CN106600066A - SCADA data-based wind driven generator gearbox fatigue life estimation method - Google Patents
SCADA data-based wind driven generator gearbox fatigue life estimation method Download PDFInfo
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- CN106600066A CN106600066A CN201611175646.9A CN201611175646A CN106600066A CN 106600066 A CN106600066 A CN 106600066A CN 201611175646 A CN201611175646 A CN 201611175646A CN 106600066 A CN106600066 A CN 106600066A
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- G—PHYSICS
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
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Abstract
The invention relates to an SCADA data-based wind driven generator gearbox fatigue life estimation method. The method includes the following steps that: SCADA data are processed, so that average wind speed and turbulence degree can be obtained, and a wind speed time sequence with short time intervals is obtained through restoration by using the Von Karman wind speed model according to hub height, the average wind speed and the turbulence degree; the wind speed time sequence is transformed into an impeller torque time sequence, the stress time sequence of an interior transmission component of a gearbox is obtained through calculation by using a wind driven generator gearbox kinetic model according to the impeller torque time sequence, a rain-flow counting method is adopted to process the stress time sequence, so that a stress spectrum can be obtained, and the Goodman linear equation is adopted to correct stress magnitude in the stress spectrum and a corresponding cycle index; and the cumulative fatigue damage of the gearbox is calculated through using a fatigue cumulative damage calculation method according to the corrected stress spectrum and the S-N curve of a motor gearbox gear. The method of the invention has the advantages of high sensitivity, high reliability and low cost.
Description
Technical field
The invention belongs to technical field of wind power generation, and in particular to a kind of gear of wind driven generator based on SCADA data
Case fatigue life estimation method.
Background technology
Common wind-driven generator using the installation pattern of trunnion axis, is turned wind wheel by powerful raising speed gear-box
Speed brings up to the generating rotating speed matched with rear end generator.The presence of gear-box causes the frame for movement of wind-driven generator more multiple
Miscellaneous, most of wind power generating sets put into operation after certain time limit, and mechanical breakdown starts to take place frequently.Effectively assess wind-power electricity generation
Machine box portion is lost situation, rational gear-box repair schedule can be provided for operator of wind power plant, in gear-box
The suitable time is arranged to be safeguarded to gear-box or changed before failure, it is ensured that the benefit of wind energy turbine set.
When the means at present, being monitored to wind-driven generator wheel-box running status are mainly run by gear-box
Vibration state or operating temperature are estimated to its health status.The current level of vibration of such method collection gear-box or lubrication
Oil temperature, obtains the level of vibration or lubricating oil temperature size at the spike vibration frequency of gear-box, the work shape to gear-box
State is estimated.Gearbox parts are believed due to the failure produced by fatigue in its early period of origination, vibration signal or lubricating oil temperature
Number ANOMALOUS VARIATIONS it is generally fainter, therefore, changed to realize what is monitored according to the current vibration of gear-box and temperature signal
Method cannot make effectively judgement to the source of trouble.
The content of the invention
The present invention proposes a kind of wind-driven generator wheel-box fatigue life estimation method based on SCADA data, with height
The characteristics of sensitivity, high confidence level and low cost.
In order to solve above-mentioned technical problem, it is tired that the present invention provides a kind of wind-driven generator wheel-box based on SCADA data
Labor life estimation method, step is as follows：
Step one, carries out processing acquisition mean wind speed and turbulivity to SCADA data；According to hub height, mean wind speed,
Turbulivity, using Von Karman Wind speed models, restores the wind speed time series of short time interval；
Step 2, by wind speed time series impeller torque time series is converted into, and is used according to impeller torque time series
Wind-driven generator wheel-box kinetic model, calculates the stress time sequence for obtaining gear-box internal transmission part；Using rain stream
Counting method is processed stress time series, obtains classification and the corresponding cycle-index of the classification of stress intensity, i.e., should
Power is composed；The stress intensity inside stress spectra and corresponding cycle-index are modified using Goodman linear equations；
Step 3, according to revised stress spectra and the S-N curves of motor gearbox gear, using Cumulative Fatigue Damage
Computational methods, calculate the accumulative fatigue damage of gear-box.
