Real-time updating method for building damage based on bim and on-site perception data

Abstract

The application discloses a building damage real-time updating method based on BIM and field perception data, relates to the technical field of damage updating, and is used for solving the problem of reduced damage feature extraction accuracy. The acceleration peak, displacement amplitude and strain overrun of a building monitoring point are collected, a cross-scale response feature vector is constructed in combination with a historical damage baseline of a corresponding component in a BIM model, multi-source response data is normalized and baseline corrected, timing correction is performed based on different modal sampling frequencies, response features of each mode in different frequency bands are analyzed and response differences between modes are detected, a sensitivity difference weight matrix is generated, multi-modal response features are adaptively fused to generate a unified damage evaluation index according to the weight matrix, and the damage evaluation result is mapped to a corresponding component position of the BIM model and a differentiated updating strategy is executed according to the component type, so that the accuracy of building damage state recognition and model dynamic updating is improved.

Description

Technical Field

[0001] This invention relates to the field of seismic damage update technology, and more specifically, to a method for real-time updating of building seismic damage based on BIM and on-site perception data. Background Technology

[0002] With the development of building structure monitoring technology and building information modeling technology, the perception of building structure status and dynamic updating of seismic damage information under earthquake action is gradually shifting from traditional manual inspection methods to data-driven intelligent analysis methods. Existing building seismic damage assessment methods usually involve deploying multiple types of monitoring equipment at key locations of the building structure to collect on-site perception data such as structural vibration response, deformation response, and material stress response. This data is then combined with component spatial information in the building information model to achieve a visual representation of the seismic damage status, thereby assisting in rapid post-earthquake assessment and emergency decision-making.

[0003] The existing technology has the following shortcomings: Currently, existing technologies typically assess the post-earthquake structural condition by associating on-site monitoring data such as vibration, displacement, and strain with component information in a building information model. However, they lack mechanisms for data benchmark correction based on historical component damage and dynamic fusion adjustment for different sensor modal response characteristics. This results in reduced accuracy of damage feature extraction and increased interference from abnormal responses. Therefore, a real-time update method for building seismic damage based on BIM and on-site sensing data is proposed.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a method for real-time updating of building seismic damage based on BIM and on-site sensing data. This method addresses the problems mentioned in the background by employing multi-source sensing data fusion, historical damage baseline correction, modal response feature analysis, and adaptive damage assessment technology based on sensitivity weights.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for real-time updating of building seismic damage based on BIM and on-site sensing data, comprising the following steps: Step S1: Collect the peak acceleration, displacement amplitude, and strain exceeding the limit at the monitoring points of the building, read the sampling frequency of each modal sensor, and retrieve the historical damage baseline of the corresponding component in the BIM model; Step S2: Generate a cross-dimensional response feature vector by combining peak acceleration, displacement amplitude, and strain over-limit. Then, determine the normalized response features by baseline correction and normalization of the cross-dimensional response feature vector using the historical damage baseline of the corresponding component. Step S3: Evaluate the timing alignment benchmark based on the modal sampling frequency and perform timing correction on the normalized response characteristics. Analyze the difference in response intensity distribution of each mode in the high-frequency vibration and low-frequency deformation frequency bands. After detecting the conflict in response direction between modes, generate a sensitivity difference weight matrix. Step S4: Based on the sensitivity difference weight matrix, adaptively weightedly fuse the modal response features to generate a unified damage assessment index. Map the unified damage assessment index to the corresponding component spatial location in the BIM model, determine the damage level according to the component type, and trigger a differentiated update strategy.

[0007] In a preferred embodiment, in step S1, the acquisition period is set starting from the moment the earthquake event is triggered, the sequence of vibration acceleration is acquired, and the maximum absolute value within the acquisition period is taken as the acceleration peak value. When collecting inter-layer relative displacement, the program sequence takes the maximum absolute value within the collection period as the displacement amplitude. When collecting strain data, the program will take the cumulative value within the collection period as the strain excess value, which is the difference between the strain value and the design yield strain. Access the BIM model database to retrieve the historical damage baseline of the corresponding component accumulated during historical earthquake events.

