CN102023317B - Method for deploying strong wind monitoring points on rapid transit railway - Google Patents
Method for deploying strong wind monitoring points on rapid transit railway Download PDFInfo
- Publication number
- CN102023317B CN102023317B CN201010506850A CN201010506850A CN102023317B CN 102023317 B CN102023317 B CN 102023317B CN 201010506850 A CN201010506850 A CN 201010506850A CN 201010506850 A CN201010506850 A CN 201010506850A CN 102023317 B CN102023317 B CN 102023317B
- Authority
- CN
- China
- Prior art keywords
- wind
- error
- simulation
- along
- railway
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
Images
Landscapes
- Aerodynamic Tests, Hydrodynamic Tests, Wind Tunnels, And Water Tanks (AREA)
Abstract
The invention discloses a method for deploying strong wind monitoring points on a rapid transit railway, comprising the following steps: analyzing the gale distribution characteristics and carrying out statistics on the wind speed frequency distribution under each wind direction based on the information of wind speeds, wind directions and the like of weather stations along and around the rapid transit railway line, and deploying basic monitoring points; establishing the correlationship of winds fields between any two monitoring points along the railway line under complicated terrains based on the geographic and geomorphic information, simulating the wind fields along the rapid transit railway line by adopting the computational fluid dynamics (CFD) method theory and method, and deploying interpolated monitoring points; and simulating the wind fields of special road sections, and deploying special monitoring points by combining with wind tunnel tests. The method provided by the invention overcomes the defects of high cost, strong subjectivity, low accuracy and the like in the traditional method which gives priority to field survey and qualitative analysis, realizes deployment of strong wind monitoring points in rapid transit railways under various weather types and environmental conditions, has high simulation accuracy and low monitoring point deploying cost, and provides support for effective monitoring and safety running of rapid transit railways.
Description
Technical field
The invention belongs to the monitoring and the control technology field of high-speed railway safe driving under the strong wind weather, relate to a kind of method that high-speed railway gale monitoring point is laid that is used for, specifically relating to a kind of is the main distribution method of monitoring point by different level with the quantitative Analysis.
Background technology
High-speed railway is characteristics such as movement capacity is strong, speed is fast, percent of punctuality is high, round-the-clock running, business efficiency height because of having, and role becomes increasingly conspicuous in the communications and transportation system.In order to alleviate the pressure of transportation by railroad, satisfy the needs of national economy and social development, China is building high-speed railway energetically at present.Because the car body of bullet train is light, speed is fast; Produce during operation rise buoyancy and to face upward the moment of bowing big; Train offside wind effect is responsive; Especially at some special road sections such as especially big bridge, high embankment, hills and bend in zone, air port, very easily produce derailing, capsizing case, and then cause great casualties and tremendous economic loss.The high wind monitoring means that adopts at present is to set up several monitoring points along the railway, and wind speed wind direction sensor and collecting unit are installed, and gathers the wind speed and direction data in real time.Therefore, how to carry out gale monitoring point and lay, the validity that guarantees Monitoring Data is the important step of setting up monitor and early warning system with representative.
Because high-speed railway is the new things that China just rose in recent years, worldwide developing history is not long yet, and domestic and international research about high-speed railway gale monitoring points distributing method seldom.At present, the research of Chinese scholars with highway weather monitoring point lay, the addressing of wind energy turbine set microcosmic and atmosphere environment supervision optimization are layouted is main.In the research that highway weather monitoring point is laid, the researcher adopts qualitative analysis methods to dwindle the cloth point range earlier more, chooses the position, monitoring point in conjunction with examine on the spot and expert consulting.This method depends on researcher's experience to a great extent, and subjectivity is strong, and does not relate to the science computing method of monitoring point quantity, is difficult to judge whether existing monitoring point can satisfy road air monitoring requirement completely.The method of wind energy turbine set microcosmic addressing also is difficult to directly apply to the high-speed railway monitoring and layouts.In the wind energy turbine set addressing, researcher's multiselect is got the big position of average wind energy under the long period yardstick, therefore the equal wind power of weight analysis mean wind speed wind direction, average wind energy peace.Consider stabilization of equipment performance, avoid wind speed to change violent position.And the probability that the high-speed railway monitoring is layouted and needed the size of consideration extreme value wind speed and high wind to occur has very big difference with the addressing of wind energy turbine set microcosmic.It then is to lay a large amount of eyeballs position that atmosphere environment supervision optimization is layouted, and from the eyeball position, chooses representative optimum position through the whole bag of tricks such as correlation analysis, cluster analysis, neural network, fuzzy mathematicses again.Because high-speed railway gale monitoring cost is high, be difficult to before having confirmed the optimum position, lay the eyeball position on a large scale, so the atmosphere environment supervision points distributing method is not suitable for the laying of high-speed railway gale monitoring point.
