CN106650194A - Evaluation method for static load performance of railway steel bridge based on static strain extremum prediction - Google Patents
Evaluation method for static load performance of railway steel bridge based on static strain extremum prediction Download PDFInfo
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Abstract
The invention discloses an evaluation method for a static load performance of a railway steel bridge based on a static strain extremum prediction, which relates to an evaluation field of the static load performance of the railway steel bridge. The evaluation method for the static load performance of the railway steel bridge based on the static strain extremum prediction includes the following steps. 1) Strain data of the least favored area of key components of the railway steel bridge is collected. 2) Static strain constituents of the strain data is extracted by utilizing a wavelet packet analysis method. 3) A diurnal variation extremum of the static strain constituents is obtained by using a first-order difference. 4) A cumulative distribution character of the diurnal variation extremum is fitted through using a generalized extremum value distribution function. 5) The static load performance of the least favored stress area of the key components of the railway steel bridge is evaluated. The evaluation method for the static load performance of the railway steel bridge based on the static strain extremum prediction can effectively avoid that a strain maximum or a strain minimum is not the strain extremum, and make extracted strain extremum data more accurate, and guarantee uniqueness of probabilistic statistical characteristics of the strain extremum.
Description
Technical field
The present invention relates to railway steel bridge static behavior evaluation areas, and in particular to a kind of ferrum based on static strain prediction of extremum
Road steel bridge static behavior appraisal procedure.
Background technology
The static behavior of railway steel bridge is directly connected to the operation security of railroad train, if the railway under environmental load effect
The key member of steel bridge fails to find in time and renovate more than maximum permissible value, can be extremely dangerous, or even the disconnected car of generation beam is ruined
Catastrophic event, therefore carry out railway steel bridge static behavior evaluation work it is significant.
At present, existing research worker carries out emphasis monitoring for the strain regime of railway steel bridge key member, and chooses
The strain extreme value of Monitoring Data compares with Design Theory maximum, so as to judge the static behavior of railway steel bridge at this stage.But
There is a shortcoming in a kind of this method, i.e., the strain extreme value of limited Monitoring Data can not represent railway steel bridge within the whole operation phase
Strain extreme value, therefore cannot realize the static behavior to railroad bridge in whole service phase assess.Separately there is research worker
Attempting the static behavior using the probabilistic statistical characteristicses of Monitoring Data strain extreme value to railroad bridge in whole service phase is carried out
Assess, but the method still suffers from two problems and has to be solved：(1) the strain extreme value for being adopted is the maximum of one day planted agent's varied curve
Value and minima, but the maximum and minima not necessarily extreme value of one day planted agent's varied curve, that is, be likely to be strain curve
Endpoint value, therefore extract strain extreme value data it is not accurate enough；(2) probabilistic statistical characteristicses for straining extreme value adopt probability density
Function is describing, but probability density function is relevant with the post bar width of strain extreme value probability density histogram, causes probability close
Degree function loses uniqueness.
The content of the invention
For defect present in prior art, it is an object of the invention to provide a kind of title.
