CN107103398A - Flood discharge based on stochastic transition function method induces place vibration prediction method - Google Patents
Flood discharge based on stochastic transition function method induces place vibration prediction method Download PDFInfo
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Abstract
The present invention discloses a kind of flood discharge based on stochastic transition function method and induces place vibration prediction method, including：The measured signal of each single vibration source is filtered after processing, constitute many vibration source excitation source signals, as input signal, the measured signal for exporting measuring point is filtered after processing, output response signal is used as, based on the input signal and output response signal, transmission function is set up, the unbiased esti-mator method based on transmission function calculates the signal that predicts the outcome, the superimposed noise sequence on the basis of the signal that predicts the outcome, predicts the outcome as final.The Forecasting Methodology of the present invention is applied to the place vibration prediction of multiple activation source flow fluctuation load joint incentive input system, and it is more accurate to predict the outcome, and the anticipation that place vibration can be induced for flood discharge provides scientific basis with assessing.
Description
Technical field
Place vibration prediction method is induced the present invention relates to a kind of flood discharge based on stochastic transition function method, belongs to water conservancy water
Electrical engineering technical field.
Background technology
Place vibration repeated caused by high dam flood discharge and the duration is long, easily cause foundation liquefaction, building base
The harm such as plinth differential settlement, building masonry wall cracking.Normal work to precision instrument produces harmful effect, causes building
Quadratic noise is produced, is also easy to induce building generation resonance.Vibration can disturb the normal life of resident simultaneously, and body and mind is made
Into a certain degree of influence.Therefore, in the actual motion of power station, induce flood discharge place vibration and make prediction, anticipation place
Oscillation intensity, assesses the influence of shuttle belt, is the effective means for avoiding or reducing above-mentioned harm.
Place vibration prediction method based on measured data calculation of transfer function, due to can predict oscillation intensity and
Spectral characteristic, the advantages of quick on-line prediction can be carried out, the main means as the vibration of prediction place.But dam aerial drainage is lured
Various factors coupling power of hair place vibration " hydrodynamic load-dam body-stiling basin-ground-place " interaction with the influence of is asked
Topic, is predicted to place vibration and is related to：1) hydrodynamic load-aerial drainage Structure Interaction System；2) aerial drainage structure-big dam foundation
Plinth system with interaction；3) stratum vibration wave propagation systems, three subsystems interaction, mutual lotus root are closed, and, each subsystem
There is the influence of various disturbing factors and uncertain factor in vibration transmittance process so that high dam flood discharge induces place vibration problem
Complex.
The problems such as being vibrated in the past by transmission function to place is predicted, more by setting up single excitation and single response
Relational implementation, similar high dam flood discharge is induced the single response that place vibrated under this multiple activation source forcing export forecasting research compared with
It is few, place vibration prediction method still is induced without a kind of relatively reasonable flood discharge at present, accurately prediction knot can be obtained
Really.
The content of the invention
In view of the foregoing, place is induced it is an object of the invention to provide a kind of flood discharge based on stochastic transition function method
Vibration prediction method, is filtered after processing to the measured signal of each vibration source, constitutes many vibration source pumping signals and believes as input
Number, the measured signal for exporting measuring point is filtered after processing, as output response signal, transmission function is set up, based on transmission
The unbiased esti-mator of function calculates the signal that predicts the outcome, and noise correction is carried out in basis of signals predicting the outcome, as final
Predict the outcome, it is more accurate to predict the outcome, place vibration can be induced for flood discharge and makes anticipation and assessment.
To achieve the above object, the present invention uses following technical scheme：
A kind of flood discharge based on stochastic transition function method induces place vibration prediction method, including：
The measured signal of each single vibration source is filtered after processing, many vibration source excitation source signals is constituted, is used as input
Signal,
The measured signal for exporting measuring point is filtered after processing, as output response signal,
Based on the input signal and output response signal, transmission function is set up, the unbiased esti-mator method based on transmission function, meter
Calculation predicts the outcome signal,
The superimposed noise sequence on the basis of the signal that predicts the outcome, predicts the outcome as final.