In step one, the wind speed time series is in 10min, at intervals of the wind speed time series of 0.1s.
In step one, the Von Karman Wind speed models are：
In formula,Be wind speed on longitudinal component from frequency spectrum, f is the frequency of wind speed change, σuFor wind speed change
Standard deviation；For dimensionless frequency parameter, xLuFor the length dimension of turbulent flow longitudinal component,For mean wind speed；H sends out for wind-force
Motor wheel hub apart from ground height, h1For atmospheric boundary layer thickness；Parametera、β1、β2And F1Difference is as follows,
A=0.535+2.76 (0.138-A)0.68
A=0.115 [1+0.315 (1-h/h1)0.68]2/3
β1=2.357a-0.761
β2=1- β1
In step 2, using wind-driven generator wheel-box kinetic model, calculate and obtain gear-box internal transmission part
During stress time sequence, using Newmark method motor gearbox kinetic model is solved..
Compared with prior art, its remarkable advantage is that the present invention is produced using in wind-driven generator running to the present invention
Raw SCADA data, calculates the accumulative fatigue damage of gear-box, and the residual life to gear-box carries out quantum chemical method, pair event
The judgement in barrier source has higher sensitivity and confidence level, while also the life-span for gear calculates and status monitoring provides one
The solution of low cost；The present invention adopts the method to calculate gear-box fatigue life to comment gear-box health status
Estimate, can be applied not only to the monitoring of gear-box health status, the design of wind-driven generator wheel-box can also be applied to.
Description of the drawings
Fig. 1 is the inventive method schematic flow sheet；
Fig. 2 is the handling process schematic diagram of SCADA data in the inventive method；
Fig. 3 is the inventive method middle gear case Stress calculation and arranges schematic flow sheet；
Fig. 4 is gear-box three-level transmission coordinate schematic diagram.
Specific embodiment
It is easy to understand, according to technical scheme, in the case where the connotation of the present invention is not changed, this area
Those skilled in the art can imagine the present invention based on SCADA data wind-driven generator wheel-box fatigue life estimation method
Numerous embodiments.Therefore, detailed description below and accompanying drawing are only the exemplary illustrations to technical scheme,
And be not to be construed as the whole of the present invention or be considered as the restriction to technical solution of the present invention or restriction.
With reference to accompanying drawing, the inventive method includes process, the calculating of gearbox drive component stress and the gear of SCADA data
Three parts of case Calculation of Fatigue Life.
1st, the process of SCADA data
SCADA system, i.e. data acquisition analysis system are widely used to wind-power electricity generation, and the system is by collecting wind-powered electricity generation
Data during unit operation are analyzed to the runnability and state of unit, and then realize the local runtime of wind power generating set
Or remotely control.SCADA system is averaged typically per 5 to 10 minutes to the data for gathering, and collects wind power generating set multiple
Run signal, and record archive.Air speed data in the mainly SCADA data that the present invention is used, including the wind of every 10min
Fast mean value Vmean, maximum VmaxWith minimum of a value Vmin.The present invention restores the turbulivity in the time period according to equation below
I。
After obtaining the size of turbulivity I, according to the foundation rule of Von Karman Wind speed models, restore short in 10min
The wind speed time series of time interval, joins the wind speed time series as the input of wind-driven generator wheel-box kinetic model
Number is standby.The foundation rule of Von Karman Wind speed models is as follows：
A=0.535+2.76 (0.138-A)0.68
A=0.115 [1+0.315 (1-h/h1)0.68]2/3
β1=2.357a-0.761
β2=1- β1
In formula, SuuBe wind speed on longitudinal component from frequency spectrum, f is the frequency of wind speed change, σuFor the mark of wind speed change
It is accurate poor；For dimensionless frequency parameter, xLuFor the length dimension of turbulent flow longitudinal component,For mean wind speed；H is wind-driven generator
Wheel hub apart from ground height, h1For atmospheric boundary layer thickness.By hub height, mean wind speed, wind speed change frequency and wind speed
The information such as the standard deviation of change are updated in above-mentioned formula, can obtain hub height center by Von Karman Wind speed models
The short time interval time series of place's wind speed.