To reach object above, the present invention is adopted the technical scheme that：A kind of rail iron based on static strain prediction of extremum
Bridge static behavior appraisal procedure, the method comprises the steps,
Step a. gathered the strain data of railroad bridge key member stress most unfavorable combination within L days sampling time；
Step b. extracts the static strain composition in the strain data using analysis method of wavelet packet；
Step c. is divided in units of day to the static strain composition, to all static strain values in daily according to adopting
Collection sequencing does first-order difference process, static strain value is obtained in daily difference sequence, by the difference sequence in every day
Row are arbitrarily divided into many parts, and every a difference sequence is each sued for peace, then the summation to every a difference sequence
As a result take absolute value and be added and try to achieve summation, compare in the case of segmentation number identical described in trying to achieve under different cut-points
The size of summation, cut-point when determining that the summation is maximum, segmentation of the comparison difference sequence when the summation is maximum
Size under point, so that it is determined that diurnal variation maximum and diurnal variation minimum in the interior static strain composition daily, and then determine
And diurnal variation maximum D in the static strain composition in the relatively more described L days sampling timeMAXWith diurnal variation minimum DMIN；
Step d. utilizes generalized extreme value distribution function G (DMAX) and F (DMIN) be fitted respectively it is described in the L days sampling time
Diurnal variation maximum D in static strain compositionMAXWith diurnal variation minimum DMINCumulative distribution character：
Step e. carries out static behavior assessment to the railroad bridge key member stress most unfavorable combination：Wherein,
In formula, P is outcross probability, using Newton iteration method and with reference to the generalized extreme value distribution function G (DMAX) and F
(DMIN), solving equation (4) and equation (5), static strain standard value when determining that outcross probability is PWith
WithRepresentWithIn maximum absolute value person, willWith design permissible valueFerrum described in multilevel iudge
The static behavior of road and bridge beam, ifThen the static behavior of the railroad bridge key member stress most unfavorable combination is in
Safe condition；Conversely, then the static behavior of the railroad bridge key member stress most unfavorable combination is in non-secure states.
On the basis of above-mentioned technical proposal, the strain is gathered using fiber Bragg grating strain sensor in step a
Data, and using fiber-optical grating temperature sensor as temperature-compensating.
On the basis of above-mentioned technical proposal, sampling time L is more than 200 days in step a, and sample frequency is more than 1/
600Hz is less than 1Hz.
On the basis of above-mentioned technical proposal, the analysis method of wavelet packet specifically include by collect it is all described should
Become data and constitute strain sequence according to collection sequencing, after the strain sequence is carried out into wavelet packet on c-th yardstick point
Solution, obtains 2cIndividual wavelet packet coefficient, extracts first wavelet packet coefficient and is reconstructed, and obtains quiet in the strain sequence
Strain composition, wherein c is measurement point number coefficient.
On the basis of above-mentioned technical proposal, the measurement point number coefficient c is equal to 5.
On the basis of above-mentioned technical proposal, the difference sequence of the every day in step c is arbitrarily divided into three parts.
On the basis of above-mentioned technical proposal, diurnal variation maximum in the static strain composition in the L days sampling time
DMAXThe fitting of cumulative distribution character include, calculate diurnal variation maximum DMAXAccumulated probability value, and using described wide
Adopted Extremal distribution function G (DMAX) it is fitted, wherein：
In formula, b, d and r represent respectively G (DMAX) scale parameter, location parameter and form parameter, the day tried to achieve will be calculated
Change maximum DMAXWith diurnal variation maximum DMAXAccumulated probability value substitute into respectively in formula (2), using method of least square determine
The optimal value of b, d and r；
Diurnal variation minimum D in the static strain composition in the L days sampling timeMINCumulative distribution character fitting
Including calculating diurnal variation minimum DMINAccumulated probability value, and using the generalized extreme value distribution function F (DMIN) to it
Fitting, wherein
In formula, g, h and λ represent respectively F (DMIN) scale parameter, location parameter and form parameter, the day tried to achieve will be calculated
Change very little value DMINWith diurnal variation minimum DMINAccumulated probability value substitute into respectively in formula (3), using method of least square determine
The optimal value of g, h and λ；
On the basis of above-mentioned technical proposal, the value of the outcross probability P is 0.01.
Compared with prior art, it is an advantage of the current invention that：
(1) the railway steel bridge static behavior appraisal procedure based on static strain prediction of extremum in the present invention, it utilizes single order
Difference determine strain extreme value, so as to be prevented effectively from strain maximum or minima be not strain extreme value situation so that extraction
Strain extreme value data are more accurate.
(2) the railway steel bridge static behavior appraisal procedure based on static strain prediction of extremum in the present invention, it is using cumulative
Probit overcomes probabilistic statistical characteristicses in traditional method does not have the shortcoming of uniqueness, it is ensured that strain extreme value probabilistic statistical characteristicses
Uniqueness, and this method more can accurately and effectively to railroad bridge in whole service phase static behavior assessment, can obtain
To being widely popularized and apply.
