CN105508147A  Bending moment matching method for singlepoint fatigue loading test of wind blade  Google Patents
Bending moment matching method for singlepoint fatigue loading test of wind blade Download PDFInfo
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 CN105508147A CN105508147A CN201511004114.4A CN201511004114A CN105508147A CN 105508147 A CN105508147 A CN 105508147A CN 201511004114 A CN201511004114 A CN 201511004114A CN 105508147 A CN105508147 A CN 105508147A
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 238000011068 load Methods 0.000 title claims abstract description 34
 238000005452 bending Methods 0.000 title abstract description 12
 238000005457 optimization Methods 0.000 claims abstract description 28
 238000006467 substitution reaction Methods 0.000 claims abstract description 4
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 230000005484 gravity Effects 0.000 claims description 10
 230000005611 electricity Effects 0.000 claims description 8
 230000005284 excitation Effects 0.000 claims description 5
 230000000875 corresponding Effects 0.000 claims description 3
 238000009661 fatigue test Methods 0.000 description 6
 238000009826 distribution Methods 0.000 description 5
 230000001808 coupling Effects 0.000 description 4
 238000010168 coupling process Methods 0.000 description 4
 238000005859 coupling reaction Methods 0.000 description 4
 238000004364 calculation method Methods 0.000 description 3
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Classifications

 F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
 F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01F04
 F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
 F05B2260/00—Function
 F05B2260/83—Testing, e.g. methods, components or tools therefor

 F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
 F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01F04
 F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
 F05B2260/00—Function
 F05B2260/84—Modelling or simulation

 Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSSSECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSSREFERENCE 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 ENDUSER APPLICATIONS
 Y02B10/00—Integration of renewable energy sources in buildings
 Y02B10/30—Wind power

 Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSSSECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSSREFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
 Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
 Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
 Y02P80/00—Climate change mitigation technologies for sectorwide applications
 Y02P80/20—Climate change mitigation technologies for sectorwide applications using renewable energy
Abstract
The invention belongs to a singlepoint fatigue loading test system for a wind blade and particularly relates to a bending moment matching method for a singlepoint fatigue loading test of the wind blade. The method comprises the following steps: dispersing the blade into n dispersive parts along the wing direction according to an equivalent substitution rule; determining an actual total bending moment value mode; finally, in combination with a dichotomization method rule, aiming at a certain section, taking the minimum value of the difference of a theoretical bending moment and the actual total bending moment value as a target function from the tip of the blade, and taking the errors of the other sections as inequality constraint conditions in order to design an optimization solution algorithm based on the target function and the constraint conditions; optimizing the quantity, mass and position of added balance weights by building a mathematic model and guaranteeing that the quantity of the added balance weights is smallest. By the method disclosed by the invention, the actual test bending moment of the blade can be matched with the theoretical bending moment as far as possible on the premise that least balancing weights are added; the fatigue loading test precision of the blade is improved and can strictly reach the error requirements of industrial requirements Delta (generally 7% at present).
Description
Technical field
The present invention relates to a kind of wind electricity blade singlepoint fatigue loading test moment of flexure matching process, be particularly useful for the fatigue loading test of megawatt windpower blade, belong to the singlepoint fatigue loading pilot system of fan blade.
