CN102900609B - Giant magnetostrictive flap wind turbine blade vibration reduction system and control method - Google Patents

Abstract

The invention discloses a giant magnetostrictive flap wind turbine blade vibration reduction system and a control method, belonging to the technical field of wind power generation. The invention adopts the technical scheme that the system comprises a giant magnetostrictive flap wind turbine blade, a wind speed measurement laser radar, an embedded vibration control card and an upper computer. The giant magnetostrictive flap wind turbine blade comprises three fiber optic strain sensors and three giant magnetostrictive actuators. The embedded vibration control card comprises an ARM (Advanced RISC Machines) main control chip, an FPGA (Field Programmable Gate Array) circuit, an A/D (Analog to Digital) converter, a first low pass filter, a signal conditioner, a voltage-controlled constant current source, a second low pass filter, a digital to analog converter and a USB (Universal Serial Bus) port. The giant magnetostrictive flap wind turbine blade vibration reduction system and the control method have the beneficial effects that vibration reduction of the wind turbine blade which is provided with flap structures is realized under small amplitude and low frequency, and the antijamming capability of the system is improved.

Description

Pneumatic equipment blades made vibration insulating system and the controlling method of ultra-magnetic telescopic flap configurations

Technical field

The invention belongs to technical field of wind power generation, relate in particular to a kind of pneumatic equipment blades made vibration insulating system and controlling method of ultra-magnetic telescopic flap configurations.

Background technique

There is abundant wind resource in the whole world.Nearly ten years, be accompanied by the whole world increasingly mature to environmental problem pay attention to day by day, soaring oil prices and wind power technology, global wind-powered electricity generation has obtained extraordinary development, and the development of China's wind-powered electricity generation is particularly rapid.The generating field grid-connected effectively principal mode of utilization of wind energy that just becoming of large scale wind power machine and large-scale wind electricity.

Pneumatic equipment blades made, in rotary course, is subject to the rapid fluctuations load action from various separate sources air-flows, comprises what wind tower shadow, wind shear and the driftage etc. of turbulent flow caused.Air stream produces irregular elastic vibration on flexible blade, and especially blade is being waved perpendicular to the flexure vibrations on plane of rotation, is one of key factor causing wind energy conversion system fatigue load.In recent years, in order to realize the scale utilization of wind energy, the physical dimension of pneumatic equipment blades made is continuing increase, but has also increased the load on pneumatic equipment blades made.Because blade loading has affected other assemblies as the load of machine driven system and shaft tower, cause wind-powered electricity generation overall cost sharply soaring.The traditional fixedly air-foil blade cost of simple reduction, limited to reducing overall cost effect.

Summary of the invention

For the existing large scale wind power machine blade of mentioning in background technique, in the shortcoming and defect aspect reduction fatigue loading, the present invention proposes a kind of pneumatic equipment blades made vibration insulating system and controlling method of ultra-magnetic telescopic flap configurations.

A pneumatic equipment blades made vibration insulating system for ultra-magnetic telescopic flap configurations, is characterized in that, described system comprises pneumatic equipment blades made, survey wind speed lidar, embedded vibration control card and the upper-position unit of ultra-magnetic telescopic flap configurations; The pneumatic equipment blades made of described ultra-magnetic telescopic flap configurations comprises three fiber optic strain sensors and three ultra-magnetic telescopic actuator; Described embedded vibration control card comprises ARM main control chip, FPGA circuit, analog-digital converter, the first low-pass filter, signal conditioner, voltage controlled current source, the second low-pass filter, digital to analog converter and USB interface;

Wherein, described three fiber optic strain sensors, signal conditioner, the first low-pass filter, analog-digital converter, FPGA circuit are connected in turn with ARM main control chip; Described three strain transducers are for gathering the strain signal of the pneumatic equipment blades made with flap configurations; Described signal conditioner changes voltage signal into for the signal dress that fiber optic strain sensor is detected; Described the first low-pass filter is used for filtering high-frequency interferencing signal; Described analog-digital converter is for converting analogue signal to digital signal; Described FPGA circuit is for processing the digital signal receiving;

Described FPGA circuit, digital to analog converter, the second low-pass filter, voltage controlled current source and three ultra-magnetic telescopic actuator are connected in turn; Described digital to analog converter is for converting digital signal to analogue signal; Described the second low-pass filter is for becoming stair-stepping analog voltage amount the analog voltage amount of smoothed curve shape; Described voltage controlled current source is for converting analog voltage signal to current signal; Described three ultra-magnetic telescopic actuator produce corresponding elongation or shrink and then wing flap is swung according to current signal and produce different amount;

Described survey wind speed lidar is connected with described analog-digital converter; Described survey wind speed lidar is used for providing with reference to strain signal;

Described ARM main control chip is connected by USB interface with described upper-position unit; Described ARM main control chip is for monitoring the operation conditions of embedded vibration control card and the order of upper-position unit and FPGA and data transmission.

