CN105072761A - Smart type tunnel lighting control module algorithm - Google Patents
Smart type tunnel lighting control module algorithm Download PDFInfo
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- CN105072761A CN105072761A CN201510495054.4A CN201510495054A CN105072761A CN 105072761 A CN105072761 A CN 105072761A CN 201510495054 A CN201510495054 A CN 201510495054A CN 105072761 A CN105072761 A CN 105072761A
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B20/00—Energy efficient lighting technologies, e.g. halogen lamps or gas discharge lamps
- Y02B20/40—Control techniques providing energy savings, e.g. smart controller or presence detection
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Abstract
The invention discloses a smart type tunnel lighting control module algorithm. The algorithm comprises steps of establishing a mathematic model reflecting data of traffic volume of a tunnel; comparing and adjusting actually-measured average data of the traffic volume of the tunnel; calculating the sampling average value of running speed in the tunnel to replace the real-time average running speed in the tunnel; determining size of the brightness reduction coefficient k of the entrance segment according to the traffic volume and average and the real-time average running speed in the tunnel; determining brightness of the entrance segment according to the brightness outside the tunnel entrance and the brightness reduction coefficient k of the entrance segment; and determining brightness of the transition segment, the middle segment and the exit segment according to the brightness of the entrance segment. According to the invention, different brightness is controlled in separated time, so energy is saved, use requirements of traffic flows in all time frames can be met and effects of energy conservation and emission reduction are achieved. Illumination power consumption is reduced by 40, so it is possible to use an led powered by solar energy to provide light for the tunnel.
Description
Technical field
The present invention relates to the technical field of building site attendance checking system management application, refer to a kind of intelligent tunnel illumination Controlling model algorithm especially.
Background technology
Current most of vcehicular tunnel dimming energy-saving control system has significant energy-saving effect in actual applications, significantly reduces the operation costs in tunnel.But, in Energy Saving Control Model investigation and application, still there is obvious weak point.Energy Saving Control is roughly divided into four-stage: the 1st stage, and the energy saving means of tunnel light modulation " stair-corridor sense light " formula that level is lower is in multiple tunnel applications inside and outside the province; In 2nd stage, artificial evaluation is done to brightness in hole, sets up the Mathematical Modeling of the luminance of outer caves and tunnel strengthening segment energy-saving lamp supply current relation, embed controller, control brightness in hole; In 3rd stage, according to seasonal law, set up the Mathematical Modeling of season and tunnel strengthening segment energy-saving lamp supply current relation, embed controller, control brightness in hole.Above-mentioned three phases Energy Saving Control mode is applied, though can obtain good energy-saving effect, is difficult to ensure that tunnel dimming function is safe and reliable and energy-efficient for a long time; In 4th stage, according to " vcehicular tunnel dimmer design specification ", be in research and progressively application stage according to the operating mode determination light modulations such as the volume of traffic, the luminance of outer caves, seasonal law and operational management scheme.
So far, the research and development of the safe and efficient energy-conserving control technology of the 4th stage tunnel light modulation and application Main Basis tunnel traffic amount, the luminance of outer caves and tunnel driving average speed three and the Mathematical Modeling of brightness in hole, embed controller, brightness in control hole.But major defect is:
1, tunnel traffic amount: determine current tunnel traffic amount according to front halfhour vehicle flowrate number, the scheme participating in built calculated with mathematical model lacks reasonability;
2, by Tunnel Design speed per hour, move with quiet generation, lack scientific;
3, control brightness in hole with the size of the duty ratio modulation lamp current of PWM pulse-width modulation, lack the closed loop control mechanism of brightness actual value feedback in hole.
Therefore, in-depth research must be carried out to control system Mathematical Modeling, to ensure the safe and reliable of tunnel dimming function and energy-efficient for a long time, improve economical, efficiency, the application for new technology, new technology makes the formulation of higher levels of technical standard and implements to be supported technically and economically.