Background technique
Current singlepoint fatigue loading test method is one of main stream approach of wind electricity blade Fatigue test in the world.Singlepoint fatigue loading test method applies singlepointexcitation in blade profile to about 70% place usually makes itself and blade resonance to complete Fatigue test.According to IEC6140023FullScaleStructuralTestingofWindTurbineBlade standard, the theoretical moment of flexure that the actual moment of flexure of each end section of blade caused by this singlepointexcitation should provide with blade design side as far as possible matches.Be typically employed in blade surface both at home and abroad and add multiple balancing weight to ensure that the moment of flexure matching error δ in each cross section controls in certain margin of error (the usual value of this error is for 7% at present).But owing to lacking effective moment of flexure matching process, most blade testing producer is by means of only experience or simple computation, blade profile to correct position only add a balancing weight to realize the coupling of actual moment of flexure and theoretical moment of flexure, matching error is larger, the relative error in some cross section is considerably beyond 7%, the fatigue test data precision drawn thus is not high, causes the distortion of singlepoint fatigue loading experimental test result to a certain extent, is difficult to meet highprecision blade fatigue test request.Or in the paper " MW level wind electricity blade loading system key technology research. " as Zhang Lei's peace, though give calculation of Bending Moment model, but model is too simple and followup Optimization Steps is ambiguous, do not provide concrete implementation method, the Bending moment distribution data descendant drawn thus cannot verify, reliability is not high.Data according to certain blade production firm provides: the design military service phase is certain the model blade in 20 years, although have passed the test of singlepoint fatigue loading, actual life does not far reach projected life.Along with wind energy conversion system is gradually to megawattgrade highpower future development, blade dimensions increases thereupon, harsher to the requirement of the strength and stiffness of blade, and highprecision blade fatigue load test will be one of the research emphasis in crop leaf measuring field.Therefore, propose a kind of effective realitytheoretical moment of flexure matching process, the distribution precision of actual moment of flexure in test can be improved, thus improve the fatigue loading test accuracy of blade.
Summary of the invention
According to above deficiency of the prior art, the technical problem to be solved in the present invention is: the wind electricity blade singlepoint fatigue loading test moment of flexure matching process providing a kind of and can make theoretical moment of flexure and actual moment of flexure control errors between the two within δ, effectively improve the reality of bladetheoretical moment of flexure coupling.
Wind electricity blade singlepoint fatigue loading test moment of flexure matching process of the present invention, comprises the following steps:
(1) according to equivalent substitution principle by blade along the wing to being divided into n discrete portions, obtain (n+1) individual cross section, in test by fatigue loading drive unit drive blade vibration, produce excitation force simultaneously;
(2) Modling model:
Set up the actual moment of flexure model only considering blade deadweight, this model representation is
T1
_{k}for a certain cross section k of this model Leaf (k=1,2 ..., n+1) and the actual moment at place;
Set up after adding balancing weight, consider the actual moment of flexure model of drive unit weight and balancing weight weight, this model representation is
T2
_{k}for a certain cross section k of this model Leaf (k=1,2 ..., n+1) and the actual moment at place;
Obtain actual total moment of flexure model by abovementioned, this model representation is
T
_{k}＝T1
_{k}+T2
_{k}；[3]
T
_{k}for a certain cross section k of this model Leaf (k=1,2 ..., n+1) and the total moment of reality at place;
Wherein, i is cross section numbering, and j is that the balancing weight on the right of the k of cross section is numbered (if do not have balancing weight on the right of the k of cross section, j just need not number, and namely j does not exist, then T2k=0), N is the balancing weight sum of all interpolations, and p is the sum (p≤N) of the balancing weight on the right of the k of cross section, ρ
_{i}for the line mass density of each discrete portions, b
_{i}for the length of each discrete portions, L
_{ki}for end section k and ith discrete portions ρ
_{i}the distance at center of gravity place, f is blade excited frequency, y
_{i}for ρ
_{i}the amplitude at affiliated discrete portions center of gravity place, g is gravity accleration, t
_{k}for end section k is to the distance of blade root, y
_{mj}for balancing weight m
_{j}the vibration amplitude at center of gravity place, r
_{k}for fatigue loading drive unit is to the distance of end section k, M is the equivalent mass of fatigue loading drive unit, y
_{m}for the vibration amplitude at fatigue loading drive unit place, above each parameter is the given value that can measure; m
_{j}for the balancing weight quality of adding, x
_{j}for the distance of the balancing weight distance root of blade of interpolation, m
_{j}with x
_{j}for unknownvalue;
(3) T will be calculated
_{k}, the quality m of each balancing weight added
_{j}and each balancing weight is to the distance x of blade root
_{j}(i.e. the point of addition of balancing weight) is unknownvalue, and known conditions is: according to Fatigue test requirement, for arbitrary cross section k (1≤k≤n+1) of blade, the total moment T of the reality on it
_{k}with theoretical moment T
_{k}' error need control within the specific limits, that is:
T′
_{k}T
_{k}/T
_{k}≤δ(k＝1,2…,n+1)；[4]
Wherein, δ is original set value;
Be optimized according to formula [4] and solve, finally draw the number of added balancing weight and quality and position and the balancing weight number of adding is minimum.When Optimization Solution, conventional mathematical software can be adopted, as Matlab, Lindo, Lingo etc.