Described survey wind speed lidar is arranged on the cabin windward side of the wind energy conversion system of ultra-magnetic telescopic flap configurations.

Described three fiber optic strain sensors are arranged on the windward side of the pneumatic equipment blades made of ultra-magnetic telescopic flap configurations, respectively three wing flaps of corresponding described blade.

Described wing flap comprises web, fixed hinge, turning joint, rotating disk and rotating shaft; Described fixed hinge is arranged on the web of pneumatic equipment blades made of ultra-magnetic telescopic flap configurations; One end of described ultra-magnetic telescopic actuator is connected with fixed hinge by rotating articulated manner, and the other end of ultra-magnetic telescopic actuator is connected with rotating disk by turning joint; Rotating disk and wing flap are means of fixation; Ultra-magnetic telescopic actuator encloses wing flap to rotate around the axis.

The angle range that described ultra-magnetic telescopic actuator encloses wing flap to rotate around the axis is between-5 ° to+5 °.

A controlling method for the pneumatic equipment blades made vibration insulating system of ultra-magnetic telescopic flap configurations, is characterized in that, specifically comprises the following steps:

Step 1: initialization of variable

Determine that 6 tunnels are by the exponent number of filter signal, exponent number is set as N; Step-length is μ; Initialization input vector X (k) and output vector F ₁(k), F ₂and F (k) ₃and G (k) ₁(k), G ₂and G (k) ₃(k);

Step 2: the matching of right to use vector initial value fitting algorithm obtains weight vector initial value V=[v ₀, v ₁..., v _n] ^tand W=[w ₀, w ₁..., w _n] ^t;

Step 3: upgrade wave filter weight coefficient, and export controlled quentity controlled variable;

Step 31: set k=1;

Step 32: upgrade initial value in input vector X (k): X (k) and respectively move to right one; Read in current input x (k), and X (k) [0]=x (k);

Step 33: read in error current signal e ₁(k), e ₂and e (k) ₃(k);

Step 34: upgrade two wave filter weight coefficients: concrete steps comprise:

Step 341: set i=0;

Step 342: according to formula calculating filter weight coefficient;

w ₁[i]=w ₁[i]-2*μ*e ₁(k)*g ₁[i];v ₁[i]=v ₁[i]-2*μ*e ₁(k)*f ₁[i]；

w ₂[i]=w ₂[i]-2*μ*e ₂(k)*g ₂[i];v ₂[i]=v ₂[i]-2*μ*e ₂(k)*f ₂[i]；

w ₃[i]=w ₃[i]-2*μ*e ₃(k)*g ₃[i];v ₃[i]=v ₃[i]-2*μ*e ₃(k)*f ₃[i]；

Step 343: make i=i+1;

Step 344: judge whether i is less than N+1; If so, perform step 342; No, perform step 35;

Step 35: calculating filter output:

Output vector F ₁(k), F ₂and F (k) ₃and G (k) ₁(k), G ₂and G (k) ₃(k) intermediate value respectively moves to right 1; Calculate current output value:

$f_1\left(k\right)=\underset{j=0}{\overset{N}{\mathrm{\Σ}}}{w}_{1_j}\left(k\right)x(k-j);f_2\left(k\right)=\underset{j=0}{\overset{N}{\mathrm{\Σ}}}{w}_{2_j}\left(k\right)x(k-j);f_3\left(k\right)=\underset{j=0}{\overset{N}{\mathrm{\Σ}}}{w}_{3_j}\left(k\right)x(k-j);$

$g_1\left(k\right)=\underset{i=0}{\overset{N}{\mathrm{\Σ}}}{v}_{1_i}\left(k\right)x(k-i);g_2\left(k\right)=\underset{i=0}{\overset{N}{\mathrm{\Σ}}}{v}_{2_i}\left(k\right)x(k-i);g_3\left(k\right)=\underset{i=0}{\overset{N}{\mathrm{\Σ}}}{v}_{3_i}\left(k\right)x(k-i);$

F ₁(k)[0]=f ₁(k);F ₂(k)[0]=f ₂(k);F ₃(k)[0]=f ₃(k);G ₁(k)[0]=g ₁(k);G ₂(k)[0]=g ₂(k);G ₃(k)[0]=g ₃(k)；

Step 36: output controlled quentity controlled variable F ₁(k) [0]=f ₁(k), F ₂(k) [0]=f ₂(k), F ₃(k) [0]=f ₃(k);

Step 37: make k=k+1, and judge whether k is less than 100000; If so, return to step 32; No, perform step 38;

Step 38: finishing control: end loop, by e ₁(k), e ₂(k), e ₃(k), f ₁(k), f ₂(k), f ₃(k), w ₁, w ₂, w ₃, v ₁, v ₂, v ₃writing in files is preserved.