It is described processing is filtered to measured signal method be：
S1：The construction white noise signal corresponding with the signal length of measured signal, carries out EEMD decomposition, calculating is made an uproar to it
Sound desired value ηj；
ηj=σj/σ1 (3)
Wherein, σjFor the standard deviation of j-th of IMF component, σ1For the standard deviation of the 1st IMF component；
Wherein, cj(k) it is j-th of IMF component,For cj(k) average, N is signal length；
S2：EEMD decomposition is carried out to measured signal, the standard deviation sigma of its each IMF component is calculatedj’；
S3：Calculate the noise criteria difference λ of each IMF components through the EEMD measured signals decomposedj；
Noise criteria difference λjCalculation formula be：
λj=ηjσ1` (4)
Wherein, j=2,3,4 ..., n, n be integer；
S4：Differentiate the noise contribution included in each IMF components of measured signal, work as λjEqual to or more than corresponding σj' when, will
J-th of IMF component is directly filtered out；Work as λjLess than corresponding σj' when, wavelet filter is carried out to j-th of IMF component.
The calculation formula of the wavelet filter is：
The variance of the noise sequence is：
Wherein, x is the output response signal before filtering process, and y is the output response signal after filtering process,For filtering
The variance of time series after processing,For the variance of the noise sequence after filtering process.
It is an advantage of the invention that：
1st, to each vibration source the EEMD and wavelet threshold that measured signal and the measured signal of output measuring point is improved join
The filtering noise reduction process of conjunction, can both effectively filter out white noise, and the useful component in vibration signal can be accurately retained again, improve place
The accuracy of vibration prediction；
2nd, many vibration source pumping signals are constituted after the filtered processing of the measured signal of each vibration source, is used as input signal, output
As output response signal after the filtered processing of measured signal of measuring point, transmission function is set up, the unbiased based on transmission function is estimated
Meter method carries out place vibration prediction, and the energy variation characteristic that can reflect exactly during the Vibration propagation of place passes through experiment
Checking, predicts that obtained place rumble spectrum characteristic is consistent or close with measured result；
3rd, predicted the outcome what transmission function was exported in basis of signals, carry out noise correction, place can be accurately reflected and shaken
Oscillation intensity variation characteristic in dynamic communication process；
4th, method of the invention is applied to the place vibration of multiple activation source flow fluctuation load joint incentive input system in advance
Survey, it is more accurate to predict the outcome, the anticipation that place vibration can be induced for flood discharge provides scientific basis with assessing.
Brief description of the drawings
Fig. 1 is the method flow schematic diagram of the present invention.
Fig. 2 is the signal amplitude schematic diagram of output using many vibration source pumping signals as input signal calculation of transfer function, input
Signal and the non-filtered processing of output response signal.
Fig. 3 is the schematic diagram of calculation result that coherence transfer function is calculated using many vibration source pumping signals as input signal, input
Signal and the non-filtered processing of output response signal.
Fig. 4 be using many vibration source pumping signals as input signal calculation of transfer function, carry out actual condition vibration prediction with
The time-histories Comparative result schematic diagram of measured result.
Fig. 5 A are the vibration predictions that actual condition is carried out using many vibration source pumping signals as input signal calculation of transfer function
Fourier spectrum schematic diagram of calculation result；
Fig. 5 B are the Fourier spectrum schematic diagram of calculation result of the measured result of actual condition shown in Fig. 5 A.
Fig. 6 is the white noise group that energy is identical, signal length is different that the present invention is constructed, ratio ηjWith the pass between N values
It is schematic diagram.
Fig. 7 is energy difference, the signal length identical white noise group, ratio η that the present invention is constructedjWith the pass between i values
It is schematic diagram.
Fig. 8 is that predict the outcome letter using method progress actual condition prediction of the invention, the amplitude schematic diagram of prediction signal
Number it is not added with noise sequence.
Fig. 9 is that predict the outcome letter using method progress actual condition prediction of the invention, the frequency diagram of prediction signal
Number it is not added with noise sequence.
Figure 10 is to carry out actual condition prediction, the time-histories result pair predicted the outcome with measured result using the method for the present invention
Compare schematic diagram.
