CN111337924A - Crack identification and detection method for bridge health monitoring - Google Patents
Crack identification and detection method for bridge health monitoring Download PDFInfo
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- CN111337924A CN111337924A CN202010299669.0A CN202010299669A CN111337924A CN 111337924 A CN111337924 A CN 111337924A CN 202010299669 A CN202010299669 A CN 202010299669A CN 111337924 A CN111337924 A CN 111337924A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
- G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
- G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
- G01S13/9021—SAR image post-processing techniques
- G01S13/9023—SAR image post-processing techniques combined with interferometric techniques
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Abstract
A crack identification and detection method for bridge health safety monitoring. Transmitting an electromagnetic wave signal from a radar to the surface of the bridge by a frequency modulation continuous wave technology of a ground-based SAR, reflecting the electromagnetic wave signal from the surface of the bridge and then receiving the electromagnetic wave signal, performing difference frequency difference processing on the phases of the transmitted signal and the received signal, further performing noise elimination and atmospheric correction, and processing corresponding characteristic point network pixels to form a radar sight line direction distortion diagram of the monitoring point; error processing and model calculation in the monitoring process are carried out, and then a conversion model is constructed to obtain a deformation value of the self-vibration direction of the bridge; establishing a qualitative or quantitative cracking and damage judgment standard of the bridge by combining the loading deformation characteristic of the bridge; and (4) carrying out mutation inflection point analysis by combining the bridge structure and mechanical characteristics, and qualitatively judging whether the bridge has crack damage and health potential safety hazard. The invention has simple and convenient process, high monitoring and positioning speed and high precision, does not need to directly contact the bridge, is safe and reliable, can replace various sensors such as level, close-range photography, stress strain gauges and the like in bridge operation health monitoring, and has obvious safety and economic benefits.
Description
Technical Field
The invention belongs to the technical field of civil engineering and surveying and mapping engineering, and particularly relates to a crack identification and detection method for bridge health safety monitoring.
Background
Unreasonable design parameters, long-term overload transportation, aging, natural disasters and other reasons can cause cracking, deformation and even damage of a bridge concrete structure, the safety and the bearing capacity of the bridge concrete structure are weakened, and the operation safety of the bridge is influenced. The amplitude can increase under the condition that the bridge structures are damaged, and the damage can be aggravated by static load or dynamic load under the condition that a plurality of damages exist. Therefore, detection of damage such as cracks should be enhanced, and particularly, occurrence of multiple damages should be excluded. At present, a displacement measurement sensor is the most commonly used method for acquiring deformation of a bridge structure, but a bridge often spans rivers, sea channels or mountainous regions, the existing displacement sensor is difficult to finely reflect micro deformation conditions of the bridge structure in an economic, comprehensive and effective mode, and particularly the occurrence and development of micro deformation such as cracks are difficult to identify. The ground-based synthetic aperture radar (GBSAR) system combines the differential interference, synthetic aperture and frequency modulation continuous wave technology, and has the capacity of acquiring submillimeter-level deformation of a point target in a monitoring range. Compared with common deformation monitoring methods such as precision level, stress strain gauges, total stations, three-dimensional laser scanners, close-range photogrammetry and GPS, the ground-based interference radar does not need to be in contact with a target area, is convenient to install quickly, is slightly influenced by severe meteorological conditions such as cloud, fog and rain, and provides a submillimeter-level point cloud surface monitoring result. From the analysis of the monitoring results, the bridge pier is a stable area of the bridge, but the deformation and the amplitude of other parts of the bridge linearly increase along with the increase of the loading.
Disclosure of Invention
The invention aims to provide a crack identification and detection method for bridge health safety monitoring, which can be used for rapidly and accurately acquiring crack generation and development changes of a bridge at low cost according to the structural characteristics of the bridge to obtain evaluation parameters of bridge health safety.