Simultaneously; Built in China, build or several high-speed railway mileages yet to be built long; Cross over a plurality of climate zones; It is numerous to be positioned at special wind environments such as the bridge of growing up, overpass, hills and air port, mountain area along the line, and the high-speed railway wind field along the line of directly indiscriminately imitating external layout principle and method for numerical simulation analysis China possibly cause bigger error.Therefore, carry out the synthetic study of high-speed railway gale monitoring points distributing method, significant for guarantee driving safety.
Summary of the invention
The objective of the invention is to overcome the weak point that exists in the existing method, a kind of with different levels high-speed railway gale monitoring point distribution method is provided.This method is modeled as the master with fluid numerical value, and in conjunction with wind tunnel experiment, quantitative test high-speed railway strong wind probability along the line is chosen position, representational monitoring point, and the phenomenon of effectively anti-leak-stopping cloth, many cloth occurs.
Technical scheme of the present invention is following:
The method that a kind of high-speed railway gale monitoring point is laid; It is characterized in that; Through the statistical study of high-speed railway weather station along the line data, the fluid numerical simulation of strong wind probability of occurrence; In conjunction with wind tunnel experiment, realize the laying of fundamental surveillance point, interior slotting monitoring point, three different levels monitoring points of special monitoring point.
The method that a kind of high-speed railway gale monitoring point is laid comprises the steps:
(1) temperature, pressure, wind data along the line to high-speed railway and conventional on every side weather station data are carried out statistical study; Set up Two-parameter Weibull Distribution wind speed probability model; Utilize historical summary to carry out the calibration of model parameter, on the high geomorphic unit of strong wind probability of occurrence, lay the fundamental surveillance point;
(2) divide geomorphic unit; In same geomorphic unit based on the dependency relation of point-to-point transmission wind field arbitrarily along the line of railway under the topography and geomorphology source investigation complex-terrain; Set up the relevance function of strong wind probability of occurrence; And utilize the high-speed railway wind field along the line under the factor actings in conjunction such as Navier-Stokes flow equation simulation elevation, roughness of ground surface, barrier, insert the monitoring point in laying;
(3) wind field to special road section carries out numerical Simulation of High Resolution and wind tunnel experiment simulation; The strong wind frequency of occurrences is laid the special monitoring point on all greater than the position of preset frequency in numerical simulation and twice simulation of wind tunnel experiment, and wherein said special road section comprises that described special road section comprises bend, high embankment, tunnel, bealock, hills.
The present invention compares with existing method, has following advantage:
To lay the position of the least possible monitoring point in the best, make it obtain high-speed railway strong wind characteristic along the line as much as possible, guarantee that representativeness, reliability and the accuracy of Monitoring Data is purpose, proposing a kind of is main distribution method by different level with the quantitative Analysis.The present invention makes full use of statistical study, Fluid Mechanics Computation is theoretical and the advantage of multiple technologies means such as method, wind tunnel experiment; Overcoming classic method is high, the deficiencies such as subjectivity is too strong, precision of cost that the master is caused with examine on the spot, qualitative analysis; Realized under the various climate types, the laying of high-speed railway gale monitoring point under the various environmental baseline; Simulation precision is high, and the cost of layouting is low, for effective monitoring of railway gale and the safe operation of high-speed railway provide support.
Description of drawings
Fig. 1 is a high-speed railway gale monitoring point distribution method synoptic diagram;
Fig. 2 is a high-speed railway wind rose map along the line;
Fig. 3 is high-speed railway wind speed frequency distribution histogram along the line and Weibull distribution curve;
Fig. 4 is the curve of total error with variable in distance.