Summary of the invention
The object of the invention is to solve the above problems, a kind of intelligent tunnel illumination Controlling model algorithm of simple, efficiently and accurately is provided.Comprise the following steps:
S01: the Mathematical Modeling setting up reflection tunnel traffic amount data;
S02: make comparisons with current actual measurement tunnel traffic amount average data, adjust;
S03: calculate tunnel road speed sample mean, substitutes real-time tunnel driving average speed;
S04: according to tunnel traffic amount and real-time tunnel driving average speed, determine the size of entrance brightness reduction coefficient k;
S05: according to the luminance of outer caves and entrance brightness reduction coefficient k, determine the brightness of entrance;
S06: according to the brightness of entrance, determines the brightness of changeover portion, interlude, outlet section.
As preferably, the step S01 of described intelligent tunnel illumination Controlling model algorithm comprises:
Traffic data x sample value is averaged, and obtains sample mean (samplemean),
(1)
Calculate the sample variance (samplevariance) of each sample value and sample mean,
Calculating sampling standard deviation (samplestandarddeviation),
(3)
When sampled data meets normal distribution, standard deviation in population (populationstandarddeviation) σ equals sample standard deviation S, utilize above-mentioned sample mean and sample standard deviation value S, calculate 90% or 95% and hold population mean (populationmean) μ and drop on confidence interval wherein:
During confidence interval when probability P is 95% assurance:
(4)
During confidence interval when probability P is 90% assurance:
(5)
Obtained by formula (4):
（6）
Obtained by formula (5):
（7）
As preferably, the step S02 of described intelligent tunnel illumination Controlling model algorithm: according to the confidence interval described in S01 as yardstick, make comparisons with current actual measurement traffic data mean value, and automatically after adjustment as current traffic volume control data.
As preferably, the step S03 of described intelligent tunnel illumination Controlling model algorithm: adopt Doppler anemometer, detects tunnel road speed, gets sample mean number, substitutes real-time tunnel driving average speed.
As preferably, the step S04 of described intelligent tunnel illumination Controlling model algorithm: show 4.1.1 according to " highway tunnel illumination design details ", determines the size of population section brightness reduction coefficient k.
As preferably, the step S05 of described intelligent tunnel illumination Controlling model algorithm: road tunnel entrance section is divided into TH1, TH2 two illumination stage, brightness corresponding with it calculates by formula (8), (9) respectively:
Lth1=k·L20(S)(8)
Lth2=0.5·k·L20(S)(9)
In formula: Lth1---the brightness (cd/m2) of entrance TH1;
The brightness (cd/m2) of Lth2---entrance TH2;
K---entrance brightness reduction coefficient;
L20 (S)---the luminance of outer caves (cd/m2).
As preferably, the step S06 of described intelligent tunnel illumination Controlling model algorithm: the relation of the brightness of the entrance brightness specified by " highway tunnel illumination design details " and changeover portion, interlude, outlet section, draws the brightness value of interlude, outlet section.
The present invention has following beneficial effect: adopt the brightness that point time controling is different, energy savings.According to the concrete condition time-division transfer of middle short tunnel, by day, at dusk and take night to open all illuminations, 1/2 lighting and 1/3 lighting, both met the use of each period magnitude of traffic flow, had the effect reaching energy-saving and emission-reduction; Day illumination lower power consumption 40% is solar powered led like this as tunnel illumination become a kind of may.
Accompanying drawing explanation
Fig. 1 is schematic flow sheet of the present invention.
Embodiment
Below in conjunction with specific embodiment, and by reference to the accompanying drawings, technical scheme of the present invention is further described:
As shown in Figure 1, intelligent tunnel illumination Controlling model algorithm comprises:
S01: the Mathematical Modeling setting up reflection tunnel traffic amount data;
S02: make comparisons with current actual measurement tunnel traffic amount average data, adjust;
S03: calculate tunnel road speed sample mean, substitutes real-time tunnel driving average speed;
S04: according to tunnel traffic amount and real-time tunnel driving average speed, determine the size of entrance brightness reduction coefficient k;
S05: according to the luminance of outer caves and entrance brightness reduction coefficient k, determine the brightness of entrance;
S06: according to the brightness of entrance, determines the brightness of changeover portion, interlude, outlet section.
