CN101782372B - Intelligent diagnosis method for bridge telescopic seam injury based on girder end longitudinal displacement - Google Patents
Intelligent diagnosis method for bridge telescopic seam injury based on girder end longitudinal displacement Download PDFInfo
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Abstract
The present invention relates to an intelligent diagnosis method for bridge telescopic seam injury based on girder end longitudinal displacement. The long-term monitoring data of main girder longitudinal displacement, temperature and vertical acceleration after a bridge is built are obtained by mounting a small number of sensors on the bridge; a relevance model of the main girder longitudinal displacement, the bridge temperature and the vertical acceleration in a healthy state is established step by step; the influence of the main girder temperature and the vertical acceleration on the longitudinal displacement can be eliminated on the basis of the relevance model, and the environment condition uniformization displacement which can reflect a working state of a telescopic seam is obtained. When the method is applied to the injury diagnosis of the telescopic seam, the monitoring data in an unknown state are processed just by adopting the established relevance model, and finally, the environment condition uniformization displacement of the healthy state and the unknown state is simultaneously input into a mean value control map; and if the telescopic seam generates injury, a sample point of the control map can exceed a control line, thereby realizing the intelligent recognition on the injury of the telescopic seam.
Description
Technical field
The present invention is a kind of intelligent method that is applied to the diagnosis of bridge structure telescopic seam injury, relates to the Non-Destructive Testing field of science of bridge building.
Background technology
Bridge is when temperature variation, and bridge floor has the linear deformation of expanding and shrinking, and in addition, under the effect of vehicular load, bridge floor also can produce length travel.For satisfying this distortion, will between the beam-ends of bridge and abutment, the expansion joint be set.In bridge structure, the expansion joint not only will be satisfied because the linear deformation of temperature variation and the caused girder of vehicular load also will be satisfied the displacement that concrete shrinkage and creep causes, and subdues because the secondary stress of the caused superstructure of non-uniform settling
[1], therefore, the expansion joint is a structural elements very important in the bridge, whether its state safety not only is related to the operation of whole bridge structure, the driving states when also directly having influence on vehicle by bridge.The stressed complexity of bridge expanssion joint, it is the weak link of bridge always, but because exist such as the design and construction defective, management maintenance is not good at and situation such as overload of vehicle aggravation, the situation that makes expansion joint in the actual engineering be damaged is comparatively serious, therefore need monitor and assess the state at expansion joint, so that find the generation of its damage exactly, and in time the expansion joint is repaired or changed.
At present, telescopic seam injury detects the main artificial mode that regularly detects that adopts, and there is following problem in this mode: (1) manual detection subjective, can not make quantitative judgement to the faulted condition at expansion joint; (2) manual detection can influence traffic usually, and lacks the accumulation of historical data; (3) real-time is relatively poor, can not find the generation of telescopic seam injury in time, might have influence on the safety of bridge structure and driving; (4) check that overall expenses is higher owing to need long-term regular appointment surfaceman to carry out the scene.Therefore, at the shortcoming of above-mentioned manual detection, press for a kind of intelligent method of development the state of bridge expanssion joint is carried out damage in real time.The development of bridge structural health monitoring technology provides opportunity for achieving the above object
[2-3]Can on bridge structure, lay sensor in the engineering construction process, during the bridge operation, write down the data such as vertical displacement, structure temperature, traffic loading of beam-ends chronically, by these Monitoring Data, the bridge managerial personnel just can assess " health " state at expansion joint, for the maintenance, repair and the management decision at expansion joint provides foundation and guidance.
List of references
[1]Chen?Wai-Fah，Duan?Lian.Bridge?engineering?handbook[M].Boca?Raton：CRC?Press，2000.
[2] Li Aiqun, Miu Changqing, Li Zhaoxia. Runyang Changjiang Highway Bridge structural healthy monitoring system research [J]. Southeast China University's journal (natural science edition), 2003,33 (5): 544-548.
