CN110411686A - The quiet dynamic image holography condition health monitoring diagnostic method of bridge and system - Google Patents
The quiet dynamic image holography condition health monitoring diagnostic method of bridge and system Download PDFInfo
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- CN110411686A CN110411686A CN201910187373.7A CN201910187373A CN110411686A CN 110411686 A CN110411686 A CN 110411686A CN 201910187373 A CN201910187373 A CN 201910187373A CN 110411686 A CN110411686 A CN 110411686A
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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
- 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
- G01M5/00—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings
- G01M5/0033—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings by determining damage, crack or wear
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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
- G01M5/00—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings
- G01M5/0041—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings by determining deflection or stress
- G01M5/005—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings by determining deflection or stress by means of external apparatus, e.g. test benches or portable test systems
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Abstract
The invention discloses a kind of quiet dynamic image holography condition health monitoring diagnostic methods of bridge, by obtaining environmental information to healthy bridge, bridge deck traffic status information and bridge facade image collection information, and the limit element artificial module of lossless bridge is established according to healthy bridge, utilize the structure feature form and structural dynamic characteristic of above-mentioned data acquisition simulation model, and it is contrasted with the true structure feature form and structural dynamic form of healthy bridge, by difference value accumulated statistics and difference value changing rule is obtained after circulation, after historical sample data machine deep learning, establish the function curve of the virtual condition function curve of healthy bridge and the theory state of lossless bridge, when use, the health status for working as front axle beam is obtained by function comparison.
Description
Technical field
The invention belongs to civil structure and safety engineering field, in particular to a kind of quiet dynamic image holography condition of bridge is strong
Health monitoring, diagnosing method.
Background technique
In civil structure engineering field, especially great infrastructure such as large bridge etc. has certain service life
Structural body needs to take effective safety monitoring management measure, to ensure that these structures prevent great peace during use
The generation of full accident.
Existing highway bridge safety inspection is roughly divided into three classes, first is that inspecting periodically: every 2~6 years by equipment special to bridge
Primary inspection comprehensively is carried out, informative data, conclusion is credible, but checks that the frequency is low, it is difficult to which timely learning is adjacent to be inspected periodically twice
Between the safe and healthy problem of structure；Second is that regular safety inspection: it is required that monthly no less than once manually being pacified to bridge
Full inspection lacks quantized data, it is difficult to reach the actual effect of inspection though the frequency is high；Third is that conventional Bridge Long Period Health prison
Examining system installs series sensor in bridge, can high frequency time acquisition treatment rates condition response data, and take this to analyze
Speculate the current configuration state of bridge, but the disposable Meteorological of the system is big, sensor life-time is shorter, data reliability with
Time and reduce, it is difficult to be widely used in the Long Period Health Monitoring of large bridge.
In the prior art, there are also relatively simple and effective monitoring mode be obtained using fixed point photography different time or
The situation of change of characteristic speckle figure carries out the deformation monitoring of key point or regional area, the party on different operating condition flowering structure bodies
On the basis of method is built upon fixed photography and can get a distinct image, it is generally only applicable to the deformation prison of indoor small structure
It surveys or the shortterm deflection of outdoor large structure specified point monitors, it is impossible to be used in the civil engineering structure of the big scale of construction is whole and forms
The monitoring of component geometry metamorphosis.So far, still cannot economical, easily obtain large-scale civil engineering structure it is whole and
The holographic data of building block geometric shape variation.
To solve the above problems, " structure for folding difference analysis based on contour line image becomes Chinese patent ZL201610300691
Shape monitoring method " discloses a kind of method for detecting bridge, obtains reflection main structure body by fixed point or multi-angle of view photography and wraps
Photo containing main building block of interest, carry out photo processing obtain Digitized Structure contour line striograph, and will be each when
The same structure contour line image of phase carries out the folded analysis of difference with structure image contour line for the first time, and the structure for obtaining different times becomes
The safe condition with pre- geodesic structure is relatively evaluated in graphic data, the analysis according to all previous deformation data, and whole process is simple and square
Just, the deformation shape for obtaining specified point or specific cell domain can only be changed according to characteristic speckle by avoiding traditional deformation of image test
The defect of condition, the holographic geometry that can obtain the overall and each concern position of large scale structure and building block within the scope of photo become
Graphic data；But the splicing that several image pictures need to be carried out for large bridge this method, first is that there are image picture splicings
Error problem, second is that each stitching image of theory calls should be that bridge is in same situation lower moment while obtaining, this is to operation bridge
Beam is actually unable to satisfy, artificial to participate in still remaining, it is understood that there may be biggish error, acquired result are still not objective enough
It sees.
Therefore, it is necessary to a kind of monitoring and pre-alarming methods for large bridge, can objectively obtain bridge beam action and shape
State data are simultaneously compared with the gross data of healthy bridge, to learn the health status of bridge, and automatic by computer
Realize, formed big data obtain and conveying, have the characteristics that with existing artificial detection compared with economy, conveniently, in real time, into
Row monitoring while, have no effect on its operation use, can economical and efficient, timely and accurately discovery be related to the structures such as bridge safety
Disease hidden danger, it is ensured that safe handling.