First judge whether present period is in emergent, maintenance according to collection signal, if so, controller controls the whole dimming lamp in tunnel and is opened to high-high brightness; Whether be in power interruption recovering operating mode, if so, controller controls the whole dimming lamp in tunnel and is opened to high-high brightness, and >=the 1min that holds time, enter procedure auto-control pattern; The controlling of sampling of above-mentioned two class operating modes, judgement and disposal are all included unified Mathematical Modeling in and are controlled.If above-mentioned situation does not belong to emergent, maintenance or power interruption recovering operating mode, the comprehensive closed-loop control Mathematical Modeling namely according to brightness in the tunnel traffic amount set up, the luminance of outer caves and tunnel driving average speed three and hole controls.Contain the control software design of above-mentioned Mathematical Modeling with machine language establishment, embed controller, gather current information, judge real-time working condition, call historical data, calculate controlling element, control brightness in hole, store deal with data.
Embodiment: change and determine current tunnel traffic amount according to front halfhour vehicle flowrate number, in order to earlier month with the large data mathematical statistics method of period vehicle flowrate, sets up the real-time traffic amount data that real-time computational mathematics model calculates this period.
Such as 11:30-12:00 traffic data is determined:
11:30-12:00 traffic data in the past, as front ten days same period data, last year is with each ten days same period data before and after the period, this year front ten, with what day same period data, is waited other and this period related data, arranges weight according to degree of association size, getting 20 data is 1 group, be divided into some groups by stochastical sampling program, to often organizing data, to get arithmetic average be sample value, obtains x1, x2, ┄, x20;
1,20 sample values are averaged, obtain sample mean (samplemean),
(11)
2, the sample variance (samplevariance) of each sample value and sample mean is calculated,
(12)
3, calculating sampling standard deviation (samplestandarddeviation),
(13)
Theoretical according to sample mean central limit, the sampled data adopted is many, meet normal distribution, the input data of controller will meet population mean (populationmean) μ of present case, and now standard deviation in population (populationstandarddeviation) σ should equal sample standard deviation S.Therefore, utilize above-mentioned sample mean and sample standard deviation value S, 90% or 95% can be calculated and hold population mean and must drop on confidence interval wherein.
During confidence interval when probability P is 95% assurance:
(14)
During confidence interval when probability P is 90% assurance:
(15)
Obtained by formula (14):
（16）
Obtained by formula (15):
（17）
According to this confidence interval as yardstick, make comparisons with current measured data mean value and adjust.Current measured data is obtained by the vehicle flowrate data linear regression of half an hour, hour, an and a half hours before current.Controller automatically detects these data and whether falls confidence interval, or before or after, make comparisons, and as current traffic volume control data after automatically adjusting.
Finally be defined as Mathematical Modeling and embed controller, all calculating all completes in the calculated with mathematical model program embedding controller.The Mathematical Modeling of controller, except bearing evaluation work, collects initial data in addition, carries, compares, judges and the work of execution result data.
Above-mentioned embodiment is used for explaining and the present invention is described, instead of limits the invention, and in the protection range of spirit of the present invention and claim, any amendment make the present invention and change, all fall into protection scope of the present invention.
Claims (7)
1. an intelligent tunnel illumination Controlling model algorithm, is characterized in that comprising:
S01: the Mathematical Modeling setting up reflection tunnel traffic amount data;
S02: make comparisons with current actual measurement tunnel traffic amount average data, adjust;
S03: calculate tunnel road speed sample mean, substitutes real-time tunnel driving average speed;
S04: according to tunnel traffic amount and real-time tunnel driving average speed, determine the size of entrance brightness reduction coefficient k;
S05: according to the luminance of outer caves and entrance brightness reduction coefficient k, determine the brightness of entrance;
S06: according to the brightness of entrance, determines the brightness of changeover portion, interlude, outlet section.
