A bridge group evaluation method fusing multi-source remote sensing and DS-InSAR

Abstract

The application discloses a bridge group evaluation method fusing multi-source remote sensing and DS-InSAR, and relates to the technical field of structural health monitoring. The method comprises the following steps: extracting the spatial position, geometric size and expansion joint position of the bridge group based on optical remote sensing images; obtaining multi-temporal SAR images, identifying and constructing an observation point network, and combining DEM to obtain differential phase through differential interference processing; performing time series analysis based on a combined temperature model to inverse linear deformation rate and thermal expansion coefficient; identifying suspected risk bridges in combination with preset specification limits; constructing a multi-index evaluation system containing settlement indexes, inclination indexes and rate indexes for the suspected bridges, calculating a comprehensive safety value through an analytic hierarchy process and determining a technical condition grade. The application realizes rapid deformation monitoring and risk grading evaluation of urban bridge groups, and has the advantages of wide monitoring range, high automation degree, objective evaluation results and the like.

Description

Technical Field

[0001] This invention relates to the field of structural health monitoring and infrastructure safety assessment technology, and more specifically, to a method for assessing bridge groups that integrates multi-source remote sensing and DS-InSAR. Background Technology

[0002] Bridges are a crucial component of transportation infrastructure. With increasing traffic volume, longer service life, and the impact of factors such as overloading, insufficient operation and maintenance, and material degradation, bridge structures may experience cumulative deformations such as settlement, deflection, and tilting, thereby affecting their normal service performance. Therefore, long-term monitoring and evaluation of their structural condition throughout their service life is urgently needed. Traditional deformation monitoring methods (such as connecting pipes, deflectometers, GPS, and 3D laser scanning) have limitations such as low automation, high cost, poor durability, and reliance on point sampling, resulting in low detection efficiency and making them unsuitable for the practical needs of long-term deformation monitoring of large-scale urban bridge clusters.

[0003] Spaceborne synthetic aperture radar interferometry (InSAR) is an active microwave remote sensing technology that, due to its all-weather, all-time, wide-area, and high-precision characteristics, has been applied in fields such as surface deformation monitoring and bridge deformation identification. However, existing bridge monitoring research based on InSAR technology still focuses mainly on individual bridges, and systematic monitoring methods and assessment systems for urban bridge groups are still incomplete. At the same time, current bridge safety assessments often mainly utilize macroscopic indicators such as deformation amount, deformation rate, and uneven settlement. How to combine the thermal expansion response characteristics under temperature effects and construct a multi-indicator risk assessment system to achieve the quantitative translation of macroscopic deformation information into structural risk status still requires further research. Summary of the Invention

[0004] The purpose of this invention is to provide a bridge group assessment method that integrates multi-source remote sensing and DS-InSAR (Distributed Scatterer Synthetic Aperture Radar Interferometry) to overcome at least some of the defects in the existing technology, and to achieve lightweight monitoring at the scale of urban bridge groups, rapid identification of suspected risky bridges, and multi-index safety risk classification.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: A bridge cluster assessment method integrating multi-source remote sensing and DS-InSAR includes the following steps: Step 1: Acquire optical remote sensing images of the target bridge group, and extract the spatial location, geometric dimensions, and expansion joint locations of each bridge based on the optical remote sensing images. This step utilizes the non-contact and wide-area advantages of high-resolution optical remote sensing images to quickly obtain prior information on the structural geometry of the bridge group, providing basic data support for subsequent InSAR deformation monitoring and avoiding the tedious process of on-site measurement required by traditional methods.

[0006] Step 2: Acquire multi-temporal SAR images covering the target bridge group, identify and construct an observation point network in the SAR images, and perform differential interferometry processing in conjunction with the digital elevation model (DEM) to obtain the differential phase of each observation point. This step, by constructing a two-layer network of permanent scatterer (PS) points and distributed scatterer (DS) points, can obtain high-density reliable observation points in complex urban environments, improving the spatial resolution and accuracy of deformation monitoring.

[0007] Step 3: Based on the combined temperature model, perform time-series analysis on the differential phase to invert the linear deformation rate and thermal expansion response parameters at each observation point. This step separates the thermal expansion effect from the deformation signal, enabling a more accurate identification of the bridge structure's response characteristics under temperature effects, and providing crucial information for subsequent structural deterioration identification.