Figure 11 A are to carry out actual condition prediction, the Fourier spectrum result of calculation predicted the outcome using the method for the present invention
Schematic diagram.
Under Figure 11 B are actual condition shown in Figure 11 A, the Fourier spectrum schematic diagram of calculation result of measured result.
Figure 12,13 are, using method of the invention, the result being predicted to be vibrated to Xiangjiabahydropower project T9 measuring points place
Schematic diagram.
Embodiment
Below in conjunction with drawings and examples, the present invention is described in further detail.
As shown in figure 1, the flood discharge disclosed by the invention based on stochastic transition function method induces place vibration prediction method, bag
Include：Using improved EEMD and wavelet filter method, the measured signal for inducing flood discharge each single vibration source in place enters
After row filtering process, many vibration source pumping signals are constituted, input signal is used as；The measured signal of any point near place is carried out
After filtering process, as output response signal, transmission function is set up based on the input signal and output response signal, based on transmission
The unbiased esti-mator method of function carries out place vibration prediction, and noise sequence is added on the basis of the output signal of transmission function to carry out
Noise correction, predicts the outcome as final.Specifically：
First, many vibration source pumping signals using flood discharge place is input signals, and the measured signal of any point (shakes near place
Dynamic signal) it is output response signal, transmission function is set up, the unbiased esti-mator method based on transmission function carries out place vibration prediction.
Using whole Ba Qu as the input of transmission function system, the vertical acceleration vibration signal of all driving sources is joined
Cooperate the input signal for transmission function, nearby optional position is used as output measuring point to selection Ba Qu.Due to the collection of vibration signal
Occur simultaneously, therefore use time domain stacking method, the vibration signal of all vibration sources is overlapped as many vibration source pumping signals.
In a specific embodiment, many vibration source pumping signals under 12 identical flood discharge operating modes are chosen as input signal, place is specific
The vertical acceleration vibration signal of measuring point is as output response signal, according to the unbiased esti-mator method H of transmission functionn, passed
Delivery function Hn1。
As shown in Fig. 2 in terms of the amplitude evolution in vibration transmittance process, transfer function Hn1In 0~10.0Hz frequency ranges
Amplitude is larger, peak value occurs at 5.0Hz or so places, and there is also larger peak value, explanation at 18.5Hz, 22.0Hz and 29.5Hz
Place vibration has amplification at these frequencies；Transfer function Hn1Occur small energy peak always in 0~40.0Hz, it is and many
The interference that vibration source pumping signal joint input is subject to is larger relevant.As shown in figure 3, being calculated from relevant transferometer in terms of result, 0
~15.0Hz frequency ranges, transfer function Hn1Coherence factor between 0.1~0.6, in 20.0~40.0Hz frequency ranges, coherence factor
It is overall to have reduced, but there is higher value at some frequencies.As can be seen that signal is affected by noise larger, accordingly, it is difficult to directly
Connect the vibration acceleration size degree for showing that a certain frequency range aerial drainage excitation load is delivered to place ground.
A certain flood discharge operating mode is chosen, the vertical vibration situation to specific measuring point is predicted.As shown in figure 4, from time-histories knot
Fruit comparison diagram can be seen that the amplitude that predicts the outcome and be significantly greater than prototype measurement result, as shown in Fig. 5 A, 5B, calculates and ties from frequency spectrum
Fruit comparison diagram can be seen that the vibration frequency of prediction compared with measured result, in low frequency, high frequency treatment, many many energy peaks,
Measured result signal only has dominant frequency band at 0~6.0Hz mono-, peak value occurs at 8.0Hz or so places, and the signal that predicts the outcome has 0
Two dominant frequency bands of~6.0Hz and 8.0~12.0Hz.