2., according to intelligent tunnel illumination Controlling model algorithm according to claim 1, it is characterized in that step S01 comprises: traffic data x sample value is averaged, obtain sample mean (samplemean),
(1)
Calculate the sample variance (samplevariance) of each sample value and sample mean,
Calculating sampling standard deviation (samplestandarddeviation),
(3)
When sampled data meets normal distribution, standard deviation in population (populationstandarddeviation) σ equals sample standard deviation S, utilize above-mentioned sample mean and sample standard deviation value S, calculate 90% or 95% and hold population mean (populationmean) μ and drop on confidence interval wherein:
During confidence interval when probability P is 95% assurance:
(4)
During confidence interval when probability P is 90% assurance:
(5)
Obtained by formula (4):
（6）
Obtained by formula (5):
（7）。
3. according to intelligent tunnel illumination Controlling model algorithm according to claim 2, it is characterized in that step S02: according to the confidence interval described in S01 as yardstick, make comparisons with current actual measurement traffic data mean value, and as current traffic volume control data after automatically adjusting.
4. according to intelligent tunnel illumination Controlling model algorithm according to claim 1, it is characterized in that step S03: adopt Doppler anemometer to detect tunnel road speed, get sample mean number, substitute real-time tunnel driving average speed.
5. according to intelligent tunnel illumination Controlling model algorithm according to claim 1, it is characterized in that step S04: show 4.1.1 according to " highway tunnel illumination design details ", determine the size of population section brightness reduction coefficient k.
6. according to intelligent tunnel illumination Controlling model algorithm according to claim 1, it is characterized in that step S05: road tunnel entrance section is divided into TH1, TH2 two illumination stage, brightness corresponding with it calculates by formula (8), (9) respectively:
Lth1=k·L20(S)(8)
Lth2=0.5·k·L20(S)(9)
In formula: Lth1---the brightness (cd/m2) of entrance TH1;
The brightness (cd/m2) of Lth2---entrance TH2;
K---entrance brightness reduction coefficient;
L20 (S)---the luminance of outer caves (cd/m2).
7. according to intelligent tunnel illumination Controlling model algorithm according to claim 1, it is characterized in that step S06: the relation of the brightness of the entrance brightness specified by " highway tunnel illumination design details " and changeover portion, interlude, outlet section, draws the brightness value of interlude, outlet section.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110944427A (en) * | 2019-12-28 | 2020-03-31 | 上海唯视锐光电技术有限公司 | Road tunnel illumination control method and device based on variable reduction coefficient |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101965085A (en) * | 2010-09-19 | 2011-02-02 | 天津大学 | Feedforward control method for illumination adjustment according to tunnel illumination requirement |
| JP2012174663A (en) * | 2011-02-24 | 2012-09-10 | Optex Co Ltd | Light control illumination device and light control illumination system |
| CN103476193A (en) * | 2013-07-09 | 2013-12-25 | 艾宇 | Tunnel illumination dimming control system and control method |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101965085A (en) * | 2010-09-19 | 2011-02-02 | 天津大学 | Feedforward control method for illumination adjustment according to tunnel illumination requirement |
| JP2012174663A (en) * | 2011-02-24 | 2012-09-10 | Optex Co Ltd | Light control illumination device and light control illumination system |
| CN103476193A (en) * | 2013-07-09 | 2013-12-25 | 艾宇 | Tunnel illumination dimming control system and control method |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110944427A (en) * | 2019-12-28 | 2020-03-31 | 上海唯视锐光电技术有限公司 | Road tunnel illumination control method and device based on variable reduction coefficient |
| CN110944427B (en) * | 2019-12-28 | 2023-08-22 | 上海唯视锐光电技术有限公司 | Highway tunnel illumination control method and device based on variable reduction coefficient |
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Application publication date: 20151118 |