CN106556498A - Damage Identification Methods for Bridge Structures and system - Google Patents
Damage Identification Methods for Bridge Structures and system Download PDFInfo
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- CN106556498A CN106556498A CN201610985087.1A CN201610985087A CN106556498A CN 106556498 A CN106556498 A CN 106556498A CN 201610985087 A CN201610985087 A CN 201610985087A CN 106556498 A CN106556498 A CN 106556498A
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- G—PHYSICS
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- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M5/00—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings
- G01M5/0008—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings of bridges
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
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Abstract
The invention discloses Damage Identification Methods for Bridge Structures and system, methods described includes：The amount of deflection information of collection environmental variable and bridge structure；The health status of assessment bridge structure, judge whether to need to carry out non-destructive tests and send safety alarm；Go out damage position using damage location identification Model Identification；Go out degree of injury using damage extent identification Model Identification.The system includes data acquisition module, health state evaluation module, alarm module, damage location identification module, damage extent identification module and display module.Present configuration is simple, easily realization, it is adaptable to different types of rridges structure, can provide in time bridge structure health status information in detail for bridge management department, it is ensured that the safe operation of bridge structure.
Description
Technical field
The present invention relates to bridge technology field.
Background technology
In nearly twenty or thirty year, frequently there is different types of rridges accident, compare the unexpected collapse accident of seriously bridge, make in China
Into great casualties and property loss.Before the reason for bridge collapses is numerous, but certainly bridge collapses, some
Key position causes bridge structure due to the impact of the long term and various adverse environmental factors of various power static loads
Fatigue, the corrosion of material and aging, and lack, the damage of bridge structure is produced in validity period
There is decline etc. in accumulation, its rigidity, so as to have a strong impact on the service life of bridge structure, or even the serious limit peace beyond design
Gamut, causes the generation of burst accident.It can be seen that, when these Bridge Accidents occur, bridge worker especially bridge management portion
Door, could not find that Bridge performance has occurred regression in advance, so as to make early warning in advance, more could not take corresponding adding in time
Gu maintenance measures, cause taking place frequently and happening suddenly for Bridge Accidents.
The Large-sized Communication such as substantial amounts of service bridge structure infrastructure are in the urgent need to a kind of effective method monitoring and assess
Its health status, is recognized accurately the degree of impairment of bridge structure in real time.Although a large amount of scholar have carried out bridge structure both at home and abroad
The research of health monitoring systems, exploitation and practical engineering application, but security evaluation is mainly occupied with theoretical result with non-destructive tests
It is many, as the complexity of actual bridge structure and wild environment condition, the incompleteness of measured data and external disturbance cause
Uncertainty of bridge structure response etc., makes the practical application effect of existing achievement in research still have many unsatisfactory ground
Side.
The content of the invention
The technical problem to be solved in the present invention is for above-mentioned the deficiencies in the prior art, there is provided Damage Identification of Bridge Structure side
Method and system, energy direct analysis judge whether bridge structure has damage, accurately identifies damage position and degree of injury, are bridge dimension
Shield, maintenance and management decision-making provide foundation and guidance, it is ensured that the safe operation of bridge structure.
To solve above-mentioned technical problem, the technical solution used in the present invention is：
Damage Identification Methods for Bridge Structures, comprises the following steps：
(1) gather the amount of deflection information of environmental variable and bridge structure；
(2) health status of bridge structure are assessed, is judged whether to need to carry out non-destructive tests and is sent safety alarm；
(3) go out damage position using damage location identification Model Identification；
(4) go out degree of injury using damage extent identification Model Identification.
Preferably, described in the step (1), environmental variable is included suffered by ambient temperature, ambient humidity and bridge structure
Load situation.
Preferably, Least Square Support Vector Regression (LS-SVR) algorithm is adopted in the step (2).
Preferably, the step (2) includes：Anticipation function is set up, the trial Run Test or identification examination after building up according to bridge
Test and run the environmental variable and amount of deflection information that monitoring system under regular period at initial stage inner structure serviceable condition is collected
Historical data, using the Least Square Support Vector Regression (LS-SVR) algorithm set up the bridge structure amount of deflection letter
Functional relationship between breath and environmental variable, i.e. anticipation function；Information processing, in the normal operation stage of bridge structure, will be real
The environmental variable of survey substitutes into the anticipation function and is calculated, and can obtain predicting amount of deflection information, and calculate actual measurement amount of deflection information
With the difference of prediction amount of deflection information；Health state evaluation, by the actual measurement amount of deflection information and the difference and thing of predicting amount of deflection information
The standard value first drafted is analyzed, when this difference is within the scope of regulation, then it is assumed that bridge structure health state
Normally, continue gathered data, if this difference exceedes the scope of regulation, then it is assumed that there may be exception, send safety alarm.