Analyzed from above experimental result data, from the frequency spectrum of transmission function with from the point of view of distribution of amplitudes, many vibration sources are encouraged
Combined signal as transmission function input signal when, the noise jamming of each single vibration source is larger, and the phase between each transmission system
Mutually influence generates more interference, and vibration caused by non-vibration source is exaggerated, predicts the outcome and differ larger with measured result, such a
In the case of predict the outcome it is unsatisfactory.Due to flood discharge excitation category broadband arbitrary excitation, and with the change of different flood discharge operating modes
And change, that is, the transmission function for vibrating transmission is random, and it is exactly that noise is asked to analyze one of the biggest problem of stochastic transition function
Topic, thus, if can solve the problem that the noise problem of stochastic transition function, the influence factors such as noise are effectively filtered out, will be effectively improved
What place vibrated predicts the outcome.
2nd, using improved EEMD and wavelet filter method, the measured signal of each single vibration source is filtered
After processing, many vibration source pumping signals after composition noise reduction filtering processing are used as input signal；The measured signal for exporting measuring point is entered
After row filtering process, as output response signal, transmission function is set up based on the input signal and output response signal.
Low-frequency disturbance and white noise are often mixed with actual measurement hydro-structure vibratory response, by carrying out EEMD to measured signal
Decompose, low-frequency noise is generally present in rear a few rank IMF components, filters out and be relatively easy to.And white noise will be with useful signal
Decompose, be present in former rank IMF components, to ensure the integrality of signal, wavelet threshold filter need to be carried out to former rank IMF components
Ripple, remains with and uses signal component as far as possible.
Because the noise being mixed into measured signal is unknown, the standard variance of noise can only be an estimate, seriously
It has impact on the accuracy and confidence of wavelet filter.It therefore, it can utilize white noise EEMD resolution characteristics, determine that former ranks contain
The noise criteria made an uproar in IMF components is poor.
Define σjFor the standard deviation of j-th of IMF component, then：
In formula, cj(k) j-th of IMF component after being decomposed for signal through EEMD,For cj(k) average, N is signal acquisition
Length.
White noise is constructed using the random matrix randn (m, n) of normal distribution.Definition：
si=2i× randn (N, 1) (2)
Wherein, i=0,1,2,3 ..., m, 2iWhite noise sound intensity is represented, N is the length of signal acquisition, carries out hydro-structure
Or during the Vibration Prototype Observation of place, N generally takes 1000~60000.According to formula (2), different N values and i values is combined, can construct
Go out the white noise signal group of different length, different-energy.
1) construction energy is identical, the different white noise group of signal length.
By taking i=1 as an example, i=1, N=1000,2000 ..., 10000,20000 ..., 60000 are made, according to formula (2) structure
Make white noise signal group.
Each white noise signal therein, ratio calculated η are decomposed using EEMDj：
ηj=σj/σ1 (3)
Wherein, σjFor the standard deviation of j-th of IMF component, σ1For the standard deviation of the 1st IMF component.As shown in fig. 6, working as N=
When 1000~10000, ratio ηjAmplitude of variation is larger, as N ＞ 10000, ratio ηjAmplitude of variation reduces.
2) construction energy is different, signal length identical white noise group.
By taking N=20000 as an example, i=0~9, N=20000 is made, white noise signal group is constructed according to formula (2).
Each white noise signal therein is decomposed using EEMD, formula (3) ratio calculated η is utilizedj.As shown in fig. 7, working as signal
The timing of length one, the ratio η of the different white noise signal of energyjSubstantially constant.
It can be seen that, after the signal length for determining white noise, the white noise signal of different-energy decomposed through EEMD after ratio ηj
It is basicly stable, or fluctuated in the range of very little.
Based on above-mentioned experimental calculation and analysis result, (the actual measurement letter of each single vibration source is included to the measured signal of collection
Number and the output of specific measuring point measured signal) process that is filtered processing comprises the following steps：
S1：The construction white noise signal corresponding with the signal length of measured signal, is carried out to the white noise signal of construction
EEMD is decomposed, and passes through formula (3) ratio calculated ηj, it is used as the noise objective for evaluating the noise level in IMF components；
S2：EEMD decomposition is carried out to measured signal, the standard deviation sigma of its each IMF component is calculatedj’；
S3：Calculate the noise criteria difference λ of each IMF components through the EEMD measured signals decomposedj；
Generally, after the measured signal comprising white noise is decomposed through EEMD, first all white noise of IMF components
Component, therefore, the noise criteria difference λ of each IMF componentsjIt can be identified as：
λj=ηjσ1` (4)
Wherein, j=2,3,4 ..., n, n be integer.