In step 1, definite method of input vector X (k) is:

Steps A: calculate the moment of torsion infinitesimal on the impeller shaft that wind energy conversion system produces according to moment of torsion infinitesimal formula;

$\mathrm{dM}=\frac{1}{2}\mathrm{\ρ}{\mathrm{rlv}}^2(C_l\sin \mathrm{\φ}-C_d\cos \mathrm{\φ})\mathrm{dr}$

Wherein, ρ is air density, C _land C _dfor lift coefficient and resistance coefficient, φ is the angle between airflow direction and pneumatic equipment blades made plane, and l is chord length;

Step B: along length direction, moment of torsion infinitesimal is carried out to integration on blade, obtain acting on moment of torsion M on blade _n;

Step C: by obtain with reference to strain signal X (k).

In described step 2, weight vector initial value fitting algorithm is determined weight vector initial value V=[v ₀, v ₁..., v _n] ^tand W=[w ₀, w ₁..., w _n] ^t; Weight vector initial value fitting algorithm, fixed time interval is 1ms, and the initial value of W is made as to the exponent number that 0, N is wave filter; The concrete fitting algorithm of weight vector initial value V comprises the following steps:

Step 21: initialization of variable, determine exponent number N and the step size mu of the first low-pass filter three road signals; Initialization error input vector ek _iand reference signal rk (k) _i(k), intermediate variable ek _i(k), ekk _i(k), r _i(k), sum _i, i=1,2,3;

Step 22:A/D Acquisition Error input signal and reference signal, set k=1

Step 23: if k=1,2 ..., 1000, carry out following step:

Intermediate variable ekk _i(k) cumulative ekk _i(k)=ekk _i(k)+ek _i(k);

If k=1001,1002 ..., 2000, carry out following step:

Step a:rk _i(k) in, initial value respectively moves to right one; Read in current input rk _i(k), upgrade r _i(k)=rk _i(k);

Step b: upgrade intermediate variable e _i(k)=ek _i() – ekk k _i(k);

Step c: cumulative intermediate variable sum _i+=w _i(k) * r _i(k);

Steps d: ask difference e rror _i(k)=ek _i() – sum k _i;

Step e: upgrade wave filter weight coefficient:

v _i(k)=v _i(k)-2*μ*error _i(k)*r _i(k)；

Step 24:k=k+1; Judge whether k is less than or equal to 2000, if so, return to step 23; Otherwise, execution step 25;

Step 25: finishing control: end loop, by v _iwriting in files is preserved, and forms weight vector initial value V.

The invention has the beneficial effects as follows, with respect to fixing air-foil blade, the vibration-damping function of the pneumatic equipment blades made that native system has a flap configurations under slightly (micron order), low frequency (0.1～500Hz) is achieved; Improved the antijamming capability of system, working stability.The gas bullet characteristic that the present invention has improved anti-load-carrying ability, the anti-fatigue performance of pneumatic equipment blades made and optimized pneumatic equipment blades made.

Accompanying drawing explanation

Fig. 1 is the structured flowchart of the pneumatic equipment blades made vibration insulating system of a kind of ultra-magnetic telescopic flap configurations provided by the invention;

Fig. 2 is the blade structure schematic diagram of the pneumatic equipment blades made vibration insulating system of a kind of ultra-magnetic telescopic flap configurations provided by the invention;

Fig. 3 is the workflow diagram of the pneumatic equipment blades made vibration insulating system of a kind of ultra-magnetic telescopic flap configurations provided by the invention;

Fig. 4 is weight vector initial value fitting algorithm flow chart in the controlling method of pneumatic equipment blades made vibration insulating system of a kind of ultra-magnetic telescopic flap configurations provided by the invention;

Fig. 5 is the control principle block diagram of the pneumatic equipment blades made vibration insulating system of a kind of ultra-magnetic telescopic flap configurations provided by the invention;

Fig. 6 is modified model LMS adaptive filtering algorithm flow chart in the controlling method of pneumatic equipment blades made vibration insulating system of a kind of ultra-magnetic telescopic flap configurations provided by the invention;

Fig. 7 is three error signal figure that in the control procedure of pneumatic equipment blades made vibration insulating system of a kind of ultra-magnetic telescopic flap configurations provided by the invention, A/D gathers;

Fig. 8 is that in the control procedure of pneumatic equipment blades made vibration insulating system of a kind of ultra-magnetic telescopic flap configurations provided by the invention, three of D/A output control output spirograms;

Wherein, 11-blade; 21-surveys wind speed lidar; 31,32,33-fiber optic strain sensor; 41-ultra-magnetic telescopic actuator; 51,52,53-wing flap; 61-web; 71-fixed hinge; 81-turning joint; 91-rotating shaft; 101-rotating disk; The windward side in 111-cabin.

Embodiment

Below in conjunction with accompanying drawing, preferred embodiment is elaborated.Should be emphasized that, following explanation is only exemplary, rather than in order to limit the scope of the invention and to apply.