Summary of the invention
In view of this, the object of the present invention is to provide a kind of quiet dynamic image holography condition health monitoring diagnostic methods of bridge
And system, bridge beam action and status data can be objectively obtained, big data is formed and obtains and convey, and pass through computer
Automatic realize is compared analysis with the gross data of healthy bridge, and foundation is to the machine deep learning of all previous monitoring data,
Bridge is obtained in the environment changed over time and the changing rule of load action flowering structure state, to learn the health of bridge
Situation, has the characteristics that economical, conveniently, in real time compared with existing artificial detection, while being monitored, has no effect on it
Operation use, can economical and efficient, timely and accurately discovery be related to the Structural defect of bridge security, it is ensured that safe handling.
The quiet dynamic image holography condition health monitoring diagnostic method of bridge of the invention, including the following steps:
A. bridge structure initial information data are obtained；
A1. conditional information data when Ti are acquired；
The Qj section structure static image data and Ti+ of bridge when a2. acquiring the Ti under step a1 conditional information data
The Qj section structure dynamic video data of Δ period bridge；
A3. it is handled by the Qj section structure static image analysis of bridge when Ti, obtains practical bridge Qj session representations structure
The geometric shape holographic data Cs of deformation characteristic；By the Qj section structure dynamic video analysis processing of bridge when Ti+ Δ, obtain
Practical bridge Qj section structure dynamic form holographic data Ds；
B. the detailed finite element theoretical model of lossless bridge is established；
B1. the structural theory state parameter E of lossless bridge when Ti is inputted；
B2., conditional information data in step a1 when Ti are brought into the detailed finite element theoretical model of lossless bridge；
B3. according to step b1 and b2, the theory that lossless bridge Qj session representations malformation characteristic when Ti is calculated is several
The theoretical power morphology holography data Dw of what morphology holography data Cw and Ti+ Δ period lossless bridge Qj section structure；
C. the geometric shape holographic data Cs of the characterization practical structures deformation characteristic of step a3 and practical structures dynamic is complete
Breath performance data Ds malformation gross data Cw and theoretical power performance data Dw corresponding with step b3's is compared point
Analysis, geometric shape holographic data Cs and practical structures dynamic holographic performance data Ds relative to malformation gross data Cw and
The difference of theoretical power performance data Dw is within setting value, then the Qj section structure of bridge is judged as that nothing is obviously damaged just
Otherwise normal state is judged as in the presence of the anomaly sxtructure state and output abnormality position and degree obviously damaged；
D. such as the Qj section structure of step c Bridge is normal condition, then ij circulation step a2, a3, b2, b3 and c, right
The historical sample data of accumulation carries out machine deep learning；
D1. lossless bridge structure theory deformation data Cw and the theoretical power being accumulated under different condition information data
State data Dw establishes the judgement network model of lossless bridge, and persistent accumulation sample data, carries out to the judgement network model
Lasting amendment, establishes the theory deformation data Cw and theoretical power condition data Dw of lossless bridge structure with different condition information
The quiet dynamic Variation Regularity of Morphological Characteristics of theory of data effect；
The historical sample data that d2 obtains accumulation to practical bridge carries out machine deep learning, establishes practical bridge structure
What corresponding geometric shape holographic data Cs and practical structures dynamic characteristic holographic data Ds was acted on different condition information data
The practical quiet dynamic Variation Regularity of Morphological Characteristics of bridge；
E. by the knot of the theory state changing rule model of the lossless bridge under current condition information data and practical bridge
Structure state change rule model is compared analysis, ends present period, if the quiet dynamic Variation Regularity of Morphological Characteristics of the reality of bridge structure
Spread relationship with the quiet dynamic Variation Regularity of Morphological Characteristics of theory of lossless bridge is within range of set value, then it is assumed that at bridge structure
In normal condition；Otherwise it is assumed that bridge, there are structural response rule exception, monitoring system issues early warning and simultaneously exports quiet, dynamic form
Rule cross the border difference position and degree.
Further, the conditional information data include at least time duration data T, bridge local environment climatic data A and
Bridge floor vehicle crowd's traffic operation status data B；
Bridge floor vehicle people in varying environment climatic data A and the ken locating for duration T and bridge is accumulated in step d1
The lossless bridge structure theory deformation data Cw and theoretical power condition data Dw obtained under operation situation data B is led in flock-mate, builds
Found mathematics network model f (T/A/B)=g (Cw/Dw) of the quiet dynamic Variation Regularity of Morphological Characteristics of theory of lossless bridge；
Bridge floor vehicle in varying environment climatic data A and the ken locating for duration T and bridge is accumulated in step d2
The practical bridge structure geometric shape holographic data Cs and practical structures power obtained under crowd's traffic operation status data B
The mathematics network model f ' (T/A/B) of the quiet dynamic Variation Regularity of Morphological Characteristics of the reality of condition holographic data Ds=g ' (Cs/Ds).