Be preferably as follows the method for Optimization Solution in the present invention, concrete grammar is:
1) calculate do not add balancing weight before actual total moment and the maximum cross section of theoretical moment relative error, if the distance of this crosssectional distance root of blade is
add from blade tip, first add a balancing weight (even N=1), the balancing weight added is far away apart from this cross section, and the quality of required balancing weight is less, but maximum distance can not exceed the cross section meeting error requirements; Find out actual total moment and the minimum cross section of theoretical moment relative error, if the distance of this crosssectional distance root of blade is
1. the initial position of dichotomy determination balancing weight is adopted:
According to dichotomy principle, order
get x
_{1} ^{1}for x
_{1}initial value, optional a cross section a, a=1,2 ..., n+1, by the theoretical moment T on it
_{a}' and the total moment T of reality
_{a}the minimum value of difference as objective function, using the inequality constraints condition of the difference of other crosssection error as this objective function, set up objective optimization mathematical model as follows:
minG＝T′
_{a}T
_{a}；[5]
Wherein, the j=1 in formula [5] and formula [6];
Solve m
_{1}value, if m
_{1}there is solution, then make x
_{1} ^{1}=x
_{1}, x when obtaining an interpolation balancing weight
_{1}, m
_{1}optimum value, complete optimization;
If 2. without solution, according to dichotomy principle, again make
get x
_{1} ^{2}for x
_{1}initial value, optional a cross section c, cross section c with 1. in cross section a can be same cross section, also can be different cross section, by the theoretical moment T on it
_{c}' and the total moment T of reality
_{c}the minimum value of difference as objective function, using the inequality constraints condition of the error in other cross sections as this objective function, as 1. set up objective optimization mathematical model (change the subscript a in respective formula into c, p is the number of balancing weight on the right side of the c of cross section), solve m
_{1}value, if m
_{1}there is solution, then make x
_{1} ^{2}=x
_{1}, x when obtaining an interpolation balancing weight
_{1}, m
_{1}optimum value, complete optimization;
If 3. without solution, then again according to dichotomy principle, order
circulation like this, until x when obtaining an interpolation balancing weight
_{1}, m
_{1}optimum value;
If 4. x
_{1} ^{n}level off to
(namely
ε is given according to error size) time still without solution, namely still do not meet error requirements, then need interpolation second balancing weight, and calculate its point of addition, now get x
_{1} ^{1}, x
_{1} ^{2}x
_{1} ^{n}the total moment of middle reality and the minimum location point of theoretical moment relative error as the position initial value of interpolation first balancing weight, and get the m that this location point solves in abovementioned objective optimization mathematical model
_{1}as the quality of first balancing weight, add second balancing weight afterwards;
2) calculate added first balancing weight after actual total moment and the maximum cross section of theoretical moment relative error, if the distance of this crosssectional distance root of blade is
find out actual total moment and the minimum cross section of theoretical moment relative error, if the distance of this crosssectional distance root of blade is simultaneously
according to dichotomy principle, order
then x is got
_{2} ^{1}for x
_{2}initial value, adopt as 1) in step 1. 2. 3.because the balancing weight number adopted is 2, the N=2 therefore in formula [5] and formula [6]obtain the x after interpolation two balancing weights
_{1}, m
_{1}, x
_{2}and m
_{2}optimum value; If x
_{2} ^{n}level off to
(namely
and ε is given according to error size) time still without solution, namely still do not meet error requirements, then need interpolation the 3rd balancing weight and calculate its point of addition, now, getting x