Fig. 1 is the structured flowchart of the pneumatic equipment blades made vibration insulating system of a kind of ultra-magnetic telescopic flap configurations provided by the invention.In Fig. 1, described system comprises pneumatic equipment blades made, survey wind speed lidar, embedded vibration control card and the upper-position unit of ultra-magnetic telescopic flap configurations; The pneumatic equipment blades made of described ultra-magnetic telescopic flap configurations comprises three fiber optic strain sensors and three ultra-magnetic telescopic actuator; Described embedded vibration control card comprises ARM main control chip, FPGA circuit, analog-digital converter, the first low-pass filter, signal conditioner, voltage controlled current source, the second low-pass filter and digital to analog converter;

Wherein, described three fiber optic strain sensors, signal conditioner, the first low-pass filter, analog-digital converter, FPGA circuit are connected in turn with ARM main control chip; Described three strain transducers are for gathering the strain signal of the pneumatic equipment blades made with flap configurations; Described signal conditioner changes voltage signal into for the signal dress that fiber optic strain sensor is detected; Described the first low-pass filter is used for filtering high-frequency interferencing signal; Described analog-digital converter is for converting analogue signal to digital signal; Described FPGA circuit is for processing the digital signal receiving;

Described FPGA circuit, digital to analog converter, the second low-pass filter, voltage controlled current source and three ultra-magnetic telescopic actuator are connected in turn; Described digital to analog converter is for converting digital signal to analogue signal; Described the second low-pass filter is for level and smooth analog voltage amount; Described voltage controlled current source is for converting analog voltage signal to current signal; Described three ultra-magnetic telescopic actuator produce corresponding elongation or shrink and then wing flap is swung according to current signal and produce different amount;

Described survey wind speed lidar is connected with described analog-digital converter; Described survey wind speed lidar is used for providing with reference to strain signal;

Described ARM main control chip is connected by USB interface with described upper-position unit; For monitoring the operation conditions of embedded vibration control card and the order of upper-position unit and FPGA and data transmission.

Fig. 2 is the blade structure schematic diagram of the pneumatic equipment blades made vibration insulating system of a kind of ultra-magnetic telescopic flap configurations provided by the invention.In Fig. 2, described survey wind speed lidar is arranged on the cabin windward side of the wind energy conversion system of ultra-magnetic telescopic flap configurations; Described three fiber optic strain sensors are arranged on the windward side of the pneumatic equipment blades made of ultra-magnetic telescopic flap configurations, respectively three wing flaps of corresponding described blade.

Described wing flap comprises web, fixed hinge, turning joint, rotating disk and rotating shaft; Described fixed hinge is arranged on the web of pneumatic equipment blades made of ultra-magnetic telescopic flap configurations; One end of described ultra-magnetic telescopic actuator is connected with fixed hinge by rotating articulated manner, and the other end of ultra-magnetic telescopic actuator is connected with rotating disk by turning joint; Rotating disk and wing flap are means of fixation; Ultra-magnetic telescopic actuator encloses wing flap to rotate around the axis; The angle range that described ultra-magnetic telescopic actuator encloses wing flap to rotate around the axis is between-5 ° to+5 °.

Fig. 3 is the workflow diagram of the pneumatic equipment blades made vibration insulating system of a kind of ultra-magnetic telescopic flap configurations provided by the invention.In Fig. 3, control system workflow of the present invention comprises the following steps:

Step 301: each vector of initialization, comprises the exponent number of input vector, output vector and digital filter.

Step 302: judge whether that matching crosses weight vector initial value, if not, perform step 303; To perform step 304;

Step 303: right to use vector initial value fitting algorithm is estimated weight vector initial value, and weights are kept to Flash ROM;

Step 304: under real-time controlled conditions, real-time update input vector X (k) and 3 fiber optic strain sensor output vector E ₁(k), E ₂and E (k) ₃(k), through modified model minimum mean square self-adaption filtering active vibration control algorithm F ₁(k)=f{E ₁(k), X (k) }, F ₂(k)=f{E ₂(k), X (k) } and F ₃(k)=f{E ₃(k), X (k) } calculate and control output vector F ₁(k), F ₂and F (k) ₃(k);

Step 305: control output vector F ₁(k), F ₂and F (k) ₃(k) after D/A converter conversion, export respectively three ultra-magnetic telescopic actuator to; Calculate initial 100 E ₁(k), E ₂and E (k) ₃(k) root-mean-square error RMSE ₁₁, RMSE ₂₁and RMSE ₃₁and preserve; Calculate in real time nearest 100 E ₁(k), E ₂and E (k) ₃(k) root-mean-square error RMSE ₁₂, RMSE ₂₂and RMSE ₃₂.Judgement RMSE ₁₂/ RMSE ₁₁, RMSE ₂₂/ RMSE ₂₁and RMSE ₃₂/ RMSE ₃₁these 3 ratios, if be all less than 0.1, system judgement restrains, and finishes this Active Vibration Control, if so, finishes this Active Vibration Control; No, return to step 304.