[0008] Step 4: Based on the linear deformation rate and thermal expansion response parameters, and in conjunction with preset standard limits, identify suspected bridges with abnormal deformation risks. This step, by comparing the measured deformation parameters with the standard limits, can quickly screen out risk targets requiring key attention at the bridge group scale, significantly improving monitoring efficiency.

[0009] Step 5: For the suspected bridge, a multi-indicator evaluation system including settlement, tilt, and rate indicators is constructed. The weight of each indicator is determined using the Analytic Hierarchy Process (AHP), and the comprehensive safety value of the bridge is calculated based on the monitoring values ​​of each indicator to determine the bridge's technical condition level. This step quantifies macroscopic deformation information into an interpretable structural risk level, providing a scientific basis for decision-making in the operation, maintenance, and risk management of urban bridges.

[0010] Optionally, in step 1, extracting the geometric dimensions and expansion joint locations specifically includes: The Canny operator was used to extract the outline of the main girder of the bridge, and the planar shape of the bridge was determined through morphological operations based on the pixel coordinates of the two ends of the bridge. , With image spatial resolution Calculate the bridge length : ; Calculate the bridge width based on the pixel coordinates of the two transverse ends of the bridge. Alternatively, the bridge width can be obtained from the bridge design parameters. ; A one-dimensional projection of the image grayscale values ​​along the longitudinal direction of the bridge yields the grayscale distribution function. The points where the gray-level gradient changes abruptly are identified as candidate locations for expansion joints. : ; In the formula, This represents the longitudinal length of the bridge.

[0011] Optionally, in step 2, identifying and constructing the observation point network specifically includes: using amplitude threshold and amplitude deviation index to screen permanent scatterer PS points, connecting PS points through Delaunay triangulation to construct the first layer network; using statistical homogeneous pixel identification method to screen distributed scatterer DS points, and constructing the second layer network.

[0012] Optionally, in step 3, the combined temperature model is expressed as: ; In the formula, Differential phase, For radar wavelength, As the time baseline, The linear deformation rate along the line of sight. Slope distance For radar incident angle, For vertical baseline, For DEM elevation error, For the temperature field of the bridge structure, The coefficient of thermal expansion is... The residual phase; the thermal expansion response parameter is the coefficient of thermal expansion. .

[0013] Optionally, in step 4, identifying suspected bridges with abnormal deformation risks specifically includes: performing the following comparisons: comparing the linear deformation rate of each bridge with a preset deformation rate threshold, and comparing the thermal expansion response parameters of each bridge with a preset thermal expansion threshold; if the linear deformation rate of any bridge exceeds the deformation rate threshold, or its thermal expansion response parameters exceed the thermal expansion threshold, then the bridge is marked as a suspected bridge.

[0014] Optionally, in step 5, the settlement index includes the maximum settlement. and cumulative settlement The tilt index includes the pitch angle. and maximum pitch angle The rate indicators include the settling rate. ; Among them, the maximum settlement To determine the linear deformation rate along the line of sight and radar incident angle The calculated maximum vertical displacement, the settlement rate The vertical settlement rate is calculated based on the linear deformation rate ν along the line of sight. The pitch angle Based on the maximum longitudinal settlement difference of the bridge With bridge length calculate: .

[0015] Optionally, the tilt index also includes longitudinal angular deformation. and lateral angular deformation ; The longitudinal angular deformation Based on the maximum longitudinal settlement difference of the bridge With bridge span calculate: ; The lateral angular deformation Based on the maximum difference in the transverse tilt angle of the bridge With bridge span calculate: ; The maximum tilt angle Based on the vertical displacement values ​​on both sides of the same cross-section of the bridge , With bridge width calculate: , For each local tilt angle The maximum value.

[0016] Optionally, step 5, which involves determining the weights of each indicator using the analytic hierarchy process (AHP) and calculating the overall safety value of the bridge, includes: determining the weights of each indicator using the AHP. The monitoring values ​​of each indicator are dimensionless to obtain the safety index of each indicator. Calculate the comprehensive safety value using the following formula. : ; In the formula, n This refers to the number of indicators.

[0017] Optionally, in step 5, determining the bridge's technical condition level specifically includes: calculating the comprehensive safety value... Compare with multiple preset level threshold ranges, and according to The threshold range in which the bridge is located determines its technical condition level.