Preferably, in the step (3), damage location identification model is built using C- support vector classifications (C-SVC) algorithm
It is vertical.
Preferably, the step (3) includes：Damage location identification model is set up, the FEM (finite element) model of bridge structure is set up,
Bridge structure is calculated under various load cases, structure not damaged and when occurring to damage in various degree, bridge structure key section
Maximum defluxion, construct signatures for damage detection variable, using multi-class classification method C- support vector classifications algorithm set up damage
Location recognition model；Amount of deflection information processing, according to actual measurement amount of deflection information, extracts each designated key section of bridge structure surveyed
Maximum defluxion, tectonic transition is signatures for damage detection；The signatures for damage detection is input into the damage by damage location identification
In location recognition model, by comparison-of-pair sorting, damage position information is identified.
Preferably, in the step (4), damage extent identification model is built using ε-support vector regression (ε-SVC) algorithm
It is vertical.
Preferably, the step (4) includes：Damage extent identification model is set up, when damaged according to each crucial section respectively
Signatures for damage detection variable, damage extent identification model is set up using ε-support vector regression algorithm；Information processing, obtains
Damage position information and signatures for damage detection；The signatures for damage detection is input into damage extent identification mould by damage extent identification
In type, by relative analyses, degree of injury information is identified.
Preferably, the bridge is railroad bridge.
Damage Identification of Bridge Structure system, including：Data acquisition module, health state evaluation module, alarm module, damage
Location identification module, damage extent identification module and display module；The data acquisition module is used to gather scratching for bridge structure
Degree information and environmental variable, connect the data input pin of the health state evaluation module；The health state evaluation module is used
In assessment bridge structure health status and judge whether to need to carry out non-destructive tests and send safety alarm；The alarm module
Signal input part connect the alarm signal output ends of the health state evaluation module；Deposit in the damage location identification module
Damage location identification model is contained, damage position is can recognize that；Be stored with the damage extent identification module degree of injury
Identification model, can recognize that degree of injury.
Data acquisition module：For gathering the amount of deflection information of each key position of bridge structure, while gathering bridge structure
The environmental variables such as suffered load situation, ambient temperature, humidity.
Health state evaluation module：Be stored with the standard value of default bridge structure health state estimation, by amount of deflection
After the process of information, contrast with evaluation criteria, judge whether to need to carry out non-destructive tests and send safety alarm.
Alarm module：Alarm is sent when amount of deflection information exceedes health state evaluation standard value.
Damage location identification module：The Bridge Structural Damage that is stored with location recognition model, after amount of deflection information processing being surveyed
Signatures for damage detection is obtained, then is entered in damage location identification model, damage position is recognized accurately.
Damage extent identification module：The Bridge Structural Damage that is stored with degree identification model, the damage position that will identify that and
Signatures for damage detection is input in damage extent identification model, and degree of injury is recognized accurately.
Display module：Show the information such as the degree of signatures for damage detection, the position damaged and damage.
Using the beneficial effect produced by above-mentioned technical proposal it is：
(1) the overall work of bridge structure as amount of deflection can reflect the comprehensive load capacity of bridge structure, can be shown again
Make performance, and amount of deflection is affected little by external interference, for long-span bridge girder construction, load rushes when train or vehicle are passed a bridge
Hit coefficient less, monitoring signals are reliable and stable.Therefore, the present invention chooses the dependent variable of the amount of deflection as anticipation function of bridge structure
(i.e. the parameter index of bridge structure health state estimation).
(2) health state evaluation module of the invention judges the health status of bridge structure, structure using anticipation function method
Simply, and the amount of deflection information that needs resists the dry ability of scratching strong, the health status of bridge structure can be obtained in real time, is made in advance pre-
It is alert.
(3) damage location identification module of the invention, it is only necessary to the maximum defluxion in some crucial sections of bridge structure
Construct signatures for damage detection, input damage location identification model can Real time identification go out damage position.
