Bridge earthquake damage rapid assessment method and system

Abstract

The invention relates to the technical field of bridge structure health monitoring, and particularly provides a bridge earthquake damage rapid assessment method and system, and the method comprises the steps: carrying out the cross-modal coupling calibration of a time-history sudden change feature and a phase of a space energy spectrum, and generating a high-confidence three-dimensional dynamic response field; inputting the spatial gradient distribution characteristics into a nonlinear material state inversion program, performing path integrity verification in combination with an energy dissipation path, and outputting a potential damage topology boundary of the bridge; dividing an output bridge potential damage topological boundary into discretized damage units, and mapping strain constraints of the discretized damage units into triple decision-making indexes including a traffic capacity attenuation coefficient, an emergency disposal aging threshold value and an aftershock risk level through a bridge structure function attenuation rule. The system comprises a mixed field dynamic response reconstruction module, a damage sensitive domain reverse locking module and a function level damage quantitative mapping module. According to the method, deterministic mapping of the bridge structure damage state and the engineering function index is realized.

Description

Technical Field

[0001] This invention relates to the field of bridge structural health monitoring technology, and in particular to a method and system for rapid assessment of bridge seismic damage. Background Technology

[0002] With my country's transportation network now ranking first in the world, bridge structural health monitoring has become a core issue in infrastructure operation and maintenance. Traditional manual inspection methods suffer from three major drawbacks: first, they rely on engineers' subjective experience, resulting in an evaluation dispersion of up to 40%; second, the inspection cycle is long (an average of 72 man-hours per bridge), making it difficult to meet the needs of rapid response after sudden disasters; and third, high-risk areas (such as anchorage areas of suspension bridges and towers of cable-stayed bridges) have poor accessibility. Data from the Ministry of Transport in 2023 shows that approximately 12% of my country's in-service bridges have hidden damage that has not been detected in a timely manner, highlighting the urgent need to establish a standardized and intelligent rapid assessment system; in particular, a rapid assessment scheme for bridge seismic damage is lacking.

[0003] Prior art 1, Chinese Patent Application No. 202510032337.9, discloses a method and system for evaluating the dynamic seismic performance of beam bridges, including model preparation, model establishment, boundary conditions and load application, analysis and calculation, and result analysis and evaluation. Through detailed data collection and model preparation, a detailed finite element model of the bridge is accurately constructed, fully considering the actual characteristics of the main beam, piers, supports, and other key components, and reasonably setting boundary conditions and applying seismic loads. Although it estimates the seismic performance of the bridge under seismic loading, accurately identifies potential weak points in the bridge under seismic loading, and provides a reliable basis for formulating targeted seismic reinforcement measures, significantly improving the efficiency and reliability of bridge structure seismic analysis and performance evaluation; however, it relies on a static finite element model: a high-precision bridge model needs to be pre-constructed, and it depends on detailed data collection, making it difficult to adapt to the rapid assessment of dynamic damage during earthquakes; the lagging process of model calculation and result evaluation cannot respond in real time to sudden damage evolution during earthquakes; it does not integrate multi-source sensor data, relying solely on finite element simulation, and lacks collaborative verification with measured strain mutation signals and three-dimensional deformation fields.

[0004] Prior art two, Chinese patent application number 202410242063.1, discloses a bridge seismic response prediction and rapid post-earthquake assessment system based on digital twins, including a seismic simulation module, a digital twin model module, a seismic response prediction module, and a seismic damage assessment module. While it enables the simulation, prediction, and rapid assessment of bridge response and technical condition under various seismic scenarios, providing support for pre-earthquake bridge repair and reinforcement and post-earthquake emergency decision-making, and ensuring the safety and reliability of bridge engineering, it suffers from several drawbacks. The digital twin model is outdated, relying on historical data for training, and its dynamic response prediction during earthquakes is limited by the model update speed. Furthermore, it fails to address the cross-modal data fusion problem, and does not achieve real-time calibration of contact strain signals and non-contact spatial scanning, affecting the accuracy of damage boundary positioning. Finally, it provides insufficient decision support, offering only damage assessment results without generating timely treatment thresholds.

[0005] Prior art three, Chinese patent application number 202310000042.4, discloses an online real-time simulation calculation system for bridges based on seismic load monitoring. It establishes an online simulation analysis model of the bridge based on its structure, and corrects and dynamically updates the model based on the bridge structural response obtained from bridge health monitoring. It acquires real-time monitoring acceleration time history curves of the bridge triggered by earthquakes using a triaxial seismograph, and performs dynamic time history analysis of the bridge using measured ground motion time history data, manually input data, and station data as input loads to understand the seismic response characteristics of the bridge structure, assess the seismic response of the bridge structure, and determine whether damage has occurred. While online simulation and real-time calculation systems for bridges can perform online analysis and calculation of bridge responses under seismic loads, enabling real-time analysis, rapid assessment, and intuitive visualization of bridge structural responses to facilitate quick decision-making by bridge management departments, they suffer from several drawbacks. These include reliance on a single data source, basing decisions solely on acceleration time-history curves, neglecting the coupling effect of strain abrupt changes and three-dimensional deformation, and easily missing localized damage. Furthermore, they lack damage-free topological boundary quantization, failing to extract energy dissipation paths and material nonlinear states, thus limiting damage assessment to the overall response level. Finally, they lack tiered decision indicators, failing to map damage into actionable decision parameters such as traffic capacity and risk level.

[0006] Current technologies 1, 2, and 3 suffer from difficulties in multi-source data fusion, crude damage topology quantification, and lagging decision support. Therefore, this invention provides a method and system for rapid assessment of bridge seismic damage. Summary of the Invention

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] One aspect of the present invention provides a method for rapid assessment of bridge seismic damage, comprising the following steps: extracting spatial gradient distribution features and energy dissipation paths based on the output high-confidence three-dimensional dynamic response field; obtaining the potential damage topological boundary of the bridge; dividing the output potential damage topological boundary of the bridge into discretized damage units, and applying biaxial residual strain constraints to each unit; mapping the strain constraints of the discretized damage units into a triple decision index of traffic capacity attenuation coefficient, emergency response time threshold, and aftershock risk level through bridge structural function attenuation rules.

[0009] In one alternative implementation, the process of mapping the strain constraints of discretized damage elements to triple decision indices includes the following steps:

[0010] For each discretized damage element, the biaxial residual strain constraint is subjected to master-slave axis strain separation, and the amplitude of the master strain axis and the variability of the secondary strain axis are extracted. When the variability of the secondary strain axis exceeds the set proportion of the amplitude of the master strain axis, the strain energy redistribution mechanism is triggered, and the equivalent functional attenuation coefficient is output.

[0011] The equivalent functional attenuation coefficient is combined with the attenuation coefficient based on the core damage domain unit to generate a lane-level attenuation gradient through weight enhancement; based on the attenuation coefficient of the complementary damage ring unit, diffusion suppression is activated to output the regional traffic reduction rate; the lane-level attenuation gradient and the regional traffic reduction rate are fused to form the traffic capacity attenuation coefficient.

[0012] The principal strain axis amplitude is used to identify unit clusters that meet the strain space correlation conditions, construct aftershock chain triggering domains, extract strain gradient abrupt change interfaces within unit clusters, and mark high-risk areas of local instability; aftershock chain triggering domains and high-risk areas of local instability are fused by risk field superposition rules to output aftershock risk levels.

[0013] The traffic capacity attenuation coefficient and aftershock risk level are input into the time-sensitivity convergence program; the rapid response time window and the emergency reinforcement time window form the emergency response time threshold.

[0014] In one optional implementation, when the traffic capacity attenuation coefficient is not less than the threshold corresponding to the aftershock risk level, the traffic priority mode is activated to generate a rapid response time window; when the aftershock risk level is greater than the threshold corresponding to the traffic capacity attenuation coefficient, the risk containment mode is triggered to output an emergency reinforcement time window.

[0015] In one optional implementation, the process of forming an emergency response time threshold by combining a rapid response time window and an emergency reinforcement time window includes the following steps:

[0016] The traffic capacity attenuation coefficient is obtained, and the traffic resistance gradient field is generated based on the spatial distribution of the core damage domain. The road network vulnerability barrier is calculated based on the connectivity of complementary damage ring units. The traffic resistance gradient field and the road network vulnerability barrier are superimposed to form a functional attenuation potential energy field. The aftershock risk level, the aftershock chain triggering domain driving instability energy accumulation rate, and the stress redistribution time-varying function triggered by the high-risk area of ​​local instability are fused to generate a risk kinetic energy field.

[0017] The functional decay potential energy field and the risk kinetic energy field are coupled into a field equilibrium.