In step e, by bridge floor vehicle crowd's traffic operation shape in the amblent air temperature data A of current T period and the ken
The quiet dynamic shape of reality of the theory quiet dynamic Variation Regularity of Morphological Characteristics [T/A/B/Cw/Dw] and practical bridge of lossless bridge under condition data B
State changing rule [T/A/B/Cs/Ds] is compared analysis, ends present period, if the quiet dynamic form of the reality of bridge structure becomes
Quiet dynamic Variation Regularity of Morphological Characteristics f (the T/A/B)=g (Cw/Dw) of the theory of law f ' (T/A/B)=g ' (Cs/Ds) and lossless bridge
Spread relationship within range of set value, then confirm that bridge structure is in normal condition；Otherwise it is assumed that there are structure shapes for bridge
State response pattern is abnormal, monitoring system issue early warning and export quiet, dynamic form law cross the border difference position and degree.
Further, in step a2, bridge local environment climatic data includes temperature, humidity, sunshine, wind, rain, snow when Ti
At least one of climatic information data；Bridge floor vehicle crowd traffic operation status data includes in scope of sight when Ti
At least one of vehicle fleet size, vehicle, car weight, position, speed and Crowds Distribute information data.
Further, in step a2 and step e, bridge structure static image data and Ti+ Δ period bridge structure are dynamic when Ti
State image acquisitions may be set to:
Bridge structure static image data and Ti+ Δ period bridge knot when acquiring Ti simultaneously to the same section structure of bridge
Structure dynamic image data；
Alternatively, first successively continuous acquire the multiple section structure static image datas of bridge respectively, then bridge is successively acquired respectively
The multiple section structure dynamic image video datas of beam；
Alternatively, being directed to specific bridge or specified structure region, it is set as trigger-type and obtains bridge structure static image data
With the fixing camera of structure dynamics video data, the trigger-type acquisition, which refers to, sets specific trigger condition for bridge
Indicate that fixing camera acquires image data when generation.
Further, the vibration shape, amplitude and vibration frequency can get according to the analysis of bridge structure dynamic video data data.
Further, in step a1, obtaining conditional information data for the first time can obtain under bridge light condition, as bridge
Monitor the basic data of starting.
Further, if the bridge is the large bridge in construction, Qj section is the bridge to have completed in process of construction
Section, the conditional information data include at least time duration data and bridge construction status data.
The invention also discloses a kind of quiet dynamic image holography condition health monitoring systems of bridge, comprising:
Conditional information data capture unit, for obtaining the conditional information data of bridge；
Image information data capture unit, for obtaining the static image data and dynamic vision frequency of practical bridge structure
According to；
Central processing unit, for receiving, storing, analyze, treatment conditions information data obtain bridge conditional information number
According to the practical bridge geometric shape holographic data of image information data acquisition and structural dynamic characteristic holographic data, and be used for
The gross data store, analyze, handling lossless bridge completes the quiet dynamic image holography condition health monitoring diagnosis side of the bridge
The step a to e of method.
Further, conditional information data capture unit includes at least the clock list for obtaining bridge time duration data
Member, the environmental information monitoring unit for obtaining bridge local environment information data and for obtaining bridge floor traffic operation
The bridge deck traffic information monitoring unit of status data；The image information data capture unit is in the horizontal and vertical direction can be certainly
The intelligent imaging acquisition device for moving touring rotation, sectional obtains quiet in the length and short transverse of the monitored bridge in edge
State image and dynamic video.
Beneficial effects of the present invention: the quiet dynamic image holography condition health monitoring diagnostic method of bridge of the invention and system,
The conventional bridges such as more existing displacement, acceleration and strain by installing sensor acquisition limited configurations point at setting position
Health monitoring systems have the characteristics that following several:
1, contactless monitoring, data have reliability.Amblent air temperature, vehicle effect, structural form and reason of the invention
By analysis four big components be independently of other than pontic monitoring and analytical equipment, periodic calibrating can be carried out, be fetched data
Long-term reliability provide credible guarantee.Monitoring data obtain the normal use for not influencing bridge.
2, touring rotation image collection, data holographic and device economy.The present invention utilizes one (or several) position control
The high speed high definition image acquisition device of touring steering obtains Structural Static to large bridge sectional and moves image modality holographic data,
Means guarantee is provided economically to obtain the dynamic image modality holographic data of exhaustively Structural Static.
3, quiet dynamic holographic form monitoring, diagnosis is more accurate evidence.The present invention is by obtaining amblent air temperature to healthy bridge
Information, bridge floor vehicular traffic operation information and bridge structure static image and dynamic video acquire information, and according to healthy bridge
Amblent air temperature and vehicle effect are inputted the theoretical model by the finite element theory model for establishing lossless bridge, and analysis obtains lossless
The theoretical geometric shape of bridge structure changes and dynamic characteristics, and acquires acquisition with by static image and dynamic video
The practical geometric shape of current bridge structure changes and the holographic comparative analysis of dynamic characteristics progress, at the beginning of bridge health monitoring
Phase can be according to the theoretical quiet dynamic form of lossless bridge and when actually quiet dynamic form carries out holographic comparative analysis (to quiet dynamic shape to front axle beam
The comprehensive comparative analysis of the carry out such as geometrical property of state curve such as slope, convex-concave degree, inflection point, frequency, amplitude, phase), it [avoids
Quiet dynamic monitoring data in conventional bridge health monitoring only in accordance with limited measure node, which are analyzed and determined, (not can be carried out holographic characteristic
Form compares) the structural form information response that structural damage generates may be omitted], in conjunction with the comparison of traditional control point magnitude
The diagnosis of progress initial stage health status (is equivalent to the rigid graduate students of medical college to practise medicine).