[0018] Compared with the prior art, the present invention has the following beneficial effects: (1) It realizes rapid deformation monitoring at the scale of urban bridge groups, with a wide monitoring range and a high degree of automation, effectively overcoming the limitations of traditional point monitoring methods; (2) By introducing thermal expansion response parameters, we can analyze the deformation characteristics of bridge structures under temperature action in depth and improve the accuracy of structural deterioration identification. (3) A multi-index comprehensive evaluation system was constructed, which transforms InSAR macro deformation information into an interpretable bridge technical condition level. The evaluation results are objective and quantifiable, thereby improving the ability to identify and classify risks at the group scale and providing reliable technical support for the operation, maintenance and risk management of urban bridges. (4) By combining the preliminary screening of suspected risk bridges with the detailed assessment of key bridges, the monitoring resources were efficiently allocated, and the scientific and economical nature of risk management of urban bridge clusters was improved. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort, wherein: Figure 1 This is a flowchart illustrating the bridge group assessment method that integrates multi-source remote sensing and DS-InSAR provided in an embodiment of the present invention.

[0020] Figure 2 This is a schematic diagram of the DS-InSAR data processing flow in an embodiment of the present invention.

[0021] Figure 3 This is a schematic diagram of the satellite observation geometry in an embodiment of the present invention.

[0022] Figure 4 This is a schematic diagram of the overall longitudinal tilt angle of the bridge longitudinal settlement mode in an embodiment of the present invention.

[0023] Figure 5 This is a schematic diagram of the longitudinal angular deformation of the bridge longitudinal settlement mode in an embodiment of the present invention.

[0024] Figure 6 This is a schematic diagram of the settlement of a multi-span continuous beam in the longitudinal settlement mode of a bridge according to an embodiment of the present invention.

[0025] Figure 7 This is a schematic diagram of the settlement of a single-span beam in the longitudinal settlement mode of a bridge according to an embodiment of the present invention.

[0026] Figure 8 This is a schematic diagram of a partial lateral tilt angle of a bridge in a lateral tilt mode according to an embodiment of the present invention.

[0027] Figure 9 This is a schematic diagram of the rate of change of the lateral tilt angle of a bridge in an embodiment of the present invention. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0029] This invention provides a method for assessing bridge clusters that integrates multi-source remote sensing and DS-InSAR, comprising the following steps: Step 1: Acquire optical remote sensing images of the target bridge group, and extract the spatial location, geometric dimensions, and expansion joint locations of each bridge based on the optical remote sensing images; Step 2: Acquire multi-temporal SAR images covering the target bridge group, identify and construct an observation point network in the SAR images, and perform differential interferometry processing in combination with a digital elevation model to obtain the differential phase of each observation point; Step 3: Perform time-series analysis on the differential phase based on the combined temperature model to invert the linear deformation rate and thermal expansion response parameters at each observation point; Step 4: Based on the linear deformation rate and thermal expansion response parameters, and in conjunction with the preset standard limits, identify suspected bridges with abnormal deformation risks; Step 5: For the suspected bridge, construct a multi-index evaluation system including settlement index, tilt index and rate index, determine the weight of each index through the analytic hierarchy process, and calculate the comprehensive safety value of the bridge based on the monitoring values ​​of each index to determine the technical condition level of the bridge.

[0030] Step 1, extracting the geometric dimensions and expansion joint locations, specifically includes: The Canny operator was used to extract the outline of the main girder of the bridge, and the planar shape of the bridge was determined through morphological operations based on the pixel coordinates of the two ends of the bridge. , With image spatial resolution Calculate the bridge length : ; Calculate the bridge width based on the pixel coordinates of the two transverse ends of the bridge. Alternatively, the bridge width can be obtained from the bridge design parameters. ; A one-dimensional projection of the image grayscale values ​​along the longitudinal direction of the bridge yields the grayscale distribution function. The points where the gray-level gradient changes abruptly are identified as candidate locations for expansion joints. : ; In the formula, This represents the longitudinal length of the bridge.

[0031] In step 2, identifying and constructing the observation point network specifically includes: using amplitude threshold and amplitude deviation index to screen permanent scatterer PS points, connecting PS points through Delaunay triangulation to construct the first layer network; using statistical homogeneous pixel identification method to screen distributed scatterer DS points, and constructing the second layer network.

[0032] In step 3, the combined temperature model is expressed as: ; In the formula, Differential phase, For radar wavelength, As the time baseline, The linear deformation rate along the line of sight. Slope distance For radar incident angle, For vertical baseline, For DEM elevation error, For the temperature field of the bridge structure, The coefficient of thermal expansion is... The residual phase; the thermal expansion response parameter is the coefficient of thermal expansion. .