To achieve the above object, the embodiments of the present invention are: a crack identification and detection method for bridge health safety monitoring comprises the following steps:
(1) transmitting an electromagnetic wave signal from a radar to the surface of the bridge by a frequency modulation continuous wave technology of a ground-based SAR, reflecting the electromagnetic wave signal from the surface of the bridge and then receiving the electromagnetic wave signal, performing difference frequency difference processing on the phases of the transmitted signal and the received signal, further performing noise elimination and atmospheric correction, and processing corresponding characteristic point network pixels to form a radar sight line direction distortion diagram of the monitoring point;
(2) error processing and model resolving in the monitoring process are carried out, the accuracy of monitoring the deformation of the visual line direction of the ground SAR is ensured, and then a conversion model is constructed to obtain the deformation value of the self-vibration direction of the bridge;
(3) establishing a qualitative or quantitative cracking and damage judgment standard of the bridge by combining the loading deformation characteristics of the bridge, thereby realizing the crack identification evaluation on the health of the bridge;
(4) and (4) carrying out mutation inflection point analysis by combining the bridge structure and mechanical characteristics, and qualitatively judging whether the bridge has crack damage and health potential safety hazard.
In the step (1), the processing of the corresponding feature point network pixels includes phase filtering, unwrapping, coordinate transformation, geocoding and the like.
In the step (2), the error processing comprises atmospheric effect influence, phase integer ambiguity, noise and the like, and the atmospheric effect influence is corrected by adopting a corresponding atmospheric error model; for the influence of phase integer ambiguity error, a permanent scatterer method is adopted for processing and a corresponding phase unwrapping method is adopted for solving the problem; and for the influence interference of the noise, filtering by adopting a smooth spline function.
In the step (3), the bridge loading deformation characteristics include dynamic characteristics such as natural vibration frequency, damping ratio, rigidity and bearing capacity.
The method has the advantages of simple and convenient process, high monitoring and positioning speed and high precision, does not need to directly contact the bridge, is safe and reliable, can replace various sensors such as level, close-range photography, stress strain gauges and the like in bridge operation health monitoring, has obvious safety and economic benefits, and has positive significance for crack identification and health deformation monitoring evaluation of the bridge
Drawings
FIG. 1 is a GBSAR data processing flow of the present invention;
FIG. 2 is a geometric relationship diagram of the radar sight line and the vertical deformation direction of the present invention;
FIG. 3 is a graph of SAR monitoring and radar intensity mapping for a solid model bridge foundation according to the present invention;
fig. 4 is a time series of deformation (LOS) of characteristic points of a monitored area according to the present invention.
Detailed Description
A crack identification and detection method for bridge health safety monitoring comprises the following specific steps:
(1) frequency modulation continuous wave technology of ground-based SAR (synthetic aperture radar) by transmitting a signal with center frequency f through radarcFrequency modulating signal with bandwidth B toThe bridge surface, the frequency signal f reflected by the bridge surface and received, transmitted and receivedb. The radar can only record phase information of less than a whole circle in the phase of the target echo, namely the obtained phase is winding. The interference phase can be obtained by performing differential interference on two-phase radar images of the same target at different moments, as shown in formula (1):
wherein phi isωIn order to interfere with the phase of the phase,
for the phase component related to the actual displacement,
is the atmospheric phase component of the air phase,
as a noise phase component, k1、k2The integer ambiguities of the phases of the target points at two moments in time are respectively. After noise elimination and atmospheric correction, solving the deformation value delta r of the target in the LOS direction by the phase difference after unwrapping:
where λ is the wavelength.
The ground-based SAR data processing process is similar to satellite-borne time-series INSAR data processing, and the data processing flow is shown in FIG. 1. Firstly, carrying out focusing processing on acquired original data to obtain a single-view complex (SLC) SAR image with two-dimensional resolution, then generating a high-coherence point network by an SAR image set, carrying out phase filtering and unwrapping on pixels of the coherence point network, and carrying out geocoding to form a monitoring deformation graph.