4, image mosaic is abandoned, machine learning gets wisdom diagnosis.With [T/A/B/Cw/Dw] ij and [T/A/B/Cs/
Ds] the gradually accumulation of ij sample data gradually establishes and improves bridge by the machine deep learning to historical sample data
At various complex conditions (annual time T, amblent air temperature A, various types of vehicles load action B), the quiet dynamic condition of bridge practical structures
The mapping relations and changing rule of [Cs] and [Ds] and lossless bridge theoretical construct quiet dynamic condition [Cw] and [Dw], make the later period according to
The real time health diagnosis obtained according to bridge monitoring big data and artificial intelligence analysis is more fine and smooth accurate.
The present invention is used to detect and evaluate the safety of bridge, is realized by the storage and calculating of data, passes through big data
Processing and operation obtain, easy to operate, the time is short, high-efficient, requires detection bridge low, improves the structural bodies such as bridge
Safe early warning ability, thus have the advantages that work efficiency is high, at low cost, it can be achieved that a wide range of bridge safety supervision of high frequency.
The present invention can form the whole monitoring of large bridge as needed, can also be as desired for a certain spy of bridge
Point region is detected, and can rapidly obtain data and by calculating whole, the reading of the detection data storage to later period that obtains result
Data Analysis Services be automatically performed from the background by software, can maximumlly avoid artificial subjective factor from influencing；
Detection and safety evaluation of the present invention for structural bodies such as bridges, reduce daily management personnel technical requirements, can
Realize the security evaluation and early warning of large bridge, effective guarantee structure safe operation reduces its pipe, forms this, has biggish
Social and economic implications, while also with good application prospect.
Detailed description of the invention
The invention will be further described with reference to the accompanying drawings and examples.
Fig. 1 is the flow diagram of method of the invention；
Fig. 2 is the functional block diagram of system of the invention；
Fig. 3 is that data of the invention acquire distribution schematic diagram (facade)；
Fig. 4 is that data of the invention acquire distribution schematic diagram (plane).
Specific embodiment
The quiet dynamic image holography condition health monitoring diagnostic method of bridge of the invention, including the following steps:
A. bridge structure initial information data are obtained；
A1. conditional information data when Ti are acquired；Conditional information data, which are generally comprised, has actual influence to bridge life
Data, such as time duration data, bridge local environment climatic data, bridge floor traffic state data etc. all pairs of bridges
The beam service life has influential data；
The Qj section structure static image data and Ti+ of bridge when a2. acquiring the Ti under step a1 conditional information data
The Qj section structure dynamic video data of Δ period bridge；Static image data can utilize Chinese patent ZL201610300691
The method of " the structural deformation monitoring method of difference analysis is folded based on contour line image " is obtained, and existing computer view can also be used
Feel that measuring technique carries out structure probability edge extracting and holographic morphological parameters extractive technique, details are not described herein；Dynamic video
Data generally comprise the amplitude that can characterize bridge state, the vibration shape and vibration frequency etc., utilize existing computer vision measurement
Technology realizes Euler's visual movement information amplifying technique, and the movement key message decomposed based on SVD is extracted, and existing skill is belonged to
The application of art, details are not described herein；
A3. it is handled by the Qj section structure static image analysis of bridge when Ti, obtains practical bridge Qj session representations structure
The geometric shape holographic data Cs of deformation characteristic；By the Qj section structure dynamic video analysis processing of bridge when Ti+ Δ, obtain
Practical bridge Qj section structure dynamic holographic morphological data Ds；Geometric shape holographic data Cs and dynamic holographic morphological data Ds
For the real response of bridge；
B. the detailed finite element theoretical model of lossless bridge is established；
B1. the structural theory state parameter E of lossless bridge when Ti is inputted；Structural theory state parameter E refers to that the time prolongs
The theoretical bridge influenced when the material being included in when continuing to Ti with characteristic；
B2., conditional information data in step a1 when Ti are brought into the detailed finite element theoretical model of lossless bridge；
B3. according to step b1 and b2, the theory that lossless bridge Qj session representations malformation characteristic when Ti is calculated is several
The theoretical dynamic holographic morphological data Dw of what morphology holography data Cw and Ti+ Δ period lossless bridge Qj section structure is (i.e. lossless
The theoretical response of bridge)；Under the premise of known conditions information data, lossless bridge theory geometric shape is obtained by calculating
Holographic data Cw and theoretical dynamic holographic morphological data Dw, belongs to the prior art, details are not described herein；
C. the geometric shape holographic data Cs of the characterization practical structures deformation characteristic of step a3 and practical structures dynamic is complete
Breath performance data Ds malformation gross data Dw and theoretical power performance data Dw corresponding with step b3's is compared point
Analysis, geometric shape holographic data Cs and practical structures dynamic holographic performance data Ds relative to malformation gross data Cw and
The difference of theoretical power performance data Dw is then healthy bridge state within setting value, otherwise for textural anomaly and is exported different