2nd, the calculating of gearbox drive component stress
The control of optimum tip speed ratio and pitch control according to wind-driven generator, is converted into wind speed time series impeller and turns
Square time series.
When wind speed is below rated wind speed, it is as follows that the machine torque of impeller calculated mode,
Tm=0.5 ρ π Rv4Cp/ωr
In formula, TmFor wind wheel machine torque；ωrFor wind wheel angular velocity of rotation；R is wind wheel radius；V is wind speed, and ρ is air
Density；CPFor power coefficient.
During when wind speed is higher than rated wind speed and less than shutting down wind speed, it is as follows that the machine torque of impeller calculated mode,
Tm=PE/ωr
In formula, PEFor rated power；ωrThe specified angular velocity of rotation of-wind wheel.
Bring the time series of wind speed v into both the above computing formula, wind wheel machine torque T is obtained by calculatingm
And the time series of impeller torque.
The present invention is carried out using lumped parameter method on the basis of the key structural parameters of prominent gear-box to transmission system
Dynamic Modeling, adds gear pair engagement time-varying rigidity and damping in model, bearing rigidity and damping and power transmission shaft are reversed
The characterisitic parameter such as rigidity and damping, using the wind speed time series of the short time interval of hub height as the |input paramete of model,
Calculate the dynamic response of gear-box internal transmission part.The basic dynamic formula of model is as follows：
In above formula, M represents general mass matrix；C represents broad sense damping matrix；K represents the generalized stiffness matrix；Q represents wide
Adopted coordinates matrix, the equation represents a kinetics relation when gear mesh is engaged.Based on above formula, according to gear-box
Concrete structure sets up the wind-driven generator wheel-box model of multiple frees degree, adds what two-stage parallel gears was constituted with primary planet wheel
As a example by three-level transmission, it is as follows that its model sets up process：
As shown in figure 4, taking the torsional displacement u of each componenti(i=c, r, s, p1, p2, p3,1,2,3,4) is generalized coordinates.
kct,krt,kstPlanet carrier, ring gear and the tangential support stiffness of sun gear are represented respectively；cct,crt,cstRepresent planet carrier, ring gear
Damping is tangentially supported with sun gear.kcu, ksu, k23, k4uThe torsion of planet carrier, sun gear, gear 2 and the output shaft of gear 4 is represented respectively
Turn rigidity；ccu, csu, c23, c4uThe damping of planet carrier, sun gear, gear 2 and the output shaft of gear 4 is represented respectively；kspi(i=1,2,3)
Represent the mesh stiffness between sun gear and planetary gear；cspi(i=1,2,3) the engagement resistance between sun gear and planetary gear is represented
Buddhist nun.krpi(i=1,2,3) represent the mesh stiffness between ring gear and planetary gear, crpi(i=1,2,3) ring gear and row are represented
Engagement damping between star-wheel.k12Represent the mesh stiffness between gear 1 and gear 2；c12Represent between gear 1 and gear 2
Engagement damping.k34Represent the mesh stiffness between gear 3 and gear 4；c34Represent the engagement damping between gear 3 and gear 4.