(4) damage extent identification module of the invention, can also use signatures for damage detection during damage location identification, defeated
The degree of damage is quickly recognized in entering damage extent identification model.
Present configuration is simple, easily realization, it is adaptable to different types of rridges structure, can provide in time in detail for bridge management department
Most bridge structure health status information, it is ensured that the safe operation of bridge structure.
Description of the drawings
Fig. 1 is the principle schematic of Bridge Damage Assessment Method system one embodiment of the present invention；
Fig. 2 is the principle schematic of health state evaluation module in the present invention；
Fig. 3 is the principle schematic of damage location identification module in the present invention；
Fig. 4 is the principle schematic of damage extent identification module in the present invention；
Fig. 5 is the workflow schematic diagram of Bridge Structural Damage Identification one embodiment of the present invention.
Specific embodiment
The present invention is further detailed explanation with reference to the accompanying drawings and detailed description.
As shown in figure 1, be one embodiment of the present of invention, including：
(1) deflection data harvester, is capable of achieving the real-time monitoring of multi-measuring point deflection of bridge span information, ensure that bridge is scratched
Accurate, the reliability of degree Monitoring Data.
(2) bridge structure health state estimation module, the standard value of the default bridge structure health state estimation that is stored with
And the anticipation function of amount of deflection.After system receives deflection data information and processed, contrast with evaluation criteria, assess bridge structure
Health status, judge whether to need to carry out non-destructive tests and send safety alarm.Fig. 2 is bridge structure health state estimation mould
The FB(flow block) of block, the ε in figure1iAnd ε2i(i=1,2 ..., n are measuring point numbering) is two evaluation criterias,For intact bridge
The predictive value of structural deflection information, yiFor the amount of deflection information of the bridge structure of amount of deflection acquisition system actual measurement.
(3) Fig. 3 is the FB(flow block) of Bridge Structural Damage location identification module, initially sets up the FEM (finite element) model of bridge,
Prepare training set and test set, damage location identification model is set up using C-SVC, Bridge Structural Damage location recognition mould is stored in
In block；Signatures for damage detection will be obtained after the deflection data information processing for collecting, then be entered into damage location identification mould
In type, damage position is recognized accurately.
(4) FB(flow block)s of the Fig. 4 for Bridge Structural Damage degree identification module, selects existing training set and survey in (3)
The data of examination collection correspondence difference damage position, set up Bridge Structural Damage degree identification model using ε-SVR methods；By in (3)
The signatures for damage detection for collecting is input in damage extent identification model, you can identify degree of injury.
(5) display module：Show the information such as the degree of signatures for damage detection, the position damaged and damage.
The concrete operating principle of the embodiment of the present invention is as shown in figure 5, comprise the following steps：
(A) preparation work：Before the work of Damage Identification of Bridge Structure module, need in advance to set up anticipation function, damage position
Put identification model, damage extent identification model.
(1) anticipation function：
(1) Statistic analysis models set up between structural deflection and reason amount (load, ambient temperature and humidity etc.), be exactly
Using a large amount of measured datas of health monitoring acquisition are carried out to intact structure through many support vector regression methods, set up intact
Corresponding relation between the amount of deflection (dependent variable) and reason amount (independent variable) of structure, that is, set up and comment for bridge structure health state
The anticipation function estimated
{ y }=and f (K, T, P ...) } (1)
Wherein, { y } is measuring point amount of deflection etc.；F () is the mapping function from reason amount to amount of deflection；K is structure self performance
Parameter；T is ambient temperature factor；P is load；Etc..This function reflects the entirety of bridge structure to a certain extent
Mechanical property, reflects the internal relation of deflection of bridge structure and reason amount, and bridge structure is can be predicted when known to reason amount
Amount of deflection.
(2) predetermined estimation criterion epsilon1iAnd ε2iIt is determined that
①ε1iDetermination
ε1i(i=1,2 ..., numerical value n) is mainly according to a large amount of actual measurement numbers that health monitoring acquisition is carried out to intact structure
According to through statistical analysiss, and at the beginning of the result that is analyzed with predictive value of the measured value of integrated structure amount of deflection and determine one
Level alarming value.It is equivalent to specified in railroad bridge calibrating specification " general value ".