[3]Ko?J?M，Ni?Y?Q.Technology?developments?in?structural?health?monitoring?of?large-scalebridges[J].Engineering?Structures，2005，27(12)：1715-1725.
Summary of the invention
Technical matters: the purpose of this invention is to provide a kind of telescopic seam injury diagnostic method, solve the deficiency of existing detection technique based on the girder end longitudinal displacement exception monitoring.
Technical scheme: basic thought of the present invention is: because the purpose at expansion joint is set in the end of bridge main beam is exactly in order to satisfy the needs of the vertical displacement of girder, therefore, the Changing Pattern of girder end longitudinal displacement has just implied the status information at expansion joint, when damage takes place in the expansion joint, ANOMALOUS VARIATIONS will take place in girder end longitudinal displacement, based on the variation of this displacement, just can discern the damage of bridge expanssion joint.
But, as described in the background art, under the operation situation of bridge, the effect of temperature, vehicular load will cause that girder end longitudinal displacement fluctuates (temperature, vehicular load cause the principle of beam-ends displacement see Figure of description 1 and Fig. 2) in the scope of a broad, this fluctuation will flood or masking structures because of change in displacement that telescopic seam injury caused.Therefore, method of the present invention is: the mathematical model of setting up environmental baselines such as girder end longitudinal displacement under the normal condition of expansion joint and temperature, vehicular load, eliminate the influence of environmental baseline on this basis to length travel, obtain really to reflect the length travel of expansion joint health status, and adopt the method for mean chart to discern, thereby set up the intelligent method that can carry out the real-time online damage to the expansion joint state by the caused length travel ANOMALOUS VARIATIONS of telescopic seam injury.
The intelligent method that the bridge telescopic seam injury based on girder end longitudinal displacement that the present invention proposes is diagnosed is:
1) setting of the length travel of girder beam-ends and bridge environmental conditions ensor
When bridge construction is built, the length travel sensor is set in girder beam-ends position, simultaneously, at the span centre position mounting temperature sensor and the acceleration transducer of girder, in order to the temperature of monitoring girder with because the vertical acceleration of girder that vehicular load causes;
2) processing of Monitoring Data
With 10-min is computation interval, and the raw data that sensor obtains is handled, and calculates the typical value of girder end longitudinal displacement, temperature and vehicular load;
3) the mathematics correlation model of length travel and environmental baseline under the serviceable condition
A) choose bridge construction and build up n days the Monitoring Data in back and set up correlation model, length travel D, temperature T and vehicular load typical value R,
B) method of employing linear regression is set up the relation between temperature T and the girder end longitudinal displacement D, and the regression model parameter is calculated by least square method,
C) before the correlation model of setting up vehicular load typical value R and displacement, eliminate the influence of temperature earlier to length travel, choosing reference temperature is T
r, with the original test value D of displacement " normalization " to reference temperature T
r, the girder end longitudinal displacement value D of the temperature effect that is eliminated
1,
D) adopt linear regression to set up D
1With the correlation models of vehicular load typical value R, similar with step c) then, the reference value of choosing vehicular load is R
r, with the D that obtains in the step c)
1" normalization " is to the reference value R of vehicular load
r, the shift value D of the vehicular load that is eliminated influence
2
4) the control chart level of significance determines
The shift value D that step 3) is calculated
2Get daily mean, be designated as D
2, with its input mean chart, adjust the level of significance of control chart, make a said n sample point all drop within the upper and lower control line of control chart;
5) intelligent diagnostics of telescopic seam injury
To m days monitoring data of unknown state, the correlation model under the serviceable condition of employing expansion joint is eliminated the influence of temperature and vehicular load, obtains m per day shift value on this basis, is designated as D
3The conspicuousness that keeps step 4) to determine is constant, with D
2And D
3Import mean chart simultaneously, at this moment, if all n+m sample still all is positioned at upper and lower control line, illustrate that then the expansion joint state is for normal, if there is sample to drop on beyond the control line, the expansion joint abnormal state then is described, can make the early warning that damage takes place at the expansion joint.
