CN102721523A - Method for establishing interval wind spectrum model - Google Patents

Method for establishing interval wind spectrum model Download PDF

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CN102721523A
CN102721523A CN201210172732XA CN201210172732A CN102721523A CN 102721523 A CN102721523 A CN 102721523A CN 201210172732X A CN201210172732X A CN 201210172732XA CN 201210172732 A CN201210172732 A CN 201210172732A CN 102721523 A CN102721523 A CN 102721523A
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wind
spectrum model
actual measurement
interval
wind spectrum
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王浩
程怀宇
郭彤
吴明明
王龙花
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Southeast University
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Abstract

The invention relates to a method for establishing an interval wind spectrum model and aims to solve the problem that an existing single curve wind spectrum model cannot show the randomness and the difference of the typhoon every time, so that the simulated wind spectrum model can comprise various wind environments in which structures are positioned. The method comprises the following steps of: firstly, obtaining an actual measurement wind spectrum model by carrying out power spectral analysis on a great amount of wind characteristic actual measurement data; secondly, finding out each maximum peak point and minimum peak point of the actual measurement wind spectrum model in a frequency domain, wherein the peak points correspond to different frequency values; and finally, fitting an upper limit spectral curve of the interval wind spectrum model according to all the maximum peak points and fitting a lower limit spectral curve of the interval wind spectrum model according to all the minimum peak points. Obviously, the interval wind spectrum model can obtain an analysis result capable of reflecting a more real condition and has obvious advancement and reliability, and thus, the interval wind spectrum model established by the method can guide the development tendency of the wind spectrum model in the future and can more accurately guide the wind-resistant design of the engineering structure.