S4：According to the standard deviation sigma of each IMF components of measured signalj' with the noise criteria difference λ of each IMF components of measured signalj's
Relation, differentiates the noise contribution included in each IMF components, and carry out corresponding filtering process.
Specifically, working as λjEqual to or more than corresponding σj' when, illustrate j-th of all noise component(s) of IMF components, can be with
Directly filter out；Work as λjLess than corresponding σj' when, illustrate to contain useful signal in j-th of IMF component, tackle j-th of IMF points
Amount carries out wavelet filter, and the former calculation formula of wavelet filter is：
Wherein, σ is the standard deviation of noise, and value is λ herej, N is signal length, is obtained：
The measured signal of each single vibration source of collection is filtered after processing using above-mentioned filter processing method, constituted
Many vibration source pumping signals are carried out as input signal using above-mentioned filter processing method to the measured signal of the output measuring point of collection
Filtering process, as output response signal, based on the input signal and output response signal, sets up transmission function, based on transmission
The unbiased esti-mator method of function, carries out the prediction of place vibration.Because input signal and output response signal pass through filtering process
Eliminate noise and environmental impact factor so that the transmission function of foundation is more accurate, predicts the outcome in mode of vibration (by frequency spectrum
Angle embody) aspect it is more accurate.
3rd, transmission function is set up based on above-mentioned Article 2, the unbiased esti-mator method based on transmission function, calculating obtains prediction knot
Superimposed noise sequence on the basis of fruit signal, the signal that predicts the outcome herein, predicts the outcome as final.
The transmission function of foregoing foundation, its input signal is handled after filtering with output response signal, has filtered out noise
And such environmental effects, the spectral characteristic predicted the outcome is closer to the spectral characteristic of prototype measurement, and the vibration predicted the outcome
Intensity is less than the oscillation intensity of prototype measurement.Therefore, transmission function can be added to according to signal to noise ratio formula construction noise sequence
In the signal that predicts the outcome of output, reduction input, influence of the output end filtering process to vibration amplitude precision of prediction.Filtering process
The signal to noise ratio of output response signal afterwards is：
Wherein, x is the output response signal before filtering process, and y is the output response signal after filtering process,For filtering
The variance of time series after processing,For the variance of the noise sequence after filtering process.Therefore, noise sequence variance can be represented
For：
By the noise sequence of construction, in the signal that predicts the outcome for being added to transmission function output, final prediction knot is used as
Really so that predict the outcome in terms of mode of vibration, oscillation intensity closer to prototype measurement result, predict the outcome and be relatively defined
Really.
4th, the checking of method
To 12 identical operating modes, using aperture, fall bank, lead wall, the power that disappears bottom plate, at end sill as input measuring point, with specific measuring point
T9 is the vibration signal of output measuring point, respectively collection input measuring point and output measuring point, using the EEMD and small echo threshold of aforementioned improved
Value filtering method is filtered processing respectively, and the measured signal of each input measuring point is filtered after processing, and superposition composition to shake
Source forcing source, as input signal, is filtered as output response signal after processing to the measured signal for exporting measuring point, sets up
Transfer function Hn3, the unbiased esti-mator method based on transmission function, progress place vibration.
As shown in Figure 8,9, transfer function Hn3Coherence factor in 0~8.0Hz highests, reach peak value in 3.0Hz or so, say
Bright energy loses less in the frequency range transmittance process, and coherence factor is gradually reduced after 10.0Hz.From vibration transmittance process
In amplitude evolution see, transfer function Hn3Occurring obvious peak value at 2.8Hz, main transmission energy concentrates on 1.0~
4.0Hz is interval, also has a small amount of peak Distribution in high frequency treatment.It can be seen that, pass through the input signal after filtering process and output response letter
Number transmission function set up, vibration prediction result more meets measured result.
