CN101235723B - Express highway section multi- tunnel gathering type intelligent aeration control method - Google Patents
Express highway section multi- tunnel gathering type intelligent aeration control method Download PDFInfo
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- CN101235723B CN101235723B CN2008100453519A CN200810045351A CN101235723B CN 101235723 B CN101235723 B CN 101235723B CN 2008100453519 A CN2008100453519 A CN 2008100453519A CN 200810045351 A CN200810045351 A CN 200810045351A CN 101235723 B CN101235723 B CN 101235723B
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Abstract
The invention relates to a multi-tunnel assembling-type intelligent ventilation control method of expressway section, which comprises utilizing a continuity character that expressway traffic flow passes through a plurality of tunnels on sections in turn, an antecedence tunnel dopes out traffic flow data and contaminant concentration of a next control periodic time according to actual measured traffic flow and contaminant concentration data, a subsequent tunnel predicts traffic flow data and contaminant concentration of a next control periodic time of the subsequent tunnel according traffic flow of current control cycle of antecedence tunnel and the actual measured traffic flow and contaminant concentration data of the tunnel, and each tunnel controls the starting times of fans according predicted value of contaminant through adopting a model of intelligent fuzzy reasoning. The method can more accurately beforehand predict concentration variation of traffic flow, smog and carbon monoxide in adjacent tunnels, thereby beforehand and accurately controlling starting amount of a jet fan, the control method has excellent ventilation control effect, which can simultaneously reduce energy consumption, and can improve service span of fans.
Description
Technical field
The present invention relates to a kind of control method of Highway Tunnel Ventilation System, especially the control method of many tunnel ventilation systems on the express highway section.
Background technology
The control method of Highway Tunnel Ventilation System mainly contains at present: fixed routine control, FEEDBACK CONTROL.The fixed routine control method is not considered the situation of change of smog, carbonomonoxide concentration and the traffic volume, but press the time interval (as Day and night, festivals or holidays are with at ordinary times) in advance compiled program control blower fan running, this method can not adapt to the variation of traffic flow, is mainly used in the Ventilation Control of municipal highway tunnel.Reaction type control method is by smog transmitance sensor that is distributed in each point in the tunnel and carbonomonoxide concentration sensor, directly detect smokescope and the CO concentration value that driving vehicle gives off, pollution concentration current in the tunnel (VI value and CO value) and control desired value are compared, to be no more than desired value is principle, after handling as calculated, provide control signal, the operating number of blower fan is controlled.The many tunnels of China more generally adopt this mode to carry out Ventilation Control at present.But because the variation of tunnel pollutant levels is bigger, this control method is easy to generate fluctuation to the control of blower fan, be that start-stop is frequent, cause it not only to consume a large amount of electric energy, also shortened the application life of blower fan, owing to detect the time delay of data feedback, produce pollutant levels unavoidably and exceed standard simultaneously, blower fan just increases unlatching quantity; Perhaps wagon flow reduces, and pollution concentration is very low, does not reduce the unlatching quantity of blower fan yet, the waste energy; Make that Ventilation Control effect (tunnel operating environment) is undesirable.
Summary of the invention
Purpose of the present invention just provides a kind of express highway section multi-tunnel gathering type intelligent aeration control method, and this method can predict in advance that traffic flow and smog in the tunnel, carbonomonoxide concentration change, thus the unlatching quantity of control jet blower fan in advance; Control effectively, reduce simultaneously energy consumption again, improve the application life of blower fan.