Tabled look-up according to level of significance α and residual distribution rule and make m values, then confidence interval is
In formula,For not damaged when amount of deflection predictive value；SiFor standard deviation, its value is
Wherein, yijFor j-th measured value of i-th response quautity；N is by the total sample number that adopts.If actual measured value
Fall in confidence interval formula (2), then it is assumed that measured value is normal, otherwise is considered as exception.It follows that evaluation criteria ε1iCan be by
Following formula determines
ε1i=mSiI=1,2 ..., n (4)
②ε2iDetermination
Make bridge structure bear its all possible load case effect, when calculating bridge structure not damaged, beam body each
The maximum defluxion in section (section can be determined every 1/4 span or 1/8 span).
Bridge structure is equally made to bear its all possible load case effect, while making bridge structure integral rigidity reduction
During 10% or 15% (selecting corresponding degree of injury according to practical situation for different bridge structures) for original rigidity etc.,
Calculate the maximum defluxion of each section of beam body (section can be determined every 1/4 span or 1/8 span).
Calculate under each operating mode, there is the difference damaged with maximum defluxion during not damaged in each section of beam body, as accordingly
Second evaluation criteria ε2i。
(2) damage location identification model：
1. signatures for damage detection
Structural damage typically has two kinds of situations：One is that the quality of structure changes；Two is that the rigidity of structure is reduced.For
Civil engineering structure, its quality typically seldom change, and mass change is little to structure influence in other words, so civil engineering
The damage of structure is commonly considered as the rigidity of structure and there occurs change.In view of the mechanics of materials and railway bridges and culverts design fundamental norms
In all pass through to control the amount of deflection of bridge and rigidity inspection is carried out in safety limit calculate, i.e. the amount of deflection of structure is the ginseng for reflecting the rigidity of structure
One of number.
For railroad bridge structure, when train passes through bridge, train and bridge constitute a complicated train-bridge time-varying
System, the displacement of each node in bridge structure are continually changing the change of position on bridge with train, it is considered to bridge structure
Practical situation and actually detected technology, in the face of huge data, the present invention is set up based on the maximum defluxion at bridge some nodes
The index of non-destructive tests, will bridge structure some nodes maximum defluxion rate of change as Damage Identification of Bridge Structure finger
Mark.And the impact of vehicle-bridge coupled vibration is put aside, vehicular load is reduced to into a series of ranks dead loads on bridge during calculating
It is mobile, try to achieve node maximum defluxion and be multiplied by corresponding impact coefficient 1+ μ again.Signatures for damage detection is：
Wherein：
1+ μ --- for impact coefficient, relevant specification can be looked into；
--- when mobile dead load operating mode q is acted on, when structure is intact, k node maximum displacements；
--- when mobile dead load operating mode q is acted on, during structural damage, k node maximum displacements；
Δykq--- when mobile dead load operating mode q is acted on, k node maximum displacement rate of changes, as signatures for damage detection.
It can be seen that, when calculating signatures for damage detection, can not also consider the impact of impact coefficient.
2. set up damage location identification model
First, set up the FEM (finite element) model of bridge structure, calculate bridge structure in various load cases (such as：It is unit, double
Machine, unit train, two-shipper train etc.) under, when structure not damaged is with occurring to damage in various degree, the maximum defluxion of some nodes.
Again by a certain damage position, during correspondence Injured level, the signatures for damage detection composition one of each node is vectorial, as damages
Hinder distinguishing indexes column vector { Δ y }
Wherein：M is node total number.
Each signatures for damage detection column vector { Δ y } one damage position ele (damage list in FEM (finite element) model of correspondence
Unit's numbering).Some damage position ele may correspond to num signatures for damage detection column vector { { Δ y }1,{Δy}2,…,{Δ
y}num}.This is because, when damage position ele occurs to damage, degree of injury is different or load case is different, can all draw
Different signatures for damage detection column vectors.But, these signatures for damage detection column vectors are respectively provided with and are different from other damage positions
The same characteristic features of corresponding signatures for damage detection column vector, you can with the signatures for damage detection corresponding to damage position ele
Column vector is all classified as a class.Therefore, damage location identification problem is multicategory classification problem.
Secondly, damage location identification model is set up using multi-class classification method (C-SVC).El 2 class classifying ruless of construction,
Wherein fele(ΔySimulation), the training sample that ele positions are damaged by ele=1 ..., el and other training samples separate, if Δ ySimulation
Belong to the signatures for damage detection of ele positions damage, then sgn [fele(ΔySimulation)]=1, otherwise sgn [fele(ΔySimulation)]=- 1.