[0033] In step 4, identifying suspected bridges with abnormal deformation risks specifically includes: performing the following comparisons: comparing the linear deformation rate of each bridge with a preset deformation rate threshold, and comparing the thermal expansion response parameters of each bridge with a preset thermal expansion threshold; if the linear deformation rate of any bridge exceeds the deformation rate threshold, or its thermal expansion response parameters exceed the thermal expansion threshold, then the bridge is marked as a suspected bridge.

[0034] In step 5, the settlement index includes the maximum settlement. and cumulative settlement The tilt index includes the pitch angle. and maximum pitch angle The rate indicators include the settling rate. ; Among them, the maximum settlement To determine the linear deformation rate along the line of sight and radar incident angle The calculated maximum vertical displacement, the settlement rate The vertical settlement rate is calculated based on the linear deformation rate ν along the line of sight. The pitch angle Based on the maximum longitudinal settlement difference of the bridge With bridge length calculate: .

[0035] Furthermore, the tilt index also includes longitudinal angular deformation. and lateral angular deformation ; The longitudinal angular deformation Based on the maximum longitudinal settlement difference of the bridge With bridge span calculate: ; The lateral angular deformation Based on the maximum difference in the transverse tilt angle of the bridge With bridge span calculate: ; The maximum tilt angle Based on the vertical displacement values ​​on both sides of the same cross-section of the bridge , With bridge width calculate: , For each local tilt angle The maximum value.

[0036] Step 5, which involves determining the weights of each indicator using the analytic hierarchy process (AHP) and calculating the overall safety value of the bridge, includes: determining the weights of each indicator using the AHP. The monitoring values ​​of each indicator are dimensionless to obtain the safety index of each indicator. Calculate the comprehensive safety value using the following formula. : ; In the formula, n This refers to the number of indicators.

[0037] Furthermore, determining the bridge's technical condition level specifically includes: calculating the comprehensive safety value. Compare with multiple preset level threshold ranges, and according to The threshold range in which the bridge is located determines its technical condition level.

[0038] To make the objectives, technical solutions, and advantages of this invention clearer, the following description will be provided in conjunction with the appendix. Figures 1 to 9 The invention will be further described in detail below with reference to the embodiments.

[0039] Example 1 Please combine Figure 1 As shown, this embodiment provides a bridge cluster assessment method that integrates multi-source remote sensing and DS-InSAR, including the following steps: Step 1: Extraction of bridge structure geometric information based on optical remote sensing imagery; Acquire high-resolution optical remote sensing imagery of the target bridge group. In this embodiment, optical satellite imagery provided by "Tianditu" can be used, with a spatial resolution of 0.6m, which is sufficient to clearly identify the main structure and outline features of urban bridges. Based on the optical remote sensing imagery, extract the spatial location, geometric dimensions, and expansion joint locations of each bridge.

[0040] Specifically, the steps for extracting geometric dimensions and expansion joint locations include: The Canny operator was used to extract the outline of the main girder of the bridge, and morphological operations (such as dilation and erosion) were applied to enhance continuous linear features in order to determine the overall planar morphology of the bridge. This was based on the pixel coordinates of the two ends of the bridge. , With image spatial resolution Calculate the bridge length : ; This formula, based on the product of pixel coordinate difference and spatial resolution, can accurately calculate the actual length of a bridge, avoiding the tedious process of on-site measurement required by traditional methods, and has the beneficial effects of high efficiency and accuracy.

[0041] Bridge width The width can be obtained in two ways: calculate the bridge width based on the pixel coordinates of the two ends of the bridge's lateral direction. Alternatively, the bridge width can be obtained from the bridge design parameters. The method for calculating the width based on the pixel coordinates of the two ends of the bridge deck is similar to that for length calculation, using the product of the difference in pixel coordinates between the two ends of the bridge deck and the spatial resolution. The former is suitable when the horizontal outline of the bridge is clear in the image, while the latter is suitable when the bridge design data is known. The two methods complement each other, improving the applicability of the method.

[0042] Expansion joints typically appear as high-contrast thin lines distributed along the bridge's longitudinal direction in optical images. By performing a one-dimensional projection of the image's grayscale values ​​along the bridge's longitudinal direction, the grayscale distribution function can be obtained. The points where the gray-level gradient changes abruptly are identified as candidate locations for expansion joints. : ; In the formula, The longitudinal length of the bridge is used. This method, based on abrupt change detection of gray-level gradients, can accurately locate the expansion joint, providing a basis for subsequent analysis of the segmental deformation characteristics of the bridge. It achieves automated identification of expansion joint locations, avoiding the subjectivity and inefficiency of manual interpretation.