Embodiment
Below in conjunction with accompanying drawing the present invention is described further.
Accompanying drawing 1 is the implementation procedure that high-speed railway gale monitoring point is laid.
(1) wind speed along the line and conventional weather station on every side, wind direction data are analyzed to high-speed railway.Add up the frequency that each wind direction occurs, draw wind rose map.Fig. 2 is a high-speed railway weather station along the line wind rose map, representes the frequency that 12 wind directions occur.With 1m/s is at interval, and the frequency that each interval wind speed occurs on the statistics all directions is set up Two-parameter Weibull Distribution wind speed probability model, utilizes maximum-likelihood method to carry out the calibration of model parameter.Curve-fitting results is as shown in Figure 3, and transverse axis is represented the wind speed size, and the longitudinal axis is represented the frequency that this wind speed occurs.
The formula of Two-parameter Weibull Distribution is:
In the formula, p is the probability that wind speed equals vm/s, and k is the mould shapes parameter, and A is the model dimension parameter.
(2) serve as main according to the division geomorphic unit with elevation and increased surface covering, maximum effect radius of the interior strong wind of same geomorphic unit is got 20km, in this radius, sets up the relevance function of wind field on any two positions along the line.Step (2) is set up and further is included in maximum effect radius of confirming strong wind in the same geomorphic unit in the relevance function of strong wind probability of occurrence; The correlativity of wind speed weakens with the increase of distance gradually between 2 along the line of the railway in this scope, and the formula of relevance function is:
In the formula, q is the related coefficient of wind speed between 2 along the line of the railway, and d is the distance between 2.With the position that possesses complete meteorological data as initial point; Utilize Navier-Stokes flow equation simulation high-speed railway wind field along the line; Model parameter substitution Navier-Stokes flow equations such as length and width height with elevation, roughness of ground surface, barrier; Calculate pairing strong wind probability of occurrence of different distance and the simulation error that causes by the computed in software capabilities limits, draw simulation error-distance Curve.Simulation error-distance function and relevance function multiply each other, and draw the change curve of total error with distance, utilize the change curve of least square fitting total error with distance.In high-speed railway control, the error upper limit gets 20%.As shown in Figure 4,20% the pairing distance of the error upper limit is inserted the cloth dot spacing of monitoring point promptly on this curve.
(3) size of adjustment computational grid is carried out the simulation of high resolving power (resolution is 50 meters) to the wind field of special road sections such as bend, high embankment, tunnel, bealock, hills, calculates the railway strong wind frequency of occurrences along the line.Utilize the wind field of wind tunnel experiment simulation special road section, calculate the railway strong wind frequency of occurrences along the line.The result of calculation of contrast step (1), the described fluid simulation of step (2) and wind tunnel experiment, the strong wind frequency of occurrences is all greater than laying the special monitoring point on the position of preset frequency in twice simulation.
Claims (2)
1. the method that high-speed railway gale monitoring point is laid is characterized in that said method comprises the steps:
(1) wind speed along the line and conventional weather station on every side, wind direction data are carried out statistical study to high-speed railway; Utilize the strong wind frequency of occurrences on the boundary layer airflow modular estimate railway all kinds of topography and geomorphologies along the line unit, lay the fundamental surveillance point on greater than the geomorphic unit of preset frequency in the strong wind frequency of occurrences;
Set up Two-parameter Weibull Distribution wind speed probability model, utilize maximum-likelihood method to confirm model parameter, the formula of Two-parameter Weibull Distribution is:
In the formula, p is the probability that wind speed equals vm/s, and k is the mould shapes parameter, and v is a wind speed, and A is the model dimension parameter;
(2) divide geomorphic unit; The foundation of dividing geomorphic unit comprises elevation and increased surface covering; In same geomorphic unit,, set up the relevance function of point-to-point transmission strong wind probability of occurrence, simulation high-speed railway wind field along the line based on the dependency relation of point-to-point transmission wind field arbitrarily along the line of railway under the topography and geomorphology source investigation complex-terrain; Calculate high-speed railway strong wind probability of occurrence and simulation error along the line; Reach in overall error and to insert the monitoring point in laying on the position of the error upper limit, wherein, said overall error comprises two parts of Model Calculation error that simulation error and distance change cause greatly;
Utilize Navier-Stokes flow equation simulation high-speed railway wind field along the line; Calculate high-speed railway strong wind probability of occurrence and simulation error along the line; Draw simulation error-distance Curve, and, draw overall error with the said railway change curve of the distance of point-to-point transmission arbitrarily along the line in conjunction with the relevance function of described strong wind probability of occurrence; Utilize this curve of least square fitting, the cloth dot spacing of the pairing interpolation of estimation error upper limit monitoring point;
(3) wind field to special road section carries out numerical Simulation of High Resolution and wind tunnel experiment simulation; All greater than laying the special monitoring point on the position of preset frequency, wherein said special road section comprises bend, high embankment, tunnel, bealock, local landform to the strong wind frequency of occurrences in numerical simulation and wind tunnel experiment.