Predicted the outcome what above-mentioned transmission function was exported in basis of signals, calculated using formula (8) and obtain noise sequence standard
Difference, to specific measuring point T9 predict the outcome signal addition noise sequence, obtain final time-histories predict the outcome (shown in Figure 10) and
Spectrum prediction result (shown in Figure 11 A, 11B), as illustrated, method under this invention, can accurately predict place vibration
Dominant frequency, meanwhile, in 0~10.0Hz frequency ranges, the place rumble spectrum distribution predicted the outcome with measured result is quite similar, and
And, it with the addition of the amplitude prediction result after noise sequence and coincide preferably with actual observation result.
Using the method for the present invention, 2013~2015 years Xiangjiabahydropower project T9 measuring points place Vibration Conditions are carried out pre-
Survey, as shown in Figure 12,13, T9 measuring points predict the outcome and measured result coincide it is preferable：First, oscillation intensity is on the whole with the power that disappears
Pond inflow-rate of water turbine increases and increased；Secondly, oscillation intensity is more sensitive to flood discharge mode, and the different flood discharge modes of same aerial drainage operating mode are shaken
Fatigue resistance is otherwise varied.
The technical principle described above for being presently preferred embodiments of the present invention and its being used, for those skilled in the art
For, without departing from the spirit and scope of the present invention, any equivalent change based on the basis of technical solution of the present invention
Change, simply replacement etc. obviously changes, belong within the scope of the present invention.
Claims (4)
1. the flood discharge based on stochastic transition function method induces place vibration prediction method, it is characterised in that including：
The measured signal of each single vibration source is filtered after processing, many vibration source excitation source signals are constituted, as input signal,
The measured signal for exporting measuring point is filtered after processing, as output response signal,
Based on the input signal and output response signal, transmission function is set up, the unbiased esti-mator method based on transmission function calculates pre-
Survey consequential signal,
The superimposed noise sequence on the basis of the signal that predicts the outcome, predicts the outcome as final.
2. the flood discharge according to claim 1 based on stochastic transition function method induces place vibration prediction method, its feature
Be, it is described processing is filtered to measured signal method be：
S1：The construction white noise signal corresponding with the signal length of measured signal, EEMD decomposition is carried out to it, is calculated noise and is referred to
Scale value ηj；
ηj=σj/σ1 (3)
Wherein, σjFor the standard deviation of j-th of IMF component, σ1For the standard deviation of the 1st IMF component；
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S2：EEMD decomposition is carried out to measured signal, the standard deviation sigma of its each IMF component is calculatedj’；
S3：Calculate the noise criteria difference λ of each IMF components through the EEMD measured signals decomposedj；
Noise criteria difference λjCalculation formula be：
λj=ηjσ1` (4)
Wherein, j=2,3,4 ..., n, n be integer；
S4：Differentiate the noise contribution included in each IMF components of measured signal, work as λjEqual to or more than corresponding σj' when, by the jth
Individual IMF components are directly filtered out；Work as λjLess than corresponding σj' when, wavelet filter is carried out to j-th of IMF component.
3. the flood discharge according to claim 2 based on stochastic transition function method induces place vibration prediction method, its feature
It is, the calculation formula of the wavelet filter is：
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4. the flood discharge according to claim 1 based on stochastic transition function method induces place vibration prediction method, its feature
It is, the variance of the noise sequence is：
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Priority Applications (1)
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| CN104614144A (en) * | 2015-03-04 | 2015-05-13 | 水利部交通运输部国家能源局南京水利科学研究院 | Method for predicting soil vibration caused by flood discharge and energy dissipation |
| CN106250653A (en) * | 2016-08-16 | 2016-12-21 | 北京交通大学 | A kind of full information high accuracy transmission function prediction method |
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| CN104614144A (en) * | 2015-03-04 | 2015-05-13 | 水利部交通运输部国家能源局南京水利科学研究院 | Method for predicting soil vibration caused by flood discharge and energy dissipation |
| CN106250653A (en) * | 2016-08-16 | 2016-12-21 | 北京交通大学 | A kind of full information high accuracy transmission function prediction method |
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| 张龑: "《高坝泄洪诱发场地振动振源特性与传播规律研究》", 《中国博士学位论文全文数据库 工程科技Ⅱ辑》 * |
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