Beneficial effect: the engineering reality that very easily is damaged at bridge expanssion joint under the operation state, the present invention comprehensively adopts means such as on-the-spot test, linear regression, mean chart to propose intelligent method based on the damage of girder end longitudinal displacement, has following beneficial effect:
(1) number of sensors of installation required for the present invention is less, only needs displacement transducer, temperature sensor and acceleration transducer.Simultaneously, the method that the present invention adopts is simple, can programming realization comparatively easily, the conveniently application of actual engineering in computing machine.
(2) the present invention has considered that comprehensively environmental factor is to influence that girder end longitudinal displacement produced, substep has been eliminated the influence to the displacement test value of structure temperature, vehicular load, eliminates the health status that shift value after the such environmental effects can reflect bridge expanssion joint under the operation state exactly.
(3) the present invention's method of introducing mean chart is carried out the test of hypothesis of multisample to the ANOMALOUS VARIATIONS of girder end longitudinal displacement, can reduce the possibility of erroneous judgement.
(4) the present invention can carry out on-line monitoring to the expansion joint state, need not manual intervention in the implementation procedure of method, has reduced the expenditure of manpower work, can realize the unattended intellectual monitoring of bridge expanssion joint, has wide future in engineering applications.
Description of drawings
Free beam length travel deformation pattern when Fig. 1 is the temperature rising, T among the figure ↑ expression temperature raises, d
tThe girder end longitudinal displacement that the expression temperature causes;
Fig. 2 is a free beam length travel deformation pattern under the vehicular load effect, and F represents vehicular load among the figure, d
fThe girder end longitudinal displacement that the expression vehicular load causes;
Fig. 3 is the correlativity scatter diagram of length travel of girder the North and temperature;
Fig. 4 is the correlativity scatter diagram of length travel of the girder south and temperature;
Fig. 5 is the correlativity scatter diagram of length travel of girder the North and acceleration-root-mean square, and the acceleration RMS among the figure represents acceleration-root-mean square;
Fig. 6 is the correlativity scatter diagram of length travel of the girder south and acceleration-root-mean square, and the acceleration RMS among the figure represents acceleration-root-mean square;
Fig. 7 is the per day measured value of girder the North length travel and the normalized value behind the elimination environmental impact;
Fig. 8 is the per day measured value of girder south length travel and the normalized value behind the elimination environmental impact;
Fig. 9 is the displacement mean chart under the normal condition of expansion joint, and the UCL among the figure represents upper control line, and LCL represents control line down, and CL is the center line of control chart;
Displacement mean chart under Figure 10 telescopic seam injury state, the UCL among the figure represents upper control line, and LCL represents control line down, and CL is the center line of control chart.
Embodiment
Below specific embodiments of the present invention is further described:
(1) in the setting up procedure of girder end longitudinal displacement and bridge environmental conditions ensor, the setting of layout quantity, position and the parameter of sensor is decided by the type of bridge, the concrete conditions such as environment of striding footpath, bridge deck width and bridge site, usually at the girder beam-ends length travel sensor is set respectively, at the girder span centre temperature sensor and an acceleration transducer are set, can satisfy needs of the present invention.
(2) primary monitoring data is done following processing: girder end longitudinal displacement and structure temperature data are interval its mean value that calculates with 10-min, with this as the girder end longitudinal displacement in this time section and the typical value of structure temperature, with 10-min is interval root mean square (the Root Mean Square that calculates the vertical acceleration of girder, brief note is RMS), with this intensity typical value as the vehicular load in this time period.
(3) select bridge construction to finish n days the Monitoring Data in back and set up correlation model, this is because the intact state that is in can be thought in interior during this period of time expansion joint, represents displacement, temperature and vehicular load typical value respectively with D, T and R, and total sample number is 144 * n.