The present invention realizes its goal of the invention, and the technical scheme that is adopted is:
A kind of express highway section multi-tunnel gathering type intelligent aeration control method, in each tunnel, utilize Vehicle analyzer, smokescope and carbonmonoxide detector, wind speed detector respectively traffic flow, smog and carbonomonoxide concentration, wind speed in the tunnel separately to be detected, the unlatching or the closed condition of the jet blower in the tunnel are controlled by data processing and control system according to testing result, it is characterized in that: the described way of by data analysis and control system the opening of the jet blower in the tunnel being controlled according to testing result is:
First tunnel:
A1, forecasting traffic flow: data are handled and control system receives the traffic flow q that the current control cycle in this tunnel is measured
1t, in conjunction with the traffic flow q of the last control cycle in this tunnel
1 (t-1), calculate the traffic flow q of this next control cycle of tunnel according to following formula
1 (t+1):
q
1(t+1)＝β
1·q
1t+γ
1·q
1(t-1)
β wherein
1, γ
1Be q
1t, q
1 (t-1)Weight coefficient, satisfy β
1+ γ
1=1;
B1, pollutant levels prediction and control: by smog and carbonomonoxide concentration value and the traffic flow q that data are handled and control system is surveyed according to current control cycle
1tAnd wind speed, and the traffic flow q in next this tunnel of control cycle that dopes
1 (t+1), draw the smog of next control cycle, the predicted value of carbonomonoxide concentration, with the control desired value VI of predicted value and smog, carbon monoxide
E, CO
ECarry out fuzzy reasoning, jet blower is opened quantity carry out fuzzy control;
Tunnel after second, third reaches:
A2, forecasting traffic flow: data are handled and control system receives the traffic flow q that the current control cycle in this tunnel and last tunnel is measured
Mt, q
(m-1) t, in conjunction with the traffic flow q of the last control cycle in this tunnel
M (t-1), according to the traffic flow q that calculates this next control cycle of tunnel with formula
M (t+1):
q
m(t+1)＝α
m·q
(m-1)t+β
m·q
mt+γ
m·q
m(t-1)
α wherein
m, β
m, γ
mBe q
(m-1) t, q
Mt, q
M (t-1)Weight coefficient, satisfy α
m+ β
m+ γ
m=1.
B2, pollutant levels prediction and control: according to the wind speed of this tunnel current period actual measurement, the traffic flow in smog, carbonomonoxide concentration and next this tunnel of control cycle of doping, calculate the smog in next this tunnel of control cycle, the predicted value of carbonomonoxide concentration, control desired value VIE, the COE of predicted value and smog, carbon monoxide are carried out the fuzzy reasoning computing, jet blower is opened quantity carry out fuzzy control.
Compared with prior art, the invention has the beneficial effects as follows:
First tunnel: by data handle and control system according to smog and carbonomonoxide concentration value and the traffic flow and the wind speed of actual measurement, prediction draws traffic flow, the smog of next control cycle, the predicted value of carbonomonoxide concentration, and and then carry out fuzzy reasoning according to predicted value, jet blower is opened quantity carries out fuzzy control;
Second reaches tunnel later on: the traffic flow data of last tunnel Vehicle analyzer current period actual measurement is passed to data in real time handle and control system, adopt fuzzy prediction method that the traffic flow of next control cycle in current tunnel is predicted by this system.Utilize freeway traffic flow by many continuity features that the tunnel vehicle passes through successively on the highway section, made the accuracy of forecasting traffic flow in current tunnel be able to obvious raising; Further draw the smog in current tunnel of following one-period, the predicted value of carbonomonoxide concentration with this traffic flow accurately as foundation again.And the mode that adopts the intelligent fuzzy reasoning is opened (closing) quantity to blower fan in advance and is controlled.
Therefore method of the present invention has been avoided the control time delay of existing control method, and the Ventilation Control effect improves greatly, has also more effectively reduced energy consumption, the application life of having improved blower fan simultaneously.Especially second and later tunnel in, the accuracy of the value of its prediction improves greatly, its prediction is more accurate, the Ventilation Control better effects if.