Description

A kind of method for building up of interval wind spectrum model
Technical field
The present invention relates to a kind of interval wind spectrum model method for building up, be particularly useful in the engineering structure Wind resistant analysis, obtain the residing interval of wind spectrum model in works place based on field actual measurement results.
Background technology
Disaster caused by a windstorm be take place in the disaster the most frequent a kind of, huge by its casualties that causes and economic loss.Calculate that by German statistical data world's disaster caused by a windstorm causes annual with a toll of 137.7 hundred million dollars.Add in recent years, Global climate change is bigger, and it is rampant more that typhoon seems.The characteristic of research wind load and wind can strengthen the wind loading rating of structure to the effect of structure, reduce the disaster caused by a windstorm loss, thereby have very important meaning.
The engineering structure wind characteristic mainly comprises average wind characteristic and fluctuating wind characteristic.Because wind spectrum model can reflect accurately that each frequency content is made the size of contribution in the fluctuating wind, thereby is parameter main in the fluctuating wind characteristic.The field measurement of near-earth boundary layer high wind characteristic can obtain wind environment the most directly, the most real data, thereby be the most effectual way of grasping the somewhere wind characteristic.Also all match obtains existing famous wind spectrum model according to field actual measurement results.More than 90 the high wind record match that professor Davenport just once recorded according to different location, differing heights place in the world obtains level pulsation wind speed spectrum.
In recent years, along with to the continuous attention of monitoring structural health conditions and the raising of engineering structure measuring technology level, on a lot of large bridges, health monitoring systems has been installed both at home and abroad.Comprise Foyle beam bridge and Flintshire cable-stayed bridge of the Skarnsunder cable-stayed bridge of Japanese alum strait Bridge, Norway, the Sunshine Skyway cable-stayed bridge of the U.S., Canadian Confedration beam bridge, Britain etc. abroad.China comprises the blue or green Ma Qiao in Hong Kong, moistens and raise bridge, Jiangyin bridge, Shanghai Xu Pu bridge, Lu Pu bridge, Nanjing Yangtze River Bridge, yangtze river in nanjing two bridges, the Yellow River, Binzhou highway bridge etc.These monitoring systems are set up reasonable wind spectrum model effective means are provided for grasping local wind characteristic.
Because the influence of factors such as the randomness of wind characteristic wind-engaging, geographic position, the wind spectrum model otherness of at every turn surveying typhoon is very big, and this has obtained checking in long-term site-test analysis.Yet several kinds of pulsation wind speed power spectrum at present commonly used such as Davenport spectrum, Kaimal spectrum, Karman spectrum and Panofsky spectrum all are single curves, can't embody the randomness and the otherness of each typhoon.Therefore; In order to embody the typhoon characteristic in bridge site district better; The wind spectrum model of being set up needs to reflect the randomness of typhoon that so that the wind load that simulates can be more reliable, strong/typhoon is more reasonable as the structures under wind design in control load area.
Summary of the invention
Technical matters: the method for building up that the objective of the invention is to create a kind of interval wind spectrum model based on field actual measurement results; This technology is incorporated into the notion in interval in the middle of the foundation of wind spectrum model; Solved existing single curve wind spectrum model to a great extent and can't embody the randomness of each typhoon and the problem of otherness, the interval wind spectrum model that simulates can comprise the residing all kinds of wind environments of works.
Technical scheme: to the problems referred to above, the present invention at first obtains to survey wind spectrum model through a large amount of wind characteristic measured datas is carried out power spectrumanalysis; Secondly in frequency domain, find out each peak point of actual measurement wind spectrum model, these peak points comprise maximal peak point and minimum peak point, corresponding to different frequency values; Simulate the upper limit of interval wind spectrum model at last according to all maximal peak point, simulate the lower limit of interval wind spectrum model according to all minimum peak points.It is following to address the above problem the technical scheme flow process that is adopted:
The first step: carry out a large amount of violent typhoon field measurements:
Measurement method has two kinds, and a kind of is during typhoon arrives, and estimates typhoon time of arrival, and anemoscope is placed the span centre or the cat head of Longspan Bridge, and the adjustment frequency acquisition carries out the collection of wind speed and direction data; Another kind is through being installed in structural healthy monitoring system---the anemoscope among the SHMS carries out the collection of wind speed and direction data, and transmission system is sent to monitoring center with the data of acquisition system collection;
Second step: actual measurement wind speed and direction data are carried out power spectrumanalysis, obtain the actual measurement wind spectrum model:
Air speed data sample to collecting carries out analyzing and processing, selects the bigger than normal and subsample stably of one section wind speed, based on matlab large data process software; Adopt power spectral density estimation method, write the power spectrum density calculation procedure and calculate, obtain the power spectrum density of actual measurement air speed data; With the x axle is frequency; The y axle is a power spectrum density, and curve plotting is the wind spectrum model of surveying air speed data;
The 3rd step: each peak point of in frequency domain, finding out all actual measurement wind spectrum models:
The actual measurement wind spectrum model all is the very big curve that fluctuates, and all there is a series of peak point in every curve, and these peak points comprise maximal peak point and minimum peak point, corresponding to different frequency values;
The 4th step:, adopt nonlinear least square method to carry out match respectively, to obtain the bound of interval wind spectrum model to the maximal peak point and the minimum peak point of wind spectrum model;
To each segment wind spectrum model, still the down wind power spectrum expression formula of code requirement regulation is carried out match, that is:
n S u / ( u * ) 2 = a f z / ( 1 + Bf z 1 / m ) Cm Formula 1
f z = Nz / U ‾ ( z ) Formula 2
In the formula, S uBe power spectrum density, u *Be air-flow frictional resistance speed, f zBe not peaceful coordinate,
Figure BDA00001696087700032
Be mean wind speed, z is an overhead height of anemoscope, and n is the ripple frequency of wind, and c gets 5/3, and a, b and m are for fitting parameter;