[0018] When the gradient intensity of the functional decay potential energy field is not less than the diffusion intensity of the risk kinetic energy field, a dominant interface for passage is formed in the boundary region; when the diffusion intensity of the risk kinetic energy field is greater than the gradient intensity of the functional decay potential energy field, a dominant interface for risk is formed in the boundary region.

[0019] Tracing back along the traffic resistance gradient field to the road network vulnerability barrier, calculating the critical time for road network connectivity, and outputting a rapid response time window; monitoring the instability energy accumulation rate through the time-varying function of stress redistribution, solving for the critical instability time, and generating an emergency reinforcement time window.

[0020] In one alternative implementation, the process of outputting a fast processing time window includes the following steps:

[0021] Starting from the maximum point of the traffic resistance gradient field, trace along the negative gradient direction to the boundary of the road network vulnerability barrier to form a minimum resistance through path;

[0022] A dynamic barrier penetration equation is applied to the path of least resistance to extract the barrier strength integral of the path crossing the vulnerable barrier section of the road network; the strain constraint of the core damage domain unit is coupled to generate the material creep acceleration factor; and the critical time step of barrier penetration is output.

[0023] Obtain the critical time step for barrier penetration. If the path does not pass through the complementary damage ring, directly output the basic treatment time window. If the path passes through the high-risk area of ​​the ring, superimpose the ring strain constraint attenuation rate to generate the extended treatment time window. Finally, a rapid treatment time window is formed.

[0024] In one optional implementation, the process of obtaining the critical time step for barrier penetration includes the following steps:

[0025] The road network topology is mapped in the time domain by the critical time step of barrier penetration, the minimum resistance path length is loaded, and the benchmark traffic recovery rate is obtained; the strain constraint of the core damage domain is coupled to generate the material strength attenuation correction; and the interference-free basic time window is output.

[0026] Spatial penetration discrimination is performed between the minimum resistance penetration path and the spatial coordinates of the complementary damage ring; when the intersection length between the minimum resistance penetration path and the high-risk area of ​​the ring is greater than the ring width threshold, a strong interference marker is triggered; when the minimum distance between the minimum resistance penetration path and the ring boundary is not greater than the strain gradient characteristic scale, a weak interference marker is activated.

[0027] The strong interference marker drives the annular strain constraint attenuation rate to perform time window extension, extracts the master-slave axis difference of biaxial residual strain in the path crossing area, and generates the axial instability correction coefficient; obtains the cumulative amount of curvature change of the energy dissipation path of the annular element, and generates the local oscillation delay factor; outputs the comprehensive extension amount;

[0028] The non-interference basic time window and the comprehensive extension quantity are extended in the time domain; when the weak interference flag is activated, linear extension is performed and the first-level extension time window is output; when the strong interference flag is activated, exponential extension is started and the second-level extension time window is generated; finally, the extension processing time window is formed.

[0029] In one alternative implementation, the process of generating an emergency hardening time window includes the following steps:

[0030] Energy accumulation monitoring arrays are deployed in high-risk areas of local instability to collect the spatiotemporal distribution of instability energy accumulation rate in real time and generate energy accumulation isosurfaces.

[0031] Critical crossing criteria are determined by comparing the energy accumulation isosurface with the time-varying stress redistribution.

[0032] The instability critical trigger signal drives aftershock chain suppression. If the signal originates from an isolated high-risk area, a local reinforcement time window is output. If the signal covers the aftershock chain triggering domain, inter-domain energy decoupling calculation is initiated to generate a global reinforcement time window. Finally, an emergency reinforcement time window is formed.

[0033] In one optional implementation, strain abrupt change signals of key sections of the bridge during an earthquake are collected in real time by contact measurement nodes to obtain time history abrupt change characteristics. Simultaneously, a non-contact spatial scanning device is triggered to perform directional energy spectrum coverage of the three-dimensional deformation field of the entire bridge. The time history abrupt change characteristics and the phase of the spatial energy spectrum are coupled and calibrated across modes to generate a high-confidence three-dimensional dynamic response field.

[0034] In one optional implementation, based on the output high-confidence three-dimensional dynamic response field, spatial gradient distribution features and energy dissipation paths are extracted; the spatial gradient distribution features are input into a nonlinear material state inversion program, and the path integrity is verified by combining the energy dissipation paths, and the potential damage topological boundary of the bridge is output.

[0035] In another aspect, the present invention provides a rapid bridge seismic damage assessment system according to the aforementioned rapid bridge seismic damage assessment method, comprising:

[0036] The hybrid field dynamic response reconstruction module is configured to acquire strain abrupt change signals of key sections of the bridge during earthquakes in real time through contact measurement nodes, obtain time history abrupt change characteristics, and simultaneously trigger a non-contact spatial scanning device to perform directional energy spectrum coverage of the three-dimensional deformation field of the entire bridge; the time history abrupt change characteristics and the phase of the spatial energy spectrum are coupled and calibrated across modes to generate a high-confidence three-dimensional dynamic response field.

[0037] The damage-sensitive domain inverse locking module is configured to extract spatial gradient distribution features and energy dissipation paths based on the high-confidence three-dimensional dynamic response field of the output; the spatial gradient distribution features are input into the nonlinear material state inversion program, and the path integrity is verified by combining the energy dissipation paths, and the potential damage topological boundary of the bridge is output.

[0038] The functional-level damage quantization mapping module is configured to divide the output potential bridge damage topology boundary into discretized damage units and apply biaxial residual strain constraints to each unit. The strain constraints of the discretized damage units are mapped to a triple decision index of traffic capacity attenuation coefficient, emergency response time threshold, and aftershock risk level through the bridge structure function attenuation rule.

[0039] The cross-modal coupling mechanism established in this invention overcomes the spatiotemporal resolution mismatch in traditional single-modal monitoring through joint calibration of temporal strain signals and spatial energy spectrum phase. The resulting three-dimensional dynamic response field possesses both the temporal accuracy of contact measurements and the spatial continuity of non-contact measurements, providing a comprehensive reference field for damage identification. A dual verification strategy employing spatial gradient characteristics and energy dissipation paths is used. Nonlinear material state inversion addresses the identification of local material performance degradation, while energy path integrity verification ensures the mechanical rationality of the damage boundary. This combination effectively suppresses false alarms or missed detections caused by single inversion methods. A quantitative relationship between discrete damage units and macroscopic functional indicators is established through biaxial residual strain constraints. The mapping rule is based on the physical mechanism of structural functional decay, giving the output triple decision indicators a clear mechanical meaning and ensuring a strict correspondence between engineering treatment recommendations and the actual structural load-bearing state. Attached Figure Description

[0040] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0041] Figure 1 This is a flowchart of the rapid assessment method for bridge seismic damage provided in Embodiment 1 of the present invention;

[0042] Figure 2 This is a process diagram of generating a high-confidence three-dimensional dynamic response field provided in Embodiment 2 of the present invention;

[0043] Figure 3 This is a process diagram of the output bridge potential damage topology boundary provided in Embodiment 3 of the present invention;

[0044] Figure 4 This is a process diagram of mapping the strain constraints of discretized damage elements to triple decision indices, as provided in Embodiment 6 of the present invention.

[0045] Figure 5 This is a block diagram of the bridge earthquake damage rapid assessment system provided in Embodiment 13 of the present invention;

[0046] Figure 6 A block diagram of the electronic device provided by the present invention;

[0047] Figure 7 A block diagram of a computer-readable storage medium provided for this invention. Detailed Implementation

[0048] The technical solutions of the present invention will now be described with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0049] Hereinafter, the terms "first," "second," etc., are used for descriptive convenience only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0050] In this invention, unless otherwise explicitly specified and limited, the term "connection" should be interpreted broadly. For example, "connection" can be a fixed mechanical connection, a detachable mechanical connection, or an integral part; or, "connection" can be a direct connection or an indirect connection through an intermediate medium. Furthermore, unless otherwise explicitly specified and limited, the term "coupling" should be interpreted broadly. For example, "coupling" can be a direct electrical connection, such as physical contact and electrical conduction between two components; it can also be understood as an electrical connection between different components in a circuit structure through physical lines capable of transmitting electrical signals, such as copper foil or wires on a printed circuit board (PCB), to transmit electrical signals; or, "coupling" can be an indirect electrical connection between two components through an intermediate medium; or, "coupling" can be an electrical connection between two components in a non-contact manner, such as an electrical connection between two components using capacitive coupling to transmit electrical signals.