The traffic flow forecasting method in above-mentioned the 3rd and later tunnel can also be:
Data are handled and control system receives this tunnel and traffic flow q last, that the current control cycle in the first two tunnel is measured
Mt, q
(m-1) t, q
(m-2) t, in conjunction with the traffic flow q of the last control cycle in this tunnel
M (t-1), according to the traffic flow q that calculates this next control cycle of tunnel with formula
M (t+1):
q
m(t+1)＝α
m·(α
m(m-2)q
(m-2)t+α
m(m-1)q
(m-1)t)
+β
m·q
mt+γ
m·q
m(t-1)
α in the formula
m, β
m, γ
mBe respectively weight coefficient last, that traffic flow, the historical traffic flow of this tunnel actual measurement traffic flow and this tunnel are surveyed in the first two tunnel, need satisfy α
m+ β
m+ γ
m=1, α
M (m-2), α
M (m-1)Be respectively the first two, the weight coefficient of last tunnel actual measurement traffic flow, satisfy α
M (m-2)+ α
M (m-1)=1.
Like this, the forecasting traffic flow in tunnel after the inventive method reaches the 3rd on the highway section, on the basis of having considered the influence of last tunnel traffic stream, also considered the traffic flow in the first two tunnel simultaneously, the forecasting traffic flow in tunnel was accurate more, reliable after its following one-period the 3rd reached.Thereby it is more accurate, more energy-conservation to control.
Above-mentioned data are handled and control system is surveyed according to current control cycle smog and carbonomonoxide concentration
The implication of fuzzy language variable is in the table: NB-is negative big, and during NM-was negative, NS-was negative little, and Z-zero, and PS-is just little, the PM-center, and PB-is honest; S-is little, and among the M-, big among the BS-, BB-is big.
Method by above fuzzy control, it is simple to make the present invention control the foundation and the computing of model, also can carry out suitably simultaneously, effectively control: pass through Intelligent Fuzzy Control the ventilation in tunnel, can reduce blower fan start-stop frequency, prolong fan life, and saving power consumption, the fluctuation that causes in the time of also can preventing bad vehicle to run obtains stable more ventilation effect.
Below in conjunction with the drawings and the specific embodiments the present invention is described in more detail.
Description of drawings
Fig. 1 is the schematic diagram of many tunnels of embodiment of the invention control method and three kinds of detectors wherein arranging and jet blower.The direction of arrow is vehicle heading among the figure.
Fig. 2 is domain and the membership function figure of the smokescope increment Delta VI in the fuzzy Judgment control method of the embodiment of the invention.Wherein, the unit of smokescope VI and increment Delta VI thereof is 1/m (light transmittance).
Fig. 3 is domain and the membership function figure of the carbon monoxide Δ CO in the fuzzy Judgment control method of the embodiment of the invention.Wherein, the unit of carbonomonoxide concentration CO and increment Delta CO thereof is ppm.
Fig. 4 is domain and the membership function figure of the wind speed WS in the fuzzy Judgment control method of the embodiment of the invention.Wherein the unit of wind speed WS is m/s.
Fig. 5 is domain and the membership function figure of the blower fan increment Delta Njf in the fuzzy Judgment control method of the embodiment of the invention.
The specific embodiment
Embodiment
Fig. 1 illustrates, and a kind of specific embodiment of the present invention is:
A kind of express highway section multi-tunnel gathering type intelligent aeration control method, in each tunnel, utilize Vehicle analyzer CT, smokescope and carbonmonoxide detector VI/COT, wind speed detector WST respectively traffic flow, smog and carbonomonoxide concentration, wind speed in the tunnel separately to be detected, handle by data and control system is controlled unlatching or the closed condition of the jet blower JF in the tunnel according to testing result.