Description of the drawings
The flow chart of appraisal procedure during Fig. 1 is of the invention；
Fig. 2 is the elevation of Foundations of Dashengguan Changjiang River Bridge in the embodiment of the present invention；
Fig. 3 is the position of fiber Bragg grating strain sensor in the embodiment of the present invention；
Fig. 4 is the strain sequence that all strain values are constituted according to collection sequencing in the embodiment of the present invention；
Fig. 5 is that the static strain composition in sequence is strained in the embodiment of the present invention；
Fig. 6 is the change curve of diurnal variation maximum in the embodiment of the present invention；
Fig. 7 is the minimizing change curve of diurnal variation in the embodiment of the present invention；
Fig. 8 is the fitting result of diurnal variation maximum generalized extreme value distribution in the embodiment of the present invention；
Fig. 9 is the fitting result of diurnal variation minimum generalized extreme value distribution in the embodiment of the present invention.
In figure：1- top booms, 2- fiber-optical grating temperature sensors.
Specific embodiment
The present invention is described in further detail below in conjunction with drawings and Examples.
The present invention provides a kind of railway steel bridge static behavior appraisal procedure based on static strain prediction of extremum, referring to Fig. 1 institutes
The flow chart for showing, the method is comprised the following steps：
Step a. carries out strain data collection to the most unfavorable combination of railroad bridge key member：
The present invention is coupled to fiber Bragg grating strain sensor in data collecting system, and with fiber-optical grating temperature sensor
As temperature-compensating, data acquisition is carried out to the most unfavorable combination of railroad bridge key member, stress most unfavorable combination is referred to
Bridge force-bearing is maximum, at most concentration or bridge structure is easily destroyed the most place.Sample frequency is expressed as fHz, sampling time length
Represented with L, i-th strain value for collecting is represented using S (i), i=1 ..., M, M are strain value total number.Wherein, sample
Frequency is less than 1Hz more than 1/600Hz, and sampling time L is more than 200 days.
Step b. extracts the static strain composition in strain data using analysis method of wavelet packet：
Because strain data is substantially disturbed by train load, hence with analysis method of wavelet packet dependent variable is extracted
Not by the static strain composition of train load interference according in.Wherein analysis method of wavelet packet is a kind of the conventional of signal disposal and analysis
Method, can be adaptive selected frequency band and match with signal spectrum according to characteristics of signals and analysis requirement, be a kind of essence
Thin signal decomposition method, its concrete operations is：All strain values S (i) for collecting are constituted according to collection sequencing should
Become sequence, after strain sequence is carried out on c-th yardstick WAVELET PACKET DECOMPOSITION, obtain 2cIndividual wavelet packet coefficient, extracts first
Individual wavelet packet coefficient is simultaneously reconstructed, and obtains straining the static strain composition in sequence, and wherein c is measurement point number coefficient.
Step c. obtains the diurnal variation extreme value in static strain composition using first-order difference：
1. static strain composition is divided in units of day, j-th static strain value of the static strain composition in the m days is adopted
Use SmJ () represents, wherein m=1,2 ..., L, j=1,2 ..., Nm, NmFor total number of the static strain value in the m days.