Normal position and degree；Setting value is the deformation characteristics that should be had under given conditions according to healthy bridge, no longer superfluous herein
It states；
D. such as the Qj section structure of step c Bridge is normal condition, then ij circulation step a2, a3, b2, b3 and c, right
The historical sample data of accumulation carries out machine deep learning；Ij circulation refers to different condition information data item in time duration
The geometric shape holographic data Cs and practical structures dynamic holographic performance data Ds of bridge Qj section when being directed to different Ti under part
The data of data acquisition and malformation gross data Cw and theoretical power performance data Dw calculate, and carry out machine depth
The quiet dynamic form of theory of healthy bridge state actually quiet dynamic Variation Regularity of Morphological Characteristics and lossless bridge theoretical construct state is formed after habit
Changing rule；
D1. lossless bridge structure theory deformation data Cw and the theoretical power being accumulated under different condition information data
State data Dw establishes the judgement network model of lossless bridge, and persistent accumulation sample data, carries out to the judgement network model
It is lasting to modify (ij circulation) and perfect, the structural theory deformation data Cw and theoretical power condition number of the bridge structure that theorizes
According to the quiet dynamic Variation Regularity of Morphological Characteristics of theory that Dw is acted on different condition information data, cycle-index is more, and regular amendment is got over
Accurately, foundation is provided for bridge health monitoring；
The historical sample data that d2 obtains accumulation to practical bridge carries out machine deep learning (ij circulation), establishes practical
Corresponding geometric shape holographic data Cs and practical structures dynamic holographic performance data Ds are with different condition Information Number for bridge structure
According to the quiet dynamic Variation Regularity of Morphological Characteristics of the reality of effect；
E. by the knot of the theory state changing rule model of the lossless bridge under current condition information data and practical bridge
Structure state change rule model is compared analysis, ends present period, if the quiet dynamic Variation Regularity of Morphological Characteristics of the reality of bridge structure
Spread relationship with the quiet dynamic Variation Regularity of Morphological Characteristics of theory of lossless bridge then confirms at bridge structure within range of set value
In normal condition；Otherwise it is assumed that there are structural response rule exceptions (generally to lead to structural response because micro-damage gradually develops for bridge
It is regular abnormal), monitoring system issue early warning and export quiet, dynamic form law cross the border difference position and degree.
In the present embodiment, the conditional information data include at least time duration data T, bridge local environment weather number
According to A and bridge floor traffic state data B；
Duration T and difference bridge local environment climatic data A and ken bridge floor traffic are accumulated in step d1
The lossless bridge structure theory deformation data Cw and theoretical power condition data Dw obtained under status data B, establishes lossless bridge
Quiet dynamic Variation Regularity of Morphological Characteristics function f (the T/A/B)=g (Cw/Dw) of theory；I.e. in duration T and different bridge local environments
The structural theory deformation data of theoretical bridge is obtained under climatic data A and ken bridge floor traffic state data B by calculating
Cw and theoretical power condition data Dw is accumulating certain duration T and difference bridge local environment climatic data A and view
After the bridge floor traffic state data B of domain, form the function of corresponding relationship, for as judge practical bridge whether health
Standard；
Duration T and difference bridge local environment climatic data A and ken bridge floor traffic are accumulated in step d2
The practical bridge structure geometric shape holographic data Cs and practical structures dynamic holographic performance data Ds obtained under status data B
Quiet dynamic Variation Regularity of Morphological Characteristics function f ' (the T/A/B)=g ' (Cs/Ds) of reality；That is the ring locating for duration T and different bridges
Practical bridge structure geometric shape holography is obtained by camera shooting under border climatic data A and ken bridge floor traffic state data B
Data Cs and practical structures dynamic holographic performance data Ds is accumulating certain duration T and different bridge local environment gas
Wait data A and ken bridge floor traffic state data B after, form the function curve of corresponding relationship, for f (T/A/B)=
G (Cw/Dw) comparison judge practical bridge whether Jian Kang foundation；
In step e, by the nothing under the amblent air temperature data A of current T period and ken bridge floor traffic state data B
Damage quiet dynamic Variation Regularity of Morphological Characteristics [T/A/B/Cw/Dw] the i.e. f (T/A/B) of theory=g (Cw/Dw) and practical bridge reality of bridge
Quiet dynamic Variation Regularity of Morphological Characteristics [T/A/B/Cs/Ds] i.e. f ' (the T/A/B)=g ' (Cs/Ds) in border is compared analysis, when ending current
Section, if the theory of quiet dynamic Variation Regularity of Morphological Characteristics f ' (the T/A/B)=g ' (Cs/Ds) of the reality of bridge structure and lossless bridge is quiet dynamic
Variation Regularity of Morphological Characteristics f (T/A/B)=g (Cw/Dw) spread relationship then confirms that bridge structure is within range of set value
Normal condition；Otherwise it is assumed that there are structural response rule exceptions (generally to cause structural response to be advised because micro-damage gradually develops for bridge
Rule is abnormal), monitoring system issue early warning and export quiet, dynamic form law cross the border difference position and degree.