[0008] In a preferred embodiment, in step S2, the three heterogeneous physical quantities, peak acceleration, displacement amplitude, and strain over-limit, are assembled into a cross-dimensional response feature vector, which is a vector composed of the three components: peak acceleration, displacement amplitude, and strain over-limit. The Max-Min normalization method is used to perform dimensionless processing on each component of the cross-dimensional response feature vector to obtain the normalized components; Baseline correction is performed on each normalized component using the component's historical damage baseline to obtain three components of the normalized response characteristics.

[0009] In a preferred embodiment, in step S3, the time alignment benchmark is evaluated based on the sampling frequencies of the three modalities, and the lowest value among the three sampling frequencies is selected as the benchmark time axis. The normalized response characteristics acquired from the high-frequency modes are taken as an arithmetic mean or downsampled to the reference time axis using linear interpolation within each reference time window to obtain the time-corrected response characteristics. Perform a fast Fourier transform on each modal component of the time-corrected response characteristics to obtain the power spectral density distribution of each mode in the frequency domain; The frequency is divided into high-frequency vibration components, low-frequency deformation components, and transition components. The energy proportion of each mode in the high-frequency vibration components and low-frequency deformation components is calculated.

[0010] In a preferred embodiment, in step S3, intermodal response direction conflicts are detected, and the maximum deviation of each mode in the frequency band distribution is measured by Chebyshev distance. The Chebyshev distance between any two modes is calculated. When the calculated Chebyshev distance between two modes exceeds the conflict determination threshold, it is determined that there is a conflict in the response direction between the two modes; Based on the energy proportion distribution and conflict detection results, a sensitivity difference weight matrix is ​​constructed using the analytic hierarchy process (AHP). The specific steps are as follows: Step 1: Construct a third-order pairwise comparison matrix based on the matching degree between the energy distribution of each mode and the dominant frequency band of the current seismic event, and increase or decrease the importance score of the conflicting parties. Step 2: Find the largest eigenvalue and its corresponding eigenvector for the pairwise comparison matrix; Step 3: Normalize the feature vectors to obtain the weight matrix; Step 4: Calculate the consistency ratio and determine whether to accept the weighted result based on the consistency ratio.

[0011] In a preferred embodiment, in step S4, an adaptive weighted fusion is performed on the time-corrected normalized response features based on the sensitivity difference weight matrix to generate a unified damage assessment index. The unified damage assessment index is mapped to the corresponding spatial location of the component in the BIM model. The specific mapping method is as follows: The three-dimensional coordinates of each sensor installation location and the three-dimensional coordinates of the geometric center of each component are read from the BIM model database. The mapping relationship between the sensor and the component is established according to the Euclidean distance principle to obtain the spatial distance between the sensor and the component.

[0012] In a preferred embodiment, in step S4, the damage level is determined based on the component type, and the grading rules are formulated as follows: Rule A: When the component type is a load-bearing component, namely a frame column, main beam, or shear wall, the damage is classified as minor, moderate, or severe based on the comparison of the unified damage assessment index, the threshold for minor damage, and the threshold for moderate damage. Rule B stipulates that when the component type is a non-load-bearing component, such as a secondary beam, infill wall, or partition, minor damage, moderate damage, or severe damage shall be determined by comparing the unified damage assessment index, the threshold for minor damage in category II, and the threshold for moderate damage in category II.

[0013] In a preferred embodiment, in step S4, a differentiated update strategy is triggered. For components that are determined to be severely damaged, the damage attributes, stiffness reduction factor, and remaining bearing capacity of the component in the BIM model are immediately updated, and an early warning message is pushed. For components identified as having moderate damage, update the BIM model attributes in batches within the current scheduling cycle; For components determined to be slightly damaged, updates will be made uniformly in the next scheduling cycle; If the same component corresponds to multiple monitoring points and the difference in the unified damage assessment index of each point exceeds the preset value, the component is marked as a suspected state of uneven spatial damage, triggering a secondary verification process.

[0014] In a preferred embodiment, in step S1, before acquiring the peak acceleration, displacement amplitude, and strain exceeding the limit, the median absolute deviation test is first performed on the original time sequence of each mode, and it is marked as a suspicious anomaly. If the proportion of suspicious anomalies in a certain modality exceeds a preset value during the collection period, the weight of that modality in this round of fusion will be reduced, and a sensor suspected failure alarm will be pushed to the emergency command platform.