[0043] Step 2: Acquisition of bridge deformation monitoring data based on DS-InSAR technology; Acquire multi-temporal SAR images covering the target bridge group. In this embodiment, 22 scenes of COSMO-SkyMed (CSK) strip imaging mode up-orbit SAR data can be used, with image polarization of HH, wavelength of 3.1 cm, satellite incident angle of 23.9°, spatial resolution of 3m×3m, and data acquisition time covering October 2022 to August 2024.

[0044] Identify and construct a network of observation points in the SAR image. For example... Figure 2 As shown, the DS-InSAR data processing workflow includes the following sub-steps: The main image is selected based on the principle of minimum spatiotemporal baseline (in this embodiment, the image acquired on July 12, 2023 is used as the main image), and the remaining images are precisely registered and resampled.

[0045] Permanent scattering points (PS points) are screened using amplitude thresholds and amplitude deviation index (ADI). In this embodiment, ADI ≤ 0.70 and average coherence coefficient (ACC) ≥ 0.3 are used as initial selection criteria for PS points. The PS points are connected using a Delaunay triangulation to construct the first layer of the network.

[0046] A statistical homogeneous pixel identification method is used to screen distributed scattering (DS) points and construct a second-layer network. In this embodiment, GammaPTA=0.5 is used as the screening threshold to achieve DS point identification and phase optimization. The statistical homogeneous pixel identification method identifies neighboring pixels with similar scattering characteristics based on the statistical characteristics of pixels, and improves the signal-to-noise ratio of DS points through phase optimization.

[0047] Differential interferometry processing is performed using a digital elevation model (DEM) to obtain the differential phase of each observation point. This step, by constructing a two-layer network of PS and DS points, enables the acquisition of high-density, reliable observation points in complex urban environments, balancing point quality and spatial coverage density, and improving the spatial resolution and accuracy of deformation monitoring.

[0048] Step 3: Time-series deformation analysis based on the combined temperature model; Based on the combined temperature model, a time series analysis was performed on the differential phase to invert the linear deformation rate and thermal expansion response parameters of each observation point.

[0049] like Figure 3 As shown, the satellite observation geometry determines the projection relationship between the line-of-sight displacement and the three-dimensional displacement components. Introducing the thermal expansion parameter into the nonlinear deformation term of the interferometric model yields the combined temperature model, expressed as: ; In the formula, Differential phase; The radar wavelength; The time baseline is the time interval for image acquisition. The linear deformation rate along the line of sight; Slant range, which is the distance from the satellite to the target; The radar incident angle; The vertical baseline; This refers to the DEM elevation error; The temperature field of the bridge structure is the bridge temperature at the time the SAR image was acquired. The coefficient of thermal expansion; The residual phase includes unmodeled components such as atmospheric delay and noise; the thermal expansion response parameter is the coefficient of thermal expansion. .

[0050] Thermal expansion phase estimation uses air temperature data from the bridge site at the time of SAR imaging. The thermal expansion phase is obtained after differential processing. It can be represented as: ; This model separates the thermal expansion effect from the deformation signal, enabling more accurate identification of the response characteristics of bridge structures under temperature effects. This provides a key basis for subsequent structural deterioration identification and avoids the risk of traditional methods misjudging thermal expansion deformation as structural settlement.

[0051] Step 4: Identification of suspected risky bridges based on regulatory limits; Based on the linear deformation rate and thermal expansion response parameters, combined with preset standard limits, suspected bridges with abnormal deformation risks are identified.

[0052] Specifically, the following comparisons are performed: the linear deformation rate of each bridge is compared with a preset deformation rate threshold, and the thermal expansion response parameters of each bridge are compared with a preset thermal expansion threshold. If the linear deformation rate of any bridge exceeds the deformation rate threshold, or its thermal expansion response parameters exceed the thermal expansion threshold, then the bridge is marked as a suspected bridge.