Select function fele(Δ y simulations), ele=1 ..., the classification in el corresponding to maximum：
Ele=argmax { f1(ΔySimulation) ..., fel(ΔySimulation)} (7)
Wherein, ele --- for the damage position of multi classifier identification.
(3) damage extent identification model：
Signatures for damage detection is still using the signatures for damage detection in (two).The premise for carrying out damage extent identification is to damage position
Put and identify, i.e., when damage extent identification index training set is set up, known to damage position (not as variable), degree of injury
Unknown (to be identified).
In damage extent identification index training set, one damage of each signatures for damage detection column vector { Δ y } correspondence
Degree de, the computing formula of de is
Wherein, de --- degree of injury；
Rigidityw--- the rigidity (can be bending rigidity EI or Anti-pull-press rigidity EA) during not damaged；
Rigidityy--- the rigidity having during damage.
As degree of injury is a continuous variable, therefore, damage extent identification problem belongs to regression problem, that is, damage
Dependent variable of degree de for regression problem, signatures for damage detection column vector { Δ y } is the independent variable of regression problem, is returned by ε-SVR
Return and independent variable { Δ y } certain functional relationship and dependent variable de between
Wherein：F () --- for damage extent identification model；
{a1a2…am--- for weight coefficient row vector；
B --- constant.
(B) non-destructive tests：
(1) health state evaluation：
First will bridge operation phase actual monitoring to the reason for amount (include load and ambient temperature etc.) substitute into anticipation function
(formula (1)), calculates the predictive value of structural deflection
By the measured value { y } and predictive value of amount of deflectionIt is analyzed.
If
Then measured value is close to predictive value, illustrates that structural health conditions are normal；
If
Then survey response value deviate predictive value, but still in safety limit within.Although this explanation actual measurement structural response value
Deviate compared with predictive value, but still the normal safety limit for using allowed without departing from specification.Now bridge structure is strong
Health state may have occurred that change, should eliminate safe hidden trouble in time, further to the timely alert of bridge tube department
Carry out non-destructive tests.
If
Then survey structural response value and not only deviate from predictive value, and safety is normally used beyond what specification was allowed
Limit value.Bridge structure health state now is not only abnormal, and there may be serious potential safety hazard, should immediately to bridge tube
Department sends the warning message of highest level, to take effective technical measures and control measures in time, find out failure cause,
Remove the dangerous condition, it is ensured that the operation security of bridge structure.
(2) non-destructive tests：
The signatures for damage detection column vector { Δ y } of actual measurement is substituted into into formula (7), you can identify damage position；Substitute into again
Formula (9), you can identify degree of injury.
Additionally, the degree of accuracy and speed in order to ensure non-destructive tests, should ensure that and set up anticipation function, damage location identification mould
Accurately and reliably, and the employing SVC for holding water sets up each function and closes for type, the training set of damage extent identification model and test set
System and identification model.
Using the beneficial effect produced by above-mentioned technical proposal it is：
(1) the overall work of bridge structure as amount of deflection can reflect the comprehensive load capacity of bridge structure, can be shown again
Make performance, and amount of deflection is affected little by external interference, for long-span bridge girder construction, load rushes when train or vehicle are passed a bridge
Hit coefficient less, monitoring signals are reliable and stable.Therefore, the present invention chooses the dependent variable of the amount of deflection as anticipation function of bridge structure
(i.e. the parameter index of bridge structure health state estimation).
(2) health state evaluation module of the invention judges the health status of bridge structure, structure using anticipation function method
Simply, and the amount of deflection information that needs resists the dry ability of scratching strong, the health status of bridge structure can be obtained in real time, is made in advance pre-
It is alert.
(3) damage location identification module of the invention, it is only necessary to the maximum defluxion in some crucial sections of bridge structure
Construct signatures for damage detection, input damage location identification model can Real time identification go out damage position.
(4) damage extent identification module of the invention, can also use signatures for damage detection during damage location identification, defeated
The degree of damage is quickly recognized in entering damage extent identification model.
Present configuration is simple, easily realization, it is adaptable to different types of rridges structure, can provide in time in detail for bridge management department
Most bridge structure health status information, it is ensured that the safe operation of bridge structure.