The way of by data analysis and control system the opening of the jet blower JF in the tunnel being controlled according to testing result is:
First tunnel:
A1, forecasting traffic flow: data are handled and control system receives the traffic flow q that the current control cycle in this tunnel is measured
1t, in conjunction with the traffic flow q of the last control cycle in this tunnel
1 (t-1), calculate the traffic flow q of this next control cycle of tunnel according to following formula
1 (t+1):
q
1(t+1)＝β
1·q
1t+γ
1·q
1(t-1)
β wherein
1, γ
1Be q
1t, q
1 (t-1)Weight coefficient, satisfy β
1+ γ
1=1;
B1, pollutant levels prediction and control: by smog and carbonomonoxide concentration value and the traffic flow q that data are handled and control system is surveyed according to current control cycle
1tAnd wind speed, and the traffic flow q in next this tunnel of control cycle that dopes
1 (t+1), draw the smog of next control cycle, the predicted value of carbonomonoxide concentration, with the control desired value VI of predicted value and smog, carbon monoxide
E, CO
ECarry out fuzzy reasoning, jet blower is opened quantity carry out fuzzy control;
Second tunnel:
A2, forecasting traffic flow: data are handled and control system receives the traffic flow q that the current control cycle in this tunnel and last tunnel is measured
2t, q
1t, in conjunction with the traffic flow q of the last control cycle in this tunnel
2 (t-1), according to the traffic flow q that calculates this next control cycle of tunnel with formula
2 (t+1):
q
2(t+1)＝α
2·q
1t+β
2·q
2t+γ
2·q
2(t-1)
α wherein
2, β
2, γ
2Be q
1tq
2t, q
2 (t-1)Weight coefficient, satisfy α
2+ β
2+ γ
2=1.
B2, pollutant levels prediction: according to the wind speed of this tunnel current period actual measurement, the traffic flow in next this tunnel of control cycle that smog, carbonomonoxide concentration and A2 step dope, calculate the smog in next this tunnel of control cycle, the predicted value of carbonomonoxide concentration, control desired value VIE, the COE of predicted value and smog, carbon monoxide are carried out the fuzzy reasoning computing, jet blower is opened quantity carry out fuzzy control.
The 3rd traffic flow forecasting method that reaches later tunnel is in this example:
Data are handled and control system receives this tunnel and traffic flow q last, that the current control cycle in the first two tunnel is measured
Mt, q
(m-1) t, q
(m-2) t, in conjunction with the traffic flow q of the last control cycle in this tunnel
M (t-1), according to the traffic flow q that calculates this next control cycle of tunnel with formula
M (t+1):
q
m(t+1)＝α
m·(α
m(m-2)q
(m-2)t+α
m(m-1)q
(m-1)t)
+β
m·q
mt+γ
m·q
m(t-1)
α in the formula
m, β
m, γ
mBe respectively weight coefficient last, that traffic flow, the historical traffic flow of this tunnel actual measurement traffic flow and this tunnel are surveyed in the first two tunnel, need satisfy α
m+ β
m+ γ
m=1; α
M (m-2), α
M (m-1)Be respectively the first two, the weight coefficient of last tunnel actual measurement traffic flow, satisfy α
M (m-1)+ α
M (m-2)=1.M=3,4,5 ... M represents the 3rd, the 4th, the 5th respectively ... M tunnel.
The 3rd and after the pollutant levels predictions and the control method in tunnel, then identical with first, second tunnel, just wherein following one-period the forecasting traffic flow value computational methods adopt different with first, second tunnel with upper type.
Weight coefficient such as α in this routine forecasting traffic flow formula
m, β
m, γ
m, α
M (m-1), α
M (m-2)And α
2, β
2, γ
2, β
1, γ
1, can determine according to the sample data of actual measurement, promptly choose the predicted value that one group of weight coefficient makes that formula calculates and the error minimum of measured value.Can pass through optimal methods such as Powell method, search method obtains.