[0051] In this embodiment of the invention, directional terms such as "up," "down," "left," and "right" may be defined relative to the orientation of the components shown in the accompanying drawings. It should be understood that these directional terms can be relative concepts, used for relative description and clarification, and can change accordingly depending on the orientation of the components in the accompanying drawings.

[0052] Example 1:

[0053] like Figure 1 As shown in the figure, this embodiment of the invention provides a method for rapid assessment of bridge seismic damage, comprising the following steps:

[0054] Step S100: Real-time acquisition of strain abrupt change signals of key sections of the bridge during earthquakes through contact measurement nodes to obtain time history abrupt change characteristics, and synchronous triggering of non-contact spatial scanning device to perform directional energy spectrum coverage of the three-dimensional deformation field of the entire bridge; cross-modal coupling calibration of the time history abrupt change characteristics and the phase of the spatial energy spectrum to generate a high-confidence three-dimensional dynamic response field.

[0055] Step S200: Based on the output high-confidence three-dimensional dynamic response field, extract the spatial gradient distribution features and energy dissipation path; input the spatial gradient distribution features into the nonlinear material state inversion program, combine the energy dissipation path to verify the path integrity, and output the potential damage topological boundary of the bridge.

[0056] Step S300: Divide the output bridge potential damage topology boundary into discretized damage elements, and apply biaxial residual strain constraints to each element; map the strain constraints of the discretized damage elements into a triple decision index of traffic capacity attenuation coefficient, emergency response time threshold, and aftershock risk level through the bridge structure function attenuation rule.

[0057] In the above embodiments, this embodiment achieves a full-chain technology transformation from raw data acquisition to engineering decision indicators through the synergistic coupling of multiple technical features. The field reconstruction through multi-source heterogeneous data fusion, and the cross-modal coupling mechanism established in step S100, overcome the shortcomings of spatiotemporal resolution mismatch in traditional single-modal monitoring through joint calibration of temporal strain signals and spatial energy spectrum phases. The resulting three-dimensional dynamic response field possesses both the temporal accuracy of contact measurement and the spatial continuity of non-contact measurement, providing a comprehensive reference field data for damage identification. Step S200 employs a dual verification strategy of spatial gradient features and energy dissipation paths. Nonlinear material state inversion addresses the identification of local material performance degradation, while energy path integrity verification ensures the mechanical rationality of the damage boundary. The combination of these two methods effectively suppresses false alarms or missed detections caused by a single inversion method. Step S300 establishes a quantitative relationship between discrete damage units and macroscopic functional indicators through biaxial residual strain constraints. Its mapping rule is based on the physical mechanism of structural functional decay, giving the output triple decision indicators a clear mechanical meaning and ensuring that engineering treatment recommendations strictly correspond to the actual structural load-bearing state.

[0058] In summary, this embodiment improves the accuracy of initial field reconstruction through cross-modal data fusion, enhances the reliability of damage inversion by utilizing multi-physics constraints, and ultimately achieves a deterministic mapping between the damage state of the bridge structure and its engineering functional indicators. Significantly different from the traditional segmented bridge assessment process, its technical effect is reflected in compressing multi-dimensional information of the bridge, such as vibration response, deformation field, material properties, and energy dissipation, into quantitative parameters that can directly guide emergency response, and maintaining the integrity of the physical model without human intervention throughout the entire process.

[0059] Example 2:

[0060] like Figure 2 As shown, based on Example 1, the process of generating a high-confidence three-dimensional dynamic response field in step S100 of this embodiment of the invention includes the following steps:

[0061] Step S101: The raw strain pulse sequence captured by the contact measurement node is processed by an inflection point sharpness filter to extract a set of abrupt inflection point timestamps with non-stationary characteristics, and the pulse amplitude is separated to generate an energy distribution vector.

[0062] Step S102: The original energy spectrum phase cloud of the non-contact scan is driven by the output abrupt change inflection point timestamp set, and the spatiotemporal slice synchronization engine is started to generate a phase space slice aligned with the abrupt change time.

[0063] Step S103: Input the phase space slice into the dual-domain confidence compensator and load the energy distribution vector as the weight source; drive the phase amplitude correction with the energy distribution vector to generate the energy-compensated phase field; constrain the spatial interpolation boundary with the abrupt inflection point timestamp set and output the spatiotemporal constrained deformation field; fuse the energy-compensated phase field and the spatiotemporal constrained deformation field to form a high-confidence three-dimensional dynamic response field.

[0064] In the above embodiments, this embodiment constructs a high-fidelity dynamic deformation characterization system with physical consistency through multimodal sensing data fusion and spatiotemporal coupling calculation. Specifically, based on the spatiotemporal phase-locked mechanism of strain pulse inflection point characteristics and energy spectrum phase cloud, nanosecond-level synchronization of contact and non-contact measurement data is achieved, breaking through the bottleneck of temporal mismatch between mechanical response and optical measurement in traditional methods. The dual-domain confidence compensation architecture transforms the temporal energy distribution characteristics of the strain sensor into amplitude constraints of the energy spectrum phase field through an energy-phase coupling correction algorithm. At the same time, it utilizes the topological continuity of the spatial interpolation process constrained by the mechanical abrupt inflection point to effectively suppress Doppler phase ambiguity and mechanical vibration artifacts in optical measurements. The final output three-dimensional dynamic response field simultaneously possesses: the temporal impact characteristics of the strain pulse (microsecond-level temporal resolution), the spatial gradient information of the energy spectrum phase field (sub-millimeter-level spatial resolution), and the physical confidence weight distribution obtained through energy-spatiotemporal dual constraints, providing a fused data field with both high spatiotemporal accuracy and physical interpretability for structural dynamic deformation analysis.

[0065] In summary, this embodiment is particularly suitable for multi-physics coupling characterization of structural transient response under extreme load conditions such as earthquakes, and solves the problem of response field distortion caused by insufficient dynamic range and inconsistent spatiotemporal references in traditional single-mode measurements.

[0066] Example 3:

[0067] like Figure 3 As shown, based on Example 1, the process of outputting the potential damage topological boundary of the bridge in step S200 of this embodiment of the invention includes the following steps:

[0068] Step S201: Input the high-confidence three-dimensional dynamic response field into the spatial differential operator, extract the set of normal gradient extreme points and the tangential gradient variation interval along the principal stress trajectory line, and merge them to form a two-way gradient distribution feature;

[0069] Step S202: Drive the yield front positioning equation with the set of extreme points of the normal gradient of the bidirectional gradient distribution characteristics to generate the coordinates of the potential plastic domain; trigger the stiffness degradation threshold determination in the tangential gradient variation interval and output the brittle damage probability field; superimpose the coordinates of the potential plastic domain and the brittle damage probability field to form the initial damage topology map.

[0070] Step S203: Perform path coverage matching between the energy dissipation path extracted from the high-confidence three-dimensional dynamic response field and the initially selected damage topology map; integrate and verify the damage unit and the hidden damage unit to form the potential damage topology boundary of the bridge;

[0071] If the energy dissipation path passes through the initially selected damage region and there is a path energy flux density depression, it is marked as a verification damage unit.

[0072] If the energy dissipation path detours around the initially selected damage area but exhibits abrupt changes in path curvature, it is identified as a hidden damage unit.

[0073] In the above embodiments, this embodiment achieves the physical feature fusion identification and precise boundary positioning of bridge damage areas through the collaborative calculation of multi-dimensional gradient analysis and energy path verification. Specific technical effects include: bidirectional gradient feature extraction: based on the set of extreme points of the normal gradient and the variation range of the tangential gradient of the principal stress trajectory, potential plastic yield fronts and stiffness degradation regions are respectively characterized, forming a dual-criteria fusion mechanism for initial damage screening, improving the physical interpretability of damage identification. Damage probability field and plastic domain superposition: the plastic domain coordinates output by the yield front positioning equation are spatially superimposed with the brittle damage probability field triggered by the tangential gradient to construct a preliminary damage topology map, achieving collaborative detection of ductile and brittle damage, avoiding missed detections or misjudgments caused by a single criterion. Energy dissipation path verification optimization: the energy dissipation path in the high-confidence dynamic response field is used to perform coverage matching on the preliminary damage topology. Through the physical features of energy flux density depressions (verifying damage units) and path curvature abrupt changes (hidden damage units), the preliminary damage boundary is corrected, enhancing the robustness of damage identification and ensuring that the topology boundary simultaneously covers both visible and hidden damage.

[0074] In summary, the bridge potential damage topological boundary output by this embodiment has both gradient abrupt change characteristics and energy transfer anomalies for dual verification, providing a highly reliable damage spatial distribution characterization for structural health monitoring.