(2) Error processing and bridge natural vibration direction deformation solving
In the crack deformation identification and detection of the ground SAR, the crack deformation identification and detection method usually existsThe influence of atmospheric refraction, shielding and the like can cause the measurement error of the radar visual line, resulting in the result obtained in the formula (1)
kiAnd (4) value errors are introduced, and deformation resolving errors are introduced. For the
Correcting the influence of the error by adopting an error model; k is a radical ofiThe influence of value error is solved by adopting a PS method to process and a corresponding phase unwrapping method; for the
The influence of (2) is interfered, and a model smoothing spline function is adopted for filtering processing. For an input signal f (x)i) The low-pass filtering of the deformation time sequence of the point location of the foundation SAR in the time dimension can be realized by adopting a smooth spline, and the optimal estimation of the deformation information is obtained by calculating the minimum value of a cost function J (lambda):
J(λ)＝min{||Δri-Δdi||2+λ||DΔri||2} (3)
wherein the content of the first and second substances,
in the formula (3), Δ diLOS direction deformation value of PS point of ith scene image; λ is a smoothing coefficient, and when the value of λ approaches 0, the curve passes through as many points as possible, and when it approaches 1, the result approaches a straight line. In order to solve the uncertainty influence of the selection of lambda on the smoothing result, the generalized cross-validation method (GCV) can be used for carrying out optimal estimation on the value of the lambda, and the formula (3) is converted into linear operation by a method of solving a free extreme value:
(In+λDTD)Δri＝Δdi(4)
λ＝argmin(GCV) (5)
in the formula InIs an n-order identity matrix. Then, the optimal lambda can be obtained by the loop iteration of the formula (5)。
The algorithm relies only on input and output signals, and the progressive optimum of the threshold can be obtained directly from the minimization error function:
in the formula, tr is a trace of the matrix. According to the optimal lambda value, the deformation component delta r after smoothing can be calculated by the formula (4)i. The smoothing spline filtering automatically selects corresponding smoothing parameters according to the information difference of the characteristic points of the permanent scatterers, can effectively weaken the influence of phase jump caused by unwrapping errors, and accurately separate outliers in the deformation time sequence of the characteristic points of the permanent scatterers, thereby accurately resolving the deformation value of the radar line of sight.
In order to formulate a crack identification judgment basis and standard, the structural characteristics and the dynamic characteristics of the bridge are combined, analysis such as the self-vibration frequency, the amplitude and the damping ratio of the bridge is carried out, and a conversion model from deformation in the radar sight line direction to deformation in the self-vibration amplitude direction of the bridge is constructed. As shown in fig. 2, the conversion relationship and the error processing analysis are as the following formula (7), and when the medium error of the monitoring value and the like meets the precision requirement of precision engineering measurement, the precision of the deformation monitoring of the foundation SAR is considered reliable and effective.
(S1-ΔS)2-(H1-ΔH)2＝S1 2-H1 2(7)
Wherein the content of the first and second substances,
the median error can be expressed as:
(3) determination of qualitative and quantitative criteria
The experimental and analytical examples combined with a certain indoor solid model bridge are as follows: the solid model bridge used in the experiment is a three-span prestressed concrete continuous box girder bridge (65m +110m +65m), the midspan of the model solid bridge is manufactured in the experiment plant in a reduced mode according to the geometric similarity ratio of 1:4, the total length is 35m, and the midspan span is 27.41 m. The two side span simulation states mainly apply vertical counter force through the ground anchor point, so that the model support hogging moment accords with the dead weight effect characteristic of the three-span continuous bridge. The deformation information of the characteristic parts of the bridge is effectively extracted and analyzed by adopting a foundation SAR, 6 corner reflectors (P1-P6 respectively) are arranged at the bridge piers of the southwest side (loading side) of the bridge and the bridges 1/8, 1/4, 1/2, 3/4 and 7/8, and radar observation is positioned at the position where the bridge heads of the southeast side of the bridge move outwards by 3 meters. The solid model bridge foundation SAR monitoring and radar intensity image is shown in fig. 3.