[0015] In a preferred embodiment, in step S4, after each damage level determination, in addition to writing the current damage attribute field, the equivalent stiffness reduction factor and the remaining bearing capacity ratio of the component are updated synchronously. The design of the incremental update mechanism for component damage attributes involves maintaining a damage event time sequence queue for each component in the BIM model. Once a new round of fusion is completed, the current event is appended to the end of the queue by timestamp, and the historical damage baseline is updated. The updated historical damage baseline replaces the original historical damage baseline and is written back to the BIM component attribute field for retrieval during the next aftershock event fusion.

[0016] The technical effects and advantages of this invention are as follows: This invention collects peak acceleration, displacement amplitude, and strain exceedance data from building monitoring points. It then constructs a cross-dimensional response feature vector by combining this data with the historical damage baseline of corresponding components in the BIM model. The multi-source response data is normalized and baseline corrected. Temporal correction is performed based on different modal sampling frequencies. The response characteristics of each mode in different frequency bands are analyzed, and differences in response between modes are detected. A sensitivity difference weight matrix is ​​generated. Based on this weight matrix, the multi-modal response features are adaptively fused to generate a unified damage assessment index. The damage assessment results are mapped to the corresponding component locations in the BIM model, and a differentiated update strategy is executed according to the component type. This improves the accuracy of building seismic damage status identification and dynamic model updates, achieves real-time linkage between on-site sensing data and BIM model damage information, reduces the lag in post-earthquake manual inspections and model maintenance, and improves the efficiency of building seismic damage assessment and emergency response. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating the implementation of the real-time update method for building seismic damage based on BIM and on-site perception data, as per the present invention.

[0018] Figure 2 This is a schematic diagram illustrating the steps of the real-time updating method for building seismic damage based on BIM and on-site perception data according to the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] This invention collects peak acceleration, displacement amplitude, and strain exceedance data from monitoring points on buildings. It then constructs a cross-dimensional response feature vector by combining this data with the historical damage baseline of corresponding components in the BIM model. The multi-source response data is normalized and baseline corrected. Temporal correction is performed based on different modal sampling frequencies. The response characteristics of each mode in different frequency bands are analyzed, and differences in response between modes are detected. A sensitivity difference weight matrix is ​​generated. Based on this weight matrix, the multi-modal response features are adaptively fused to generate a unified damage assessment index. The damage assessment results are mapped to the corresponding component locations in the BIM model, and a differentiated update strategy is executed according to the component type. This improves the accuracy of building seismic damage state identification and dynamic model updates.

[0021] Example 1 Please see Figures 1 to 2 The specific operation process of the real-time update method for building seismic damage based on BIM and on-site perception data is as follows: Step S1: Collect the peak acceleration, displacement amplitude, and strain exceeding the limit at the monitoring points of the building, read the sampling frequency of each modal sensor, and retrieve the historical damage baseline of the corresponding component in the BIM model; Step S2: Generate a cross-dimensional response feature vector by combining peak acceleration, displacement amplitude, and strain over-limit. Then, determine the normalized response features by baseline correction and normalization of the cross-dimensional response feature vector using the historical damage baseline of the corresponding component. Step S3: Evaluate the timing alignment benchmark based on the modal sampling frequency and perform timing correction on the normalized response characteristics. Analyze the difference in response intensity distribution of each mode in the high-frequency vibration and low-frequency deformation frequency bands. After detecting the conflict in response direction between modes, generate a sensitivity difference weight matrix. Step S4: Based on the sensitivity difference weight matrix, adaptively weightedly fuse the modal response features to generate a unified damage assessment index. Map the unified damage assessment index to the corresponding component spatial location in the BIM model, determine the damage level according to the component type, and trigger a differentiated update strategy.

[0022] The specific implementation is as follows: In step S1, the data acquisition period is selected as T seconds, starting from the moment the earthquake event is triggered. In this embodiment, T is 60 seconds. Data is collected synchronously by three types of sensors that are attached or bolted to the surface of building components.