[0075] Example 4:

[0076] Based on Example 3, the process of integrating the verification damage unit and the hidden damage unit to form the potential damage topological boundary of the bridge in step S203 of the present invention includes the following steps:

[0077] Step S2031: Input the energy flux density depression region of the energy dissipation path and the initial damage topology map into the spatial overlay analyzer. When the depression region completely covers the initial damage unit, activate the damage confidence enhancement program to generate a set of high-confidence damage unit coordinates. When the depression region partially covers the initial damage unit, trigger boundary contraction to output the accurate damage profile.

[0078] Step S2032: Drive the bypass path tracking engine based on the curvature change point of the energy path, trace back along the bypass path from the curvature change point as the starting point, and capture the path avoidance vertices; connect the path avoidance vertices to form a spatial avoidance polygon, and perform spatial difference extraction of hidden damage units with the initially selected damage topology map.

[0079] Step S2033: Input the high-confidence damage element, the precise damage profile, and the hidden damage element into the topology fusion controller. The high-confidence element is used as the core damage domain and a spatial priority weight is applied. The precise profile and the hidden element are checked for edge fit to generate a complementary damage ring. Finally, the potential damage topology boundary of the bridge is output by fusing the spatial priority weight and the complementary damage ring through the ring domain expansion rule.

[0080] In the above embodiments, this embodiment achieves precise three-dimensional spatial localization and boundary optimization for bridge damage identification through multi-module collaboration; by analyzing the spatial overlay of energy flux density depressions and initially selected damage, it realizes the probability classification of damage existence, generates a deterministic damage coordinate set for full coverage, and outputs sub-pixel-level damage contours for partial coverage, establishing a quantitative standard for confidence measurement of damage identification. For hidden damage detection, an anomaly detection mechanism based on energy path curvature features is used, constructing spatial avoidance polygons through reverse tracing of detour paths, and extracting damage within traditional detection blind spots using spatial difference operations. For topology fusion optimization, a hierarchical damage spatial representation model is established, achieving edge fitting and geometric verification of multi-source damage data, and completing the three-dimensional reconstruction of damage boundaries through a ring domain expansion algorithm.

[0081] In summary, this embodiment breaks through the limitations of traditional two-dimensional damage detection and constructs a three-dimensional damage topology representation; it integrates direct evidence (energy flow anomaly) and indirect evidence (path avoidance) to achieve multimodal verification; it outputs a damage probability distribution model with spatial priority; and it provides sub-millimeter-level damage boundary input for subsequent structural load-bearing capacity assessment.

[0082] Example 5:

[0083] Based on Example 4, the process of fusing spatial priority weights and complementary damage ring output bridge potential damage topology boundaries through ring domain expansion rules in step S2033 of this embodiment of the invention includes the following steps:

[0084] Step S20331: Input the coordinate set of high-confidence damage elements into the spatial priority weight allocator, generate radial expansion priority coefficients based on the cumulative strain mutation within the high-confidence damage elements, obtain the circumferential expansion intensity gradient based on the energy dissipation path density, and couple them to form the core domain expansion vector field.

[0085] Step S20332: The precise contour is fitted to the boundary verification device of the hidden unit input. The precise contour provides the outer boundary constraint trajectory; the hidden unit outputs the inner boundary filling interval; the strain continuity detection makes the outer boundary constraint trajectory and the inner boundary filling interval form a seamless closed loop.

[0086] Step S20333: Load the closed loop as the expansion boundary container for the core damage domain expansion vector field, and activate the vector-driven expansion; when the expansion front contacts the inner wall of the loop, trigger the strain gradient balancing mechanism; output the fused damage topology boundary.

[0087] If the strain gradient of the core damage domain is greater than or equal to the strain threshold of the annular zone, annular zone absorption is performed; if the strain gradient of the core damage domain is less than the strain threshold of the annular zone, a buffer isolation layer is formed.

[0088] In the above embodiments, this embodiment realizes the dynamic optimization and reconstruction of the bridge damage spatial topology; the spatial fusion mechanism of multi-source damage data achieves three-dimensional spatial integration of high-confidence damage units, precise contours, and hidden damage units through the dynamic coupling of the core domain expansion vector field and complementary damage rings; the spatial priority weight allocator ensures that the core damage domain maintains the dominant influence of strain mutation accumulation during expansion, while the circumferential expansion intensity gradient adjusts the damage boundary expansion trend according to the energy flux density distribution. Boundary constraint and strain continuity optimization, the precise contour provides the outer boundary constraint trajectory to ensure that the damage expansion conforms to the physical structure constraints, and the hidden units fill the missing areas of the inner boundary to form a complete closed ring; the strain continuity detection mechanism makes the inner and outer boundaries seamlessly connected, avoids topological breaks, and ensures the physical rationality of the damage boundary. Dynamic expansion and strain balance control are employed. The expansion vector field of the core damage domain drives the damage boundary to expand outward until it contacts the closed loop, triggering a strain gradient balance mechanism to ensure that the damage boundary expansion conforms to the actual structural mechanical response. Based on the comparison between the strain thresholds of the core damage domain and the loop, the damage topology is adaptively adjusted: if the strain gradient of the core domain is dominant, the expansion range of the loop is absorbed; if the strain threshold of the loop is high, a buffer isolation layer is formed to prevent excessive damage expansion. The final output is the characteristics of the damage topology boundary. The fused damage topology boundary combines the high-confidence characteristics of the core damage domain with the hidden damage information of the complementary loop, forming a complete three-dimensional damage spatial distribution model. This boundary satisfies the strain gradient balance condition, ensuring that the damage assessment results conform to the laws of structural mechanics and providing accurate damage spatial distribution input for subsequent bridge load-bearing capacity analysis.

[0089] In summary, this embodiment achieves dynamic optimization and adaptive boundary adjustment for damage identification, ensuring that the damage topology not only conforms to the constraints of the measured data but also reflects the potential damage propagation trend.

[0090] Example 6:

[0091] like Figure 4 As shown, based on Example 1, the process of mapping the strain constraint of the discretized damage element to a triple decision index in step S300 of this embodiment of the invention includes the following steps:

[0092] Step S301: Perform master-slave axis strain separation on the biaxial residual strain constraint of each discretized damage unit, and extract the amplitude of the master strain axis and the variability of the secondary strain axis; when the variability of the secondary strain axis exceeds the set proportion of the amplitude of the master strain axis, trigger the strain energy redistribution mechanism and output the equivalent functional attenuation coefficient.

[0093] Step S302: Combine the equivalent functional attenuation coefficient with the attenuation coefficient based on the core damage domain unit to generate a lane-level attenuation gradient by weight enhancement; activate diffusion suppression to output the regional traffic reduction rate based on the attenuation coefficient of the complementary damage ring unit; and fuse the lane-level attenuation gradient and the regional traffic reduction rate to form the traffic capacity attenuation coefficient.

[0094] Step S303: Identify the unit clusters that meet the strain space correlation conditions based on the principal strain axis amplitude, construct the aftershock chain triggering domain, extract the strain gradient abrupt change interface within the unit cluster, and mark the high-risk area of ​​local instability; fuse the aftershock chain triggering domain and the high-risk area of ​​local instability through the risk field superposition rule, and output the aftershock risk level;

[0095] Step S304: Input the traffic capacity attenuation coefficient and aftershock risk level into the time-sensitivity convergence program; form the emergency response time threshold by combining the rapid response time window and the emergency reinforcement time window;

[0096] When the traffic capacity attenuation coefficient is not less than the threshold corresponding to the aftershock risk level, the traffic priority mode is activated to generate a rapid response time window.

[0097] When the aftershock risk level exceeds the threshold corresponding to the traffic capacity attenuation coefficient, the risk containment mode is triggered, and an emergency reinforcement time window is output.