Fig. 4 is weight vector initial value fitting algorithm flow chart in the controlling method of pneumatic equipment blades made vibration insulating system of a kind of ultra-magnetic telescopic flap configurations provided by the invention.Shown in Fig. 4, the weight vector initial value fitting algorithm that adds judgement sampling to interrupt of the present invention, fixed time interval is 1ms.Experiment showed, weight vector V=[v ₀, v ₁..., v _n] ^tinitial value has the greatest impact to system, W=[w ₀, w ₁..., w _n] ^tthe impact of initial value is very little, can ignore, so the initial value of W can be made as the exponent number that 0(N is wave filter).The concrete fitting algorithm of weight vector V is as follows:

Step 401: initialization of variable, determine exponent number N and the step size mu of the first low-pass filter three road signals; Initialization error input vector ek _iand reference signal rk (k) _i(k), intermediate variable ek _i(k), ekk _i(k), r _i(k), sum _i, i=1,2,3;

Step 402:A/D Acquisition Error input signal and reference signal, set k=1

Step 403: if k=1,2 ..., 1000, carry out following step:

Intermediate variable ekk _i(k) cumulative ekk _i(k)=ekk _i(k)+ek _i(k);

If k=1001,1002 ..., 2000, carry out following step:

Step a:rk _i(k) in, initial value respectively moves to right one; Read in current input rk _i(k), upgrade r _i(k)=rk _i(k);

Step b: upgrade intermediate variable e _i(k)=ek _i() – ekk k _i(k);

Step c: cumulative intermediate variable sum _i+=w _i(k) * r _i(k);

Steps d: ask difference e rror _i(k)=ek _i() – sum k _i;

Step e: upgrade wave filter weight coefficient:

v _i(k)=v _i(k)-2*μ*error _i(k)*r _i(k)；

Step 404:k=k+1; Judge whether k is less than or equal to 2000, if so, return to step 403; Otherwise, execution step 405;

Step 405: finishing control: end loop, by v _iwriting in files is preserved, and forms weight vector initial value V.

Fig. 5 is the control principle block diagram of the pneumatic equipment blades made vibration insulating system of a kind of ultra-magnetic telescopic flap configurations provided by the invention.In Fig. 5, modified model minimum mean square self-adaption filtering control algorithm is abbreviated as LMS.A/D converter collection be x (k) (with reference to strain signal) and e ₁(k), e ₂and e (k) ₃(k) (the strain error amounts at 3 wing flap places), totally 4 A/D input channels.That D/A converter is exported is f ₁(k), f ₂and f (k) ₃(k) (control output quantity), 3 D/A output channels.Owing to not knowing the concrete control model of 3 ultra-magnetic telescopic actuator, so adopt 3 modified model minimum mean square self-adaption filtering V ₁, V ₂and V ₃ultra-magnetic telescopic actuator line modeling to 3 flap configurations respectively; Meanwhile, use 3 modified model minimum mean square self-adaption filtering W ₁, W ₂and W ₃as controller, realize the active vibration of pneumatic equipment blades made is controlled.System input output decoupling zero of the present invention, makes e ₁(k), e ₂and e (k) ₃and f (k) ₁(k), f ₂and f (k) ₃(k) set up relation one to one.Like this, the present invention just can adopt the controlling method of 3 single-input single-outputs to control, and in controlling method, the ultra-magnetic telescopic actuator that is exactly 3 flap configurations is independently controlled in real time.

The present invention needs to calculate in real time the moment of torsion of pneumatic equipment blades made.Moment of torsion infinitesimal on the impeller shaft that wind energy conversion system produces $\mathrm{dM}=\frac{1}{2}\mathrm{\ρ}{\mathrm{rvl}}^2(C_l\sin \mathrm{\φ}-C_d\cos \mathrm{\φ})\mathrm{dr},$ ρ is air density, C _land C _dfor lift coefficient and resistance coefficient, φ is the angle between airflow direction and pneumatic equipment blades made plane, and l is chord length.On blade, along length direction, moment of torsion infinitesimal is carried out to integration, just can obtain acting on moment of torsion on blade, by obtain with reference to strain, as X (k).

Fig. 6 is modified model LMS adaptive filtering algorithm flow chart in the controlling method of pneumatic equipment blades made vibration insulating system of a kind of ultra-magnetic telescopic flap configurations provided by the invention.In Fig. 6, the modified model minimum mean square self-adaption filtering control algorithm flow chart that adds the pneumatic equipment blades made of judgement sampling interruption of the present invention, modified model minimum mean square self-adaption filtering control algorithm is abbreviated as LMS in the drawings.In 1ms, embedded vibration control card will complete the calculating of 3 single-input single-outputs.Concrete control algorithm is as follows:

Step 601: initialization of variable

Determine that 6 tunnels are by the exponent number of filter signal, exponent number is set as N; Step-length is μ; Initialization input vector X (k) and output vector F ₁(k), F ₂and F (k) ₃and G (k) ₁(k), G ₂and G (k) ₃(k);

Step 602: the matching of right to use vector initial value fitting algorithm obtains weight vector initial value V=[v ₀, v ₁..., v _n] ^tand W=[w ₀, w ₁..., w _n] ^t;