In this example data handle and control system according to smog and carbonomonoxide concentration value and the traffic flow and the wind speed of current control cycle actual measurement, the concrete grammar of predicted value that draws smog, the carbonomonoxide concentration of next control cycle is:
Current traffic flow q by this tunnel
MtCalculate the theoretical discharge amount of pollutant,, calculate the theoretical concentration VI of smog and carbon monoxide again in conjunction with wind speed ws current in this tunnel
t', CO
t'; Again by the predicted value q of next control cycle traffic flow in this tunnel
M (t+1)Calculate the theoretical discharge amount of the pollutant of next control cycle, and suppose that the wind speed of this next control cycle of tunnel is identical with current wind speed ws, calculate the theoretical concentration VI of next control cycle smog and carbon monoxide
T+1', CO
T+1' calculate next control cycle smog and carbonomonoxide concentration VI by following formula again
T+1, CO
T+1:
VI
t+1＝(VI
t+1′/VI
t′)VI
t
CO
t+1＝(CO
t+1′/CO
t′)CO
t
In the formula, VI
t, CO
t, be the pollutant levels smog and the carbonomonoxide concentration of current control cycle actual measurement.
The wind speed of supposing next control cycle in the tunnel in this example is identical with the wind speed of current actual measurement.And the theoretical discharge amount VI of smog and carbonomonoxide concentration
t', CO
t', VI
T+1', CO
T+1',, calculate according to " highway tunnel ventilation illumination design standard " (JTJ 026.1-1999) by traffic flow numerical value.
In this example jet blower being opened quantity carries out the way of fuzzy control and is:
The next control cycle smog in this tunnel and carbonomonoxide concentration VI of obtaining by prediction
T+1, CO
T+1And this tunnel of the current period smog and the carbonomonoxide concentration VI that record
t, CO
tCalculate prediction increment Delta VI, the Δ CO of next control cycle smog and carbonomonoxide concentration, wind speed WS with this prediction increment Delta V, Δ CO and current period actual measurement, after the obfuscation as the input quantity of fuzzy reasoning, fuzzy inference rule according to following table, draw jet blower and open the fuzzy quantity of increment Delta NJF, obtain the unlatching increment Delta NJF of the jet blower in tunnel, back behind the ambiguity solution, realize jet blower is opened the control of quantity.
The implication of fuzzy language variable is in the table: NB-is negative big, and during NM-was negative, NS-was negative little, and Z-zero, and PS-is just little, the PM-center, and PB-is honest; S-is little, and among the M-, big among the BS-, BB-is big.
Last table has 105 decision rules, as first row, first rule that is listed as in the table is:
R1:IF Δ VI is PB and WS is BB and Δ CO is PB THEN Δ NJF is PB; It is honest promptly working as the smokescope increment, and wind speed is big, and when carbonomonoxide concentration was honest, the increment that blower fan is opened was honest.
This fuzzy inference rule table is suitable for the freeway tunnel of length at 3000m-6000m, can suitably revise and test after tested getting final product on its basis for the fuzzy control rule of the high speed tunnel ventilation system in other length range.
Fig. 2-5 has provided this example respectively when carrying out fuzzy judgement and calculating blower fan opening increment Delta NJF, smokescope increment Delta VI, carbon monoxide Δ CO, wind speed WS, the domain of blower fan increment Delta Njf and membership function figure.Input variable smokescope increment Delta VI, carbon monoxide Δ CO, the obfuscation of wind speed WS adopts the single-point fuzzy method to be drawn by domain and the membership function figure of Fig. 2-4; Output variable blower fan increment Delta NJF adopts gravity model appoach to carry out ambiguity solution by Fig. 5 domain and membership function figure.
Embodiment two
This example and embodiment one are basic identical, different only be, the 3rd and after the Forecasting Methodology of traffic flow in tunnel identical with the Forecasting Methodology in second tunnel.Be that the tunnel all calculated as follows after second, third reached:
q
m(t+1)＝α
m·q
(m-1)t+β
m·q
mt+γ
m·q
m(t-1)
α wherein
m, β
m, γ
mBe q
(m-1) t, q
Mt, q
M (t-1)Weight coefficient, satisfy α
m+ β
m+ γ m=1.M=2,3,4 ... M, represent respectively second, third, the 4th ... M tunnel.
Also be the forecasting traffic flow in tunnel after the 3rd, the 4th of this example reaches, only consider the influence in its tunnel, front, and do not consider again the influence in (the first two) tunnel, front that its prediction and calculation is simpler, but accuracy is lower.