Then have：
I. sun gear relative to i-th planetary gear displacement along external toothing line direction projection：
δspi=us-uccosαs+upi
Ii. ring gear relative to i-th planetary gear displacement along internal messing line direction projection：
δrpi=ur-uccosαr-upi
Iii. gear 1 relative to gear 2 displacement outer path of contact direction projection：
δ12=u1-u2
Iv. gear 3 relative to gear 4 displacement outer path of contact direction projection：
δ34=u3-u4
V. each component kinetics equation of planet circular system：
Wherein：
Vi. intergrade parallel gears kinematical equation：
Wherein：
Vii. high speed level parallel gears kinematical equation：
Wherein：
According to above kinetics equation, the kinetic model of three-level uni-drive gear box can be set up in matlab.
It is assumed that three planetary gears in Gear Planet Transmission level are uniformly distributed along the circumference, and with identical physical parameter and geometric parameters
Number；Engagement between gear pair is modeled as into the spring with time-varying rigidity, it is considered to the mesh stiffness and damping between gear pair,
Rolling bearing determines support stiffness and damping and power transmission shaft determines torsional rigidity and damping；Gear synthesis meshing error is not considered；
Transmissions at different levels are reduced to into lumped-parameter system, the pure torsion model of wind-driven generator wheel-box is set up.Asked with Newmark method
Solution gear-box kinetic model, the input of gearbox model is impeller torque, is output as the engagement force size of gear, i.e. driving section
Stress F of partt.The general solution approach of Newmark method is as follows：
1. calculation of initial value
I) system stiffness matrix K, mass matrix M and damping matrix C are formed；
Ii initial value x) is determined0,
Iii) selection time step delta t, parameter γ, σ, and calculate integral constant；
γ >=0.5, δ >=0.25 (0.5+ γ)2
a6=Δ t (1- γ), a7=γ Δ t
Iv) effective stiffness matrix is formed
v)Matrix carries out triangle decomposition；
2., according to very first time step-length, parameter is calculated as follows；
I) equivalent load of t+ Δ ts is calculated
Ii the displacement of t+ Δ ts) is solved；
Iii the acceleration and speed of t+ Δ ts) are calculated；
Solve after the stress of gear engagement place according to above-mentioned Newmark method, need according to GB GB/T3480-1997
The bending stress size of tooth root is calculated, computing formula is as follows：
Letter definition here is not described in detail, and detailed content can refer to GB/T3480-1997, wherein FtReceiving for part
Power size.
3rd, the process of stress time sequence and the calculating of gear-box fatigue life
3.1 the process of stress time sequence
After obtaining the time series of stress, need to carry out it statistical analysis, the present invention applies general rain-flow counting
Method carries out statistical analysis to the time series of stress.The counting principle of rain flow method is：The time is taken for ordinate, vertically to
Under；Load or stress are abscissa.Counting rule is：
I) starting point of rain stream is successively in the inner side at each peak (or paddy)；
Ii) rain stream falls at next peak (or paddy) place, until there is a peak being larger than (or less paddy) till；
Iii) just stop when rain stream runs into the rain stream flowed down from roof above；
Iv) all of complete alternation is taken out, and records respective peak value and valley.
The present invention is processed stress time series using rain flow method, obtains classification and this point of stress intensity
The corresponding cycle-index of level, i.e. stress spectra, as the |input paramete of Calculation of Fatigue Life algorithm.
Need to use the stress intensity inside the revised stress spectras of goodman and corresponding circulation when fatigue mechanisms
Number of times.At present the S-N curves or P-S-N curves of existing material is mostly that in symmetry circulating stress, i.e., average is zero effect
Under obtain, when the fatigue life of parts is estimated, mean stress is modified.What is be wherein most frequently with is to use
Goodman linear equations are modified to the S-N curves or P-S-N curves of material, and correction formula is as follows：
In formula, σeaFor equivalent zero-mean stress, MPa；σaFor stress amplitude, MPa；σbFor material strength limit, MPa；σmFor
Stress average, MPa.
Then after amendment, the Fatigue Life Curve expression formula of double-log form is：
In formula, N is fatigue life number of times, and unit is secondary；C, m are the constant relevant with material, are determined by material.