2. pair all static strain values interior daily are done first-order difference and are processed according to collection sequencing, and first-order difference process refers to
Be continuous adjacent two in static strain value difference, so as to obtain difference sequence of the static strain value in daily.Wherein difference sequence
K-th value being listed in the m days adopts DmK () represents, k=1,2 ..., Nm-1。
3. the difference sequence of every day can be arbitrarily divided into as needed many parts, and the difference sequence in the present invention is divided
Three parts are segmented into, it is of the invention by the difference sequence { D in the m days in order to conclude explanationm(1),Dm(2),...,Dm(Nm- 1) } split
For three parts, wherein first part of difference sequence is { Dm(1),Dm(2),...,Dm(p1,m), second part of difference sequence is { Dm(p1,m+
1),Dm(p1,m+2),...,Dm(p1,m+p2,m), the 3rd part of difference sequence is { Dm(p2,m+1),Dm(p2,m+2),...,Dm(Nm-
1) }, wherein p1,m、p2,mTwo cut-points of difference sequence in respectively the m days, and meet 1 ＜ p1,m＜ p2,m＜ Nm-1。
4. all values summation in pair three parts of difference sequences, uses Zm,l(p1,m,p2,m) represent that value is p in the m days1,m,p2,m
When l part difference sequence sums, wherein l=1,2,3, then according to following formula tries to achieve Zm,1(p1,m,p2,m)、Zm,2(p1,m,p2,m) and
Zm,3(p1,m,p2,m) three's sum：
Qm(p1,m,p2,m)=| Zm,1(p1,m,p2,m)|+|Zm,2(p1,m,p2,m)|+|Zm,3(p1,m,p2,m)| (1)
In formula, Qm(p1,m,p2,m) result of calculation and p1,m, p2,mValue is relevant, to p1,m, p2,mIt is chosen at the ＜ p of constraints 11,m
＜ p2,m＜ NmAll possible value under -1, substitutes in formula (1) and calculates corresponding Qm(p1,m,p2,m) value, all Qm(p1,m,
p2,m) maximum is certainly existed in value, it is assumed that this maximum is by p1,m=a1,m、p2,m=a2,mObtain, then in the m days
Diurnal variation maximum in static strain composition is Dm(a1,m) and Dm(a2,m) both in higher value, diurnal variation minimum be Dm
(a1,m) and Dm(a2,m) both in smaller value, in the diurnal variation maximum determined in the m days in static strain composition and minimum
After value, by relatively more daily diurnal variation maximum and minimum, so that it is determined that the diurnal variation maximum in all natural law L and
Minimum, wherein the diurnal variation maximum in all natural law L adopts DMAXRepresent, the diurnal variation minimum of all natural law L is adopted
DMINRepresent.
The present invention determines strain extreme value using first-order difference, is not strain so as to be prevented effectively from strain maximum or minima
The situation of extreme value so that the strain extreme value data of extraction are more accurate.
Step d. utilizes the cumulative distribution character of generalized extreme value distribution Function Fitting diurnal variation extreme value：
1. diurnal variation maximum D is calculatedMAXAccumulated probability value, stochastic finite element theory in, accumulated probability value determine
Justice is less than the probability of happening of a certain numerical value for statistical variable, and using its fitting of generalized extreme value distribution function pair：
In formula, G (DMAX) represent generalized extreme value distribution function, b, d and r represent respectively G (DMAX) scale parameter, position
Parameter and form parameter, will calculate the diurnal variation maximum and diurnal variation maximum D tried to achieveMAXAccumulated probability value substitute into respectively
Determine the optimal value of b, d and r in formula (2) and using method of least square；
2. the minimizing accumulated probability value of diurnal variation is calculated, and using its fitting of generalized extreme value distribution function pair：
In formula, F (DMIN) represent generalized extreme value distribution function, g, h and λ represent respectively F (DMIN) scale parameter, position
Parameter and form parameter, will calculate the diurnal variation minimum and diurnal variation minimum D tried to achieveMINAccumulated probability value substitute into respectively
Determine the optimal value of g, h and λ in formula (3) and using method of least square.
Step e. carries out static behavior assessment to the railroad bridge key member stress most unfavorable combination：
Using Newton iteration method solving equation (4) and equation (5), static strain standard value when determining that outcross probability is PWithOutcross probability refers to over a period to come, possible to meet with the probability for being more than or equal to given parameters value.
WithRepresentWithIn maximum absolute value person, willWith design permissible valueFerrum described in multilevel iudge
The static behavior of road and bridge beam, ifThen the static behavior of the railroad bridge key member stress most unfavorable combination is in
Safe condition；Conversely, then the static behavior of the railroad bridge key member stress most unfavorable combination is in non-secure states.
Newton iteration method is a kind of important method of solving equation root, its great advantage be equation or it is single near put down
Side's convergence；100 years design service phases according to railroad bridge consider that the value of outcross probability P is 0.01.