[0023] The first type consists of triaxial accelerometers fixed at frame column nodes and mid-span of main beams. A program sequence is used to collect vibration acceleration at a sampling frequency of 100Hz, and the maximum absolute value within the acquisition period is taken as the peak acceleration. ;、 The second type consists of laser displacement gauges or wire-type displacement gauges deployed between floors. These gauges use a 10Hz sampling frequency to collect the relative displacement between floors, and the maximum absolute value within the sampling period is taken as the displacement amplitude. ; The third type consists of resistance strain gauges bonded to the stressed surfaces of beams and columns. A program sequence is used to collect strain data at a sampling frequency of 50Hz, and strain values ​​exceeding the design yield strain are recorded. The difference is taken as the cumulative value within the acquisition period as the strain exceedance. .

[0024] Simultaneously read the sampling frequencies of the three types of sensors. The subscript i takes the values ​​1, 2, and 3, which correspond to the three modes of acceleration, displacement, and strain, respectively.

[0025] Then access the BIM model database to retrieve the historical damage baseline of the corresponding component accumulated during historical earthquake events. The value ranges from 0 to 1, where 0 indicates no historical damage and 1 indicates that the critical level of severe damage has been reached. Historical damage baseline It is obtained by updating the BIM model successively after previous main shock and aftershock events, reflecting the cumulative damage status of components before this earthquake.

[0026] It should be noted that the historical damage baseline of the component It is the equivalent damage index accumulated by the component in all the earthquake events it has experienced before this earthquake. Specifically, it is quantified as the weighted cumulative value of the damage assessment index of the component in each event, divided by the severe damage threshold and normalized to the range of 0 to 1.

[0027] In step S2, the peak acceleration is... Displacement amplitude Strain exceeding limits Three heterogeneous physical quantities are assembled into a cross-dimensional response eigenvector. ,writing equal to , , A vector consisting of three components.

[0028] Max-Min normalization method was used for Perform dimensionless processing on each component separately: First, read the modal response baseline value of the component in a non-destructive state from the BIM component attribute database. , , The acceleration, displacement, and strain baseline responses of the component under the design seismic motion are obtained from structural dynamics analysis or historical monitoring data, and then the normalized components are calculated using the following formula. : in Take in sequence , , The original values ​​of the three modes, The reference response value for the corresponding mode , , , Take the lower limit value of this mode under lossless free vibration state, in this example... Set the value to 0.

[0029] Then, the component historical damage baseline is used. Baseline correction is performed on each normalized component to obtain the normalized response characteristics. The three components: Where λ is the preset damage accumulation modulation coefficient, with a value ranging from 0.1 to 0.5.

[0030] In the above formula The larger the value, the more severe the historical cumulative damage to the component. The larger the value, the more severe the current damage should be, reflecting the higher historical damage of the component under the same physical response, which aligns with the engineering principle of the cumulative effect of the mainshock and aftershocks; when When it is 0 equal This means that components without historical damage are judged solely based on the current response.

[0031] It should be explained that the damage accumulation modulation coefficient is set by professionals in the field according to the actual structural type and the accuracy requirements of seismic damage monitoring, such as λ being 0.3, etc., which will not be elaborated here.

[0032] In step S3, the sampling frequencies of the three modes are first determined. The timing alignment benchmark is evaluated by selecting the lowest value among the three sampling frequencies. As the reference time axis, in this example Equal to 10Hz, corresponding to displacement mode; Normalized response characteristics acquired from high-frequency modes (acceleration 100Hz, strain 50Hz) Within each reference time window, the arithmetic mean is taken or the data is downsampled to the reference time axis using linear interpolation to obtain the time-corrected response characteristics. .

[0033] Next to Perform a Fast Fourier Transform on each modal component to obtain the power spectral density distribution of each mode in the frequency domain. ; Components with frequencies greater than 10 Hz are designated as high-frequency vibration components, components with frequencies less than 1 Hz are designated as low-frequency deformation components, and components between 1 Hz and 10 Hz are designated as transitional components and do not participate in subsequent conflict determination. The energy proportion of each mode in the high-frequency vibration component and the low-frequency deformation component is calculated. and : in The energy proportion of the i-th mode in the high-frequency vibration components, Let be the energy percentage of the i-th mode in the low-frequency deformation component, and both values ​​range from 0 to 1. The power spectral density distribution of each mode in the frequency domain, For the sign of differentiation, The result of the derivative of the frequency is... For frequency.