[0098] In the above embodiments, this embodiment realizes the dynamic coupling optimization of bridge damage assessment and decision support. Its technical effects are as follows: Multi-dimensional decision mapping of damage strain constraints, through master-slave axis strain separation and strain energy redistribution mechanisms, transforms the biaxial residual strain constraints of discretized damage units into equivalent functional attenuation coefficients, ensuring that damage assessment reflects both the macroscopic mechanical degradation dominated by the master strain and captures local functional anomalies caused by secondary strain variations; combining the attenuation characteristics of the core damage domain and complementary damage rings, lane-level attenuation gradients and regional traffic reduction rates are generated, forming a comprehensive traffic capacity attenuation coefficient, quantifying the overall downward trend of bridge bearing capacity. Dynamic identification of high-risk areas and construction of risk fields: Master strain axis amplitude screening selects unit clusters that meet strain space correlation conditions, constructs aftershock chain triggering domains, and identifies potential structural chain failure paths; strain gradient abrupt change interfaces mark high-risk areas of local instability, and aftershock chain triggering domains and high-risk areas are fused through risk field superposition rules to output aftershock risk levels, achieving dynamic prediction of structural stability degradation. The system adaptively matches time-sensitive convergence with decision-making modes. The traffic capacity attenuation coefficient and aftershock risk level are input into the time-sensitive convergence program, activating differentiated treatment modes based on different threshold conditions. The program employs two modes: a traffic priority mode (rapid response time window) that prioritizes restoring traffic function and limiting further damage when traffic capacity degradation is dominant; and a risk containment mode (emergency reinforcement time window) that prioritizes suppressing structural instability chain reactions and preventing sudden damage when aftershock risk is dominant. The two modes dynamically switch to ensure that the decision-making logic aligns with both the bridge's current mechanical state and the evolving potential risks. The final output decision support characteristics, with three decision indicators (traffic capacity attenuation coefficient, aftershock risk level, and time-sensitive threshold) forming a closed-loop evaluation system, provide quantitative basis for bridge maintenance. By integrating multi-dimensional data on strain constraints, functional attenuation, and risk prediction, the system achieves cross-scale mapping from micro-damage to macro-level decision-making, supporting the formulation of precise and differentiated maintenance strategies.

[0099] In summary, this embodiment transforms discrete damage data into actionable decision indicators through dynamic coupling analysis of strain, function, and risk, ensuring that bridge safety assessment is real-time, accurate, and forward-looking.

[0100] Example 7:

[0101] Based on Example 6, the process of forming an emergency response time threshold from the rapid response time window and the emergency reinforcement time window in step S304 of this embodiment of the invention includes the following steps:

[0102] Step S3041: Obtain the traffic capacity attenuation coefficient, generate the traffic resistance gradient field based on the spatial distribution of the core damage domain; calculate the road network vulnerability barrier based on the connectivity of complementary damage ring units; the traffic resistance gradient field and the road network vulnerability barrier are superimposed to form a functional attenuation potential energy field; simultaneously obtain the aftershock risk level, the aftershock chain triggering domain driving instability energy accumulation rate, and the time-varying function of stress redistribution triggered by local instability high-risk areas, and fuse them to generate a risk kinetic energy field;

[0103] Step S3042: The functional decay potential energy field and the risk kinetic energy field are coupled into a field equilibrium;

[0104] When the gradient intensity of the functional decay potential energy field is not less than the diffusion intensity of the risk kinetic energy field, a dominant interface for passage is formed in the boundary region; when the diffusion intensity of the risk kinetic energy field is greater than the gradient intensity of the functional decay potential energy field, a dominant interface for risk is formed in the boundary region.

[0105] Step S3043: Trace along the traffic resistance gradient field to the road network vulnerability barrier, calculate the critical time for road network connection, and output the rapid response time window; monitor the instability energy accumulation rate through the time-varying function of stress redistribution, solve for the critical instability time, and generate the emergency reinforcement time window.

[0106] In the above embodiments, this embodiment achieves the adaptive generation of the emergency response threshold for bridges after earthquakes through dynamic coupling analysis of the functional decay potential energy field and the risk kinetic energy field. The core effects of its combined technical features are as follows: decision boundary division driven by dual-field coupling; the functional decay potential energy field (traffic resistance gradient field and road network vulnerability barrier) quantifies the spatial deterioration trend of bridge traffic capacity and reflects the potential path of structural functional failure; the risk kinetic energy field (instability energy accumulation rate and stress redistribution time-varying function) characterizes the dynamic propagation intensity of aftershock chain damage and predicts the time-varying risk of local instability; through the comparison of the two field intensities (gradient intensity and diffusion intensity), a traffic-dominant interface or a risk-dominant interface is formed in the boundary area, dynamically dividing the decision boundary between "ensuring traffic" and "controlling risk". The critical conditions for determining the time-sensitive threshold are solved, with a rapid response time window: based on the calculation of the critical time for road network connectivity, ensuring that key repairs are completed before the traffic capacity accelerates its decline, thus maintaining traffic function; and an emergency reinforcement time window: through monitoring the critical point of the instability energy accumulation rate and the time-varying function of stress redistribution, reinforcement intervention is triggered before structural instability. The priority of the two time windows is dynamically allocated by the coverage area of ​​the dominant interface, achieving adaptive matching between the response strategy and the actual state of the bridge. The closed-loop optimization logic of emergency response prioritizes restoring traffic function and suppressing the further expansion of the traffic resistance gradient field when functional decline is dominant (the area of ​​the traffic-dominant interface is larger); when instability risk is dominant (the area of ​​the risk-dominant interface is larger), priority is given to blocking aftershock chain reactions and reducing the diffusion intensity of the risk kinetic energy field. The final output emergency response time-sensitive threshold integrates the dual requirements of structural function maintenance and stability control, forming a closed-loop optimization system of assessment-decision-intervention.

[0107] In summary, this embodiment transforms the complex bridge damage state into an operable and timely decision-making indicator by using multi-physics field coupling (potential energy field - kinetic energy field), critical time solution (road network connectivity / instability criticality), and dynamic priority allocation (interface coverage area). This solves the problems of ambiguous timing and statically fixed priorities in traditional methods, and significantly improves the accuracy and timeliness of post-earthquake emergency response.

[0108] Example 8:

[0109] Based on Example 7, the process of outputting the rapid processing time window in step S3043 provided in this embodiment of the invention includes the following steps:

[0110] Step S30431: Starting from the maximum point of the traffic resistance gradient field, trace along the negative gradient direction to the boundary of the road network vulnerability barrier to form a minimum resistance through path;

[0111] Step S30432: Apply a dynamic barrier penetration equation to the path of least resistance, extract the barrier strength integral of the path crossing the vulnerable barrier section of the road network; couple the strain constraint of the core damage domain unit to generate the material creep acceleration factor; output the critical time step of barrier penetration.

[0112] Step S30433: Obtain the critical time step of barrier penetration. If the path does not pass through the complementary damage ring, directly output the basic treatment time window. If the path passes through the high-risk area of ​​the ring, superimpose the ring strain constraint attenuation rate to generate the extended treatment time window. Finally, a rapid treatment time window is formed.

[0113] Among them, the dynamic barrier penetration equation system constructed based on step S30432 follows the core principle of the dynamic game between barrier strength and material creep:

[0114] Formula 1: Path barrier strength integral; theoretically quantifies the energy consumption of a path with minimum resistance crossing the barrier region;

[0115]

[0116] In the formula, Ξ represents the integral value of the barrier strength; Indicates the path of least resistance; Θ ijkl (x) represents the fourth-order road network vulnerability tensor; R i R represents the spatial coordinate function of the path in the i-direction; j R represents the spatial coordinate function of the path in the j-direction; k R represents the spatial coordinate function of the path in the k-direction; l A function representing the spatial coordinates of the path in the l-direction; This represents the tensor product operator; s represents the path arc length parameter; ds represents the path differential element; its function is to operate along the path. The fourth-order direct product of the integral fourth-order tensor Θ and the path tangent vector characterizes the combined hindering effect of the anisotropic drag of the barrier region on the passage process; tensor component Θ ijkl The order is determined by the road network topology and the state of material damage.

[0117] Formula 2: Creep-Barrier Dynamic Equilibrium Equation, which theoretically describes the time-varying game process between material creep and barrier strength;

[0118]

[0119] In the formula, Γ(τ) represents the material creep acceleration factor (time variable); k represents the damage creep sensitivity coefficient; Represents the strain gradient mode of the core damage domain; γ represents the path curvature suppression factor; t0 represents the moment the ground motion ceases; Function: To establish the evolution equation of the creep factor Γ: Numerator term The denominator represents the creep acceleration effect driven by the potential barrier strength. Characterizes the inhibition of the acceleration effect by creep accumulation; The term introduces the inhibitory effect of path curvature on creep.

[0120] Formula 3 defines the critical condition for barrier penetration, and theoretically determines the critical state at which a path can penetrate the barrier:

[0121]

[0122] In the formula, t c B represents the critical time step (output) for barrier penetration; B represents the spatial domain of the road network vulnerability barrier; Θ nnnn Represents the barrier normal principal component tensor; cosh -1 It represents the inverse hyperbolic cosine function; its function is to determine that when the creep accumulation (left term) reaches the critical threshold (right term) constructed by the inverse hyperbolic function of the ratio of the barrier normal intensity to the path length, the barrier is penetrated; this condition integrates the path geometric characteristics and the spatial distribution of the barrier, breaking through the traditional stress intensity factor criterion.

