imaging instrument to calculate the average body temperature of the human body in the area and the average value of body temperature change values caused by the change of the thermal environment of a calculator in a short time when the calculator enters the other area from one area;
the piston wind module tests the piston wind speed and the wind temperature and calculates the amount of air exchanged between the interior of the station and the outside;
the system is also provided with a fresh air volume real-time analysis unit, wherein the fresh air volume value is determined by the number of the station personnel and the exchange quantity of the inside and outside air of the station, namely L1 (fresh air) is S M + L2 (exchange quantity of the inside and outside air), wherein L1 is the fresh air volume required by the station, S is the personnel number, M is the fresh air volume required by a single person, L2 is the exchange quantity of the inside and outside air, and delta LReal-time analysisΔ S + Δ L2 (internal and external air exchange amount), where Δ LReal-time analysisThe fresh air quantity required to be increased or decreased relative to a certain moment of the station is delta S, the number of people increased or decreased relative to the certain moment of the station is delta S, the fresh air quantity required by a single person is M, and the fresh air quantity required by a single person is delta L2The amount of increase or decrease in the indoor and outdoor air exchange at that time.
2. A ventilating and air-conditioning control method for a subway station through visual monitoring as claimed in claim 1, wherein: a freezing water flow real-time analysis unit is also arranged, wherein for a constant temperature difference system, the freezing water flow is determined by station cold load, new air cold load and reheating quantity, namely
Figure FDA0003519290740000021
Wherein VReal-time analysisIs water flow, Q is system cooling capacity, CPρ is the density of water at a temperature, Δ T is the temperature difference of water, and Q ═ Q1+Q2+Q3Wherein Q is the system cold quantity, Q1For indoor cooling load, Q2Is a new air cooling load, Q3Is reheat;
thus, it is possible to provide
Figure FDA0003519290740000022
Wherein Δ VReal-time analysisFor the water flow, Δ Q, to be increased or decreased at a station relative to a certain time1For increasing or decreasing indoor cooling load, Δ Q, of the station at a certain time2The station increases or decreases fresh air cooling load at a certain moment, CPThe specific heat capacity at constant pressure is defined as rho, which corresponds to the density of water at temperature, and Δ T is the temperature difference of water.
3. A ventilating and air-conditioning control method for a subway station through visual monitoring as claimed in claim 1 or 2, wherein: the device is also provided with a historical data learning unit, and a real-time analysis unit for the number of the personnel is arranged through the historical data learning unit; a piston wind speed, wind volume and wind temperature real-time analysis unit; a real-time body temperature analysis unit of a person; a fresh air volume real-time analysis unit; a real-time analysis unit for the flow rate of the chilled water; and constructing a machine learning algorithm by using the fan air volume and the chilled water flow controller to obtain a training value.
4. As in claimThe underground station ventilation air-conditioning control method through visual monitoring as claimed in claim 1, is characterized in that: for the air conditioning mode, the air volume of the new air blower is determined by the fresh air volume, the real-time value and the learning value are jointly determined, the air volume of the air blower is also jointly determined by the real-time value and the learning value, and for the primary air return system, the air volume of the air blower is
Figure FDA0003519290740000023
Wherein G isReal-time analysisFor the amount of air supply, Q1For residual heat in the room iNIs the enthalpy value of indoor air, i0Is the enthalpy value of the air supply point, and
Figure FDA0003519290740000024
wherein Δ GReal-time analysisFor the amount of air supply required to be increased or decreased relative to a certain moment, Δ Q1For increasing or decreasing the residual heat in the room relative to the need at a certain moment, iNIs the enthalpy value of indoor air, i0Is the enthalpy value of the air supply point.
5. A ventilating and air-conditioning control method for a subway station through visual monitoring as claimed in claim 1, wherein: for the ventilation mode, the air volume of the air feeder is jointly decided by a real-time value and a learning value,
Figure FDA0003519290740000031
wherein G isReal-time analysisFor the amount of air supply, QDisplay deviceIs residual heat in the room, tPIs the outdoor air temperature, tSIs the temperature of the air in the room,
Figure FDA0003519290740000032
Figure FDA0003519290740000033
wherein Δ GReal-time analysisFor the amount of air supply required to be increased or decreased relative to a certain moment, Δ QDisplay deviceFor increasing or decreasing the residual heat in the room relative to the requirement at a certain moment, tPFor the temperature of outdoor air，tSIs the indoor air temperature.