[0034] It should be noted that setting 10Hz as the lower limit of high-frequency vibration components and 1Hz as the upper limit of low-frequency deformation components is based on the engineering distribution of the natural frequencies of building structures: the first-order natural frequencies of multi-story frame structures are usually below 1Hz, and the local vibration frequencies of components are usually above 10Hz. This division can effectively separate the overall deformation of the structure from the local vibration response.

[0035] To detect conflicts in the response directions between modes, Chebyshev distance is used to measure the maximum deviation of each mode in the frequency band distribution. The distance is calculated for any two modes i and j. : in , These represent the energy proportions of mode i and mode j in the high-frequency vibration components, respectively. , These represent the energy proportions of mode i and mode j in the low-frequency deformation components, respectively.

[0036] when Exceeding the conflict determination threshold When this occurs, it is determined that there is a conflict in the response direction between mode i and mode j.

[0037] It should be explained that the conflict determination threshold is determined by the upper quartile of the energy proportion distribution of normal mode fusion cases in historical earthquake events.

[0038] Based on the energy proportion distribution and conflict detection results, the sensitivity difference weight matrix W is constructed using the analytic hierarchy process (AHP); the specific steps are as follows: Step 1: Construct a 3rd-order pairwise comparison matrix A based on the matching degree between the energy distribution of each mode and the dominant frequency band of the current seismic event. If a frequency band with a high proportion of energy of a certain mode is consistent with the dominant frequency band of the seismic event, its importance score is increased by one level; for mode pairs that are judged to be in conflict, the importance score of the conflicting party is decreased by one level. Step 2: Find the largest eigenvalue of the pairwise comparison matrix A. and its corresponding eigenvectors; Step 3: Normalize the eigenvectors to obtain the weight matrix W, which can be written as W = ... , , A vector consisting of three components, and satisfying add add It equals 1; Step 4: Calculate the consistency ratio CR. If CR is less than 0.1, accept the weighted result; otherwise, reconstruct the comparison matrix.

[0039] In step S4, the normalized response features after time-series correction are analyzed based on the sensitivity difference weight matrix W. Perform adaptive weighted fusion to generate a unified damage assessment index. : in , , The normalized response characteristics after time-series correction for acceleration, displacement, and strain are respectively presented. , , These are the fusion weights for the corresponding modalities. The value ranges from 0 to 1, with a larger value indicating more severe current damage to the component.

[0040] Then Mapping to the corresponding spatial location of the component in the BIM model. The specific mapping method is as follows: Write the 3D coordinates of each sensor installation location from the BIM model database. The three-dimensional coordinates of the geometric centers of each component are written as follows: A mapping relationship between the sensor and the component is established according to the Euclidean principle of closest distance. The spatial distance between sensor s and component c is... Calculate using the following formula: For each sensor s, select one that makes The smallest component c is used as the mapping target, and... Write the current damage attribute field of the corresponding component.

[0041] Based on the type of component, the damage level is determined, and the following classification rules are established: Rule A states that when the component type is a load-bearing component, i.e., a frame column, main beam, or shear wall, Damage less than the first-class minor damage threshold 'a' is considered minor damage. Damage falling between the threshold of minor damage (a) and the threshold of moderate damage (b) is classified as moderate damage. Damage exceeding the Class I intermediate damage threshold is classified as severe damage; Rule B states that when the component type is a non-load-bearing component, i.e., a secondary beam, infill wall, or partition, Damage less than the Class II minor damage threshold c is considered minor damage. Damage falling between the Class II minor damage threshold c and the Class II moderate damage threshold d is classified as moderate damage. Damage exceeding the Class II damage threshold d is classified as severe damage.

[0042] The above-mentioned grading thresholds are obtained from the statistical distribution of component damage indicators that have been verified on-site after the earthquake in the historical earthquake damage database, and the empirical quantile values ​​at the grading critical points are taken.

[0043] Trigger differentiated update strategy: For components that are determined to be severely damaged, immediately update the damage attributes, stiffness reduction factor, and remaining bearing capacity ratio of the component in the BIM model and push the early warning information to the emergency command platform; For components identified as having moderate damage, the BIM model attributes are updated in batches within the current scheduling cycle. In this embodiment, the scheduling cycle is 30 seconds. For components determined to be slightly damaged, updates will be made uniformly in the next scheduling cycle; If the same component corresponds to multiple monitoring points and each point If the difference exceeds 0.2, the component is marked as potentially exhibiting spatial damage non-uniformity, triggering a secondary verification process to retrieve data from adjacent components. Perform a topology consistency check.