[0053] In this embodiment, a case study is conducted using 48 bridges in a certain city. For example, taking steel arch bridge B36 as an example, its measured thermal expansion rate of 0.96 mm / ℃ exceeds the thermal expansion rate limit of 0.9 mm / ℃ specified in the "General Specifications for Design of Urban Highway Bridges and Culverts" (JTG D60-2015), and its measured deformation rate of 12.91 mm / year exceeds the deformation rate limit of 10 mm / year specified in the "Technical Specifications for Monitoring and Control of Urban Bridges" (DB61 / T5027-2022). Furthermore, the settlement curve shows a clear overall downward trend during the study period. Therefore, this bridge is marked as a suspected abnormal deformation bridge.

[0054] This method compares and analyzes the deformation rate and thermal expansion rate of each bridge within a bridge group, initially identifying six bridges that may exhibit abnormal response characteristics. These bridges are then marked as suspected bridges for further evaluation. This step enables rapid screening of key risk targets at the bridge group scale, significantly improving monitoring efficiency and avoiding the waste of resources required for detailed evaluation of all bridges.

[0055] Step 5: Comprehensive safety assessment of bridges based on a multi-indicator evaluation system.

[0056] For the suspected bridge, a multi-index evaluation system including settlement index, tilt index and rate index is constructed. The weight of each index is determined by the analytic hierarchy process, and the comprehensive safety value of the bridge is calculated based on the monitoring value of each index to determine the technical condition level of the bridge.

[0057] The settlement index includes the maximum settlement. and cumulative settlement The tilt index includes the pitch angle. and maximum pitch angle The rate indicators include the settling rate. .

[0058] Among them, the maximum settlement To determine the linear deformation rate along the line of sight and radar incident angle The calculated maximum vertical displacement, the settlement rate The vertical settlement rate is calculated based on the linear deformation rate ν along the line of sight. The conversion relationship is based on satellite observation geometry. ; In the formula, For line-of-sight displacement, , , These represent displacements in the vertical, north-south, and east-west directions, respectively. From a side viewpoint For satellite azimuth, Let be the angle between the bridge and the north-south direction. When longitudinal and lateral deformations are negligible, the vertical deformation... With visual distortion satisfy: ; This conversion relationship can transform SAR satellite line-of-sight observations into vertical settlement indicators commonly used in engineering, improving the intuitiveness and engineering applicability of the assessment results.

[0059] like Figures 4 to 7 As shown, the longitudinal settlement pattern of a bridge can be determined by the longitudinal tilt angle. and longitudinal angular deformation Quantify it. Figure 4 This demonstrates the definition of the overall longitudinal tilt angle of a bridge. Figure 5 This demonstrates the definition of longitudinal angular deformation. Figure 6 and Figure 7 The settlement modes of multi-span continuous beams and single-span beams are shown respectively. The longitudinal tilt angle... Based on the maximum longitudinal settlement difference of the bridge With bridge length calculate: ; Pitch angle It reflects the overall tilt of the bridge in the longitudinal direction, can identify the overall unevenness of the bridge settlement, and is an important indicator for assessing the structural safety of bridges.

[0060] Furthermore, the tilt index also includes longitudinal angular deformation. and lateral angular deformation .

[0061] The longitudinal angular deformation Based on the maximum longitudinal settlement difference of the bridge With bridge span calculate: ; like Figure 8 and Figure 9 As shown, the lateral tilt pattern of a bridge can be determined by the local tilt angle. and lateral angular deformation Quantification is performed. Among them, Figure 8 This demonstrates the definition of local yaw angle. Figure 9 This demonstrates the rate of change of the lateral tilt angle along the bridge direction. The lateral angular deformation... Based on the maximum difference in the transverse tilt angle of the bridge With bridge span calculate: ; The maximum tilt angle Based on the vertical displacement values ​​on both sides of the same cross-section of the bridge , With bridge width calculate: ; For each local tilt angle The maximum value.

[0062] Longitudinal and transverse angular deformations reflect the curvature of bridge deformation in local sections, and can identify local deformation anomalies, such as beam bending caused by support settlement. They are important indicators for assessing bridge structural damage.

[0063] In this embodiment, a four-level threshold system is adopted for the bridge evaluation index thresholds, as shown in Table 1: Table 1 Threshold System for Bridge Safety Assessment Indicators The steps for determining the weights of each indicator and calculating the overall safety value of a bridge using the analytic hierarchy process (AHP) include: determining the weights of each indicator based on the AHP. (Importance comparison was performed using a 1-9 scale); the monitoring values ​​of each indicator were dimensionless (by mapping each indicator value to the range of 0-100 using a piecewise linear function) to obtain the safety index of each indicator. Calculate the comprehensive safety value using the following formula. : ; In the formula, n In this embodiment, the number of indicators is... .