Step 603: upgrade wave filter weight coefficient, and export controlled quentity controlled variable;

Step 6031: set k=1;

Step 6032: upgrade initial value in input vector X (k): X (k) and respectively move to right one; Read in current input x (k), and X (k) [0]=x (k);

Step 6033: read in error current signal e ₁(k), e ₂and e (k) ₃(k);

Step 6034: upgrade two wave filter weight coefficients: concrete steps comprise:

Step is 1.: set i=0;

Step is 2.: according to formula calculating filter weight coefficient;

w ₁[i]=w ₁[i]-2*μ*e ₁(k)*g ₁[i];v ₁[i]=v ₁[i]-2*μ*e ₁(k)*f ₁[i]；

w ₂[i]=w ₂[i]-2*μ*e ₂(k)*g ₂[i];v ₂[i]=v ₂[i]-2*μ*e ₂(k)*f ₂[i]；

w ₃[i]=w ₃[i]-2*μ*e ₃(k)*g ₃[i];v ₃[i]=v ₃[i]-2*μ*e ₃(k)*f ₃[i]；

Step is 3.: make i=i+1;

Step is 4.: judge whether i is less than N+1; If so, perform step 2.; No, perform step 6035;

Step 6035: calculating filter output:

Output vector F ₁(k), F ₂and F (k) ₃and G (k) ₁(k), G ₂and G (k) ₃(k) intermediate value respectively moves to right 1; Calculate current output value:

$f_1\left(k\right)=\underset{j=0}{\overset{N}{\mathrm{\Σ}}}{w}_{1_j}\left(k\right)x(k-j);f_2\left(k\right)=\underset{j=0}{\overset{N}{\mathrm{\Σ}}}{w}_{2_j}\left(k\right)x(k-j);f_3\left(k\right)=\underset{j=0}{\overset{N}{\mathrm{\Σ}}}{w}_{3_j}\left(k\right)x(k-j);$

$g_1\left(k\right)=\underset{i=0}{\overset{N}{\mathrm{\Σ}}}{v}_{1_i}\left(k\right)x(k-i);g_2\left(k\right)=\underset{i=0}{\overset{N}{\mathrm{\Σ}}}{v}_{2_i}\left(k\right)x(k-i);g_3\left(k\right)=\underset{i=0}{\overset{N}{\mathrm{\Σ}}}{v}_{3_i}\left(k\right)x(k-i);$

F ₁(k)[0]=f ₁(k);F ₂(k)[0]=f ₂(k);F ₃(k)[0]=f ₃(k);G ₁(k)[0]=g ₁(k);G ₂(k)[0]=g ₂(k);G ₃(k)[0]=g ₃(k)；

Step 6036: output controlled quentity controlled variable F ₁(k) [0]=f ₁(k), F ₂(k) [0]=f ₂(k), F ₃(k) [0]=f ₃(k);

Step 6037: make k=k+1, and judge whether k is less than 100000; If so, return to step 6032; No, perform step 6038;

Step 6038: finishing control: end loop, by e ₁(k), e ₂(k), e ₃(k), f ₁(k), f ₂(k), f ₃(k), w ₁, w ₂, w ₃, v ₁, v ₂, v ₃writing in files is preserved.

Fig. 7 is three error signal figure that in the control procedure of pneumatic equipment blades made vibration insulating system of a kind of ultra-magnetic telescopic flap configurations provided by the invention, A/D gathers; Fig. 8 is that in the control procedure of pneumatic equipment blades made vibration insulating system of a kind of ultra-magnetic telescopic flap configurations provided by the invention, three of D/A output control output spirograms.As shown in Figure 7,8, the control effect image that uses upper-position unit to obtain by USB interface for the present invention.Front 1000 sampling times (1ms) do not apply modified model minimum mean square self-adaption filtering control algorithm to vibration-isolating platform, are used for contrasting the effect that applies control algorithm front and back.Wherein, Fig. 7 is the error signal e that A/D gathers ₁(k), e ₂and e (k) ₃(k), corresponding with the error signal image of the 1st, 2 in figure and 3 passages successively; Fig. 8 is the control output quantity f of D/A output ₁(k), f ₂and f (k) ₃(k), corresponding with the control signal image of the 1st, 2 in figure and 3 passages successively.Since the 1001st sampling time, same sampling time interval, corresponding error signal e _iand control output signal f (k) _i(k) be within the same sampling period, to complete (i=1,2,3), sample altogether 6000 times, the working control time is 5s.As seen from Figure 8, apply modified model minimum mean square self-adaption filtering control algorithm and do not apply modified model minimum mean square self-adaption filtering control algorithm that the good results are evident.

The above; be only the present invention's embodiment preferably, but protection scope of the present invention is not limited to this, is anyly familiar with in technical scope that those skilled in the art disclose in the present invention; the variation that can expect easily or replacement, within all should being encompassed in protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection domain of claim.