(4) method of employing linear regression is set up the relation between temperature T and the girder end longitudinal displacement D, and the model tormulation formula is:
D＝β
0+β
1T (1)
In the formula, β
0And β
1Be regression coefficient, can obtain by the method for least square:
In the formula, S
DTCovariance for displacement and temperature; S
TTVariance for temperature; D and T are respectively the average of displacement and temperature.
(5) choosing reference temperature is T
r, with its substitution formula (1), the reference value that obtains displacement is D
r,, obtain calculation of displacement value D simultaneously with also substitution formula of temperature typical value T (1)
tSo, can calculate the girder end longitudinal displacement value D that eliminates temperature effect
1:
D
1＝D-(D
t-D
r) (3)
(6) set up the shift value D that has eliminated temperature effect
1Linear regression model (LRM) with vehicular load typical value R:
D
1＝β
2+β
3R (4)
In the formula, β
2And β
3Be regression coefficient, can similar formula (2) calculate.The reference value of choosing vehicular load is R
r,, obtain the reference value D of displacement with its substitution formula (4)
Rr,, obtain calculation of displacement value D with also substitution formula of vehicular load typical value R (4)
Tt, can calculate the shift value D that has eliminated the vehicular load influence
2:
D
2＝D
1-(D
tt-D
rr) (5)
(7) will eliminate 144 * n the shift value D that temperature and vehicular load influence
2Get daily mean, obtained n displacement sample, be designated as D
2, with D
2The input mean chart, the level of significance of adjustment control chart makes a said n sample point all drop within the upper and lower control line (UCL, LCL).
(8) to m days of unknown state monitoring data, at first it is treated to the typical value that 10-min is a computation interval, adopt correlation model under the serviceable condition of expansion joint to eliminate the influence of temperature and vehicular load then, calculate 144 * m and eliminate the shift value D that temperature and vehicular load influence
3, and then get daily mean, and obtain m displacement sample, be designated as D
3Consistent under the level of significance of retentive control figure and the serviceable condition is with D
2And D
3Import mean chart simultaneously, at this moment, if all n+m sample still all is positioned at upper and lower control line, illustrate that then the expansion joint state is for normal, if there is sample to drop on beyond the control line, the expansion joint abnormal state then is described, can make the early warning that damage takes place at the expansion joint.
Raising Bridge South branch of a river suspension bridge with profit below is example, and specific implementation process of the present invention is described:
The Monitoring Data of choosing 100 days in January, 2006 to June is set up the correlativity of girder end longitudinal displacement and temperature and vehicular load, what sensor was selected for use is the displacement transducer at girder two ends, the temperature sensor and the vertical acceleration transducer of girder span centre, distance when being with 10-min, calculated the typical value of length travel, temperature and vehicular load, totally 144 * 100=14400 sample.
Fig. 3 and Fig. 4 have provided girder the North, the displacement of the south and the correlativity scatter diagram of temperature respectively, from scheming this two width of cloth figure as can be seen, there is stronger linear dependence between girder end longitudinal displacement and the temperature, and shows the feature of " it is little that the high displacement of temperature is big, temperature is hanged down displacement ".Find that by Fig. 3 the constant interval of girder the North displacement is [23.0cm, 28.7cm] simultaneously, found that by Fig. 4 the constant interval of the south is [20.6cm, 33.0cm], the amplitude of variation that can get girder end longitudinal displacement thus is 51.7cm and 53.6cm.
Table 1 has provided the displacement D of employing linear regression analysis foundation and the correlation models of temperature T.
The linear regression model (LRM) of table 1 temperature-displacement
| The position | Regression function (displacement: D (cm) temperature: T (℃)) |
| The girder the North | D＝-17.6681+1.0032T |
| The girder south | D＝-15.5170+1.0097T |
Choose reference temperature T
rBe 20 ℃,, obtain the reference displacement D of beam-ends the linear model of reference temperature value substitution table 1
r,, obtain calculation of displacement value D simultaneously with the temperature typical value T also model of substitution table 1
t, the girder end longitudinal displacement value D of the temperature effect that is eliminated
1
Fig. 5 and Fig. 6 have provided the length travel D of the girder the North and the south respectively
1With the correlativity scatter diagram of vehicular load typical value R (acceleration RMS), as can be seen from the figure distribution of data points is disperseed, but still can see R and D
1Between have tangible correlativity, show the feature of " the big displacement of load is little, and the little displacement of load is big ".