Below by taking the chord member axial strain of Foundations of Dashengguan Changjiang River Bridge as an example, the specific implementation process of the present invention is illustrated.
The elevation of Foundations of Dashengguan Changjiang River Bridge shown in Figure 2, and the set of fiber Bragg grating strain sensor cloth shown in Fig. 3
Schematic diagram is put, fiber Bragg grating strain sensor 2 is arranged on into the axial location of Foundations of Dashengguan Changjiang River Bridge span centre side purlin top boom 1,
And be coupled in data collecting system, using the temperature sensor of fiber grating as temperature-compensating, the axial strain of top boom 1 is entered
Row data acquisition.Sample frequency f is 1Hz, and sampling time length L is 232 days, and i-th strain value for collecting adopts S (i) tables
Show, i=1 ..., 33408.
Shown in Figure 4, it is all strain values S (i) of Foundations of Dashengguan Changjiang River Bridge according to answering that collection sequencing is constituted
Become sequence.
It is shown in Figure 5, strain sequence is carried out the WAVELET PACKET DECOMPOSITION on the 5th yardstick, 32 wavelet packet coefficients are obtained,
Extract first wavelet packet coefficient and be reconstructed, obtain straining the static strain composition in sequence.
Static strain composition is divided in units of day, j-th static strain value of the static strain composition in the m days is adopted
SmJ () represents, wherein m=1,2 ..., 232, j=1,2 ..., 144.It is first according to collection to all static strain values in daily
First-order difference process is sequentially done afterwards, obtains difference sequence of the static strain value in daily, k-th in the m days of difference sequence
Value adopts DmK () represents, k=1,2 ..., 143.
The the 3rd and the 4th step in above-mentioned steps c determines diurnal variation maximum D in 232 daysMAXWith diurnal variation minimum
DMIN, respectively referring to shown in Fig. 6 and Fig. 7.According to correlation computations step in step d, using method of least square determine b, d and r and
The optimal parameter value of g, h and λ, wherein b=41.3228, d=33.0127, r=-0.4071；G=54.4519, h=-
24.6663rd, λ=- 0.612298, substitute into each numerical computations obtain diurnal variation maximum generalized extreme value distribution fitting result and
The fitting result of diurnal variation minimum generalized extreme value distribution, respectively referring to shown in Fig. 8 and Fig. 9.
The equation (4) in above-mentioned steps e and equation (5) are solved using Newton iteration method, it is determined that having outcross probability to be P
Static strain standard valueWithWherein：Outcross probability P is 0.01.
Result of calculation is：Then chooseWithIn maximum absolutely
To being worth, i.e.,WillWith design permissible valueThe static load of multilevel iudge railroad bridge
Performance：Known pass railroad bridge steel of winning completely select Q420, thenUnderstandThen the static behavior of key member stress most unfavorable combination is in a safe condition.
The present invention is not limited to above-mentioned embodiment, for those skilled in the art, without departing from
On the premise of the principle of the invention, some improvements and modifications can also be made, these improvements and modifications are also considered as the protection of the present invention
Within the scope of.The content not being described in detail in this specification belongs to prior art known to professional and technical personnel in the field.