_{2} ^{1}, x
_{2} ^{2}x
_{2} ^{n}the point of addition of these two balancing weights, as the point of addition of second balancing weight, is substituted into (now N=2) in the objective optimization mathematical model of abovementioned foundation, the m solved by the total moment of middle reality and the minimum location point of theoretical moment relative error
_{1}as quality, the m of first balancing weight
_{2}as the quality of second balancing weight, add the 3rd balancing weight afterwards;
3) the Optimization Solution step of the 3rd balancing weight is added as 2), if add three balancing weights still without solution, then need interpolation the 4th ..., until add the individual balancing weight of N ' have solution, then get the point of addition point x of the N number of balancing weight solved
_{1}, x
_{2}x
_{n '}, now in the objective optimization mathematical model of abovementioned foundation, (making N=N ') solves the quality of the balancing weight corresponding to each point of addition point;
According to the method for abovementioned Optimization Solution, the number of the balancing weight added of formula [4], quality and position can be met, and the balancing weight number of adding is minimum.
The beneficial effect that the present invention is compared with prior art had is:
1, the present invention is to blade either end cross section, and the model accuracy calculating its actual Bending moment distribution is higher;
2, the present invention is directed to the quantity of added balancing weight, position and quality, give concrete calculating and optimization method, and meet the minimum number of the balancing weight added;
3, the precision of moment of flexure coupling of the present invention is high, within the theoretical moment of flexure in blade either end cross section and actual moment of flexure error can be strict controlled in δ (being generally 7% at present).
Accompanying drawing explanation
Fig. 1 is the Bending moment distribution analysis chart only considering that blade is conducted oneself with dignity;
Fig. 2 adds after balancing weight, considers the Bending moment distribution analysis chart of drive unit weight and balancing weight weight;
Fig. 3 is the theoretical moment plotted curve of certain type blade in the present embodiment;
Fig. 4 is the plotted curve of the equivalent line density of mass of certain type blade in the present embodiment;
Fig. 5 is the plotted curve of the vibration amplitude in each cross section of certain type blade in the present embodiment;
Fig. 6 is each section moment plotted curve of certain type blade under excitation force and deadweight acting in conjunction in the present embodiment;
Fig. 7 is the total moment of reality in each cross section of certain type blade in the present embodiment and the comparison diagram of theoretical moment;
Fig. 8 is the error effects figure after the total moment of reality in certain each cross section of type blade in the present embodiment mates with theoretical moment.
Embodiment
Below in conjunction with specific embodiment, the present invention is described further:
Certain blade testing center provides certain type blade that length is 40.3m, and according to equivalent substitution principle by this blade along the wing to being separated into 22 discrete portions, obtain 23 cross sections, i is cross section numbering, the length bi=1.5m of each discrete portions, table 1 gives the theoretical moment T ' in each cross section in this blade fatigue load test
_{k}, each discrete portions line mass density p
_{i}and the amplitude y at each discrete portions center of gravity place to be measured by laser testing instrument
_{i}; And drive each discrete portions to rotate generation excitation force, the mass M=700Kg of this fatigue loading drive unit, the amplitude y at its center of gravity place by fatigue loading drive unit
_{m}=0.4, it drives the vibration frequency f=0.78Hz of this blade vibration.Adopt mathematical software MatLab to be optimized in the present embodiment to solve.