Claims (10)
1. Damage Identification Methods for Bridge Structures, it is characterised in that comprise the following steps：
（1）The amount of deflection information of collection environmental variable and bridge structure；
（2）The health status of assessment bridge structure, judge whether to need to carry out non-destructive tests and send safety alarm；
（3）Go out damage position using damage location identification Model Identification；
（4）Go out degree of injury using damage extent identification Model Identification.
2. Damage Identification Methods for Bridge Structures according to claim 1, it is characterised in that the step（1）Described in environment
Variable includes the load situation suffered by ambient temperature, ambient humidity and bridge structure.
3. Damage Identification Methods for Bridge Structures according to claim 1, it is characterised in that the step（2）It is middle to adopt minimum
Two take advantage of support vector regression algorithm.
4. Damage Identification Methods for Bridge Structures according to claim 3, it is characterised in that the step（2）Including：Set up
Anticipation function, according to environmental variable and the historical data of amount of deflection information, using the Least Square Support Vector Regression algorithm
Set up anticipation function；The environmental variable of actual measurement is substituted into the anticipation function and is calculated by information processing, can obtain predicting amount of deflection
Information, and calculate the difference of actual measurement amount of deflection information and prediction amount of deflection information；Health state evaluation, by the actual measurement amount of deflection information
It is analyzed with the standard value drafted in advance with the difference of prediction amount of deflection information, when this difference is within the scope of regulation
When, then it is assumed that bridge structure health state is normal, continues gathered data, if this difference exceedes the scope of regulation, then it is assumed that can
Can there is exception, send safety alarm.
5. Damage Identification Methods for Bridge Structures according to claim 1, it is characterised in that the step（3）Middle damage position
Identification model is set up using C- support vector classifications algorithm.
6. Damage Identification Methods for Bridge Structures according to claim 5, it is characterised in that the step（3）Including：Set up
Damage location identification model, sets up the FEM (finite element) model of bridge structure, calculates bridge structure under various load cases, structure without
When damaging and occur to damage in various degree, the maximum defluxion in bridge structure key section constructs signatures for damage detection variable, adopts
C- support vector classification algorithms set up damage location identification model；Amount of deflection information processing, according to actual measurement amount of deflection information, extracts real
The maximum defluxion in the bridge structure key section for measuring, tectonic transition is signatures for damage detection；Damage location identification, by the damage
Hinder distinguishing indexes to be input in the damage location identification model, by comparison-of-pair sorting, identify damage position information.
7. Damage Identification Methods for Bridge Structures according to claim 1, it is characterised in that the step（4）Middle degree of injury
Identification model is set up using ε-support vector regression algorithm.
8. Damage Identification Methods for Bridge Structures according to claim 7, it is characterised in that the step（4）Including：Set up
Damage extent identification model, according to signatures for damage detection variable, sets up degree of injury knowledge using ε-support vector regression algorithm
Other model；Information processing, obtains damage position information and signatures for damage detection；Damage extent identification, the non-destructive tests are referred to
In mark input damage extent identification model, by relative analyses, degree of injury information is identified.
9. Damage Identification Methods for Bridge Structures according to claim 1, it is characterised in that the bridge is railroad bridge.
10. Damage Identification of Bridge Structure system, it is characterised in that include：Data acquisition module, health state evaluation module, report
Alert module, damage location identification module, damage extent identification module and display module；The data acquisition module is used to gather bridge
The amount of deflection information of girder construction and environmental variable, connect the data input pin of the health state evaluation module；The health status
Evaluation module is used to assess the health status of bridge structure and judge whether to need to carry out non-destructive tests and send safety alarm；Institute
The signal input part for stating alarm module connects the alarm signal output ends of the health state evaluation module；The damage position is known
Be stored with other module damage location identification model, can recognize that damage position；Store in the damage extent identification module
There is degree of injury identification model, can recognize that degree of injury.
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| CN114580239A (en) * | 2022-03-07 | 2022-06-03 | 合肥工业大学 | Bridge damage identification method considering uncertainty |
| CN114580239B (en) * | 2022-03-07 | 2022-09-27 | 合肥工业大学 | Bridge damage identification method considering uncertainty |
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| CN116070068A (en) * | 2023-04-06 | 2023-05-05 | 石家庄铁道大学 | Stay cable damage identification method, device and terminal based on wavelet transformation of primary derivative of girder deflection difference |
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