2. the method that high-speed railway gale monitoring point as claimed in claim 1 is laid; It is characterized in that: the said simulation error of step (2) is the error that is caused by the computed in software capabilities limits, and total error comprises that simulation error and distance become two parts of Model Calculation error that cause greatly.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201010506850A CN102023317B (en) | 2010-10-14 | 2010-10-14 | Method for deploying strong wind monitoring points on rapid transit railway |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201010506850A CN102023317B (en) | 2010-10-14 | 2010-10-14 | Method for deploying strong wind monitoring points on rapid transit railway |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102023317A CN102023317A (en) | 2011-04-20 |
| CN102023317B true CN102023317B (en) | 2012-09-12 |
Family
ID=43864846
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201010506850A Expired - Fee Related CN102023317B (en) | 2010-10-14 | 2010-10-14 | Method for deploying strong wind monitoring points on rapid transit railway |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102023317B (en) |
Families Citing this family (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103336860B (en) * | 2013-06-07 | 2015-08-05 | 国家电网公司 | A kind of electrical network wind speed profile drawing generating method |
| CN103675355B (en) * | 2013-11-19 | 2016-06-08 | 中国大唐集团科学技术研究院有限公司 | Anemoscope monitoring method and system |
| CN104015757B (en) * | 2014-06-09 | 2015-05-13 | 中南大学 | Railway train operation safety situation judgment method and device with multi-information integration |
| CN105740990B (en) * | 2016-02-26 | 2019-12-10 | 中铁第四勘察设计院集团有限公司 | method for selecting resident monitoring points in railway wind monitoring system |
| CN106897517B (en) * | 2017-02-22 | 2019-11-15 | 中铁二院工程集团有限责任公司 | Line of high-speed railway gale monitoring optimizes automatic search method of arranging net |
| CN108090285B (en) * | 2017-12-20 | 2021-06-01 | 中国科学院西北生态环境资源研究院 | Microclimate observation point distribution method for wind disaster monitoring of power transmission line in complex terrain |
| CN108427834A (en) * | 2018-02-13 | 2018-08-21 | 中国气象科学研究院 | Engineering typhoon fining numerical simulation system based on mesoscale model and method |
| CN109141808B (en) * | 2018-10-29 | 2020-06-09 | 广州地铁集团有限公司 | Method for deducing wind speed space along subway overhead line multipoint wind speed sensing line |
| CN109765335A (en) * | 2018-12-25 | 2019-05-17 | 北京英视睿达科技有限公司 | Method, control device and the electronic equipment of monitoring point are set in monitoring region |
| CN111079808B (en) * | 2019-12-05 | 2023-06-09 | 国网湖南省电力有限公司 | Quick wind gust prediction method and system based on weather typing |
| CN111239857B (en) * | 2020-02-18 | 2020-09-11 | 潘新民 | Strong wind forecasting method for special terrain |
| CN111880242B (en) * | 2020-07-22 | 2022-03-25 | 中国气象局气象探测中心 | Method for arranging strong wind monitoring points along high-speed rail |
| CN112348050B (en) * | 2020-09-30 | 2023-09-26 | 中国铁路上海局集团有限公司 | Anemometer arrangement method based on wind characteristics along high-speed rail |
| CN112498419B (en) * | 2020-11-25 | 2022-09-09 | 中铁第四勘察设计院集团有限公司 | Encryption method, device, equipment and storage medium |
| CN112577702B (en) * | 2020-12-09 | 2022-10-18 | 中国建筑第八工程局有限公司 | Wind environment simulation and prediction method for construction site |
| CN115936474B (en) * | 2022-10-17 | 2023-08-08 | 中南大学 | Method for setting strong wind monitoring points along high-speed railway |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101571551A (en) * | 2009-02-18 | 2009-11-04 | 中南大学 | Railway strong wind acquiring method and system |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP4882678B2 (en) * | 2006-11-06 | 2012-02-22 | 富士通株式会社 | Wind direction and wind speed monitoring method, wind direction and wind speed monitoring device |