Equally, table 2 has provided the displacement D that adopts regretional analysis to set up
1Correlation models with vehicular load typical value R.
The linear regression model (LRM) of table 2 vehicular load-displacement
| The position | Regression function (displacement: D 1(cm) acceleration RMS:R (cm/s 2)) |
| The north section | D 1＝2.8834-0.5391R |
| The south | D 1＝5.6170-0.6646R |
Choose with reference to vehicular load typical value R
rBe 1cm/s
2,, obtain the reference displacement D of beam-ends with the linear model of vehicular load typical value substitution table 2
Rr,, obtain calculation of displacement value D simultaneously with the vehicular load typical value R also model of substitution table 2
Tt, the girder end longitudinal displacement value D of the temperature that is eliminated and vehicular load influence
2
With D
2Get daily mean, obtain 100 samples, be designated as D
2
Get the data when the monitoring data were as the unknown of expansion joint state in other 48 days again, adopt method of the present invention to obtain 48 per day displacement samples, be designated as D
3
Normalized value after Fig. 7 and Fig. 8 have provided the per day measured value of the length travel of the girder the North and the south respectively and eliminated environmental impact.Solid line is represented the per day measured value of displacement among the figure, and preceding 100 samples of dotted line are promptly represented D
2, back 48 samples are then represented D
3, the displacement normalized value curvilinear motion of north and south end is all very steady as can be seen from this two width of cloth figure, and amplitude is very little, and this illustrates that method of the present invention removed the influence of environmental factor to girder end longitudinal displacement effectively,
With D
2And D
3Import mean chart simultaneously, Fig. 9 has provided the displacement mean chart under the normal condition of expansion joint.Preceding 100 data statement expansion joint serviceable condition, i.e. D among the figure
248 data in back are represented expansion joint unknown state, i.e. D
3By the level of significance of adjusting control chart preceding 100 samples just in time are positioned at up and down within the control line, simultaneously, can find that back 48 samples equally also are positioned within the control line, this explanation expansion joint this moment is in health status.
In order to check the present invention that the effect of lesion assessment is carried out at the expansion joint, the above-mentioned average displacement typical value of 48 days 10-min of getting is in addition applied certain variation, simulate the influence of telescopic seam injury with this to displacement:
D
m＝D-εΔD (6)
In the formula, D is back 48 days 10-min displacement measured value; D
mBe 48 days the 10-min shift simulation value in back under the telescopic seam injury state; ε represents level of damage, is taken as 1.0% here; Δ D is the annual variation amplitude of north and south end carriage end length travel, promptly above 53.6cm and the 51.7cm that introduces.
Again with D
mCalculate 48 per day displacement samples according to method of the present invention, be designated as D
3Then with D
2And D
3Also import mean chart simultaneously, the level of significance of retentive control figure is constant, Figure 10 has provided the displacement mean chart under the Simulation Damage state of expansion joint, as can be seen from the figure when telescopic seam injury causes that 1.0% variation takes place in displacement, 48 samples in back are control line under the convergence significantly, and there is the part sample to runaway, at this moment, can judges that the expansion joint damages.
Above example shows that method proposed by the invention can eliminate the influence that environmental baseline changes girder end longitudinal displacement effectively, extract the length travel normalized value that can reflect the expansion joint state, can be applied to the long-term on-line monitoring and the damage of bridge expanssion joint.