Table 1
The singlepoint fatigue loading test moment of flexure matching process of certain the type blade in the present embodiment is as follows:
(1) under the excitation force of fatigue loading drive unit generation, only consider blade deadweight, table 1 data brought into formula [1]:
To discrete and formed 23 cross sections, the actual moment on it can calculate respectively, and computational process is as follows:
(2), after adding balancing weight, consider the weight of fatigue loading drive unit and the weight of balancing weight, then the actual moment in all cross sections is calculated as follows:
The balancing weight quality m added
_{j}with position x
_{j}for known variables, be expressed in matrix as:
In formula: N is the quantity of adding balancing weight.
Data in table 1 are brought into formula [2]:
Wherein: p is the sum of the balancing weight on the right of the k of cross section, p≤N; J is the balancing weight numbering on the right of the k of cross section; If do not have balancing weight on the right of the k of cross section, namely j does not exist, then j is without the need to numbering, T2
_{k}=0;
Actual moment on it can calculate respectively, and result of calculation is as follows:
Now, [T2
_{1}, T2
_{2}..., T2
_{23}] in containing unknown quantity m
_{j}, x
_{j}.
(3) the total moment of reality in all cross sections is calculated, according to formula [3]:
T
_{k}＝T1
_{k}+T2
_{k}
Can obtain:
$\left[\begin{array}{c}{T}_{1}\\ {T}_{2}\\ .\\ .\\ .\\ {T}_{23}\end{array}\right]=\left[\begin{array}{c}T{1}_{1}\\ T{1}_{2}\\ .\\ .\\ .\\ T{1}_{23}\end{array}\right]+\left[\begin{array}{c}T{2}_{1}\\ T{2}_{2}\\ .\\ .\\ .\\ T{2}_{23}\end{array}\right]$
Now, [T
_{1}, T
_{2}..., T
_{23}] in containing unknown quantity m
_{j}, x
_{j}.
(4) according to Fatigue test requirement, for arbitrary cross section k (1≤k≤23) of this blade, the total moment T of the reality on it
_{k}with theoretical moment T
_{k}' relative error δ need in the scope of control 7%, i.e. demand fulfillment formula [4]:
T′
_{k}T
_{k}/T
_{k}≤δ
Namely should meet:
$\mathrm{\δ}\×\left[\begin{array}{c}{T}_{1}\\ {T}_{2}\\ .\\ .\\ .\\ {T}_{23}\end{array}\right]\≤\left[\begin{array}{c}{T}_{1}^{\′}{T}_{1}\\ {T}_{2}^{\′}{T}_{2}\\ .\\ .\\ .\\ {T}_{23}^{\′}{T}_{23}\end{array}\right]\≤\mathrm{\δ}\×\left[\begin{array}{c}{T}_{1}\\ {T}_{2}\\ .\\ .\\ .\\ {T}_{23}\end{array}\right]$
According to formula [4] by abovementioned with unknown quantity m
_{j}, x
_{j}objective function optimize in Matlab, wherein Optimization Steps is as follows:
1) first calculate do not add balancing weight before actual total moment and the maximum sectional position of theoretical moment relative error be
all cross sections do not meet error requirements, and wherein actual total moment and the minimum sectional position of theoretical moment relative error are
${s}_{1}^{2}=40.3m,$ Order
${{x}_{1}}^{1}=({s}_{1}^{1}+{s}_{1}^{2})/2=20.15m,$ Initial value (the setting of first balancing weight is determined according to dichotomy principle
time, ε=10
^{2}, x
_{1} ^{n}level off to
):
1. first x is got
_{1} ^{1}for x
_{1}initial value, for convenience of calculating, select the minimum value of the difference of the total moment of the reality of cross section k=1 and theoretical moment as objective function, the difference of the error in other cross sections, as the inequality constraints condition of this objective function, sets up objective optimization mathematical model as follows in Matlab:
minG＝T′
_{1}T
_{1}[5]
Note: the N=1 in formula [5], formula [6], p are the number (p≤N) of balancing weight on the right of the k of cross section;
2. result of calculation display without separating, then continues step.