6. A ventilating and air-conditioning control method for a subway station through visual monitoring as claimed in claim 1, wherein:
the method comprises the following steps that firstly, a station hall, an entrance and an exit in a video calculation module and a transfer channel camera calculate the number of people in the area, the difference of the flow of people is calculated to judge whether a station is in a people inrush or inrush time period, a camera in a station waiting area calculates the total number of people in the area, the sum of the number of people in the two areas is calculated, then a fresh air quantity real-time analysis unit receives data of the video calculation module and a piston air calculation module, analysis and calculation are carried out, when the personnel belong to the inrush time period, the fresh air quantity is increased, when the personnel are in the inrush time period, the fresh air quantity is considered to be reduced or kept in combination with the total number of people in the station, the piston air module data participate in calculation as influence factors, and further a fresh air quantity real-time analysis unit makes analysis and calculation:
ΔLreal-time analysisΔ S + Δ L2 (internal and external air exchange amount) ═ f (a, Δ S)
Wherein Δ LReal-time analysisThe air volume is the new air volume which needs to be increased or decreased relative to a certain moment in a station, delta S is the number of people which need to be increased or decreased relative to the certain moment in the station, M is the new air volume which needs to be increased or decreased relative to indoor and outdoor air exchange of the station at a certain moment, delta L2 is the piston air influence factor a;
the air volume of the new fan is a base number plus variable:
L＝f(Llearned value，ΔLReal time)
Analyzing and calculating the week rule by the previous time nodes of each day and the previous week data to obtain a base number LLearned valueAnd deriving the variable value DeltaL from the real-time dataReal-time analysisAnd from the analysis results of the radix plus the variables, the present and future control logic f (L) is obtainedLearned value，ΔLReal time)；
Meanwhile, the calculation module of the thermal imaging instrument calculates the average body temperature of personnel in the station through the station hall and the station thermal imaging instrument, and the meter is TAverage of the population；
Through the data of the entrance, the transfer passage and the thermal imaging instrument in the vehicle body, the average value of the body temperature change values caused by the change of the thermal environment of a person entering from one area to the other area in a short time is calculated as delta TAverage of the populationWhen T isAverage of the population、ΔTAverage of the populationWhen increasing or reducing, correspondingly consider increasing or reducing the refrigerated water flow, further the real-time analysis unit of refrigerated water flow considers personnel's load and new trend load simultaneously, promptly:
Figure FDA0003519290740000041
wherein, is Δ VReal-time analysisFor the water flow, Δ Q, to be increased or decreased at a station relative to a certain time1For increasing or decreasing indoor cooling load, Δ Q, of the station at a certain time2The station increases or decreases fresh air cooling load at a certain moment, CPFor specific heat capacity at constant pressure, ρ is the density of water at the temperature corresponding to ρ, Δ T is the temperature difference of water, TAverage of the populationIs the average temperature of human body, delta T, in the stationAverage of the populationThe average value of body temperature change values caused by the change of the thermal environment of a person in a short time when the person enters another area from one area, wherein delta L is the new air volume required to be increased or reduced relative to a certain moment at a station, and delta L is the change value of the air volume of a fan instead of delta LReal time，
The final blower has an air volume of
Figure FDA0003519290740000051
Wherein the content of the first and second substances,
Figure FDA0003519290740000052
the chilled water flow value is a base plus variable:
Figure FDA0003519290740000053
7. a ventilating and air-conditioning control method for a subway station through visual monitoring as claimed in claim 1, wherein:
the method comprises the following steps that firstly, a station hall, an entrance and an exit in a video calculation module and a transfer channel camera calculate the number of people in the area, the difference of the flow of people is calculated to judge whether a station is in a people inrush or inrush time period, a camera in a station waiting area calculates the total number of people in the area, the sum of the number of people in the two areas is calculated, then a fresh air quantity real-time analysis unit receives data of the video calculation module and a piston air calculation module, analysis and calculation are carried out, when the personnel belong to the inrush time period, the fresh air quantity is increased, when the personnel are in the inrush time period, the fresh air quantity is considered to be reduced or kept in combination with the total number of people in the station, the piston air module data participate in calculation as influence factors, and further a fresh air quantity real-time analysis unit makes analysis and calculation:
ΔLreal-time analysisΔ S + Δ L2 (internal and external air exchange amount) ═ f (a, Δ S)
Wherein, DeltaL is the fresh air quantity which needs to be increased or decreased relative to a certain moment in a station, DeltaS is the number of people which needs to be increased or decreased relative to a certain moment in the station, M is the fresh air quantity which needs to be increased or decreased relative to a certain moment in the station, DeltaL 2 is the indoor and outdoor air exchange increase or decrease relative to a certain moment in the station, a is a piston air influence factor,
the fresh air volume is a base number plus variable:
L＝f(Llearned value，ΔL)
Analyzing and calculating the week rule by the previous time nodes of each day and the previous week data to obtain a base number LLearned valueAnd deriving the variable value DeltaL from the real-time dataReal-time analysisAnd from the analysis results of the radix plus the variables, the present and future control logic f (L) is obtainedLearned value，ΔL)，
Meanwhile, the calculation module of the thermal imaging instrument calculates the average body temperature of personnel in the station through the station hall and the station thermal imaging instrument and records the average body temperature as TAverage of the population，
The data of the thermal imaging instrument in the vehicle body is transmitted to the computer through the gateway, the transfer passage and the data of the thermal imaging instrument in the vehicle body, so that the computer can enter from one area to another areaThe average value of the body temperature change values caused by the change of the thermal environment is recorded as delta TAverage of the populationWhen T isAverage of the population、ΔTAverage of the populationIncreasing or decreasing the blower or exhaust air volume, Q, when increasing or decreasing, respectivelyDisplay device＝S×QShow everyone+QE+QL，ΔQDisplay device＝ΔS×QShow everyone+QL＝f(TAverage of the population、ΔTAverage of the populationΔ S, Δ L), wherein QDisplay deviceShowing heat quantity for station, S is number of station people, QShow everyoneIs the sensible heat of a single person, QEFor the apparatus to develop heat, QLFor giving out heat of fresh air, Delta QDisplay deviceThe sensible heat which needs to be increased or reduced at a certain time of the station is provided, delta S is the number of persons which are increased or reduced at the certain time of the station, and finally the air volume of the air feeder is as follows:
Figure FDA0003519290740000061
Figure FDA0003519290740000062
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