In the present embodiment, in step a2, when Ti bridge local environment climatic data include temperature, humidity, sunshine, wind,
Rain, snow at least one of climatic information data, certainly, may also include earthquake, tsunami, air pH value etc. all to bridge
The weather conditions that beam influences can have and stress for the difference of bridge local environment；Bridge deck traffic status data is included in when Ti
Driving quantity, vehicle, car weight, position, velocity information data in scope of sight is at least one, according to the use condition of bridge
It is different, it may include subway, light rail, train etc. by the frequency, car weight, speed, details are not described herein.
In the present embodiment, in step a2 and step e, bridge structure static image data and Ti+ Δ period bridge knot when Ti
The acquisition of structure dynamic image data may be set to:
Bridge structure static image data and Ti+ Δ period bridge knot when acquiring Ti simultaneously to the same section structure of bridge
Structure dynamic image data；
Alternatively, the first successively multiple section structure bridge structure static image datas of continuous acquisition bridge, then successively adopt respectively
Collect the multiple section structure dynamic image datas of bridge；
Alternatively, being directed to specific bridge or specified structure region, it is set as trigger-type and obtains bridge structure static image data
With the fixing camera of structure dynamics image data, the trigger-type acquisition, which refers to, sets specific trigger condition for bridge
Indicate that fixing camera acquires image data when generation, according to the characteristics of bridge and trigger-type data can be used in the convention that is open to traffic
Acquisition, such as the health that bridge can be significantly reacted by the static and dynamic deformation that process bridge occurs of load-carrying vehicle
Situation, setup parameter load-carrying vehicle by when triggering obtain data, at this point, conditional information data should include trigger condition,
That is the trigger datas such as truck also include certainly on the influential other conditions information data of bridge life tool, trigger-type
The data of acquisition include bridge structure static image data and bridge structure dynamic image data.
In the present embodiment, bridge structure dynamic video data includes the vibration shape, amplitude and vibration frequency, these data obtain
It obtains through existing high-definition camera and realizes that Euler's visual movement information is put using existing computer vision measurement technology
Big technology, and extracted based on the SVD movement key message for decomposing (singular value decomposition), belong to the application of the prior art, herein not
It repeats again.
In the present embodiment, in step a1, obtaining conditional information data for the first time can obtain under bridge light condition, as
The basic data of bridge monitoring starting provides basic data to the final acquisition of spread relation curve.
Monitoring method of the invention can also be used in the large bridge in construction, and Qj section is to have completed in process of construction
Bridge section, in construction process, the step of section in splicing is suitable for step a, b, c, d；But the conditional information number
According to time duration data and bridge construction status data is included at least, bridge construction status data generally comprises splicing length number
Have according to the bridge structure static image data and bridge structure dynamic image data to bridge such as (having on bridge weight influences)
Influential data, details are not described herein.
The invention also discloses a kind of quiet dynamic image holography condition health monitoring systems of bridge, comprising:
Conditional information data capture unit, for obtaining the conditional information data of bridge；
Image information data capture unit, for obtaining bridge geometric shape holographic data and practical structures dynamic holographic
Performance data；
Central processing unit, for receiving, storing, analyze, the information data for the treatment of conditions information data acquiring unit and
The bridge geometric shape holographic data and practical structures dynamic holographic performance data of image information data capture unit, Yi Jiyong
In storage, analysis, the gross data for handling lossless bridge, the quiet dynamic image holography condition health monitoring diagnosis of the bridge is completed
The step a to e of method；
In the present embodiment, conditional information data capture unit include at least for obtain bridge a time duration data when
Clock unit, the environmental information monitoring unit 2 for obtaining bridge local environment information data and for obtaining bridge floor traffic
The bridge deck traffic information monitoring unit 1 of status data；Conditional information data include time duration data, bridge local environment gas
Wait data and bridge floor traffic state data；Certainly, the necessary temperature, wet for representative locations when obtaining Ti is needed
The sensor of the data informations such as degree, sunshine, wind, rain, snow, details are not described herein；And bridge floor traffic state data then passes through
Video camera can obtain, and details are not described herein
The image information data capture unit 3 be in the horizontal and vertical direction can the intelligent imaging of automatic touring rotation adopt
Collect camera, for sectional acquisition static image and dynamic video in the length or height of monitored bridge；It is touring turn automatic
It is dynamic that existing mechanical driving structure can be used, i.e., drive camera in the rotation in each orientation using existing power (motor), and
Belong to the prior art using remote control control, details are not described herein.
As previously described and as shown, system of the invention by environmental information monitoring unit (bridge environment climatic information
Monitoring), bridge deck traffic information monitoring unit (bridge deck traffic information monitoring), (bridge structure is dynamic for image information data capture unit
Quiet imaging monitor) and central processing unit (storing lossless bridge finite element theory model on-line analysis system) four part structures
At；The amblent air temperature change information that bridge is obtained by amblent air temperature information monitoring, is acted on by bridge deck traffic information monitoring
The vehicular load change information of bridge obtains bridge structure static(al) metamorphosis data by imaging monitor, is obtained by video surveillance
Bridge structure vibration shape and dynamic characteristics delta data, by the theory analysis of lossless bridge obtain healthy bridge in environment and
Structural theory response data under Vehicle Load.