2. according to the initial position of dichotomy principle again balancing weight, then x
_{1} ^{2}=30.23m, 1. sets up objective optimization mathematical model as step and solves m in Matlab
_{1}value, result still show without separate, then continue step 3..
3. the initial position 2. redefining balancing weight as step is optimized down successively, and result all shows without separating, then continue step 4..
4. when
(i.e. x
_{1} ^{n}level off to
) time still do not meet error requirements, then need interpolation second balancing weight and calculate its point of addition, now, getting x
_{1} ^{1}, x
_{1} ^{2}x
_{1} ^{14}the total moment of middle reality and the minimum location point (x of theoretical moment relative error
_{1} ^{5}=38.59m) as the position initial value adding first balancing weight, m
_{1}=417kg, as the quality of first balancing weight, continues step 2), add second balancing weight.
2) calculate added first balancing weight after the actual total moment cross section maximum with theoretical moment relative error, it is apart from the distance of root of blade
to find out after having added first balancing weight the cross section that actual total moment is minimum with theoretical moment relative error, it is apart from the distance of root of blade simultaneously
then
according to dichotomy principle, get x
_{2} ^{1}for x
_{2}initial value, adopt as 1) in step 1. 2. 3. (note: the N=2 in formula [5], formula [6]), result all show without separate.When
time still do not meet error requirements, then need interpolation the 3rd balancing weight and calculate its point of addition.Now, x is got
_{2} ^{1}, x
_{2} ^{2}x
_{2} ^{10}the total moment of middle reality and the minimum location point x of theoretical moment relative error
_{2} ^{6}=32.48m as the point of addition of second balancing weight, and gets the location point x of abovementioned two balancing weights
_{1}=38.59m, x
_{2}the m that=32.48m solves in Matlab
_{1}=349.4kg as the quality of first balancing weight, m
_{2}=377kg, as the quality of second balancing weight, continues 3), add the 3rd balancing weight.
3) the Optimization Solution step of the 3rd balancing weight is added as 2), solve the point of addition point x of the 3rd balancing weight
_{3}=21.5m, but still do not meet error requirements, then need interpolation the 4th balancing weight, and step is with 2) solve the point of addition point x of the 4th balancing weight
_{4}=10.5m, the quality that now can solve the balancing weight corresponding to four point of addition points is as follows:
x
_{1}＝38.59m，m
_{1}＝330kg
x
_{2}＝32.48m，m
_{2}＝336kg
x
_{3}＝21.5m，m
_{3}＝170kg
x
_{4}＝10.5m，m
_{4}＝90kg
Namely balancing weight number is minimum is that four relative errors that can meet actual total moment and theoretical moment are within 7%.
Above data are brought into formula [3], calculate the total moment of reality adding each cross section after balancing weight, and by this reality always moment and theoretical moment compare, draw the percentage error of the two, specifically as shown in table 2:
Table 2
As can be seen from table 2 also, high according to the precision of the moment of flexure coupling of blade singlepoint fatigue loading of the present invention test moment of flexure matching process gained, the theoretical moment in the arbitrary cross section of blade and the error of the total moment of reality can be strict controlled within required 7%.