Claims (4)
1. express highway section multi-tunnel gathering type intelligent aeration control method, in each tunnel, utilize Vehicle analyzer CT, smokescope and carbonmonoxide detector VI/COT, wind speed detector WST is respectively to the traffic flow in the tunnel separately, smog and carbonomonoxide concentration, wind speed detects, unlatching or the closed condition of jet blower JF in the tunnel are controlled by data processing and control system according to testing result, it is characterized in that: the described way of by data analysis and control system the opening of the jet blower JF in the tunnel being controlled according to testing result is:
First tunnel:
A1, forecasting traffic flow: data are handled and control system receives the traffic flow q that the current control cycle in this tunnel is measured
1t, in conjunction with the traffic flow q of the last control cycle in this tunnel
1 (t-1), calculate the traffic flow q of this next control cycle of tunnel according to following formula
1 (t+1):
q
1(t+1)＝β
1·q
1t+γ
1·q
1(t-1)
β wherein
1, γ
1Be q
1t, q
1 (t-1)Weight coefficient, satisfy β
1+ γ
1=1;
B1, pollutant levels prediction and control: by smog and carbonomonoxide concentration value and the traffic flow q that data are handled and control system is surveyed according to current control cycle
1tAnd wind speed, and the traffic flow q in next this tunnel of control cycle that dopes
1 (t+1), draw the smog of next control cycle, the predicted value of carbonomonoxide concentration, with the control desired value VI of predicted value and smog, carbon monoxide
E, CO
ECarry out fuzzy reasoning, jet blower is opened quantity carry out fuzzy control;
Tunnel after second, third reaches:
A2, forecasting traffic flow: data are handled and control system receives the traffic flow q that the current control cycle in this tunnel and last tunnel is measured
Mt, q
(m-1) t, in conjunction with the traffic flow q of the last control cycle in this tunnel
M (t-1), according to the traffic flow q that calculates this next control cycle of tunnel with formula
M (t+1):
q
m(t+1)＝α
m·q
(m-1)t+β
m·q
mt+γ
m·q
m(t-1)
α wherein
m, β
m, γ
mBe q
(m-1) t, q
Mt, q
M (t-1)Weight coefficient, satisfy α
m+ β
m+ γ
m=1;
B2, pollutant levels prediction and control: according to the wind speed of this tunnel current period actual measurement, the traffic flow in smog, carbonomonoxide concentration and next this tunnel of control cycle of doping, calculate the smog in next this tunnel of control cycle, the predicted value of carbonomonoxide concentration, with the control desired value VI of predicted value and smog, carbon monoxide
E, CO
ECarry out the fuzzy reasoning computing, jet blower JF is opened quantity carry out fuzzy control.
2. express highway section multi-tunnel gathering type intelligent aeration control method, in each tunnel, utilize Vehicle analyzer CT, smokescope and carbonmonoxide detector VI/COT, wind speed detector WST is respectively to the traffic flow in the tunnel separately, smog and carbonomonoxide concentration, wind speed detects, unlatching or the closed condition of jet blower JF in the tunnel are controlled by data processing and control system according to testing result, it is characterized in that: the described way of by data analysis and control system the opening of the jet blower JF in the tunnel being controlled according to testing result is:
First tunnel:
A1, forecasting traffic flow: data are handled and control system receives the traffic flow q that the current control cycle in this tunnel is measured
1t, in conjunction with the traffic flow q of the last control cycle in this tunnel
1 (t-1), calculate the traffic flow q of this next control cycle of tunnel according to following formula
1 (t+1):
q
1(t+1)＝β
1·q
1t+γ
1·q
1(t-1)
β wherein
1, γ
1Be q
1t, q
1 (t-1)Weight coefficient, satisfy β
1+ γ
1=1;
B1, pollutant levels prediction and control: by smog and carbonomonoxide concentration value and the traffic flow q that data are handled and control system is surveyed according to current control cycle
1tAnd wind speed, and the traffic flow q in next this tunnel of control cycle that dopes