In use, central processing unit is used to receive, store, analyzing, handling above-mentioned clock unit (time duration number
According to T), environmental information monitoring unit (bridge local environment climatic data A), bridge deck traffic information monitoring unit (bridge floor hand over
Logical status data B) and image information data capture unit information data, and by bridge in the case where [T/A/B] is acted on each section knot
Whether the quiet dynamic response of the reality of structure [Cs/Ds] judges structure compared with the quiet dynamic response [Cw/Dw] of theory of lossless bridge
In the presence of obvious damage；After rear, machine deep learning is carried out to historical sample data practical bridge structure is obtained to respond [Cs/Ds]
With the changing rule of [T/A/B], then with the quiet dynamic response [Cw/Dw] of theory of lossless bridge with [T/A/B] changing rule into
Row comparative analysis, judging that bridge whether there is according to its accordance leads to the micro- of the quiet dynamic response rule exception of practical bridge structure
Damage gradually develops.
Finally, it is stated that the above examples are only used to illustrate the technical scheme of the present invention and are not limiting, although referring to compared with
Good embodiment describes the invention in detail, those skilled in the art should understand that, it can be to skill of the invention
Art scheme is modified or replaced equivalently, and without departing from the objective and range of technical solution of the present invention, should all be covered at this
In the scope of the claims of invention.
Claims (10)
1. a kind of quiet dynamic image holography condition health monitoring diagnostic method of bridge, it is characterised in that: include the following steps:
A. bridge structure initial information data are obtained；
A1. conditional information data when Ti are acquired；
When a2. acquiring the Ti under step a1 conditional information data when the Qj section structure static image data and Ti+ Δ of bridge
The Qj section structure dynamic video data of Duan Qiaoliang；
A3. it is handled by the Qj section structure static image analysis of bridge when Ti, obtains practical bridge Qj session representations malformation
The geometric shape holographic data Cs of characteristic；By the Qj section structure dynamic video analysis processing of bridge when Ti+ Δ, realistic bridges are obtained
Beam Qj section structure dynamic holographic morphological data Ds；
B. the detailed finite element theoretical model of lossless bridge is established；
B1. the structural theory state parameter E of lossless bridge when Ti is inputted；
B2., conditional information data in step a1 when Ti are brought into the detailed finite element theoretical model of lossless bridge；
B3. according to step b1 and b2, the theoretical geometric form of lossless bridge Qj session representations malformation characteristic when Ti is calculated
The theoretical dynamic holographic morphological data Dw of state holographic data Cw and Ti+ Δ period lossless bridge Qj section structure；
C. the geometric shape holographic data Cs of the characterization practical structures deformation characteristic of step a3 and practical structures dynamic holographic is special
Property data Ds malformation gross data Cw corresponding with step b3's and theoretical power performance data Dw are compared analysis, several
What morphology holography data Cs and practical structures dynamic holographic performance data Ds is dynamic relative to malformation gross data Cw and theory
The difference of force characteristic data Dw is within setting value, then the Qj section structure of bridge is judged as without the normal condition obviously damaged,
Otherwise it is judged as in the presence of the anomaly sxtructure state and output abnormality position and degree obviously damaged；
D. such as Qj section structure of step c Bridge is normal condition, then ij circulation step a2, a3, b2, b3 and c, to accumulation
Historical sample data carries out machine deep learning；
D1. the lossless bridge structure theory deformation data Cw and theoretical power condition data being accumulated under different condition information data
Dw establishes the judgement network model of lossless bridge, and persistent accumulation sample data, is persistently repaired to the judgement network model
Change, the structural theory deformation data Cw and theoretical power condition data Dw for the bridge structure that theorizes are with different condition information data
The quiet dynamic Variation Regularity of Morphological Characteristics of theory of effect；
The historical sample data that d2 obtains accumulation to practical bridge carries out machine deep learning, and it is corresponding to establish practical bridge structure
The reality that geometric shape holographic data Cs and practical structures dynamic holographic performance data Ds are acted on different condition information data is quiet
Dynamic Variation Regularity of Morphological Characteristics；
E. by the structure shape of the theory state changing rule model of the lossless bridge under current condition information data and practical bridge
State changing rule model is compared analysis, ends present period, if the quiet dynamic Variation Regularity of Morphological Characteristics of the reality of bridge structure and nothing
The spread relationship of the quiet dynamic Variation Regularity of Morphological Characteristics of theory of bridge is damaged within range of set value, then confirms that bridge structure is in normal
State；Otherwise it is assumed that bridge, there are structural response rule exception, monitoring system, which issues early warning and exports quiet, dynamic form law, crosses the border
The position of difference and degree.