Claims (7)

1. a pneumatic equipment blades made vibration insulating system for ultra-magnetic telescopic flap configurations, is characterized in that, described system comprises pneumatic equipment blades made, survey wind speed lidar, embedded vibration control card and the upper-position unit of ultra-magnetic telescopic flap configurations; The pneumatic equipment blades made of described ultra-magnetic telescopic flap configurations comprises three fiber optic strain sensors and three ultra-magnetic telescopic actuator; Described embedded vibration control card comprises ARM main control chip, FPGA circuit, analog-digital converter, the first low-pass filter, signal conditioner, voltage controlled current source, the second low-pass filter, digital to analog converter and USB interface;

Wherein, described three fiber optic strain sensors, signal conditioner, the first low-pass filter, analog-digital converter, FPGA circuit are connected in turn with ARM main control chip; Described three strain transducers are for gathering the strain signal of the pneumatic equipment blades made with flap configurations; Described signal conditioner changes voltage signal into for the signal dress that fiber optic strain sensor is detected; Described the first low-pass filter is used for filtering high-frequency interferencing signal; Described analog-digital converter is for converting analogue signal to digital signal; Described FPGA circuit is for processing the digital signal receiving;

Described FPGA circuit, digital to analog converter, the second low-pass filter, voltage controlled current source and three ultra-magnetic telescopic actuator are connected in turn; Described digital to analog converter is for converting digital signal to analogue signal; Described the second low-pass filter is for level and smooth analog voltage amount; Described voltage controlled current source is for converting analog voltage signal to current signal; Described three ultra-magnetic telescopic actuator produce corresponding elongation or shrink and then wing flap is swung according to current signal and produce different amount;

Described survey wind speed lidar is connected with described analog-digital converter; Described survey wind speed lidar is used for providing with reference to strain signal;

Described ARM main control chip is connected by USB interface with described upper-position unit; Described ARM main control chip is for monitoring the operation conditions of embedded vibration control card and the order of upper-position unit and FPGA and data transmission.

2. the pneumatic equipment blades made vibration insulating system of a kind of ultra-magnetic telescopic flap configurations according to claim 1, is characterized in that, described survey wind speed lidar is arranged on the cabin windward side of the wind energy conversion system of ultra-magnetic telescopic flap configurations.

3. the pneumatic equipment blades made vibration insulating system of a kind of ultra-magnetic telescopic flap configurations according to claim 1, it is characterized in that, described three fiber optic strain sensors are arranged on the windward side of the pneumatic equipment blades made of ultra-magnetic telescopic flap configurations, respectively three wing flaps of corresponding described blade.

4. the pneumatic equipment blades made vibration insulating system of a kind of ultra-magnetic telescopic flap configurations according to claim 3, is characterized in that, described wing flap comprises web, fixed hinge, turning joint, rotating disk and rotating shaft; Described fixed hinge is arranged on the web of pneumatic equipment blades made of ultra-magnetic telescopic flap configurations; One end of described ultra-magnetic telescopic actuator is connected with fixed hinge by rotating articulated manner, and the other end of ultra-magnetic telescopic actuator is connected with rotating disk by turning joint; Rotating disk and wing flap are means of fixation; Ultra-magnetic telescopic actuator encloses wing flap to rotate around the axis.

5. the pneumatic equipment blades made vibration insulating system of a kind of ultra-magnetic telescopic flap configurations according to claim 4, is characterized in that, the angle range that described ultra-magnetic telescopic actuator encloses wing flap to rotate around the axis is between-5 ° to+5 °.

6. a controlling method for the pneumatic equipment blades made vibration insulating system of ultra-magnetic telescopic flap configurations, is characterized in that, specifically comprises the following steps:

Step 1: initialization of variable

Determine that 6 tunnels are by the exponent number of filter signal, exponent number is set as N; Step-length is μ; Initialization input vector X (k) and output vector F ₁(k), F ₂and F (k) ₃and G (k) ₁(k), G ₂and G (k) ₃(k); Definite method of described input vector X (k) is:

Steps A: calculate the moment of torsion infinitesimal on the impeller shaft that wind energy conversion system produces according to moment of torsion infinitesimal formula;

$\mathrm{dM}=\frac{1}{2}{\mathrm{\ρrlv}}^2(C_l\sin \mathrm{\φ}-C_d\mathrm{sos\φ})\mathrm{dr}$

Wherein, ρ is air density, C _land C _dfor lift coefficient and resistance coefficient, φ is the angle between airflow direction and pneumatic equipment blades made plane, and l is chord length;

Step B: along length direction, moment of torsion infinitesimal is carried out to integration on blade, obtain acting on moment of torsion M on blade _n;

Step C: by obtain with reference to strain signal X (k);

Step 2: the matching of right to use vector initial value fitting algorithm obtains weight vector initial value V=[v ₀, v ₁..., v _n] ^tand W=[w ₀, w ₁..., w _n] ^t;

Step 3: upgrade wave filter weight coefficient, and export controlled quentity controlled variable;