Claims (2)
1. a wind electricity blade singlepoint fatigue loading test moment of flexure matching process, is characterized in that: comprise the following steps:
(1) according to equivalent substitution principle by blade along the wing to being divided into n discrete portions, obtain (n+1) individual cross section, in test by fatigue loading drive unit drive blade vibration, produce excitation force simultaneously;
(2) Modling model:
Set up the actual moment of flexure model only considering blade deadweight, this model representation is
t1
_{k}for a certain cross section k of this model Leaf (k=1,2 ..., n+1) and the actual moment at place;
Set up after adding balancing weight, consider the actual moment of flexure model of drive unit weight and balancing weight weight, this model representation is
$T{2}_{k}={\mathrm{\Σ}}_{j=1}^{p}{m}_{j}({x}_{j}{t}_{k})\[{\left(2\mathrm{\π}f\right)}^{2}{y}_{mj}+g\]+{\mathrm{Mr}}_{k}\[{\left(2\mathrm{\π}f\right)}^{2}{y}_{M}+g\],$ T2
_{k}for a certain cross section k of this model Leaf (k=1,2 ..., n+1) and the actual moment at place;
Obtain actual total moment of flexure model by abovementioned, this model representation is T
_{k}=T1
_{k}+ T2
_{k}, T
_{k}for a certain cross section k of this model Leaf (k=1,2 ..., n+1) and the total moment of reality at place;
Wherein, i is cross section numbering, and j is the balancing weight numbering on the right of the k of cross section, and N is the balancing weight sum of all interpolations, and p is the sum (p≤N) of the balancing weight on the right of the k of cross section, ρ
_{i}for the line mass density of each discrete portions, b
_{i}for the length of each discrete portions, L
_{ki}for end section k and ith discrete portions ρ
_{i}the distance at center of gravity place, f is blade excited frequency, y
_{i}for ρ
_{i}the amplitude at affiliated discrete portions center of gravity place, g is gravity accleration, t
_{k}for end section k is to the distance of blade root, y
_{mj}for balancing weight m
_{j}the vibration amplitude at center of gravity place, r
_{k}for fatigue loading drive unit is to the distance of end section k, M is the equivalent mass of fatigue loading drive unit, y
_{m}for the vibration amplitude at fatigue loading drive unit place, above each parameter is the given value that can measure; m
_{j}for the balancing weight quality of adding, x
_{j}for the distance of the balancing weight distance root of blade of interpolation, m
_{j}with x
_{j}for unknownvalue;
(3) basis  T '
_{k}T
_{k}/T
_{k}≤ δ is optimized and solves, wherein, k=1,2 ..., n+1, δ are original set value, finally draw the number of added balancing weight and quality and position and the balancing weight number of adding is minimum.
2. wind electricity blade singlepoint fatigue loading test moment of flexure matching process according to claim 1, is characterized in that: the method for described Optimization Solution is as follows:
1) calculate do not add balancing weight before actual total moment and the maximum cross section of theoretical moment relative error, if the distance of this crosssectional distance root of blade is
find out actual total moment and the minimum cross section of theoretical moment relative error, if the distance of this crosssectional distance root of blade is simultaneously
1. the initial value of dichotomy determination balancing weight point of addition is adopted:
According to dichotomy principle, order
get
for x
_{1}initial value, optional a cross section a, a=1,2 ..., n+1, by the theoretical moment T ' on it
_{a}moment T total with reality
_{a}the minimum value of difference as objective function, using the inequality constraints condition of the difference of other crosssection error as this objective function, set up objective optimization mathematical model as follows:
N＝1；
Solve m
_{1}value, if m
_{1}there is solution, then make x
_{1} ^{1}=x
_{1}, x when obtaining an interpolation balancing weight
_{1}, m
_{1}optimum value, complete optimization;
If 2. without solution, according to dichotomy principle, again make
get x
_{1} ^{2}for x
_{1}initial value, an optional cross section c (cross section c with 1. in cross section a can be same cross section, also can be different cross section), by the theoretical moment T on it
_{c}' and the total moment T of reality
_{c}the minimum value of difference as objective function, using the inequality constraints condition of the difference of other crosssection error as this objective function, as 1. set up objective optimization mathematical model, solve m
_{1}value, if m
_{1}there is solution, then make x
_{1} ^{2}=x
_{1}, x when obtaining an interpolation balancing weight
_{1}, m