[0044] It should be noted that in this embodiment, the damage accumulation modulation coefficient λ and the conflict determination threshold are... Auxiliary parameters such as scheduling cycle length are set by professionals in the field according to the specific building structure type and monitoring system configuration; while the thresholds for Class I minor damage (a), Class I moderate damage (b), Class II minor damage (c), and Class II moderate damage (d) are calibrated according to 30%, 60%, 40%, and 80% of the data values ​​in the historical earthquake damage database, respectively.

[0045] Through the coordinated processing of the above four steps, the heterogeneous data from multimodal sensors are fused in a coordinated manner under the constraints of differences in physical dimensions, sampling frequency, and response sensitivity. The fusion results are then fed back to the BIM model in real time, providing accurate component-level damage information for post-earthquake emergency decision-making.

[0046] In specific engineering implementations, to further improve the robustness of multimodal data fusion, this embodiment adds an outlier pre-screening mechanism to the sensor data stream.

[0047] In step S1, the peak acceleration value is collected. Displacement amplitude Strain exceeding limits Previously, the median absolute deviation test was performed on the original time sequence of each mode, and sampling points that deviated from the median of the sequence by more than 3 times the median absolute deviation were marked as suspicious outliers; If the number of suspicious anomalies in a certain mode exceeds 5% within the acquisition period T, it is determined that the sensor of that mode may have detached, saturated, or had loose wiring due to strong vibration. The weight of that mode in this round of fusion is reduced to 0.3 times the original value, and a sensor suspected failure alarm is pushed to the emergency command platform.

[0048] It should be noted that the BIM model database access in this solution adopts a domestic database interface, which is connected with the multimodal cross-scale damage identification system architecture based on domestic database and AI framework described in the project. The component attribute fields include multiple attributes such as component type, material grade, design bearing capacity, geometric dimensions, geometric center coordinates, non-destructive state benchmark response value, and historical damage baseline.

[0049] After each damage level determination, in addition to writing the current damage attribute field, the equivalent stiffness reduction factor of the component is updated synchronously. and remaining bearing capacity ratio Equivalent stiffness reduction factor Calculate using the following formula: Where α is the stiffness reduction modulation factor, 0.8 for load-bearing components and 0.4 for non-load-bearing components, reflecting the difference in stiffness attenuation rate for different component types under damage conditions; the remaining bearing capacity ratio Calculate using the following formula: Where β is the load-bearing capacity reduction modulation coefficient, which is 0.6 for load-bearing components and 0.3 for non-load-bearing components.

[0050] The larger the value, the more severe the historical cumulative damage to the component. The lower the value, the better it aligns with the cumulative effect of damage on bearing capacity attenuation. The aforementioned reduction factor and remaining bearing capacity ratio serve as input for subsequent reinforcement scheme design and emergency evacuation decisions, and are written back to the attribute fields of the corresponding components in the BIM model in real time, supporting post-earthquake visualization and reinforcement decision-making module calls.

[0051] It needs to be explained that in this example... and The purpose of simultaneous updates is to simultaneously characterize the changes in the dynamic response properties and static load-bearing capacity of the component: Used for reconstructing the overall stiffness matrix during post-earthquake structural reanalysis, reflecting the differences in dynamic response under the secondary action of aftershocks; Used for load-bearing capacity verification to determine whether components require immediate reinforcement or replacement. Both methods characterize the impact of component damage on structural performance from different physical dimensions, avoiding the biased assessment caused by using only a single indicator.

[0052] In addition, this example designs an incremental update mechanism for component damage attributes; each component in the BIM model maintains a damage event time sequence queue Q, where each element records the timestamp and event type (mainshock or aftershock) of an earthquake event. Value, damage level, , And the sensor location ID corresponding to this incident.

[0053] Once a new round of fusion is complete, the current event is appended to the end of the queue by timestamp, and the historical damage baseline is updated using the following formula. : Where γ is the cumulative modulation coefficient, ranging from 0.2 to 0.6, for example, γ of 0.4 reflects the cumulative contribution of the current injury to the historical baseline; the min function limits... The maximum value is 1 to prevent the accumulation process from exceeding the normalized range. (Updated) Replace the original Write back the BIM component attribute fields for retrieval during the next aftershock event fusion. This is the updated historical damage baseline.