2. the quiet dynamic image holography condition health monitoring diagnostic method of bridge according to claim 1, it is characterised in that: described
Conditional information data include at least time duration data T, bridge local environment climatic data A and bridge floor traffic state data
B；
Duration T and difference bridge local environment climatic data A and ken bridge floor traffic condition are accumulated in step d1
The lossless bridge structure theory deformation data Cw and theoretical power condition data Dw obtained under data B, establishes the reason of lossless bridge
By quiet dynamic Variation Regularity of Morphological Characteristics function f (T/A/B)=g (Cw/Dw)；
Duration T and difference bridge local environment climatic data A and ken bridge floor traffic condition are accumulated in step d2
The reality of the practical bridge structure geometric shape holographic data Cs and practical structures dynamic holographic performance data Ds that are obtained under data B
Quiet dynamic Variation Regularity of Morphological Characteristics function f ' (T/A/B)=g ' (Cs/Ds).
In step e, by the lossless bridge under the amblent air temperature data A of current T period and ken bridge floor traffic state data B
Theory quiet dynamic Variation Regularity of Morphological Characteristics [T/A/B/Cw/Dw] and practical bridge the quiet dynamic Variation Regularity of Morphological Characteristics [T/A/B/Cs/ of reality
Ds] it is compared analysis, end present period, if quiet dynamic Variation Regularity of Morphological Characteristics f ' (the T/A/B)=g ' of the reality of bridge structure
(Cs/Ds) the spread relationship with quiet dynamic Variation Regularity of Morphological Characteristics f (the T/A/B)=g (Cw/Dw) of theory of lossless bridge is in setting value model
Within enclosing, then confirm that bridge structure is in normal condition；Otherwise it is assumed that there are structural response rule exception, monitoring system hairs for bridge
Out early warning and export quiet, dynamic form law cross the border difference position and degree.
3. the quiet dynamic image holography condition health monitoring diagnostic method of bridge according to claim 1, it is characterised in that: step
In a2, when Ti bridge local environment climatic data include temperature, humidity, sunshine, wind, rain, in snow climatic information data at least
It is a kind of；Bridge deck traffic status data includes driving quantity, vehicle, car weight, position, velocity information number in scope of sight when Ti
According at least one.
4. the quiet dynamic image holography condition health monitoring diagnostic method of bridge according to claim 3, it is characterised in that: step
In a2, when Ti bridge local environment climatic data include temperature, humidity, illumination, wind, rain, in snow climatic information data at least
It is a kind of；Bridge deck traffic status data includes driving quantity, vehicle, car weight, position, velocity information number in scope of sight when Ti
According at least one.
5. the quiet dynamic image holography condition health monitoring diagnostic method of bridge according to claim 1, it is characterised in that: step
In a2 and step e, bridge structure static image data and the acquisition of Ti+ Δ period bridge structure dynamic image data can be set when Ti
Are as follows:
Bridge structure static image data and Ti+ Δ period bridge structure dynamic when acquiring Ti simultaneously to the same section structure of bridge
Image data；
Alternatively, the first successively multiple section structure bridge structure static image datas of continuous acquisition bridge, then bridge is successively acquired respectively
The multiple section structure dynamic image datas of beam；
Alternatively, being directed to specific bridge or specified structure region, it is set as trigger-type and obtains bridge structure static image data and knot
The fixing camera of structure dynamic image data, when the trigger-type acquisition refers to that setting specific trigger condition for bridge occurs
Indicate that fixing camera acquires image data.
6. the quiet dynamic image holography condition health monitoring diagnostic method of bridge according to claim 1, it is characterised in that: bridge
Structure dynamics video data includes the vibration shape, amplitude and vibration frequency.
7. the quiet dynamic image holography condition health monitoring diagnostic method of bridge according to claim 1, it is characterised in that: step
In a1, obtaining conditional information data for the first time can obtain under bridge light condition, the basic data as bridge monitoring starting.
8. the quiet dynamic image holography condition health monitoring diagnostic method of bridge according to claim 1, it is characterised in that: if institute
Stating bridge is the large bridge in construction, and Qj section is the bridge section to have completed in process of construction, the conditional information number
According to including at least time duration data and bridge construction status data.
9. a kind of quiet dynamic image holography condition health monitoring systems of bridge, it is characterised in that: include:
Conditional information data capture unit, for obtaining the conditional information data of bridge；
Image information data capture unit, for obtaining bridge geometric shape holographic data and practical structures dynamic holographic characteristic quantity
According to；
Central processing unit, for receiving, storing, analyze, the information data and image for the treatment of conditions information data acquiring unit
The bridge geometric shape holographic data and practical structures dynamic holographic performance data of information data acquiring unit, and for depositing
The gross data of storing up, analyze, handling lossless bridge completes the quiet dynamic image holography condition health monitoring diagnostic method of the bridge
Step a to e.
10. the quiet dynamic image holography condition health monitoring systems of bridge according to claim 9, it is characterised in that: condition letter
Data capture unit is ceased to include at least for obtaining the clock unit of bridge time duration data, for obtaining bridge local environment
The environmental information monitoring unit of information data and bridge deck traffic information monitoring list for obtaining bridge floor traffic state data
Member；The image information data capture unit be in the horizontal and vertical direction can the intelligent imaging of automatic touring rotation acquire camera,
For sectional acquisition static image and dynamic video in the length or height of monitored bridge.
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