_{1}optimum value, complete optimization;
If 3. without solution, then again according to dichotomy principle, order
circulation like this, until x when obtaining an interpolation balancing weight
_{1}, m
_{1}optimum value;
If 4. x
_{1} ^{n}level off to
time still without solution, then need interpolation second balancing weight, and calculate its point of addition, now get x
_{1} ^{1}, x
_{1} ^{2}x
_{1} ^{n}the total moment of middle reality and the minimum location point of theoretical moment relative error as the position initial value of interpolation first balancing weight, and get the m that this location point solves in abovementioned objective optimization mathematical model
_{1}as the quality of first balancing weight, add second balancing weight afterwards;
2) calculate added first balancing weight after actual total moment and the maximum cross section of theoretical moment relative error, if the distance of this crosssectional distance root of blade is
find out actual total moment and the minimum cross section of theoretical moment relative error, if the distance of this crosssectional distance root of blade is simultaneously
according to dichotomy principle, order
then x is got
_{2} ^{1}for x
_{2}initial value, make N=2, adopt as 1) in step 1. 2. 3. obtain the x after interpolation two balancing weights
_{1}, m
_{1}, x
_{2}and m
_{2}optimum value; If x
_{2} ^{n}level off to
time still without solution, then need interpolation the 3rd balancing weight and calculate its point of addition, now, getting x
_{2} ^{1}, x
_{2} ^{2}x
_{2} ^{n}the point of addition of these two balancing weights, as the point of addition of second balancing weight, is substituted into (now N=2) in the objective optimization mathematical model of abovementioned foundation, the m solved by the total moment of middle reality and the minimum location point of theoretical moment relative error
_{1}as the quality of first balancing weight, m
_{2}as the quality of second balancing weight, add the 3rd balancing weight afterwards;
3) the Optimization Solution step of the 3rd balancing weight is added as 2), if add three balancing weights still without solution, then need interpolation the 4th ... until add the individual balancing weight of N ' to meet error requirements, then get the point of addition point x of the individual balancing weight of the N ' solved
_{1}, x
_{2}x
_{n '}, then in the objective optimization mathematical model of abovementioned foundation, (now N=N ') solves the quality of the balancing weight corresponding to each point of addition point;
According to the method for abovementioned Optimization Solution, the number of the balancing weight added of requirement, quality and position can be met, and the balancing weight number of adding is minimum.
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CN109715939A (en) *  20160913  20190503  福斯4X股份有限公司  Method and apparatus for determining the load on wind turbine tower 
WO2019178974A1 (en) *  20180323  20190926  北京金风慧能技术有限公司  Fatigue damage monitoring method for blade of winddriven generator, and electronic device and storage medium 
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CN102004838A (en) *  20101217  20110406  中国航天空气动力技术研究院  Method for determining wind turbine blade structure based on finite difference method 
CN202768249U (en) *  20120803  20130306  国电联合动力技术有限公司  Wind generation set control system based on pneumatic torque calculation model 
WO2014121800A1 (en) *  20130208  20140814  Vestas Wind Systems A/S  Model based controller for a wind turbine generator 
CN104732060A (en) *  20150119  20150624  湖南科技大学  Online identification method for multiple loads on blades of large wind power generation set 

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CN102004838A (en) *  20101217  20110406  中国航天空气动力技术研究院  Method for determining wind turbine blade structure based on finite difference method 
CN202768249U (en) *  20120803  20130306  国电联合动力技术有限公司  Wind generation set control system based on pneumatic torque calculation model 
WO2014121800A1 (en) *  20130208  20140814  Vestas Wind Systems A/S  Model based controller for a wind turbine generator 
CN104732060A (en) *  20150119  20150624  湖南科技大学  Online identification method for multiple loads on blades of large wind power generation set 
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CN109715939A (en) *  20160913  20190503  福斯4X股份有限公司  Method and apparatus for determining the load on wind turbine tower 
WO2019178974A1 (en) *  20180323  20190926  北京金风慧能技术有限公司  Fatigue damage monitoring method for blade of winddriven generator, and electronic device and storage medium 
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