Step 31: set k=1;

Step 32: upgrade initial value in input vector X (k): X (k) and respectively move to right one; Read in current input x (k), and X (k) [0]=x (k);

Step 33: read in error current signal e ₁(k), e ₂and e (k) ₃(k);

Step 34: upgrade two wave filter weight coefficients: concrete steps comprise:

Step 341: set i=0;

Step 342: according to formula calculating filter weight coefficient;

w ₁[i]=w ₁[i]-2*μ*e ₁(k)*g ₁[i];v ₁[i]=v ₁[i]-2*μ*e ₁(k)*f ₁[i]；

w ₂[i]=w ₂[i]-2*μ*e ₂(k)*g ₂[i];v ₂[i]=v ₂[i]-2*μ*e ₂(k)*f ₂[i]；

w ₃[i]=w ₃[i]-2*μ*e ₃(k)*g ₃[i];v ₃[i]=v ₃[i]-2*μ*e ₃(k)*f ₃[i]；

Step 343: make i=i+1;

Step 344: judge whether i is less than N+1; If so, perform step 342; No, perform step 35;

Step 35: calculating filter output:

Output vector F ₁(k), F ₂and F (k) ₃and G (k) ₁(k), G ₂and G (k) ₃(k) intermediate value respectively moves to right 1; Calculate current output value:

$f_1\left(k\right)=\underset{j=0}{\overset{N}{\mathrm{\Σ}}}{w}_{1j}\left(k\right)x(k-j);f_2\left(k\right)=\underset{j=0}{\overset{N}{\mathrm{\Σ}}}{w}_{2j}\left(k\right)x(k-j);f_3\left(k\right)=\underset{j=0}{\overset{N}{\mathrm{\Σ}}}{w}_{3j}\left(k\right)x(k-j);$

$g_1\left(k\right)=\underset{i=0}{\overset{N}{\mathrm{\Σ}}}{v}_{1i}\left(k\right)x(k-i);g_2\left(k\right)=\underset{i=0}{\overset{N}{\mathrm{\Σ}}}{v}_{2i}\left(k\right)x(k-i);g_3\left(k\right)=\underset{i=0}{\overset{N}{\mathrm{\Σ}}}{v}_{3i}\left(k\right)x(k-i);$

F ₁(k)[0]=f ₁(k);F ₂(k)[0]=f ₂(k);F ₃(k)[0]=f ₃(k);G ₁(k)[0]=g ₁(k);G ₂(k)[0]=g ₂(k);G ₃(k)[0]=g ₃(k)；

Step 36: output controlled quentity controlled variable F ₁(k) [0]=f ₁(k), F ₂(k) [0]=f ₂(k), F ₃(k) [0]=f ₃(k);

Step 37: make k=k+1, and judge whether k is less than 100000; If so, return to step 32; No, perform step 38;

Step 38: finishing control: end loop, by e ₁(k), e ₂(k), e ₃(k), f ₁(k), f ₂(k), f ₃(k), w ₁, w ₂, w ₃, v ₁, v ₂, v ₃writing in files is preserved.

7. the controlling method of the pneumatic equipment blades made vibration insulating system of a kind of ultra-magnetic telescopic flap configurations according to claim 6, is characterized in that, in described step 2, weight vector initial value fitting algorithm is determined weight vector initial value V=[v ₀, v ₁..., v _n] ^tand W=[w ₀, w ₁..., w _n] ^t; Weight vector initial value fitting algorithm, fixed time interval is 1ms, and the initial value of W is made as to the exponent number that 0, N is wave filter; The concrete fitting algorithm of weight vector initial value V comprises the following steps:

Step 21: initialization of variable, determine exponent number N and the step size mu of the first low-pass filter three road signals; Initialization error input vector ek _iand reference signal rk (k) _i(k), intermediate variable ek _i(k), ekk _i(k), r _i(k), sum _i, i=1,2,3;

Step 22:A/D Acquisition Error input signal and reference signal, set k=1

Step 23: if k=1,2 ..., 1000, carry out following step:

Intermediate variable ekk _i(k) cumulative ekk _i(k)=ekk _i(k)+ek _i(k);

If k=1001,1002 ..., 2000, carry out following step:

Step a:rk _i(k) in, initial value respectively moves to right one; Read in current input rk _i(k), upgrade r _i(k)=rk _i(k);

Step b: upgrade intermediate variable e _i(k)=ek _i() – ekk k _i(k);

Step c: cumulative intermediate variable sum _i+=w _i(k) * r _i(k);

Steps d: ask difference e rror _i(k)=ek _i() – sum k _i;

Step e: upgrade wave filter weight coefficient:

v _i(k)=v _i(k)-2*μ*error _i(k)*r _i(k)；

Step 24:k=k+1; Judge whether k is less than or equal to 2000, if so, return to step 23; Otherwise, execution step 25;

Step 25: finishing control: end loop, by v _iwriting in files is preserved, and forms weight vector initial value V.