[0123] Explanation of the correlation of the formula system

[0124] enter: The path of least resistance from S30431; Inheriting the core domain strain gradient of S301; process coupling: the output Ξ of Equation 1 serves as the barrier strength input of Equation 2; the output Γ(τ) of Equation 2 serves as the creep accumulation source of Equation 3; t of Equation 3 c Output at the final critical time step; fourth-order road network vulnerability tensor Θ ijkl Characterizes the spatial anisotropy of the barrier; establishes the relationship between path geometry and material creep through the path curvature suppression factor γ; achieves a nonlinear balance between creep accumulation and barrier strength through the inverse hyperbolic cosine critical condition.

[0125] In the above embodiments, this embodiment implements a path optimization and potential energy penetration mechanism. By constructing a minimum resistance path through gradient field extreme points and combining it with a dynamic barrier penetration equation, it achieves precise location and quantitative assessment of vulnerable areas in the road network. This mechanism transforms the spatial resistance characteristics of the topology into a time-varying function through barrier strength integral calculation, providing a dynamic basis for subsequent time-dependent prediction. Multi-physics coupled time-varying modeling, with coupled calculation of material creep acceleration factors and strain constraints, establishes an explicit correlation between structural damage evolution and time parameters. This model simultaneously considers static material properties (core damage domain) and dynamic propagation characteristics (barrier penetration), forming a composite damage propagation function with time-varying features. An adaptive time window decision system, based on a path risk grading mechanism of complementary damage rings, constructs a two-layer time decision architecture including a basic time window and an extended time window through the dynamic superposition of strain constraint attenuation rates. This system can autonomously adjust the spatiotemporal coverage of the disposal time window according to the risk level of the path traversing the area.

[0126] In summary, this embodiment collectively constitutes a closed-loop spatiotemporal decision-making system: the path optimization module provides the spatial dimension solution benchmark, the potential energy penetration module establishes the time dimension transformation rules, and the adaptive decision-making module realizes the dynamic matching of spatiotemporal parameters. The final output rapid response time window is essentially the spatiotemporal stability threshold boundary of the road network system under the composite damage mode.

[0127] Example 9:

[0128] Based on Example 8, the process of obtaining the critical time step for barrier penetration in step S30433 provided in this embodiment of the invention includes the following steps:

[0129] Step S304331: Map the road network topology in the time domain by the barrier penetration critical time step, load the minimum resistance through path length, and obtain the benchmark traffic recovery rate; couple the core damage domain strain constraint to generate the material strength attenuation correction amount; output the interference-free basic time window;

[0130] Step S304332: Spatial penetration discrimination is performed between the minimum resistance penetration path and the spatial coordinates of the complementary damage ring; when the intersection length of the minimum resistance penetration path and the high-risk area of ​​the ring is greater than the ring width threshold, a strong interference marker is triggered; when the minimum distance between the minimum resistance penetration path and the ring boundary is not greater than the strain gradient characteristic scale, a weak interference marker is activated.

[0131] Step S304333: The strong interference marker drives the ring strain constraint attenuation rate to perform time window extension, extract the master-slave axis difference of the biaxial residual strain in the path crossing area, and generate the axial instability correction coefficient; obtain the cumulative amount of curvature change of the energy dissipation path of the ring element, and generate the local oscillation delay factor; output the comprehensive extension amount;

[0132] Step S304334: Perform time-domain expansion of the non-interference basic time window and the comprehensive extension quantity; when the weak interference flag is activated, perform linear extension and output the first-level extension time window; when the strong interference flag is activated, start exponential extension and generate the second-level extension time window; finally, the extension processing time window is formed.

[0133] In the above embodiments, this embodiment realizes a dynamic adaptive control mechanism for the critical time step of barrier penetration. Through multi-dimensional damage feature coupling and spatiotemporal synergistic optimization, a time window extension system with hierarchical response characteristics is constructed. The core lies in establishing a two-way feedback mechanism between path connectivity and damage domain evolution: a spatiotemporal coupling analysis framework: a benchmark traffic recovery rate is established based on the road network topology time domain mapping, and the dynamic correlation between microscopic damage evolution and macroscopic time step parameters is realized through the material strength attenuation correction amount; the spatial penetration discrimination of the minimum resistance path forms a dual marking mechanism (strong / weak interference marking) for the damage sensitive area, providing a spatial topological basis for time window adjustment. Multi-scale damage response model: the strong interference marking triggers the nonlinear time window extension of the ring strain constraint attenuation rate, the axial instability characteristics are quantified through the difference between the master and slave axes of the biaxial residual strain, and the local dynamic response is captured by the cumulative amount of curvature mutation of the energy dissipation path. The generated axial instability correction coefficient and the local oscillation delay factor constitute a second-order coupled correction term. Hierarchical time domain extension strategy: the basic time window and the comprehensive extension amount achieve differentiated expansion through the marking-driven conditional branch. Linear extension (Level 1) maintains stability under weak disturbances, while exponential extension (Level 2) enhances time-step fault tolerance for strong disturbance scenarios, forming adaptive time-step control based on the severity of damage.

[0134] In summary, this embodiment achieves intelligent tracking of complex damage evolution at the critical time step by dynamically matching the spatial characteristics of the damage domain with the time-step parameters, effectively suppressing numerical oscillations caused by material nonlinearity and local instability. This system is particularly suitable for time-step optimization control of highly nonlinear processes such as multiphase material interface penetration and crack propagation.

[0135] Example 10:

[0136] Based on Example 7, the process of generating the emergency reinforcement time window in step S3043 provided in this embodiment of the invention includes the following steps:

[0137] Step S30431: Deploy energy accumulation monitoring arrays in high-risk areas of local instability, collect spatiotemporal distribution of instability energy accumulation rate in real time, and generate energy accumulation isosurfaces;

[0138] Step S30432: Critical crossing determination is performed between the energy accumulation isosurface and the time-varying stress redistribution.

[0139] When the radius of curvature of the energy accumulation isosurface is not greater than the stress redistribution time-varying admittance threshold, an energy focusing alarm is triggered; when the expansion rate of the energy accumulation isosurface is greater than the stress redistribution time-varying diffusion capacity, a boundary breach alarm is activated; these are combined to generate an instability critical trigger signal.

[0140] Step S30433: The instability critical trigger signal drives aftershock chain suppression. If the signal originates from an isolated high-risk area, a local reinforcement time window is output. If the signal covers the aftershock chain triggering domain, the inter-domain energy decoupling calculation is initiated to generate a global reinforcement time window. Finally, an emergency reinforcement time window is formed.

[0141] In the above embodiments, this embodiment constructs an intelligent generation system for emergency reinforcement time windows based on dynamic energy evolution. It achieves real-time early warning and graded response to instability risks through an energy accumulation-stress redistribution coupling mechanism. The instability energy dynamic monitoring and early warning mechanism: Real-time capture of the spatiotemporal distribution of energy accumulation rate in local high-risk instability areas is achieved through an energy accumulation monitoring matrix, generating an energy accumulation isosurface, and performing critical crossing discrimination with the time-varying characteristics of stress redistribution. When the radius of curvature of the energy accumulation isosurface is lower than the stress redistribution admittance threshold, an energy focusing alarm is triggered; when the energy accumulation expansion rate exceeds the stress redistribution diffusion capacity, a boundary breakthrough alarm is activated. These two together constitute the critical trigger signal for instability, achieving accurate identification of instability precursors. The graded reinforcement strategy is dynamically generated: The critical trigger signal for instability drives aftershock chain suppression logic, adaptively adjusting the reinforcement strategy according to the signal coverage area. If the signal originates from an isolated high-risk area, a local reinforcement time window is generated for precise intervention targeting a single instability source; if the signal involves an aftershock chain triggering domain, inter-domain energy decoupling calculation is initiated to suppress cross-domain energy transfer, generating a global reinforcement time window to prevent instability propagation. Time-varying reinforcement window adaptive optimization: The generation process of the emergency reinforcement time window integrates the dynamic characteristics of energy accumulation and the stress redistribution response characteristics to ensure that the timing of reinforcement intervention is precisely matched with the instability evolution trend; the local reinforcement time window is suitable for concentrated energy release scenarios, while the global reinforcement time window is for multi-domain coupled instability modes, forming a hierarchical and progressive dynamic control system.

[0142] In summary, this embodiment achieves accurate prediction of critical instability states through real-time interactive analysis of energy accumulation and stress redistribution. It also dynamically adjusts reinforcement strategies based on the coverage of instability trigger signals, ensuring the accuracy and timeliness of reinforcement measures. This system is particularly suitable for scenarios such as structural dynamic instability and impact disaster prevention, effectively suppressing local energy focusing and cross-domain cascading damage, and improving structural dynamic stability.