Claims (1)
1. bridge telescopic seam injury intelligent diagnosing method based on girder end longitudinal displacement is characterized in that this damage intelligent diagnosing method is:
1) setting of the length travel of girder beam-ends and bridge environmental conditions ensor:
When bridge construction is built, the length travel sensor is set in girder beam-ends position, simultaneously, at the span centre position mounting temperature sensor and the acceleration transducer of girder, in order to the temperature of monitoring girder with because the vertical acceleration of girder that vehicular load causes;
2) processing of Monitoring Data:
With 10min is computation interval, and the raw data that sensor obtains is handled, and calculates the typical value of girder end longitudinal displacement, temperature and vehicular load; The typical value of described vehicular load is to be the interval root mean square that calculates the vertical acceleration of girder with 10min, with this intensity typical value as the vehicular load in this time period;
3) the mathematics correlation model of length travel and environmental baseline under the serviceable condition:
A) choose bridge construction and build up n days the Monitoring Data in back and set up correlation model, length travel D, temperature T and vehicular load typical value R,
B) method of employing linear regression is set up the relation between temperature T and the girder end longitudinal displacement D, and the regression model parameter is calculated by least square method,
C) before the correlation model of setting up vehicular load typical value R and displacement, eliminate the influence of temperature earlier to length travel, choosing reference temperature is T
r, with the original test value D of displacement " normalization " to reference temperature T
r, the girder end longitudinal displacement value D of the temperature effect that is eliminated
1,
Concrete grammar is: the method for employing linear regression is set up the relation between temperature T and the girder end longitudinal displacement D, and the model tormulation formula is:
D＝β
0+β
1T (1)
In the formula, β
0And β
1Be regression coefficient, can obtain by the method for least square:
In the formula, S
DTCovariance for displacement and temperature; D
TTVariance for temperature;
With
Be respectively the average of displacement and temperature, choosing reference temperature is T
r, with its substitution formula (1), the reference value that obtains displacement is D
r,, obtain calculation of displacement value D simultaneously with also substitution formula of temperature typical value T (1)
tSo, can calculate the girder end longitudinal displacement value D that eliminates temperature effect
1:
D
1＝D-(D
t-D
r) (3)
D) adopt linear regression to set up D
1With the correlation models of vehicular load typical value R, similar with step c) then, the reference value of choosing vehicular load is R
r, with the D that obtains in the step c)
1" normalization " is to the reference value R of vehicular load
r, the shift value D of the vehicular load that is eliminated influence
2
Concrete grammar is: set up the shift value D that has eliminated temperature effect
1Linear regression model (LRM) with vehicular load typical value R:
D
1＝β
2+β
3R (4)
In the formula, β
2And β
3Be regression coefficient, can similar formula (2) calculate that the reference value of choosing vehicular load is R
r,, obtain the reference value D of displacement with its substitution formula (4)
Rr,, obtain calculation of displacement value D with also substitution formula of vehicular load typical value R (4)
Tt, can calculate the shift value D that has eliminated the vehicular load influence
2:
D
2＝D
1-(D
tt-D
rr) (5)
4) determining of control chart level of significance:
The shift value D that step 3) is calculated
2Get daily mean, be designated as
, with its input mean chart, adjust the level of significance of control chart, make a said n sample point all drop within the upper and lower control line of control chart;
5) intelligent diagnostics of telescopic seam injury:
To m days monitoring data of unknown state, the correlation model under the serviceable condition of employing expansion joint is eliminated the influence of temperature and vehicular load, obtains m per day shift value on this basis, is designated as
, the conspicuousness that keeps step 4) to determine is constant, will
With
Import mean chart simultaneously, at this moment, if all n+m sample still all is positioned at upper and lower control line, illustrate that then the expansion joint state is for normal, if there is sample to drop on beyond the control line, the expansion joint abnormal state then is described, can make the early warning that damage takes place at the expansion joint.
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| CN201019026007XA CN101782372B (en) | 2010-02-04 | 2010-02-04 | Intelligent diagnosis method for bridge telescopic seam injury based on girder end longitudinal displacement |
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2010
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