1 (t+1), draw the smog of next control cycle, the predicted value of carbonomonoxide concentration, with the control desired value VI of predicted value and smog, carbon monoxide
E, CO
ECarry out fuzzy reasoning, jet blower is opened quantity carry out fuzzy control;
Second tunnel:
A2, forecasting traffic flow: data are handled and control system receives the traffic flow q that the current control cycle in this tunnel and last tunnel is measured
Mt, q
(m-1) t, in conjunction with the traffic flow q of the last control cycle in this tunnel
M (t-1), according to the traffic flow q that calculates this next control cycle of tunnel with formula
M (t+1):
q
m(t+1)＝α
m·q
(m-1)t+β
m·q
mt+γ
m·q
m(t-1)
α wherein
m, β
m, γ
mBe q
(m-1) t, q
Mt, q
M (t-1)Weight coefficient, satisfy α
m+ β
m+ γ
m=1;
B2, pollutant levels prediction and control: according to the wind speed of this tunnel current period actual measurement, the traffic flow in smog, carbonomonoxide concentration and next this tunnel of control cycle of doping, calculate the smog in next this tunnel of control cycle, the predicted value of carbonomonoxide concentration, with the control desired value VI of predicted value and smog, carbon monoxide
E, CO
ECarry out the fuzzy reasoning computing, jet blower JF is opened quantity carry out fuzzy control;
The 3rd reaches tunnel later on:
Forecasting traffic flow: data are handled and control system receives this tunnel and traffic flow q last, that the current control cycle in the first two tunnel is measured
Mt, q
(m-1) t, q
(m-2) t, in conjunction with the traffic flow q of the last control cycle in this tunnel
M (t-1), according to the traffic flow q that calculates this next control cycle of tunnel with formula
M (t+1):
q
m(t+1)＝α
m·(α
m(m-2)q
(m-2)t+α
m(m-1)q
(m-1)t)
+β
m·q
mt+γ
m·q
m(t-1)
α in the formula
m, β
m, γ
mBe respectively weight coefficient last, that traffic flow, the historical traffic flow of this tunnel actual measurement traffic flow and this tunnel are surveyed in the first two tunnel, need satisfy α
m+ β
m+ γ
m=1, α
M (m-2), α
M (m-1)Be respectively the first two, the weight coefficient of last tunnel actual measurement traffic flow, satisfy α
M (m-2)+ α
M (m-1)=1;
Pollutant levels prediction and control: according to the wind speed of this tunnel current period actual measurement, the traffic flow in smog, carbonomonoxide concentration and next this tunnel of control cycle of doping, calculate the smog in next this tunnel of control cycle, the predicted value of carbonomonoxide concentration, with the control desired value VI of predicted value and smog, carbon monoxide
E, CO
ECarry out the fuzzy reasoning computing, jet blower JF is opened quantity carry out fuzzy control.
3. a kind of express highway section multi-tunnel gathering type intelligent aeration control method according to claim 1 and 2, it is characterized in that, described data handle and control system according to smog and carbonomonoxide concentration value and the traffic flow and the wind speed of current control cycle actual measurement, the concrete grammar of predicted value that draws smog, the carbonomonoxide concentration of next control cycle is:
Current traffic flow q by this tunnel
MtCalculate the theoretical discharge amount of pollutant,, calculate the theoretical concentration VI of smog and carbon monoxide again in conjunction with wind speed WS current in this tunnel
t', CO
t'; Again by the predicted value q of next control cycle traffic flow in this tunnel
M (t+1)Calculate the theoretical discharge amount of the pollutant of next control cycle, and suppose that the wind speed of this next control cycle of tunnel is identical with current wind speed WS, calculate the theoretical concentration VI of next control cycle smog and carbon monoxide
T+1', CO
T+1', calculate next control cycle smog and carbonomonoxide concentration VI by following formula again
T+1, CO
T+1:
VI
t+1＝(VI
t+1′/VI
t′)VI
t
CO
t+1＝(CO
t+1′/CO
t′)CO
t
In the formula, VI
t, CO
t, be the pollutant levels smog and the carbonomonoxide concentration of current control cycle actual measurement.