[0143] Example 11:

[0144] Based on Example 10, the process of aftershock chain suppression driven by the instability critical trigger signal in step S30433 of the present invention includes the following steps:

[0145] Step S304331: Obtain the critical trigger signal for instability, analyze the spatial centroid coordinates of the signal source in the high-risk area of ​​local instability, and generate the risk core point; extract the direction of the maximum strain gradient in the high-risk area and determine the principal axis of instability propagation;

[0146] Step S304332: Risk core point and instability expansion main axis. Construct an exponentially decaying time gradient field along the main axis with the core point as the center. Load the residual strain amplitude of the high-risk area to generate the time compression factor and output the local reinforcement time field.

[0147] Step S304333: The critical isosurface is intercepted in the local reinforcement aging field. When the aging gradient decays to the material relaxation threshold, the effective reinforcement boundary is locked. The aging field is integrated along the instability extension principal axis to obtain the minimum reinforcement time step and form a local reinforcement time window.

[0148] In the above embodiments, this embodiment constructs a local reinforcement time window intelligent generation system based on the dynamic evolution of the instability propagation axis, and achieves precise suppression of aftershock chain effects through spatiotemporal coupling of the time-dependent gradient field. Its core technical features are: dynamic identification of the instability propagation axis and construction of the time-dependent gradient field: by analyzing the spatial centroid coordinates of the instability critical trigger signal and the direction of maximum strain gradient, the risk core point and the instability propagation axis are determined, forming the dominant path for instability energy release; an exponentially decaying time-dependent gradient field is constructed along the axis centered on the core point, and the residual strain amplitude in the high-risk area is loaded to generate a time-dependent compression factor, ensuring precise matching between the reinforcement time-dependent gradient field and the dynamic evolution characteristics of instability, and ensuring efficient distribution of reinforcement energy along the instability propagation axis. Critical interception of the time-dependent gradient field and locking of the reinforcement boundary: the local reinforcement time-dependent gradient field is intercepted through a critical isosurface. When the time-dependent gradient decays to the material relaxation threshold, the effective reinforcement boundary is automatically locked to avoid energy waste in ineffective reinforcement areas; this process, combined with the dynamic relaxation characteristics of the material, ensures that the reinforcement intervention range is consistent with the actual instability influence domain, preventing insufficient or excessive reinforcement. The minimum reinforcement time step is dynamically generated: the time-effect field is integrated along the instability extension principal axis to quantify the cumulative effect of reinforcement energy in the spatiotemporal dimension, extract the minimum reinforcement time step, and form a local reinforcement time window; this time window accurately reflects the critical time scale of instability energy release, so that reinforcement measures can be intervened at the best time to block the aftershock chain triggering path.

[0149] In summary, this embodiment achieves adaptive generation of the local reinforcement time window through the coordinated control of the instability propagation principal axis and the time-dependent gradient field, ensuring the precise release of reinforcement energy along the dominant instability path and effectively suppressing the aftershock chain reaction. This system is particularly suitable for rapid response to dynamic instability disasters, capable of blocking the diffusion of instability energy along the principal axis, and improving the local stability and overall disaster resistance of the structure.

[0150] Example 13:

[0151] like Figure 5 As shown, based on Examples 1-12, the bridge seismic damage rapid assessment system provided in this embodiment of the invention includes:

[0152] The hybrid field dynamic response reconstruction module 1 is configured to acquire strain abrupt change signals of key sections of the bridge during earthquakes in real time through contact measurement nodes, obtain time history abrupt change characteristics, and simultaneously trigger a non-contact spatial scanning device to perform directional energy spectrum coverage of the three-dimensional deformation field of the entire bridge; and perform cross-modal coupling calibration of the time history abrupt change characteristics and the phase of the spatial energy spectrum to generate a high-confidence three-dimensional dynamic response field.

[0153] Damage-sensitive domain inverse locking module 2 is configured to extract spatial gradient distribution features and energy dissipation paths based on the high-confidence three-dimensional dynamic response field of the output; input the spatial gradient distribution features into the nonlinear material state inversion program, combine the energy dissipation paths to verify the path integrity, and output the potential damage topological boundary of the bridge.

[0154] The functional-level damage quantification mapping module 3 is configured to divide the output potential bridge damage topology boundary into discretized damage units and apply biaxial residual strain constraints to each unit; the strain constraints of the discretized damage units are mapped to a triple decision index of traffic capacity attenuation coefficient, emergency response time threshold and aftershock risk level through the bridge structure function attenuation rule.

[0155] In the above embodiments, this embodiment achieves precise construction of a three-dimensional dynamic response field. Through hybrid field dynamic response reconstruction, it overcomes the limitations of traditional single-point monitoring. The cross-modal coupling of contact strain nodes and non-contact spatial scanning enables spatiotemporal synchronous calibration of time-varying signals at key sections and the three-dimensional deformation field of the entire bridge, providing a dynamic response data foundation with millimeter-level spatial resolution and millisecond-level temporal resolution for subsequent analysis. High-precision positioning of the damage area is achieved. Based on the spatial gradient characteristics of the three-dimensional response field and energy dissipation path verification, a quantitative mapping relationship between "mechanical response and material damage" is established through nonlinear material state inversion. It can identify hidden damage that cannot be detected by traditional naked-eye inspection and control the damage positioning error within the topological boundary at the structural unit level. Quantitative decision-making regarding functional impact transforms geometric damage into functional indicators: by simulating actual load conditions through biaxial residual strain constraints, the output triple decision indicators (traffic capacity coefficient, disposal timeliness threshold, and aftershock risk level) directly correspond to specific disposal needs in emergency management, such as traffic control, disaster relief resource allocation, and secondary disaster prevention.

[0156] In summary, this embodiment transforms the complex structural mechanical response of bridges into operable engineering decision parameters, enabling a complete assessment process from data collection to the generation of response recommendations within a short time after an earthquake, thus improving efficiency compared to traditional manual assessments. The system's output of triple decision indicators can be directly integrated into bridge emergency management plans, providing quantitative basis for subsequent actions such as traffic control and rescue operations.

[0157] Figure 6 A block diagram of an exemplary electronic device suitable for implementing embodiments of the present invention is shown.

[0158] The electronic device may include a central processing unit / microprocessor / main control chip, etc. 4; and a storage medium 5, coupled to the central processing unit / microprocessor / main control chip, etc. 4, and storing computer-executable instructions therein for performing the steps of various methods of embodiments of the present invention when executed by the processor.

[0159] The central processing unit / microprocessor / main control chip, etc., can include, but are not limited to, one or more processors or microprocessors.

[0160] Storage medium 5 may include, but is not limited to, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, computer storage media (e.g., hard disk, floppy disk, solid-state drive, removable disk, CD-ROM, DVD-ROM, Blu-ray disc, etc.).

[0161] In addition, the electronic device may also include (but is not limited to) a data bus 6, an input / output bus / external bus / device bus 7, a display 8, and input / output devices 9 (e.g., keyboard, mouse, speaker, etc.).

[0162] The central processing unit / microprocessor / main control chip, etc. 4 can communicate with external devices (8, 9, etc.) via I / O bus 7 through wired or wireless network (not shown).

[0163] The storage medium 5 may also store at least one computer-executable instruction for performing the steps of various functions and / or methods in the embodiments described herein when the central processing unit / microprocessor / main control chip, etc., 4 is running.

[0164] In one embodiment, the at least one computer-executable instruction may also be compiled into or comprise a software product, wherein one or more computer-executable instructions are executed by a processor to perform the steps of the various functions and / or methods in the embodiments described herein.

[0165] Figure 7 A schematic diagram of a computer-readable storage medium according to an embodiment of the present invention is shown.

[0166] like Figure 7 As shown, the non-transitory computer-readable storage medium 11 stores instructions, such as computer-readable instructions 10. When the computer-readable instructions 10 are executed by a processor, the various methods described above can be performed. The non-transitory computer-readable storage medium includes, but is not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Non-transitory non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. For example, the non-transitory computer-readable storage medium 11 can be connected to a computing device such as a computer, and then, when the computing device executes the computer-readable instructions 10 stored on the computer-readable storage medium 11, the various methods described above can be performed.

[0167] In the several embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0168] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0169] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0170] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for executing all or part of the steps of the methods of the various embodiments of this invention through a computer device (which may be a personal computer, server, or network device, etc.). The aforementioned storage medium includes: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media capable of storing program code.