[0064] The Analytic Hierarchy Process (AHP) can transform subjective judgments of multiple indicators into objective weights, avoiding the one-sidedness of single-indicator evaluation and improving the scientificity and reliability of the evaluation results.

[0065] The steps for determining the technical condition level of a bridge include: calculating the comprehensive safety value. Compare with multiple preset level threshold ranges, and according to The threshold range in which the bridge is located determines its technical condition level.

[0066] In this embodiment, based on the condition assessment principles of the "Technical Standard for Urban Bridge Maintenance" (CJJ 99-2017), the comprehensive safety value is... Mapped to bridge technical condition assessment level: >90: Class I bridge (in good condition); 80< ≤ 90: Class II bridge (good condition); 60< ≤ 80: Class III bridge (poor condition); ≤ 60: Class IV bridge (hazardous condition).

[0067] This classification transforms InSAR macroscopic deformation information into a bridge technical condition level commonly used in engineering practice, providing an intuitive and operable decision-making basis for the operation, maintenance, and risk management of urban bridges.

[0068] Example 2 Based on Example 1, this embodiment further includes a step of verifying a typical bridge using a finite element model to improve the reliability of the evaluation results.

[0069] Before step 5, a finite element model is established for a typical representative bridge. Temperature conditions are set based on the air temperature data of the bridge site area, and the finite element temperature deformation is calculated. The line-of-sight deformation of each node in the finite element model is extracted and concatenated into a node column vector. And the line-of-sight deformation results obtained from the DS-InSAR time series curves. Compare them.

[0070] The spatial consistency between finite element simulation results and InSAR observation results is quantitatively evaluated using the modal consistency index (MAC) and spatial coherence coefficient (SCC). ; ; When both indicators approach 1, it indicates that the finite element simulation and InSAR observation have good consistency in spatial deformation characteristics, verifying the accuracy of the InSAR observation results.

[0071] This verification step validates the reliability of InSAR observation results through an independent theoretical model, enhancing the credibility of the assessment results and providing a more solid basis for subsequent risk decisions.

[0072] Example 3 This embodiment optimizes the method for identifying suspected bridges in step 4 based on embodiment 1.

[0073] In step 4, in addition to comparing the relationship between the deformation rate and thermal expansion rate and the standard limits, the deformation characteristics of the settlement curve are further analyzed. For bridges whose settlement curves show obvious nonlinear trends (such as accelerated settlement, abrupt settlement, etc.), even if their deformation rate and thermal expansion rate do not exceed the standard limits, they are marked as suspected bridges for further evaluation.

[0074] This optimized method can identify early deformation anomalies and provide early warning of risks, further enhancing the method's early warning capability.

[0075] Industrial applicability The bridge group assessment method integrating multi-source remote sensing and DS-InSAR provided by this invention can be widely applied to the deformation monitoring and safety assessment of urban bridge groups. By fusing high-resolution optical remote sensing imagery with multi-temporal SAR imagery, rapid deformation information of large-scale bridge groups is acquired; through time-series analysis using a combined temperature model, effective separation of thermal expansion response and structural settlement is achieved; and through a multi-index comprehensive assessment system, the quantitative translation of macroscopic deformation information into structural risk status is realized. This invention has advantages such as wide monitoring range, high degree of automation, and objective assessment results, providing strong technical support for the operation, maintenance, and risk management of urban bridges, and possesses good industrial applicability and widespread application value.

[0076] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for evaluating bridge clusters that integrates multi-source remote sensing and DS-InSAR, characterized in that, Includes the following steps: Step 1: Acquire optical remote sensing images of the target bridge group, and extract the spatial location, geometric dimensions, and expansion joint locations of each bridge based on the optical remote sensing images; Step 2: Acquire multi-temporal SAR images covering the target bridge group, identify and construct an observation point network in the SAR images, and perform differential interferometry processing in combination with a digital elevation model to obtain the differential phase of each observation point; Step 3: Perform time-series analysis on the differential phase based on the combined temperature model to invert the linear deformation rate and thermal expansion response parameters at each observation point; Step 4: Based on the linear deformation rate and thermal expansion response parameters, and in conjunction with the preset standard limits, identify suspected bridges with abnormal deformation risks; Step 5: For the suspected bridge, construct a multi-index evaluation system including settlement index, tilt index and rate index, determine the weight of each index through the analytic hierarchy process, and calculate the comprehensive safety value of the bridge based on the monitoring values ​​of each index to determine the technical condition level of the bridge.