In the dynamic loading process of the bridge, the deformation monitoring time sequence result of the ground SAR reflects that the radar visual line is always stretched along with the increase of the vehicles and shows that the radar visual line is continuously increased; as the dynamic loading advances, the point location will be deformed more with the same vehicle applied subsequently, as shown by the increasing slope of the deformation curve in time series, as shown by the change in radar line of sight from the [ 01244 scene ] image time in fig. 4. The loading part usually has the largest displacement and gradually decreases from the loading point to characteristic points on two sides, when a crack appears below the loading part and is damaged, the response characteristic of the deformation is more obvious, the more sensitive the deformation along the radar visual line is, the larger the amplitude and the acceleration along with the increase of the loading time sequence is, but the dynamic characteristics such as the natural vibration frequency, the damping ratio, the rigidity, the bearing capacity and the like are obviously reduced, and a larger sudden change inflection point exists. In the continuous observation process, the foundation SAR can well identify the inflection point, and a qualitative or quantitative damage judgment standard of the bridge is established, so that the qualitative safety evaluation on the health of the bridge is realized.
(4) Crack damage judgment and result verification
The radar line of sight (LOS) deformation value of the bridge acquired by the ground SAR can visually reflect the occurrence and development conditions of beam body stretching and cracks, if the dead load pressurization damage of the bridge reduces the self-vibration frequency and the damping ratio of the bridge in the continuous monitoring process, the process generates structural damage of a stressed member to the bridge, the rigidity of the bridge is reduced, the structure dissipation and the capacity of resisting external input energy are weakened, the vibration attenuation is slowed down, and the bearing capacity is deteriorated. The bridge structure and the mechanical characteristics are combined to carry out structural dynamics characteristics such as frequency spectrum and damping ratio, whether damage and health potential safety hazards exist in the bridge can be judged qualitatively, and inherent monitoring risks of the traditional contact sensor are reduced.
Therefore, structural damage of the bridge can be generally identified through detection of the dynamic characteristic change, and the ground-based SAR system not only can provide high-precision and high-frequency bridge dynamic characteristic detection signals under the non-contact condition, but also can comprehensively evaluate the appearance and the internal damage of the operation condition of the ground-based SAR system, and has positive significance for crack identification and health deformation monitoring evaluation of the bridge.
Claims (4)
1. A crack identification and detection method for bridge health safety monitoring is characterized by comprising the following steps:
(1) transmitting an electromagnetic wave signal from a radar to the surface of the bridge by a frequency modulation continuous wave technology of a ground-based SAR, reflecting the electromagnetic wave signal from the surface of the bridge and then receiving the electromagnetic wave signal, performing difference frequency difference processing on the phases of the transmitted signal and the received signal, further performing noise elimination and atmospheric correction, and processing corresponding characteristic point network pixels to form a radar sight line direction distortion diagram of the monitoring point;
(2) error processing and model resolving in the monitoring process are carried out, the accuracy of monitoring the deformation of the visual line direction of the ground SAR is ensured, and then a conversion model is constructed to obtain the deformation value of the self-vibration direction of the bridge;
(3) establishing a qualitative or quantitative cracking and damage judgment standard of the bridge by combining the loading deformation characteristics of the bridge, thereby realizing the crack identification evaluation on the health of the bridge;
(4) and (4) carrying out mutation inflection point analysis by combining the bridge structure and mechanical characteristics, and qualitatively judging whether the bridge has crack damage and health potential safety hazard.
2. The crack identification and detection method for bridge health and safety monitoring as claimed in claim 1, wherein in step (1), the processing of the corresponding feature point mesh pixels comprises processing of phase filtering, unwrapping, coordinate transformation and geocoding.
3. The crack identification and detection method for bridge health and safety monitoring as claimed in claim 1, wherein in the step (2), the error processing includes processing of atmospheric effect influence, phase integer ambiguity and noise, and the atmospheric effect influence is corrected by adopting a corresponding atmospheric error model; for the influence of phase integer ambiguity error, a permanent scatterer method is adopted for processing and a corresponding phase unwrapping method is adopted for solving the problem; and for the influence interference of the noise, filtering by adopting a smooth spline function.
4. The crack identification and detection method for bridge health and safety monitoring as claimed in claim 1, wherein in the step (3), the bridge loading deformation characteristics include dynamic characteristics such as natural vibration frequency, damping ratio, rigidity and bearing capacity.
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| Publication number | Priority date | Publication date | Assignee | Title |
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