[0171] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A rapid assessment method for seismic damage to bridges, characterized in that, The process includes the following steps: Based on the output high-confidence three-dimensional dynamic response field, extract the spatial gradient distribution features and energy dissipation paths; obtain the bridge potential damage topological boundary; divide the output bridge potential damage topological boundary into discretized damage units, and apply biaxial residual strain constraints to each unit; map the strain constraints of the discretized damage units into a triple decision index of traffic capacity attenuation coefficient, emergency response time threshold, and aftershock risk level through the bridge structure function attenuation rule.

2. The rapid assessment method for bridge seismic damage as described in claim 1, characterized in that, The process of mapping the strain constraints of discretized damage elements to triple decision indices includes the following steps: For each discretized damage element, the biaxial residual strain constraint is subjected to master-slave axis strain separation, and the amplitude of the master strain axis and the variability of the secondary strain axis are extracted. When the variability of the secondary strain axis exceeds the set proportion of the amplitude of the master strain axis, the strain energy redistribution mechanism is triggered, and the equivalent functional attenuation coefficient is output. The equivalent functional attenuation coefficient is combined with the attenuation coefficient based on the core damage domain unit to generate a lane-level attenuation gradient through weight enhancement; based on the attenuation coefficient of the complementary damage ring unit, diffusion suppression is activated to output the regional traffic reduction rate; the lane-level attenuation gradient and the regional traffic reduction rate are fused to form the traffic capacity attenuation coefficient. The principal strain axis amplitude is used to identify unit clusters that meet the strain space correlation conditions, construct aftershock chain triggering domains, extract strain gradient abrupt change interfaces within unit clusters, and mark high-risk areas of local instability; aftershock chain triggering domains and high-risk areas of local instability are fused by risk field superposition rules to output aftershock risk levels. The traffic capacity attenuation coefficient and aftershock risk level are input into the time-sensitivity convergence program; the rapid response time window and the emergency reinforcement time window form the emergency response time threshold.

3. The rapid assessment method for bridge seismic damage as described in claim 1, characterized in that, When the traffic capacity attenuation coefficient is not less than the threshold corresponding to the aftershock risk level, the traffic priority mode is activated, and a rapid response time window is generated; when the aftershock risk level is greater than the threshold corresponding to the traffic capacity attenuation coefficient, the risk containment mode is triggered, and an emergency reinforcement time window is output.

4. The rapid assessment method for bridge seismic damage as described in claim 2, characterized in that, The process of establishing emergency response time thresholds by combining rapid response time windows and emergency reinforcement time windows includes the following steps: Obtain the capacity attenuation coefficient and generate the traffic resistance gradient field based on the spatial distribution of the core damage domain; calculate the road network vulnerability barrier based on the connectivity of complementary damage ring units; the traffic resistance gradient field and the road network vulnerability barrier are superimposed to form a functional attenuation potential field. Simultaneously acquire aftershock risk level, aftershock chain triggering domain drive instability energy accumulation rate, local instability high-risk zone trigger stress redistribution time-varying function, and fuse to generate risk kinetic energy field; The functional decay potential energy field and the risk kinetic energy field are coupled into a field equilibrium. When the gradient intensity of the functional decay potential field is not less than the diffusion intensity of the risk kinetic field, a dominant interface is formed in the boundary region. When the diffusion intensity of the risk kinetic energy field is greater than the gradient intensity of the functional decay potential energy field, a risk-dominant interface is formed in the boundary region. Tracing back along the traffic resistance gradient field to the road network vulnerability barrier, calculating the critical time for road network connectivity, and outputting a rapid response time window; monitoring the instability energy accumulation rate through the time-varying function of stress redistribution, solving for the critical instability time, and generating an emergency reinforcement time window.

5. The rapid assessment method for bridge seismic damage as described in claim 4, characterized in that, The process of outputting a fast processing time window includes the following steps: Starting from the maximum point of the traffic resistance gradient field, trace along the negative gradient direction to the boundary of the road network vulnerability barrier to form a minimum resistance through path; A dynamic barrier penetration equation is applied to the path of least resistance to extract the barrier strength integral of the path crossing the vulnerable barrier section of the road network. The strain constraint of the coupled core damage domain unit generates a material creep acceleration factor; The output barrier penetrates the critical time step; Obtain the critical time step for barrier penetration. If the path does not pass through the complementary damage ring, directly output the basic treatment time window. If the path passes through the high-risk area of ​​the ring, superimpose the ring strain constraint attenuation rate to generate the extended treatment time window. Finally, a rapid treatment time window is formed.

6. The rapid assessment method for bridge seismic damage as described in claim 5, characterized in that, The process of obtaining the critical time step for barrier penetration includes the following steps: The road network topology is mapped in the time domain by the critical time step of barrier penetration, the minimum resistance path length is loaded, and the benchmark traffic recovery rate is obtained; the strain constraint of the core damage domain is coupled to generate the material strength attenuation correction; and the interference-free basic time window is output. Spatial penetration discrimination is performed between the minimum resistance penetration path and the spatial coordinates of the complementary damage ring; when the intersection length between the minimum resistance penetration path and the high-risk area of ​​the ring is greater than the ring width threshold, a strong interference marker is triggered; when the minimum distance between the minimum resistance penetration path and the ring boundary is not greater than the strain gradient characteristic scale, a weak interference marker is activated. The strong interference marker drives the annular strain constraint attenuation rate to perform time window extension, extracts the master-slave axis difference of biaxial residual strain in the path crossing area, and generates the axial instability correction coefficient; obtains the cumulative amount of curvature change of the energy dissipation path of the annular element, and generates the local oscillation delay factor; outputs the comprehensive extension amount; Time-domain expansion is performed using an interference-free basic time window and integrated extension. When a weak interference flag is activated, linear extension is performed, and a first-level extension window is output; when a strong interference flag is activated, exponential extension is initiated, and a second-level extension window is generated; finally, an extension processing window is formed.

7. The rapid assessment method for bridge seismic damage as described in claim 4, characterized in that, The process of generating an emergency hardening time window includes the following steps: Energy accumulation monitoring arrays are deployed in high-risk areas of local instability to collect the spatiotemporal distribution of instability energy accumulation rate in real time and generate energy accumulation isosurfaces. Critical crossing criteria are determined by comparing the energy accumulation isosurface with the time-varying stress redistribution. The instability critical trigger signal drives the aftershock chain suppression; if the signal originates from an isolated high-risk area, a local reinforcement time window is output. If the signal covers the aftershock chain triggering domain, the energy decoupling calculation between domains is initiated to generate a global reinforcement time window; ultimately forming an emergency reinforcement time window.

8. The rapid assessment method for bridge seismic damage as described in claim 1, characterized in that, By acquiring strain abrupt change signals of key sections of the bridge in real time during earthquakes through contact measurement nodes, the time history abrupt change characteristics are obtained. Simultaneously, a non-contact spatial scanning device is triggered to perform directional energy spectrum coverage of the three-dimensional deformation field of the entire bridge. The time history abrupt change characteristics and the phase of the spatial energy spectrum are coupled and calibrated across modes to generate a high-confidence three-dimensional dynamic response field.

9. The rapid assessment method for bridge seismic damage as described in claim 8, characterized in that, Based on the high-confidence three-dimensional dynamic response field output, spatial gradient distribution features and energy dissipation paths are extracted; the spatial gradient distribution features are input into a nonlinear material state inversion program, and the path integrity is verified by combining the energy dissipation paths, and the potential damage topological boundary of the bridge is output.

10. A rapid bridge seismic damage assessment system according to any one of claims 1 to 9, characterized in that, include: The hybrid field dynamic response reconstruction module is configured to acquire strain abrupt change signals of key sections of the bridge during earthquakes in real time through contact measurement nodes, obtain time history abrupt change characteristics, and simultaneously trigger a non-contact spatial scanning device to perform directional energy spectrum coverage of the three-dimensional deformation field of the entire bridge; the time history abrupt change characteristics and the phase of the spatial energy spectrum are coupled and calibrated across modes to generate a high-confidence three-dimensional dynamic response field. The damage-sensitive domain inverse locking module is configured to extract spatial gradient distribution features and energy dissipation paths based on the high-confidence three-dimensional dynamic response field of the output; the spatial gradient distribution features are input into the nonlinear material state inversion program, and the path integrity is verified by combining the energy dissipation paths, and the potential damage topological boundary of the bridge is output. The functional-level damage quantization mapping module is configured to divide the output potential bridge damage topology boundary into discretized damage units and apply biaxial residual strain constraints to each unit. The strain constraints of the discretized damage units are mapped to a triple decision index of traffic capacity attenuation coefficient, emergency response time threshold, and aftershock risk level through the bridge structure function attenuation rule.

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