The calculating of 3.2 gear-box fatigue lives
Cumulative Fatigue Damage principle points out that material or part are circulated all when fatigue stress limits are withstood greater than, each time
A certain amount of damage can be produced to material, under Cyclic Load, fatigue damage occurs tired when constantly accumulating up to critical value
Labor is destroyed.Fatigue Summation Damage Theory can be summarized as two big class：
(1) linear Fatigue Summation Damage Theory, the theory thinks that the suffered fatigue damage under each stress level of material is
It is separate to carry out, and total damage can be with linear superposition.Wherein most representational is Palmgren-Miner theoretical,
Its theoretical calculation formula is as follows：
Wherein, stress level σiLower material reaches the global cycle times N of destructioni, need the goodman non-zeros by material
Mean stress S-N fair curve is looked into and is worth.For random load, when Miner rules are generally acknowledged that D=1, material damage.
(2) non-linear Fatigue Summation Damage Theory, the theory thinks to be deposited between the load that material born and fatigue damage
The fatigue damage produced under correlation, i.e. certain stress level has relation with stress level before and cycle-index.
Wherein most representational is Corten-Dolan theoretical.Its theoretical formula is as follows：
In formula, NgFor fatigue life of the component under multistage stress, N1For component, maximum one-level stress is independent in loading spectrum
Fatigue life under effect, σ1For the maximum stress in multistage stress spectra, αiFor alternate stress σiPeriod account for loading spectrum and always follow
The percentage of number of rings, d is material constant, can be determined by the fatigue test of secondary cycle stress.
Both the above method is the theoretical algorithm of two kinds of the most frequently used in practice calculating fatigue damages of engineering.Miner algorithms
Amount of calculation it is less, typically adopt Corten-Dolan algorithms when higher to the use requirement of material.The present invention can be according to tool
Body demand switches Calculation of Fatigue Life algorithm.
The method that the present invention estimates wind-driven generator wheel-box fatigue life using online SCADA data, the method can be with
The accumulative fatigue damage of gear-box is estimated according to SCADA data, current wind turbine gearbox health status is estimated, while
Realize the quantum chemical method of the residual life to gear-box.Quantum chemical method is exactly the accumulative fatigue damage for calculating gear-box, i.e.,
The accumulative Fatigue Damage Calculation result of Miner and Corten-Dolan algorithms.It is the D that calculates for miner algorithms carry out book
Value size；It is the N for calculating for Corten-Dolan algorithmsgThe size of value.
The present invention develops rational wind-driven generator wheel-box maintenance scheme and plays an important role to wind power plant.The present invention
It is that the method for its fatigue life is calculated with the kinetic model of gear-box based on actual SCADA data, because using
Actual SCADA data, so calculating the wind-driven generator wheel-box fatigue life for obtaining has higher confidence level.
Claims (4)
1. a kind of wind-driven generator wheel-box fatigue life estimation method based on SCADA data, it is characterised in that step is such as
Under：
Step one, carries out processing acquisition mean wind speed and turbulivity to SCADA data；According to hub height, mean wind speed, turbulent flow
Degree, using Von Karman Wind speed models, restores the wind speed time series of short time interval；
Step 2, by wind speed time series impeller torque time series is converted into, and according to impeller torque time series wind-force is used
Generator gear case kinetic model, calculates the stress time sequence for obtaining gear-box internal transmission part；Using rain-flow counting
Method is processed stress time series, obtains stress spectra；Using Goodman linear equations to the stress intensity in stress spectra and
Corresponding cycle-index is modified；
Step 3, according to revised stress spectra and the S-N curves of motor gearbox gear, is calculated using Cumulative Fatigue Damage
Method, calculates the accumulative fatigue damage of gear-box.
2., as claimed in claim 1 in the wind-driven generator wheel-box fatigue life estimation method of SCADA data, its feature exists
In in step one, the wind speed time series is in 10min, at intervals of the wind speed time series of 0.1s.