Adopt nonlinear least square method commonly used in the fit procedure, each section match gained parameter a, b and m have nothing in common with each other, and obtain the interval wind spectrum model based on the actual measurement wind characteristic at last.
Beneficial effect: prerequisite and basis that three-dimensional fluctuating wind field stimulation is the wind induced structural vibration response analysis, wind spectrum model then are the prerequisite and the bases of three-dimensional fluctuating wind field stimulation, thereby most important.In order to carry out structures under wind design and research effectively reliably, just must set up wind spectrum model accurately and reliably based on the actual measurement wind characteristic of locality, wherein must be able to consider the randomness and the otherness of wind.This patent is incorporated into the notion in interval in the middle of the foundation of wind spectrum model; Solve existing single curve wind spectrum model and can't embody the randomness of each typhoon and the problem of otherness; The interval wind spectrum model of gained can comprise the residing all kinds of wind environments of works, thereby can obtain to reflect more the analysis result of actual conditions.Because this patent has tangible advance and reliability, thereby will guide the development trend of following wind spectrum model, is used widely in the structures under wind field in future.
Description of drawings
The interval wind spectrum model of Fig. 1 set up process flow diagram,
Fig. 2 repeatedly surveys the comparison diagram of wind spectrum model and Kaimal spectrum,
Fig. 3 repeatedly surveys the comparison diagram of wind spectrum model and Kaimal spectrum and interval match spectrum.
Embodiment
According to technique scheme, comprise following 4 steps based on the foundation technology and the implementation procedure thereof of interval wind spectrum model of actual measurement wind characteristic:
1) during violent typhoon, carries out by force a large amount of/typhoon field measurement;
The wind characteristic measurement method has two kinds, a kind of be annual typhoon during, through paying close attention to weather forecast; Estimate typhoon through the on-the-spot time of works, ready in advance, carry fine measuring instrument-anemoscope and rush to the scene and install; According to the characteristic of works, select suitable measuring position, be generally span centre or cat head to the long-span bridge girder construction; With anemoscope and support is in place and carry out the adjustment of anemoscope height (or stretching out from the works surface distance), wind direction; Make the wind sample of measurement not disturbed by works, the zero degree of adjustment anemoscope is a direct north, through transmission line anemoscope is linked to each other with collecting device and carries out the collection of wind speed and direction data as far as possible; Consider the anemoscope model and gather requirement, need the SF of adjustment collecting device; Another kind is through being installed in structural healthy monitoring system---the anemoscope among the SHMS carries out the collection of wind speed and direction data; The installation method and the front of anemoscope are similar; Data acquisition is to realize through data acquisition system (DAS) in the health monitoring systems and data transmission system; Transmission system is sent to monitoring center with the data of acquisition system collection, for our Treatment Analysis data are provided convenience.
2) actual measurement wind characteristic data are carried out power spectrumanalysis, obtain the actual measurement wind spectrum model;
With the strong/typhoon wind speed and direction data sample that collects; Through selecting, rejecting; Select one section wind speed to carry out analysis of spectrum than big and the more stable wind data subsample of wind direction; Based on matlab large data process software, adopt the PSD power spectral density estimation method to write calculation procedure, obtain the actual measurement wind spectrum model of each typhoon.
3) in frequency domain, find out each peak point that all survey wind spectrum models;
Through checking and analyzing; Find the flex point on the actual measurement wind spectrum model curve, concrete grammar is: the first step, will survey the local amplification of wind spectrum model curve; Confirm the approximate location of each peak point; Second step is according to the approximate location of peak point, through the Accurate Analysis of the horizontal ordinate of wind spectrum model being confirmed the particular location of each peak point.
4), adopt nonlinear least square method to carry out match respectively to maximal peak point and minimum peak point.
For above-mentioned 4 steps are described more clearly, drawn the process flow diagram of setting up of interval wind spectrum model, as shown in Figure 1.Be the embodiment that example is introduced this patent with 4 typhoons raising bridge bridge site district through profit at present, specific as follows:
Profit is raised bridge and is built up in 2005, owing to be located in the Coastal Area in Eastern China area, the violent typhoon process is all arranged every year.In recent years, when existing typhoon " Mai Sha ", " card is exerted ", " Sang Mei ", " Wei Pa ", " phoenix " and profit such as " sea-gull " process were raised bridge bridge site district, the anemoclinograph of installing among this bridge SHMS had write down this high wind sample in bridge site district.It is carried out power spectrumanalysis, and obtaining surveying profit, to raise bridge site district down wind turbulent flow power spectral density function as shown in Figure 2 with the contrast that Kaimal composes.
According to above-mentioned peak picking method, Fig. 2 is analyzed, find whole peak points.To maximal peak point and minimum peak point, select expression formula shown in formula (1) and the formula (2) for use, adopt nonlinear least square method to carry out match respectively.Obtain the upper limit spectral curve of interval wind spectrum model by maximal peak point, obtain the lower limit spectral curve of interval wind spectrum model by the minimum peak point, so far, interval wind spectrum model is set up and is finished, and sees Fig. 3.Obviously, the interval wind spectrum model of gained can comprise the randomness and the otherness of each typhoon.
After obtaining interval wind spectrum model; Just can utilize upper limit spectral curve and lower limit spectral curve to simulate the three-dimensional pulsation wind field in bridge site district respectively; Wind field by upper limit spectral curve simulation gained can calculate the higher limit of structure wind-induced vibration response, and can calculate the lower limit that the structure wind-induced vibration responds by the wind field of lower limit spectral curve simulation gained.Therefore, the structural response that is calculated gained by interval wind spectrum model also is an interval, rather than certain concrete response.Be that response of structure can change in this is interval, obviously more reasonable.Along with the structure wind-induced vibration develops towards the direction that becomes more meticulous, the rationality of interval wind spectrum model will further obtain embodying.