4. a kind of express highway section multi-tunnel gathering type intelligent aeration control method according to claim 1 and 2 is characterized in that, describedly jet blower is opened quantity carries out the way of fuzzy control and is:
The next control cycle smog in this tunnel and carbonomonoxide concentration VI of obtaining by prediction
T+1, CO
T+1And this tunnel of the current period smog and the carbonomonoxide concentration VI that record
t, CO
tCalculate prediction increment Delta VI, the Δ CO of next control cycle smog and carbonomonoxide concentration, wind speed WS with this prediction increment Delta V, Δ CO and current period actual measurement, after the obfuscation as the input quantity of fuzzy reasoning, fuzzy inference rule according to following table, draw jet blower and open the fuzzy quantity of increment, obtain the unlatching increment of the jet blower in tunnel, back behind the ambiguity solution, realize jet blower is opened the control of quantity:
The implication of fuzzy language variable is in the table: NB-is negative big, and during NM-was negative, NS-was negative little, and Z-zero, and PS-is just little, the PM-center, and PB-is honest; S-is little, and among the M-, big among the BS-, BB-is big.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2008100453519A CN101235723B (en) | 2008-02-02 | 2008-02-02 | Express highway section multi- tunnel gathering type intelligent aeration control method |
Applications Claiming Priority (1)
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| AT10301U3 (en) * | 2008-09-01 | 2009-09-15 | Avl List Gmbh | METHOD AND REGULATION FOR REGULATING A REGULAR TRACK WITH A RECYCLING WORKING CYCLE |
| CN101644168B (en) * | 2009-05-31 | 2012-07-04 | 北京龙德时代科技发展有限公司 | Ventilation forecasting and early-warning system for mine |
| CN101581940B (en) * | 2009-06-05 | 2011-04-27 | 西安电子科技大学 | Tunnel event detection method based on integrated learning time sequence prediction |
| WO2011042980A1 (en) * | 2009-10-05 | 2011-04-14 | 株式会社創発システム研究所 | Tunnel ventilation control system of two-way tunnel using jet fan |
| CN102080561B (en) * | 2010-12-15 | 2012-07-25 | 上海市城市建设设计研究院 | Group count determining and stationing universal method of pollutant purification ventilation system for road tunnel |
| CN102913269A (en) * | 2012-11-07 | 2013-02-06 | 广西景桂自控工程有限公司 | Tunnel ventilation device |
| CN104265347B (en) * | 2014-07-25 | 2016-08-24 | 天津市市政工程设计研究院 | A kind of multiparameter tunnel ventilation control method based on rate of discharge and concentration |
| CN104154019B (en) * | 2014-08-04 | 2016-07-06 | 昆明联诚科技股份有限公司 | A kind of tunnel ventilation energy-saving control system based on fuzzy control and control method thereof |
| CN104533499A (en) * | 2015-01-23 | 2015-04-22 | 贵州现代物流工程技术研究有限责任公司 | Intelligent expressway tunnel ventilation device and intelligent expressway tunnel ventilation method |
| CN104880223A (en) * | 2015-05-20 | 2015-09-02 | 北京曼德克环境科技有限公司 | System used for environment detection and monitoring in tunnel |
| CN105569707A (en) * | 2015-12-11 | 2016-05-11 | 中铁第四勘察设计院集团有限公司 | Highway tunnel ventilation feedforward control method based on environmental forecasting |
| CN105569709B (en) * | 2016-01-25 | 2018-01-23 | 西南交通大学 | The control method of High-geotemperature railway tunnel cooling ventilation |
| CN105525936B (en) * | 2016-02-02 | 2017-11-21 | 招商局重庆交通科研设计院有限公司 | Highway Tunnels aeration control method |
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