[0054] It should be noted that the introduction of the damage event time sequence Q enables the BIM model to not only retain the latest damage state, but also to fully record the damage evolution trajectory of the building in the main shock and aftershock sequence, providing a data foundation for long-term post-earthquake health monitoring and reinforcement effect assessment.

[0055] Finally, it should be noted that in this paper, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0056] Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0057] In this document, the singular forms “a,” “an,” and “the” may also include the plural forms unless the context clearly indicates otherwise. It should also be understood that terms such as “comprising / including” or “having” specify the presence of the stated features, integrals, steps, operations, components, parts, or combinations thereof, but do not preclude the possibility of the presence or addition of one or more other features, integrals, steps, operations, components, parts, or combinations thereof. Meanwhile, the term “and / or” as used in this specification includes any and all combinations of the associated listed items.

[0058] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referred to each other.

[0059] The above description of the disclosed embodiments will enable those skilled in the art to make or use various modifications to these embodiments. It will be readily apparent to those skilled in the art that the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for real-time updating of building seismic damage based on BIM and on-site perception data, characterized in that: Includes the following steps: Step S1: Collect the peak acceleration, displacement amplitude, and strain exceeding the limit at the monitoring points of the building, read the sampling frequency of each modal sensor, and retrieve the historical damage baseline of the corresponding component in the BIM model; Step S2: Generate a cross-dimensional response feature vector by combining peak acceleration, displacement amplitude, and strain over-limit. Then, determine the normalized response features by baseline correction and normalization of the cross-dimensional response feature vector using the historical damage baseline of the corresponding component. Step S3: Evaluate the timing alignment benchmark based on the modal sampling frequency and perform timing correction on the normalized response characteristics. Analyze the difference in response intensity distribution of each mode in the high-frequency vibration and low-frequency deformation frequency bands. After detecting the conflict in response direction between modes, generate a sensitivity difference weight matrix. Step S4: Based on the sensitivity difference weight matrix, adaptively weightedly fuse the modal response features to generate a unified damage assessment index. Map the unified damage assessment index to the corresponding component spatial location in the BIM model, determine the damage level according to the component type, and trigger a differentiated update strategy.

2. The method for real-time updating of building seismic damage based on BIM and on-site perception data according to claim 1, characterized in that: In step S1, starting from the moment the earthquake event is triggered, the acquisition period is set, the sequence of vibration acceleration is acquired, and the maximum absolute value within the acquisition period is taken as the peak acceleration value. When collecting inter-layer relative displacement, the program sequence takes the maximum absolute value within the collection period as the displacement amplitude. When collecting strain data, the program will take the cumulative value within the collection period as the strain excess value, which is the difference between the strain value and the design yield strain. Access the BIM model database to retrieve the historical damage baseline of the corresponding component accumulated during historical earthquake events.

3. The method for real-time updating of building seismic damage based on BIM and on-site sensing data according to claim 2, characterized in that: In step S2, the three heterogeneous physical quantities, peak acceleration, displacement amplitude, and strain over-limit, are assembled into a cross-dimensional response feature vector. The cross-dimensional response feature vector is a vector composed of the three components: peak acceleration, displacement amplitude, and strain over-limit. The Max-Min normalization method is used to perform dimensionless processing on each component of the cross-dimensional response feature vector to obtain the normalized components; Baseline correction is performed on each normalized component using the component's historical damage baseline to obtain three components of the normalized response characteristics.

4. The method for real-time updating of building seismic damage based on BIM and on-site perception data according to claim 3, characterized in that: In step S3, the timing alignment benchmark is evaluated based on the sampling frequencies of the three modalities, and the lowest value among the three sampling frequencies is selected as the benchmark time axis. The normalized response characteristics acquired from the high-frequency modes are taken as an arithmetic mean or downsampled to the reference time axis using linear interpolation within each reference time window to obtain the time-corrected response characteristics. Perform a fast Fourier transform on each modal component of the time-corrected response characteristics to obtain the power spectral density distribution of each mode in the frequency domain; The frequency is divided into high-frequency vibration components, low-frequency deformation components, and transition components. The energy proportion of each mode in the high-frequency vibration components and low-frequency deformation components is calculated.