Claims (8)
1. a kind of railway steel bridge static behavior appraisal procedure based on static strain prediction of extremum, it is characterised in that：The method includes
Following steps,
Step a. gathered the strain data of railroad bridge key member stress most unfavorable combination within L days sampling time；
Step b. extracts the static strain composition in the strain data using analysis method of wavelet packet；
Step c. is divided in units of day to the static strain composition, first according to collection to all static strain values in daily
First-order difference process is sequentially done afterwards, static strain value is obtained in daily difference sequence, and the difference sequence in every day is appointed
Meaning is divided into many parts, and every a difference sequence is each sued for peace, then the summed result to every a difference sequence
Take absolute value and be added and try to achieve summation, the summation tried to achieve under different cut-points is compared in the case of segmentation number identical
Size, cut-point when determining that the summation is maximum, under cut-point of the comparison difference sequence when the summation is maximum
Size, so that it is determined that diurnal variation maximum and diurnal variation minimum in the static strain composition in daily, and then determine and compare
Diurnal variation maximum D in the static strain composition in the L days sampling timeMAXWith diurnal variation minimum DMIN；
Step d. utilizes generalized extreme value distribution function G (DMAX) and F (DMIN) be fitted respectively in the L days sampling time it is described it is quiet should
Become diurnal variation maximum D in compositionMAXWith diurnal variation minimum DMINCumulative distribution character：
Step e. carries out static behavior assessment to the railroad bridge key member stress most unfavorable combination：Wherein,
In formula, P is outcross probability, using Newton iteration method and with reference to the generalized extreme value distribution function G (DMAX) and F (DMIN),
Solving equation (4) and equation (5), static strain standard value when determining that outcross probability is PWith
WithRepresentWithIn maximum absolute value person, willWith design permissible valueRailway bridge described in multilevel iudge
The static behavior of beam, ifThen the static behavior of the railroad bridge key member stress most unfavorable combination is in safety
State；Conversely, then the static behavior of the railroad bridge key member stress most unfavorable combination is in non-secure states.
2. the railway steel bridge static behavior appraisal procedure of static strain prediction of extremum is based on as claimed in claim 1, and its feature exists
In：The strain data is gathered using fiber Bragg grating strain sensor in step a, and with fiber-optical grating temperature sensor work
For temperature-compensating.
3. the railway steel bridge static behavior appraisal procedure of static strain prediction of extremum is based on as claimed in claim 1, and its feature exists
In：Sampling time L is more than 200 days in step a, and sample frequency is less than 1Hz more than 1/600Hz.
4. the railway steel bridge static behavior appraisal procedure of static strain prediction of extremum is based on as claimed in claim 1, and its feature exists
In：The analysis method of wavelet packet specifically includes all described strain data that will be collected should according to collection sequencing composition
Become sequence, after the strain sequence is carried out on c-th yardstick WAVELET PACKET DECOMPOSITION, obtain 2cIndividual wavelet packet coefficient, extracts
First wavelet packet coefficient is simultaneously reconstructed, and obtains the static strain composition in the strain sequence, and wherein c is measurement point number system
Number.
5. the railway steel bridge static behavior appraisal procedure of static strain prediction of extremum is based on as claimed in claim 4, and its feature exists
In：The measurement point number coefficient c is equal to 5.
6. the railway steel bridge static behavior appraisal procedure of static strain prediction of extremum is based on as claimed in claim 1, and its feature exists
In：The difference sequence of the every day in step c is arbitrarily divided into three parts.
7. the railway steel bridge static behavior appraisal procedure of static strain prediction of extremum is based on as claimed in claim 1, and its feature exists
In：Diurnal variation maximum D in the static strain composition in the L days sampling timeMAXThe fitting of cumulative distribution character include,
Calculate diurnal variation maximum DMAXAccumulated probability value, and using the generalized extreme value distribution function G (DMAX) it is fitted,
Wherein：
In formula, b, d and r represent respectively G (DMAX) scale parameter, location parameter and form parameter, the diurnal variation tried to achieve will be calculated
Maximum DMAXWith diurnal variation maximum DMAXAccumulated probability value substitute into respectively in formula (2), using method of least square determine b, d and
The optimal value of r；
Diurnal variation minimum D in the static strain composition in the L days sampling timeMINThe fitting of cumulative distribution character include,
Calculate diurnal variation minimum DMINAccumulated probability value, and using the generalized extreme value distribution function F (DMIN) it is fitted,
Wherein
In formula, g, h and λ represent respectively F (DMIN) scale parameter, location parameter and form parameter, the diurnal variation tried to achieve will be calculated
Minimum DMINWith diurnal variation minimum DMINAccumulated probability value substitute into respectively in formula (3), using method of least square determine g, h and
The optimal value of λ.
8. the railway steel bridge static behavior appraisal procedure of static strain prediction of extremum is based on as claimed in claim 1, and its feature exists
In：The value of the outcross probability P is 0.01.
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