2. The bridge cluster assessment method integrating multi-source remote sensing and DS-InSAR as described in claim 1, characterized in that, Step 1, extracting the geometric dimensions and expansion joint locations, specifically includes: The Canny operator was used to extract the outline of the main girder of the bridge, and the planar shape of the bridge was determined through morphological operations based on the pixel coordinates of the two ends of the bridge. , With image spatial resolution Calculate the bridge length : ; Calculate the bridge width based on the pixel coordinates of the two transverse ends of the bridge. Alternatively, the bridge width can be obtained from the bridge design parameters. ; A one-dimensional projection of the image grayscale values ​​along the longitudinal direction of the bridge yields the grayscale distribution function. The points where the gray-level gradient changes abruptly are identified as candidate locations for expansion joints. : ； In the formula, This represents the longitudinal length of the bridge.

3. The bridge cluster assessment method integrating multi-source remote sensing and DS-InSAR as described in claim 1, characterized in that, In step 2, identifying and constructing the observation point network specifically includes: using amplitude threshold and amplitude deviation index to screen permanent scatterer PS points, connecting PS points through Delaunay triangulation to construct the first layer network; using statistical homogeneous pixel identification method to screen distributed scatterer DS points, and constructing the second layer network.

4. The bridge cluster assessment method integrating multi-source remote sensing and DS-InSAR as described in claim 1, characterized in that, In step 3, the combined temperature model is expressed as: ； In the formula, Differential phase, For radar wavelength, As the time baseline, The linear deformation rate along the line of sight. Slope distance For radar incident angle, For vertical baseline, For DEM elevation error, For the temperature field of the bridge structure, The coefficient of thermal expansion is... The residual phase; the thermal expansion response parameter is the coefficient of thermal expansion. .

5. The bridge cluster assessment method integrating multi-source remote sensing and DS-InSAR as described in claim 1, characterized in that, In step 4, identifying suspected bridges with abnormal deformation risks specifically includes: performing the following comparisons: comparing the linear deformation rate of each bridge with a preset deformation rate threshold, and comparing the thermal expansion response parameters of each bridge with a preset thermal expansion threshold; if the linear deformation rate of any bridge exceeds the deformation rate threshold, or its thermal expansion response parameters exceed the thermal expansion threshold, then the bridge is marked as a suspected bridge.

6. The bridge cluster assessment method integrating multi-source remote sensing and DS-InSAR as described in claim 1, characterized in that, In step 5, the settlement index includes the maximum settlement. and cumulative settlement The tilt index includes the pitch angle. and maximum pitch angle The rate indicators include the settling rate. ; Among them, the maximum settlement To determine the linear deformation rate along the line of sight and radar incident angle The calculated maximum vertical displacement, the settlement rate The vertical settlement rate is calculated based on the linear deformation rate ν along the line of sight. The pitch angle Based on the maximum longitudinal settlement difference of the bridge With bridge length calculate: .

7. The bridge cluster assessment method integrating multi-source remote sensing and DS-InSAR as described in claim 6, characterized in that, The tilt index also includes longitudinal angle deformation. and lateral angular deformation ; The longitudinal angular deformation Based on the maximum longitudinal settlement difference of the bridge With bridge span calculate: ; The lateral angular deformation Based on the maximum difference in the transverse tilt angle of the bridge With bridge span calculate: ; The maximum tilt angle Based on the vertical displacement values ​​on both sides of the same cross-section of the bridge , With bridge width calculate: ； For each local tilt angle The maximum value.

8. The bridge cluster assessment method integrating multi-source remote sensing and DS-InSAR according to claim 6 or 7, characterized in that, Step 5, which involves determining the weights of each indicator using the analytic hierarchy process (AHP) and calculating the overall safety value of the bridge, includes: determining the weights of each indicator using the AHP. The monitoring values ​​of each indicator are dimensionless to obtain the safety index of each indicator. Calculate the comprehensive safety value using the following formula. : ； In the formula, n This refers to the number of indicators.

9. The bridge cluster assessment method integrating multi-source remote sensing and DS-InSAR as described in claim 8, characterized in that, Step 5, determining the bridge's technical condition level specifically includes: calculating the comprehensive safety value... Compare with multiple preset level threshold ranges, and according to The threshold range in which the bridge is located determines its technical condition level.

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