Claims (1)

1. the method for building up of an interval wind spectrum model is characterized in that this method may further comprise the steps:
The first step: carry out a large amount of violent typhoon field measurements:
Measurement method has two kinds, and a kind of is during typhoon arrives, and estimates typhoon time of arrival, and anemoscope is placed the span centre or the cat head of Longspan Bridge, and the adjustment frequency acquisition carries out the collection of wind speed and direction data; Another kind is through being installed in structural healthy monitoring system---the anemoscope among the SHMS carries out the collection of wind speed and direction data, and transmission system is sent to monitoring center with the data of acquisition system collection;
Second step: actual measurement wind speed and direction data are carried out power spectrumanalysis, obtain the actual measurement wind spectrum model:
Air speed data sample to collecting carries out analyzing and processing, selects the bigger than normal and subsample stably of one section wind speed, based on matlab large data process software; Adopt power spectral density estimation method, write the power spectrum density calculation procedure and calculate, obtain the power spectrum density of actual measurement air speed data; With the x axle is frequency; The y axle is a power spectrum density, and curve plotting is the wind spectrum model of surveying air speed data;
The 3rd step: each peak point of in frequency domain, finding out all actual measurement wind spectrum models:
The actual measurement wind spectrum model all is the very big curve that fluctuates, and all there is a series of peak point in every curve, and these peak points comprise maximal peak point and minimum peak point, corresponding to different frequency values;
The 4th step:, adopt nonlinear least square method to carry out match respectively, to obtain the bound of interval wind spectrum model to the maximal peak point and the minimum peak point of wind spectrum model;
To each segment wind spectrum model, still the down wind power spectrum expression formula of code requirement regulation is carried out match, that is:
NS u / ( u * ) 2 = Af z / ( 1 + Bf z 1 / m ) Cm Formula 1
f z = Nz / U ‾ ( z ) Formula 2
In the formula, S uBe power spectrum density, u *Be air-flow frictional resistance speed, f zBe not peaceful coordinate,
Figure FDA00001696087600013
Be mean wind speed, z is an overhead height of anemoscope, and n is the ripple frequency of wind, and c gets 5/3, and a, b and m are for fitting parameter;
Adopt nonlinear least square method commonly used in the fit procedure, each section match gained parameter a, b and m have nothing in common with each other, and obtain the interval wind spectrum model based on the actual measurement wind characteristic at last.
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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105629237A (en) * 2015-12-25 2016-06-01 中国航天空气动力技术研究院 Wind field risk assessment method through airborne radar
CN105675913A (en) * 2016-01-20 2016-06-15 肖小玉 Intelligent machine for forming foundation pile of bridge pier
CN105699041A (en) * 2016-01-20 2016-06-22 张健敏 Intelligent sea bridge pier
CN106295159A (en) * 2016-08-04 2017-01-04 哈尔滨工业大学 A kind of wind induced structural vibration based on auto-correlation function responds efficient frequency domain estimation method
CN107180126A (en) * 2017-04-24 2017-09-19 河海大学 A kind of bridge wind shake monitoring sensor arrangement and wind vibration response reconstructing method
CN111929027A (en) * 2020-08-03 2020-11-13 中交天津港湾工程研究院有限公司 Laboratory wind spectrum simulation method

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101476988A (en) * 2009-01-05 2009-07-08 东南大学 Fine simulation method of wind spectrum model
JP2010271058A (en) * 2009-05-19 2010-12-02 Mitsubishi Electric Corp Wind measuring device
CN102323441A (en) * 2011-06-09 2012-01-18 东南大学 A kind of signal processing method of wireless anemoscope

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101476988A (en) * 2009-01-05 2009-07-08 东南大学 Fine simulation method of wind spectrum model
JP2010271058A (en) * 2009-05-19 2010-12-02 Mitsubishi Electric Corp Wind measuring device
CN102323441A (en) * 2011-06-09 2012-01-18 东南大学 A kind of signal processing method of wireless anemoscope

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
晏致涛: "大跨度中承式拱桥的耦合频域抖振分析", 《华南理工大学学报》 *
王浩等: "基于规范及实测风谱的苏通大桥抖振响应对比研究", 《土木工程学报》 *
谢以顺等: "润扬悬索桥桥址区实测强风特性的对比研究", 《空气动力学学报》 *

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105629237A (en) * 2015-12-25 2016-06-01 中国航天空气动力技术研究院 Wind field risk assessment method through airborne radar
CN105675913A (en) * 2016-01-20 2016-06-15 肖小玉 Intelligent machine for forming foundation pile of bridge pier
CN105699041A (en) * 2016-01-20 2016-06-22 张健敏 Intelligent sea bridge pier
CN106295159A (en) * 2016-08-04 2017-01-04 哈尔滨工业大学 A kind of wind induced structural vibration based on auto-correlation function responds efficient frequency domain estimation method
CN106295159B (en) * 2016-08-04 2018-11-02 哈尔滨工业大学 A kind of efficient frequency domain estimation method of wind induced structural vibration response based on auto-correlation function
CN107180126A (en) * 2017-04-24 2017-09-19 河海大学 A kind of bridge wind shake monitoring sensor arrangement and wind vibration response reconstructing method
CN107180126B (en) * 2017-04-24 2020-02-18 河海大学 Bridge wind vibration monitoring sensor arrangement and wind vibration response reconstruction method
CN111929027A (en) * 2020-08-03 2020-11-13 中交天津港湾工程研究院有限公司 Laboratory wind spectrum simulation method

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