5. The method for real-time updating of building seismic damage based on BIM and on-site perception data according to claim 1, characterized in that: In step S3, conflicts in response directions between modes are detected, and the Chebyshev distance is used to measure the maximum deviation of each mode in the frequency band distribution. The Chebyshev distance is calculated between any two modes. When the calculated Chebyshev distance between two modes exceeds the conflict determination threshold, it is determined that there is a conflict in the response direction between the two modes; Based on the energy proportion distribution and conflict detection results, a sensitivity difference weight matrix is ​​constructed using the analytic hierarchy process (AHP). The specific steps are as follows: Step 1: Construct a third-order pairwise comparison matrix based on the matching degree between the energy distribution of each mode and the dominant frequency band of the current seismic event, and increase or decrease the importance score of the conflicting parties. Step 2: Find the largest eigenvalue and its corresponding eigenvector for the pairwise comparison matrix; Step 3: Normalize the feature vectors to obtain the weight matrix; Step 4: Calculate the consistency ratio and determine whether to accept the weighted result based on the consistency ratio.

6. The method for real-time updating of building seismic damage based on BIM and on-site perception data according to claim 5, characterized in that: In step S4, an adaptive weighted fusion is performed on the normalized response features after time-series correction based on the sensitivity difference weight matrix to generate a unified damage assessment index. The unified damage assessment index is mapped to the corresponding spatial location of the component in the BIM model. The specific mapping method is as follows: The three-dimensional coordinates of each sensor installation location and the three-dimensional coordinates of the geometric center of each component are read from the BIM model database. The mapping relationship between the sensor and the component is established according to the Euclidean distance principle to obtain the spatial distance between the sensor and the component.

7. The method for real-time updating of building seismic damage based on BIM and on-site perception data according to claim 6, characterized in that: In step S4, the damage level is determined based on the component type, and the grading rules are as follows: Rule A: When the component type is a load-bearing component, namely a frame column, main beam, or shear wall, the damage is classified as minor, moderate, or severe based on a comparison of the unified damage assessment index, the threshold for minor damage, and the threshold for moderate damage. Rule B stipulates that when the component type is a non-load-bearing component, namely a secondary beam, infill wall, or partition, minor damage, moderate damage, or severe damage shall be determined by comparing the unified damage assessment index, the threshold for minor damage in category II, and the threshold for moderate damage in category II.

8. The method for real-time updating of building seismic damage based on BIM and on-site perception data according to claim 7, characterized in that: In step S4, a differentiated update strategy is triggered. For components that are determined to be severely damaged, the damage attributes, stiffness reduction factor, and remaining bearing capacity of the component in the BIM model are updated immediately, and an early warning message is pushed. For components identified as having moderate damage, update the BIM model attributes in batches within the current scheduling cycle; For components determined to be slightly damaged, updates will be made uniformly in the next scheduling cycle; If the same component corresponds to multiple monitoring points and the difference in the unified damage assessment index of each point exceeds the preset value, the component is marked as a suspected state of uneven spatial damage, triggering a secondary verification process.

9. The method for real-time updating of building seismic damage based on BIM and on-site sensing data according to claim 2, characterized in that: In step S1, before acquiring the peak acceleration, displacement amplitude, and strain exceeding the limit, the median absolute deviation test is first performed on the original time sequence of each mode, and it is marked as a suspicious anomaly. If the proportion of suspicious anomalies in a certain modality exceeds a preset value during the collection period, the weight of that modality in this round of fusion will be reduced, and a sensor suspected failure alarm will be pushed to the emergency command platform.

10. The method for real-time updating of building seismic damage based on BIM and on-site perception data according to claim 7, characterized in that: In step S4, after each damage level determination, in addition to writing the current damage attribute field, the equivalent stiffness reduction factor and the remaining bearing capacity ratio of the component are updated synchronously. The design of the incremental update mechanism for component damage attributes involves maintaining a damage event time sequence queue for each component in the BIM model. Once a new round of fusion is completed, the current event is appended to the end of the queue by timestamp, and the historical damage baseline is updated. The updated historical damage baseline replaces the original historical damage baseline and is written back to the BIM component attribute field for retrieval during the next aftershock event fusion.

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