3., as claimed in claim 1 in the wind-driven generator wheel-box fatigue life estimation method of SCADA data, its feature exists
In in step one, the Von Karman Wind speed models are：
In formula,Be wind speed on longitudinal component from frequency spectrum, f is the frequency of wind speed change, σuFor the standard of wind speed change
Difference；For dimensionless frequency parameter,xLuFor the length dimension of turbulent flow longitudinal component,For mean wind speed；H is wind-power electricity generation wheel
Hub apart from ground height, h1For atmospheric boundary layer thickness；Parametera、β1、β2And F1Difference is as follows,
A=0.535+2.76 (0.138-A)0.68
A=0.115 [1+0.315 (1-h/h1)0.68]2/3
β1=2.357a-0.761
β2=1- β1
4., as claimed in claim 1 in the wind-driven generator wheel-box fatigue life estimation method of SCADA data, its feature exists
In in step 2, using wind-driven generator wheel-box kinetic model, when calculating the stress for obtaining gear-box internal transmission part
Between sequence when, using Newmark method solve motor gearbox kinetic model.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109000922A (en) * | 2018-06-11 | 2018-12-14 | 中国北方车辆研究所 | Comprehensive actuator endurance bench test method based on road test |
| CN110030148A (en) * | 2019-04-22 | 2019-07-19 | 中南大学 | The nonlinear prediction pitch control method measured in advance based on wind speed |
| CN111159871A (en) * | 2019-12-23 | 2020-05-15 | 北京工业大学 | Random multi-axis cycle counting method based on path curve integration |
| CN112417612A (en) * | 2020-10-15 | 2021-02-26 | 浙江工业大学 | Method for tracking degradation state and evaluating failure aggregation risk of wind power gear box |
| CN113051679A (en) * | 2021-03-18 | 2021-06-29 | 湖南南方宇航高精传动有限公司 | Load processing method for main bearing of wind power gear box |
| CN114508499A (en) * | 2021-12-22 | 2022-05-17 | 中国大唐集团新能源科学技术研究院有限公司 | Fan health degree early warning system based on big data of unit operation |
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2016
- 2016-12-19 CN CN201611175646.9A patent/CN106600066A/en active Pending
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109000922A (en) * | 2018-06-11 | 2018-12-14 | 中国北方车辆研究所 | Comprehensive actuator endurance bench test method based on road test |
| CN110030148A (en) * | 2019-04-22 | 2019-07-19 | 中南大学 | The nonlinear prediction pitch control method measured in advance based on wind speed |
| CN111159871A (en) * | 2019-12-23 | 2020-05-15 | 北京工业大学 | Random multi-axis cycle counting method based on path curve integration |
| CN111159871B (en) * | 2019-12-23 | 2024-03-26 | 北京工业大学 | Random multi-axis cycle counting method based on path curve integration |
| CN112417612A (en) * | 2020-10-15 | 2021-02-26 | 浙江工业大学 | Method for tracking degradation state and evaluating failure aggregation risk of wind power gear box |
| CN112417612B (en) * | 2020-10-15 | 2023-06-09 | 浙江工业大学 | Wind power gear box degradation state tracking and failure aggregation risk assessment method |
| CN113051679A (en) * | 2021-03-18 | 2021-06-29 | 湖南南方宇航高精传动有限公司 | Load processing method for main bearing of wind power gear box |
| CN113051679B (en) * | 2021-03-18 | 2021-10-26 | 湖南南方宇航高精传动有限公司 | Load processing method for main bearing of wind power gear box |
| CN114508499A (en) * | 2021-12-22 | 2022-05-17 | 中国大唐集团新能源科学技术研究院有限公司 | Fan health degree early warning system based on big data of unit operation |
| CN114508499B (en) * | 2021-12-22 | 2024-01-09 | 大唐可再生能源试验研究院有限公司 | Fan health degree early warning system based on big data of unit operation |
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Application publication date: 20170426 |