| JP5009174B2 (en) * | 2008-01-08 | 2012-08-22 | 公益財団法人鉄道総合技術研究所 | Strong wind monitoring method and strong wind monitoring device |
-
2010
- 2010-10-14 CN CN201010506850A patent/CN102023317B/en not_active Expired - Fee Related
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101571551A (en) * | 2009-02-18 | 2009-11-04 | 中南大学 | Railway strong wind acquiring method and system |
Non-Patent Citations (3)
| Title |
|---|
| JP特开2008-116359A 2008.05.22 |
| JP特开2009-162657A 2009.07.23 |
| 王厚雄等.准高速东风型列车风速度场特性初探.《中国铁道科学》.1993,第14卷(第02期), * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102023317A (en) | 2011-04-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102023317B (en) | Method for deploying strong wind monitoring points on rapid transit railway | |
| Liu et al. | Influence of surrounding buildings on wind flow around a building predicted by CFD simulations | |
| Lubitz et al. | Wind-tunnel and field investigation of the effect of local wind direction on speed-up over hills | |
| CN103279588B (en) | Steel bridge deck Fatigue stress calculation method under vehicular load and temperature acting in conjunction | |
| CN112685965B (en) | Method and system for monitoring risk of transmission tower in typhoon | |
| Feng et al. | Computational simulations of blown sand fluxes over the surfaces of complex microtopography | |
| CN106202533A (en) | Street canyon pollutant of vehicle exhaust concentration estimating system | |
| CN106844856A (en) | Consider Field Flow Numerical Simulation method near the urban viaduct of Dynamic Traffic Flow influence | |
| Jubayer et al. | A hybrid approach for evaluating wind flow over a complex terrain | |
| KR20210050831A (en) | Real-time fine dust monitoring system and its methods | |
| Liu et al. | Aerodynamic performance analysis of trains on slope topography under crosswinds | |
| CN108090285A (en) | A kind of microclimate observation points distributing method suitable for the monitoring of complicated landform transmission line of electricity disaster caused by a windstorm | |
| Li et al. | Wind tunnel study on the morphological parameterization of building non-uniformity | |
| CN109978275A (en) | A kind of extreme wind wind speed forecasting method and system mixing CFD and deep learning | |
| CN112163381B (en) | Lateral boundary condition setting method suitable for complex terrain wind field flow numerical simulation | |
| CN112348050A (en) | Anemograph arrangement method based on wind characteristics along high-speed rail | |
| Tong et al. | Mapping the urban natural ventilation potential by hydrological simulation | |
| CN105184667A (en) | Method for dual-nested simulation of wind speed distribution of wind power plant | |
| Yazid et al. | Preliminary study on the wind flow and pollutant dispersion in an idealized Street Canyon | |
| Miao et al. | Impact assessment of urban meteorology and the atmospheric environment using urban sub-domain planning | |
| CN106897517B (en) | Line of high-speed railway gale monitoring optimizes automatic search method of arranging net | |
| CN104699906A (en) | Method of measuring spatial accessibility through vehicular trajectory data and terrain | |
| CN114154325A (en) | Method and system for evaluating steady and steady mixed wind energy resources | |
| CN108198090A (en) | A kind of power grid power transmission and distribution facility Typhoon Monitoring points distributing method | |
| Zhang et al. | Application of power grid wind monitoring data in transmission line accident warning and handling affected by typhoon |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20120912 Termination date: 20161014 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |