Ancient building anti-seismic performance analysis and evaluation system based on BIM modeling

Abstract

The invention relates to the technical field of building information, and discloses an ancient building anti-seismic performance analysis and evaluation system based on BIM modeling, and the system comprises a building parameter obtaining module which is used for dynamically collecting component material attributes, structure connection states and historical damage parameters, recognizing structure weak links, and triggering a collaborative evaluation instruction; the modal feature analysis module and the seismic response simulation module are used for respectively extracting vibration modal feature parameters and seismic wave energy distribution parameters to obtain modal feature integrity indexes and dynamic stability evaluation values; the multi-source fusion judgment module synthesizes the indexes to generate a structure reinforcing or component repairing signal; the optimization parameter generation module is matched with the anti-seismic optimization strategy and generates structure reinforcement and node connection repair parameters; the system further comprises a damage coupling analysis module and a model iteration updating module, and monitoring of historical damage evolution and closed-loop updating of the BIM model are achieved. According to the system, precise evaluation and dynamic optimization of the anti-seismic performance of the historic building are realized.

Description

Technical Field

[0001] The present invention relates to the field of building information technology, and specifically to an ancient building seismic performance analysis and evaluation system based on BIM modeling. Background Art

[0002] As an important carrier of historical and cultural heritage, the seismic performance evaluation and protection of ancient buildings have always been key problems in the field of construction engineering. Traditional ancient building seismic analysis methods have many limitations: the collection of material properties of ancient building components, structural connection states, and historical damage parameters often relies on manual detection, making it difficult to achieve dynamic real-time monitoring, and the comprehensiveness and accuracy of data collection are insufficient, resulting in the inability to accurately identify weak structural links. For example, mortise and tenon joints, as typical structural features of ancient buildings, the changes in the loosening amount and crack expansion degree have a significant impact on the overall seismic performance, but traditional methods are difficult to quantitatively analyze and dynamically track such parameters.

[0003] In the process of seismic performance evaluation of existing technologies, there is a lack of the ability to fuse and analyze multi-source data. Modal feature analysis and seismic response simulation are usually carried out independently, and it is impossible to jointly evaluate the structural stiffness distribution state and dynamic response trend, resulting in lower integrity and reliability of the evaluation results. At the same time, there is insufficient research on the evolutionary correlation between historical damage and structural response, and the influence of historical damage parameters such as cumulative settlement values and inclination deformation amounts on the current seismic performance is not fully considered, making the evaluation model unable to accurately reflect the actual seismic state of ancient buildings.

[0004] The combination of traditional seismic evaluation systems and BIM technology is not deep enough, mostly staying at the model construction level, lacking a closed-loop mechanism for iteratively updating the BIM model based on evaluation results. When generating signals for structural reinforcement or component repair, it is impossible to adjust the mesh division accuracy of the BIM model in real time, resulting in the difficulty of effectively verifying and feedback the implementation effect of the optimization strategy through the model, limiting the dynamic optimization ability of seismic analysis.

[0005] With the wide application of BIM technology in the construction field, how to deeply integrate it with the seismic performance analysis of ancient buildings to achieve full-process intelligence from data collection, multi-source analysis, simulation prediction to optimization feedback has become a technical problem to be solved urgently. Existing systems lack targeted analysis modules for special structures (such as mortise and tenon joints) and historical damage characteristics of ancient buildings, and it is difficult to meet the high-precision requirements of ancient building seismic protection. Summary of the Invention

[0006] The purpose of the present invention is to provide an ancient building seismic performance analysis and evaluation system based on BIM modeling to solve the problems raised in the above background art.

[0007] To achieve the above object, the present invention provides the following technical solutions: An ancient building seismic performance analysis and evaluation system based on BIM modeling, the system includes: A building parameter acquisition module, configured to dynamically collect the component material properties, structural connection states, and historical damage parameters of a target ancient building, obtain an ancient building structural state parameter set, identify and analyze weak structural links based on the ancient building structural state parameter set, generate seismic anomaly signals, trigger collaborative evaluation instructions according to the generated seismic anomaly signals, and execute a modal feature analysis module and a seismic response simulation module according to the triggered collaborative evaluation instructions; A modal feature analysis module, configured to extract vibration modal feature parameters of the overall structure of a target ancient building, quantitatively evaluate the structural stiffness distribution state, and obtain a modal feature integrity index; A seismic response simulation module, configured to extract seismic wave energy distribution parameters of a target ancient building, predict the trend of the structural dynamic response state, and obtain a dynamic stability evaluation value; A multi-source fusion determination module, configured to receive the modal feature integrity index and the dynamic stability evaluation value, perform collaborative analysis on the seismic performance of the ancient building, and generate a structural reinforcement signal and a component repair signal; An optimization parameter generation module, configured to receive the structural reinforcement signal and the component repair signal, perform seismic optimization strategy matching, and generate structural reinforcement parameters and joint connection repair parameters.

[0008] Preferably, the identification and analysis of weak structural links include: By dynamically collecting the component material property parameters of the target ancient building, calculating the deviation percentage from the standard strength, and marking it as the material strength anomaly degree; Extract the mortise and tenon looseness and crack propagation degree in the structural connection state parameters of the target ancient building, calculate the geometric synthesis vector modulus of the two, and mark it as the connection defect characteristic value; Collect the settlement cumulative value and tilt deformation amount in the historical damage parameters, perform normalized weighted calculation, and obtain the historical damage comprehensive index; Compare the material strength anomaly degree, the connection defect characteristic value, and the historical damage comprehensive index with preset thresholds respectively. When any parameter exceeds the corresponding threshold, generate a seismic anomaly signal.

[0009] Preferably, the quantitative evaluation of the structural stiffness distribution state includes: By applying a pulse excitation and receiving the structural vibration response signal, generate a modal vibration mode diagram and a frequency response curve; Extract the main vibration mode participation coefficient and the node displacement amplitude from the modal vibration mode diagram, calculate the product of the two and take the reciprocal to obtain the stiffness continuity coefficient; Extract the low-frequency band energy ratio and spectral density from the frequency response curve, calculate the arithmetic mean of the two, and label it as the frequency domain distribution index; Perform weighted fusion on the stiffness continuity coefficient and the frequency domain distribution index to obtain the modal feature integrity index.

[0010] Preferably, the trend prediction of the structural dynamic response state includes: Input the seismic wave acceleration time history data in real time, and extract the energy spectral intensity and spectral characteristic parameters; Construct a dynamic response prediction model, input the energy spectral intensity into the model for finite element iterative processing, and output the structural failure probability within the future time interval; Extract the main frequency component and damping component in the spectral characteristic parameters, and calculate the energy ratio of the two to obtain the spectral stability factor; Perform a linear combination of the structural failure probability and the spectral stability factor to obtain the dynamic stability evaluation value.

[0011] Preferably, the collaborative analysis of the seismic performance of ancient buildings includes: Retrieve the data of material strength abnormality, set its correction coefficient, and obtain the strength influence compensation value through calculation and processing; Perform normalization calculation on the values of the modal feature integrity index, dynamic stability evaluation value, and strength influence compensation value to generate the seismic performance fusion index; Set the seismic performance determination threshold. If the fusion index is lower than the threshold, generate a structural reinforcement signal; if it is higher than the threshold, generate a component repair signal.

[0012] Preferably, the matching of seismic optimization strategies includes: If a structural reinforcement signal is captured, trigger the overall reinforcement instruction, and dynamically adjust the reinforcement position and section enhancement parameters of the structural support system according to the instruction to generate the structural reinforcement parameters; If a component repair signal is captured, trigger the joint repair instruction, and optimize the repair range and stiffness recovery coefficient of the mortise and tenon connection system according to the instruction to generate the joint connection repair parameters.

[0013] Preferably, the system further includes: A damage coupling analysis module for monitoring the evolutionary correlation between historical damage and structural response, extracting the damage propagation rate and stress redistribution coefficient, and generating a damage coupling evaluation value; The multi-source fusion determination module further combines the damage coupling evaluation value to perform secondary correction on the seismic performance fusion index.

[0014] Preferably, the monitoring of the evolutionary correlation between historical damage and structural response includes: Collect historical damage propagation rates and dynamic response growth rates through strain sensors, calculate the rate difference between the two and take the absolute value, which is marked as the damage propagation rate difference value; Extract the stress distribution data of the damaged area and the structural response concentration area, and count the ratio of the maximum stress gradient to the average gradient, which is marked as the stress redistribution coefficient; Perform weighted summation of the damage propagation rate difference value and the stress redistribution coefficient to generate a damage coupling evaluation value.

[0015] Preferably, the system of the present invention further includes: A model iterative update module, which is used to adjust the mesh division accuracy of the BIM model in real time according to the generated structural reinforcement parameters and node connection repair parameters, and feedback the optimization result to the building parameter acquisition module to form a closed-loop analysis link.

[0016] Preferably, the specific execution process of the model iterative update module includes: If the structural reinforcement parameter involves cross-section enhancement adjustment, synchronously increase the mesh density of key components; If the node connection repair parameter involves stiffness recovery optimization, synchronously increase the number of elements in the mortise and tenon connection area; Input the updated parameters into the building parameter acquisition module and restart the seismic analysis process.

[0017] Compared with the prior art, the beneficial effects of the present invention are: The ancient building seismic performance analysis and evaluation system based on BIM modeling provided by the present invention realizes the comprehensive, accurate evaluation and optimization of the seismic performance of ancient buildings through the collaborative work of multiple modules. The building parameter acquisition module can dynamically collect component material properties, structural connection states and historical damage parameters to form a structural state parameter set. By calculating the material strength abnormality degree, connection defect characteristic value and historical damage comprehensive index and comparing them with the threshold values, the structural weak links are accurately identified and seismic abnormality signals are generated, providing a reliable basis for subsequent analysis and effectively solving the problems of incomplete data and poor real-time performance in traditional manual detection.

[0018] The modal characteristic analysis module generates modal vibration mode diagrams and frequency response curves by applying pulse excitation, extracts the stiffness continuity coefficient and the frequency domain distribution index and performs weighted fusion to obtain the modal characteristic integrity index, realizing the quantitative evaluation of the structural stiffness distribution state, making up for the deficiencies of traditional methods in stiffness evaluation and making the evaluation results more scientific.

[0019] The seismic response simulation module inputs the seismic wave acceleration time history data in real time, constructs a dynamic response prediction model to output the structural failure probability, and combines the frequency spectrum stability factor to obtain the dynamic stability evaluation value, realizing the trend prediction of the structural dynamic response state and providing dynamic prediction ability for seismic performance analysis.

[0020] The multi-source fusion determination module receives the modal feature integrity index, the dynamic stability evaluation value, and the strength influence compensation value, generates the seismic performance fusion index, compares it with the threshold value, accurately generates the structural reinforcement or component repair signal, realizes the collaborative analysis of multi-source data, and improves the comprehensiveness and accuracy of the evaluation.

[0021] The optimization parameter generation module triggers corresponding instructions according to different signals, dynamically adjusts the parameters of the structural support system or the mortise and tenon connection system, generates the structural reinforcement parameters and the node connection repair parameters, making the optimization strategy more targeted and operable.

[0022] The damage coupling analysis module monitors the evolution correlation between historical damage and structural response, extracts the damage propagation rate difference value and the stress redistribution coefficient to generate the damage coupling evaluation value, and performs a secondary correction on the seismic performance fusion index, fully considering the influence of historical damage on the current seismic performance, and further improving the evaluation accuracy.

[0023] The model iteration and update module adjusts the mesh division accuracy of the BIM model in real time according to the optimization parameters, improves the modeling accuracy of key components and the mortise and tenon connection areas, and feeds back the optimization results to the building parameter acquisition module, forming a closed-loop analysis link, realizing the full-process dynamic cycle from evaluation to optimization and then to verification, and ensuring the continuous optimization and accuracy of the seismic analysis.

[0024] The entire system is based on the BIM modeling technology, organically integrates all aspects of the seismic performance analysis of ancient buildings, and significantly improves the accuracy and efficiency of the seismic performance evaluation of ancient buildings through multi-parameter dynamic acquisition, multi-source data fusion, damage evolution analysis, and model closed-loop iteration, providing a scientific and systematic technical solution for the seismic protection of ancient buildings, and having important engineering application value and social significance. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is the working principle diagram of the ancient building seismic performance analysis and evaluation system based on BIM modeling described in the present invention; Figure 2 It is the flow chart of the quantitative evaluation of the structural stiffness distribution state; Figure 3 It is the flow chart of the trend prediction of the structural dynamic response state; Figure 4 It is the flow chart of the seismic optimization strategy matching. DETAILED DESCRIPTION OF THE INVENTION

[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0027] See also Figures 1 - 4 The present invention relates to a system for analyzing and evaluating the seismic performance of ancient buildings based on BIM modeling, and its specific implementation is as follows: The building parameter acquisition module dynamically collects the component material properties, structural connection status, and historical damage parameters of the target ancient building, thereby obtaining a set of structural state parameters. Based on this parameter set, structural weaknesses are identified and analyzed. If an anomaly seismic signal is generated, this signal triggers a collaborative assessment instruction, which in turn executes the modal characteristic analysis module and the seismic response simulation module.

[0028] The modal characteristic analysis module is used to extract the vibration modal characteristic parameters of the overall structure of the target ancient building, and the structural stiffness distribution state is quantitatively evaluated to finally obtain the modal characteristic integrity index.

[0029] With the help of the earthquake response simulation module, the seismic wave energy distribution parameters of the target ancient building are extracted, and the trend of the structural dynamic response state is predicted to obtain the dynamic stability assessment value.

[0030] The multi-source fusion judgment module receives the modal characteristic integrity index and dynamic stability assessment value, conducts a collaborative analysis of the seismic performance of ancient buildings, and generates structural reinforcement signals and component repair signals.

[0031] The optimization parameter generation module receives the structural reinforcement signal and the component repair signal, performs seismic optimization strategy matching, and generates the structural reinforcement parameters and the node connection repair parameters.

[0032] Example 1: When identifying and analyzing the weak links of the structure, it is necessary to operate according to a rigorous and systematic process. Carry out dynamic acquisition of the property parameters of the components of the target ancient building. The component material property parameters mentioned here cover multiple key aspects, such as the compressive strength, tensile strength, elastic modulus of wood, etc. During the acquisition process, professional detection equipment and technologies need to be used to ensure the accuracy and reliability of the obtained data. For example, for the detection of wood strength, non-destructive testing methods such as stress wave testing can be used. By analyzing the propagation speed and waveform of stress waves in wood, the strength performance of wood can be evaluated. After these parameters are collected, they are compared with the pre-set standard strength, and the deviation percentage between the two is calculated. This deviation percentage is marked as the material strength abnormality degree. The setting of the standard strength needs to refer to relevant ancient building material standards and the material performance data of this type of ancient building in the normal state.

[0033] Extract the mortise and tenon looseness amount and crack expansion degree in the structure connection state parameters of the target ancient building. Mortise and tenon connection is a very important connection method in the ancient building structure, and the size of its looseness directly affects the stability of the structure. For the detection of the mortise and tenon looseness amount, it can be achieved by measuring the change in the gap between the tenon and the mortise, and a high-precision displacement sensor is used for real-time monitoring. The crack expansion degree requires regular observation of the cracks in the ancient building structure, and measure the changes in the length, width and depth of the cracks. After obtaining the mortise and tenon looseness amount and crack expansion degree data, it is necessary to calculate the modulus of the geometric synthesis vector of the two. It should be clear here that the calculation of the modulus of the geometric synthesis vector is based on the principle of vector synthesis. Taking the mortise and tenon looseness amount and crack expansion degree as the two components of the vector, the modulus is obtained through vector operation. This modulus is marked as the connection defect characteristic value.

[0034] Collect the settlement cumulative value and tilt deformation amount in the historical damage parameters. The acquisition of the settlement cumulative value requires the help of leveling measurement equipment. Observation points are set at key positions of the ancient building, and leveling measurements are carried out regularly. Record the settlement data of each observation point and accumulate to obtain the settlement cumulative value. The tilt deformation amount can be measured by measuring equipment such as total station, measuring the tilt angle and direction of the main structure of the ancient building, so as to obtain the tilt deformation amount. After collecting the settlement cumulative value and tilt deformation amount, it is necessary to carry out normalized weighted calculation on these two parameters. Normalization processing is to convert parameters with different dimensions into comparable values, and weighted calculation is to assign different weight coefficients according to the importance of these two parameters for the identification of weak structural links, and obtain the historical damage comprehensive index through weighted operation.

[0035] Compare the material strength abnormality degree, the connection defect characteristic value, and the historical damage comprehensive index with the preset thresholds respectively. The determination of these preset thresholds needs to comprehensively consider the type, age, structural form of the ancient building, and relevant code standards. When any parameter exceeds the corresponding threshold, an earthquake resistance abnormality signal is generated. For example, if the material strength abnormality degree exceeds the preset threshold, it indicates that the strength of the component material has shown obvious abnormalities, which may affect the earthquake resistance performance of the structure. At this time, an earthquake resistance abnormality signal needs to be generated to take corresponding measures in a timely manner. In the whole process, the acquisition accuracy of data and the calculation accuracy need to be strictly controlled in each link to ensure the reliability of the identification and analysis results of the structural weak links, providing a strong basis for the subsequent earthquake resistance performance analysis and evaluation. At the same time, it should be noted that in actual operation, various complex situations may be encountered, and the detection methods and calculation processes need to be appropriately adjusted and optimized according to the specific situation to ensure the effectiveness and accuracy of the identification and analysis work. In addition, the collected data needs to be regularly reviewed and verified to ensure the timeliness and reliability of the data, so as to better serve the earthquake resistance performance analysis and evaluation of ancient buildings.

[0036] Embodiment 2: When quantitatively evaluating the structural stiffness distribution state, a systematic operation process needs to be followed to ensure the accuracy and reliability of the evaluation results. Apply a pulse excitation to the target ancient building structure. The application of this excitation requires selecting appropriate positions and intensities, usually operating at key components or nodes according to the structural characteristics of the ancient building to simulate the stress state of the structure under actual vibration conditions. At the same time, receive the structural vibration response signals through sensors arranged at various key parts of the structure. These sensors need to have high sensitivity and precise acquisition capabilities to be able to capture the subtle changes during the structural vibration process in real time. Based on the received response signals, use professional data analysis software to generate modal vibration shape diagrams and frequency response curves. The modal vibration shape diagrams can visually display the deformation shapes of the structure during vibration, while the frequency response curves reflect the response characteristics of the structure at different frequencies.

[0037] Extract the participation coefficients of the main vibration modes and the nodal displacement amplitudes from the modal vibration mode diagram. The participation coefficients of the main vibration modes characterize the contribution degrees of each vibration mode in the overall vibration of the structure, and this parameter can be obtained through the analysis and calculation of the modal vibration mode diagram. The nodal displacement amplitude refers to the displacement magnitude of each node during the vibration of the structure, and representative nodes need to be selected in the modal vibration mode diagram for measurement and recording. After obtaining these two parameters, calculate their product and take the reciprocal to obtain the stiffness continuity coefficient. The calculation process here needs to strictly follow the rules of mathematical operations to ensure the accuracy of the data. The stiffness continuity coefficient can reflect the continuity of the structural stiffness in the spatial distribution. The larger this coefficient is, the more uniform the distribution of the structural stiffness is, and vice versa, it indicates that there are mutations or discontinuities in the stiffness distribution.

[0038] Extract the low-frequency energy proportion and the spectral density from the frequency response curve. The low-frequency energy proportion refers to the proportion of the energy contained in the low-frequency band (usually the specific frequency range is determined according to the structural characteristics of the ancient building) in the total energy in the frequency response curve, and this parameter can be obtained through the integral operation and energy analysis of the frequency response curve. The spectral density is used to describe the distribution density of the spectrum on the frequency axis and can be calculated by statistically analyzing the number and distribution of the peaks in the spectrum. Calculate the arithmetic mean of the two and label it as the frequency domain distribution index. The frequency domain distribution index can reflect the energy distribution characteristics of the structure in the frequency domain range and is of great significance for evaluating the dynamic characteristics of the structure.

[0039] Perform weighted fusion on the stiffness continuity coefficient and the frequency domain distribution index to obtain the modal feature integrity index. During the weighted fusion process, it is necessary to reasonably determine the weight coefficients according to the importance of these two parameters for evaluating the structural stiffness distribution state. The determination of the weight coefficients usually needs to combine the characteristics of the ancient building structure, engineering experience, and relevant research results. Through weighted fusion, the characteristics of the structure in terms of spatial stiffness distribution and frequency domain energy distribution can be comprehensively considered, so as to more comprehensively and accurately evaluate the structural stiffness distribution state. The higher the modal feature integrity index is, the more complete the modal features of the structure are and the better the stiffness distribution state is. On the contrary, it indicates that there are certain problems in the structural stiffness distribution, which may affect its seismic performance.

[0040] During the entire quantitative evaluation process, the standardization of operations and the accuracy of data need to be strictly controlled at each link. For example, the application force and position of the pulse excitation need to be calculated and planned in detail to avoid damaging the ancient building structure; the sensor layout needs to be reasonable to ensure that the structural vibration response signals can be received comprehensively and accurately; scientific methods and tools need to be used for data extraction and calculation to avoid the influence of human errors. In addition, the evaluation results need to be verified and compared multiple times, and combined with the historical data and actual conditions of the ancient building, comprehensively judge whether the structural stiffness distribution state meets the requirements. If abnormalities are found in the evaluation results, the entire evaluation process needs to be checked and corrected in a timely manner to ensure that the finally obtained modal feature integrity index can truly and accurately reflect the structural stiffness distribution state, providing a reliable basis for the seismic performance analysis and evaluation of ancient buildings. At the same time, in practical applications, the evaluation process and parameters also need to be appropriately adjusted and optimized according to the characteristics and requirements of different ancient buildings to improve the applicability and effectiveness of the evaluation work.

[0041] Embodiment 3: When predicting the trend of the structural dynamic response state, it is necessary to analyze the response of ancient buildings under earthquake action with a rigorous process and scientific methods. Input the real-time earthquake wave acceleration time history data, which needs to be obtained through professional earthquake monitoring equipment or authoritative earthquake databases, covering earthquake wave samples with different magnitudes, epicentral distances, and spectral characteristics to simulate diverse earthquake conditions. After inputting the data, use signal processing technology to extract the energy spectral intensity and spectral characteristic parameters. The energy spectral intensity reflects the distribution of earthquake wave energy in different frequency bands and can be obtained by performing spectral analysis on the acceleration time history and calculating the energy accumulation value in each frequency band; the spectral characteristic parameters include the main frequency component, damping component, etc. The main frequency component can be determined by identifying the frequency corresponding to the spectral peak, and the damping component needs to be comprehensively evaluated in combination with the structural material characteristics and historical vibration test data.

[0042] Build a dynamic response prediction model. This model is based on finite element analysis and needs to establish a refined structural calculation model according to the BIM model of the ancient building to accurately simulate the constitutive relationship of component materials, the nonlinear characteristics of mortise and tenon joints, and the structural boundary conditions. Input the extracted energy spectral intensity into the model for finite element iterative processing. During the iterative process, factors such as material nonlinearity, geometric nonlinearity, and contact nonlinearity need to be considered, and the dynamic equation of the structure under earthquake waves is solved by the step-by-step integration method to output the structural failure probability in the future time interval. The calculation of the failure probability needs to define the structural failure criterion, such as the component stress exceeding the yield strength, the joint displacement exceeding the allowable limit, etc., and the overall structural failure probability is determined by statistically calculating the proportion of the number of elements that meet the failure criterion.

[0043] Extract the dominant frequency component and damping component in the spectral feature parameters, and calculate the energy ratio of the two to obtain the spectral stability factor. The dominant frequency component reflects the main energy concentration frequency of the seismic wave. If it is close to the natural vibration frequency of the structure, it is easy to trigger the resonance effect; the damping component reflects the energy dissipation ability of the structure to vibration energy. The calculation of the energy ratio requires normalizing the energies corresponding to the dominant frequency component and the damping component first, and then obtaining this factor through the numerical ratio of the two. This factor can be used to measure the stability of the spectral characteristics of the seismic wave. The closer the ratio is to 1, the more stable the spectral characteristics are, and the higher the predictability of the structural dynamic response is.

[0044] Perform a linear combination of the structural failure probability and the spectral stability factor to obtain the dynamic stability evaluation value. The weight coefficients of the two need to be determined during the linear combination process. The setting of the weight coefficients needs to consider the importance level, structural form and seismic fortification objectives of the ancient building, and can be determined through expert evaluation or statistical analysis of historical earthquake damage data. For example, for ancient buildings in high-intensity seismic fortification areas, the weight of the structural failure probability can be appropriately increased to highlight the attention to structural safety. The dynamic stability evaluation value can comprehensively reflect the failure risk of the structure under the action of seismic waves and the influence of spectral characteristics on the response, providing a quantitative basis for seismic performance evaluation.

[0045] During the entire trend prediction process, the accuracy of data input is the foundation. It is necessary to ensure that the sampling frequency, duration and amplitude of the seismic wave acceleration time history data meet the specification requirements to avoid prediction result deviations caused by data errors. In the model construction link, the complexity of the ancient building structure needs to be fully considered, such as the mechanical simplification methods of special structures such as dougong and caisson. When necessary, verify the accuracy of the model through on-site dynamic testing. When performing finite element iterative calculations, it is necessary to reasonably control the time step and convergence accuracy to ensure the reliability of the results while ensuring the calculation efficiency. In addition, it is also necessary to compare and analyze the prediction results under different seismic wave conditions, identify the dynamic response characteristics of the structure under the most unfavorable conditions, and provide targeted basis for subsequent seismic optimization. For complex ancient building groups, the multi-scale modeling method can be considered, and refined models of key nodes are embedded in the macroscopic structural model to balance calculation efficiency and accuracy. At the same time, a verification mechanism for prediction results should be established, regularly compare the prediction data with actual earthquake monitoring data or shaking table test results, and continuously optimize the model parameters and prediction methods to improve the accuracy and reliability of trend prediction.

[0046] Example 4: When conducting a collaborative analysis of the seismic performance of ancient buildings, it is necessary to achieve comprehensive evaluation through multi-dimensional data fusion and quantitative processing. Taking a wooden structure pavilion in the Qing Dynasty as an example, the data of the abnormal degree of material strength of this ancient building is retrieved. This data comes from the wood strength detection of the main components such as columns and beams by the building parameter acquisition module. For example, it is detected that the compressive strength of the eaves column wood is 15% lower than the standard value, and this value is the abnormal degree of material strength. Then, a correction coefficient is set. The determination of the correction coefficient needs to consider factors such as the degree of material aging and environmental corrosion. By combining expert experience and historical data, a correction coefficient of 0.8 is set for the abnormal degree of material strength of this eaves column. After calculation and processing, the strength influence compensation value is obtained, that is, through the operation of the abnormal degree of material strength and the correction coefficient, the influence compensation amount on the seismic performance of the structure is obtained.

[0047] Perform normalization calculations on the modal feature integrity index obtained by the modal feature analysis module, the dynamic stability evaluation value obtained by the seismic response simulation module, and the above strength influence compensation value. Taking this pavilion as an example, the modal feature integrity index is 0.72, which reflects the structural stiffness distribution state; the dynamic stability evaluation value is 0.65, which reflects the structural dynamic response trend under earthquake action; the strength influence compensation value is calculated to be 0.18. During normalization, these three values are uniformly mapped to the [0,1] interval to eliminate the influence of dimensional differences and generate a seismic performance fusion index. Specifically, through a specific normalization algorithm, 0.72, 0.65, and 0.18 are converted into comparable values, and then the fusion index is obtained through weighted calculation. Suppose the fusion index in this example is 0.61.

[0048] After that, set the seismic performance judgment threshold. The setting of the threshold needs to be based on factors such as the protection level of the ancient building and the seismic fortification intensity. For example, for ancient buildings under key protection in an area with an 8-degree seismic fortification, the judgment threshold can be set to 0.65. Compare the generated fusion index with the threshold. If the fusion index is lower than the threshold, a structural reinforcement signal is generated; if it is higher than the threshold, a component repair signal is generated. In this example, the fusion index of 0.61 is lower than the threshold of 0.65, so a structural reinforcement signal is generated, indicating that the overall structure of this pavilion needs to be reinforced.

[0049] During the collaborative analysis process, the accuracy and integrity of data are of utmost importance. For the detection of material strength abnormality, non-destructive testing techniques such as stress wave detection or wood density measurement should be used to ensure that the ancient building itself is not damaged. Taking the dougong component as an example, its internal defects are detected by a stress wave instrument, and the deviation percentage of the material strength from the standard value is calculated as the data of the material strength abnormality of the component. The acquisition of the modal feature integrity index relies on precise modal testing. By arranging acceleration sensors on each floor of the pavilion, applying environmental excitation or artificial excitation, collecting the structural vibration response signals, generating modal shape diagrams and frequency response curves, and then extracting parameters such as the participation coefficient of the main vibration mode and the node displacement amplitude, calculating the stiffness continuity coefficient and the frequency domain distribution index, and finally weighted fusion to obtain the modal feature integrity index.

[0050] The determination of the dynamic stability evaluation value needs to combine the seismic wave input and the structural dynamic response analysis. Taking this pavilion as an example, when inputting the typical seismic wave acceleration time history data that meets the local fortification intensity, such as the El Centro wave, the response of the structure under this seismic wave is calculated through a finite element model, extracting the energy spectrum intensity and the spectral characteristic parameters, constructing a dynamic response prediction model, and outputting the structural failure probability in the future time. At the same time, calculate the energy ratio of the main frequency component and the damping component in the spectral characteristic parameters to obtain the spectral stability factor, and the two are linearly combined to form the dynamic stability evaluation value.

[0051] The collaborative analysis needs to consider the coupling effects of multiple parameters. For example, when the material strength abnormality is relatively high, even if the modal feature integrity index and the dynamic stability evaluation value are at a good level, the strength influence compensation value will pull down the seismic performance fusion index, thus triggering the structural reinforcement signal. On the contrary, if the material strength abnormality is relatively low, but the modal feature integrity index shows uneven structural stiffness distribution, the dynamic stability evaluation value will also be affected, and it may be necessary to carry out targeted component repair or local reinforcement.

[0052] In actual operation, a data calibration mechanism also needs to be established. Regularly calibrate the detection equipment, such as the sensitivity calibration of sensors and the parameter optimization of stress wave instruments, to ensure the reliability of the collected data. For ancient buildings with complex structures, such as pavilions with diagonal braces or mezzanines, it is necessary to refine the layout of the detection points to avoid data omission. At the same time, combined with historical monitoring data, analyze the change trends of various parameters, such as the annual change rate of the material strength abnormality and the stability of the modal feature integrity index, to provide a basis for long-term maintenance.

[0053] Taking this Qing Dynasty wooden structure pavilion as an example, if subsequent inspections find that the looseness of the bucket arch tenon-mortise joints increases, resulting in an increase in the characteristic value of connection defects, and further affecting the decline of the modal characteristic integrity index, at this time, the collaborative analysis needs to retrieve relevant data again, update the strength influence compensation value, recalculate the fusion index, and determine whether it is necessary to adjust the reinforcement or repair strategy. This dynamic collaborative analysis mechanism can reflect the changes in the seismic performance of ancient buildings in real time and provide scientific support for protection decisions.

[0054] Example 5: During the process of matching the seismic optimization strategy, it is necessary to accurately implement structural reinforcement or component repair operations according to the signals generated by the system, and form a closed-loop optimization in combination with the damage coupling analysis and the model iteration mechanism. Taking a certain Ming Dynasty wooden structure hall as an example, when the multi-source fusion judgment module generates a structural reinforcement signal, the system automatically triggers an overall strengthening instruction. At this time, it is necessary to dynamically adjust the reinforcement position and section enhancement parameters of the structural support system according to the instruction. For example, if the analysis finds that the gable columns of this hall are inclined due to foundation settlement, and the modal characteristic integrity index shows that its stiffness continuity coefficient is low, it is necessary to add steel supports around the gable columns. The section size of the support is determined according to the bearing capacity requirements of the column. For example, a steel section of 100mm×100mm is used and connected to the column by bolts. At the same time, the layout spacing of the supports is adjusted to ensure uniform stress of the structure after reinforcement.

[0055] If a component repair signal is captured, such as the looseness of the bucket arch tenon-mortise joints in this hall exceeds the preset threshold and the characteristic value of the connection defect is high, then a node repair instruction is triggered. At this time, it is necessary to optimize the repair range and stiffness recovery coefficient of the tenon-mortise connection system. For example, for the loose tenon, epoxy resin mortar is used to fill the tenon-mortise gap. The filling thickness is determined according to the looseness. If the gap is 5mm, the filling layer thickness is controlled at 3-4mm to ensure the tight combination of the tenon and the mortise. At the same time, the surface of the bucket arch components in the repair range is treated, the decayed or weathered layer is removed, and an anti-corrosion and insect-proof coating is applied to improve the durability of the components. The stiffness recovery coefficient needs to be determined through on-site tests. For example, the hammering method is used to measure the frequency change of the components before and after repair to evaluate the stiffness recovery effect.

[0056] The system also includes a damage coupling analysis module for monitoring the evolutionary correlation between historical damage and structural response. Taking this hall as an example, the historical damage expansion rate and the dynamic response growth rate are collected through strain sensors. If the crack expansion rate at the eaves corner is monitored to be 0.2 mm / year and the dynamic response growth rate is 0.15 mm / year, calculate the rate difference between the two and take the absolute value, and the damage expansion rate difference value is 0.05 mm / year. At the same time, extract the stress distribution data of the damage area and the structural response concentration area, and statistically calculate the ratio of the maximum stress gradient to the average gradient. If the maximum stress gradient is 15 MPa / m and the average gradient is 10 MPa / m, the stress redistribution coefficient is 1.5. Perform a weighted sum of the damage expansion rate difference value and the stress redistribution coefficient to generate a damage coupling evaluation value, which will be fed back to the multi-source fusion decision-making module to perform a secondary correction on the seismic performance fusion index. For example, on the basis of the original fusion index of 0.6, it is adjusted to 0.58 according to the weighting coefficient, so as to more accurately reflect the actual seismic state of the structure.

[0057] The model iteration and update module needs to adjust the mesh division accuracy of the BIM model in real time according to the generated structural reinforcement parameters and node connection repair parameters. For example, when the structural reinforcement parameter involves the cross-section enhancement adjustment of the gable column, synchronously increase the mesh density of this column component, refine the original mesh size from 50 mm × 50 mm to 25 mm × 25 mm to more accurately simulate the stress state after reinforcement. If the node connection repair parameter involves the stiffness recovery optimization of the bucket arch tenon and mortise, increase the number of elements in the tenon and mortise connection area, and increase the element division of the connection area from 100 to 200 to ensure that the stress changes at the connection part can be accurately captured during finite element analysis. The updated parameters need to be input into the building parameter acquisition module to restart the seismic analysis process, such as performing a modal characteristic analysis again to verify whether the structural stiffness continuity coefficient after reinforcement is improved, or re-simulating the seismic response to check whether the dynamic stability evaluation value is improved.

[0058] In actual operation, the trigger of the structural reinforcement signal may be due to multiple parameter anomalies. For example, the material strength anomaly of this hall shows that the compressive strength of the beam wood has decreased by 20%, and the comprehensive historical damage index has reached 0.7 due to foundation settlement, both of which exceed the preset threshold. At this time, the overall reinforcement instruction needs to consider both the reinforcement of the beam and the lifting of the foundation. The beam can be reinforced by wrapping it with carbon fiber cloth, and the number of wrapping layers is determined according to the strength requirements. For example, two layers of carbon fiber cloth, each layer with a thickness of 0.111 mm. When wrapping, it should be noted that the lap length is not less than 100 mm. The foundation is lifted by jacking in stages, and the jacking amount each time is controlled at 1-2 mm to avoid additional stress on the structure.

[0059] The processing of component repair signals needs to combine traditional techniques with modern technologies. For example, when repairing the cracks in the wooden columns of this hall, first use the traditional inlaying technique to remove the rotten wood in the cracks, inlay dry wood according to the shape of the cracks, and then use modern structural adhesives for bonding. The selection of adhesives needs to meet the requirements of ancient building protection. For example, when choosing epoxy resin adhesives, parameters such as viscosity and curing time need to meet the construction conditions. After repair, the components need to be monitored regularly. For example, measure the crack expansion every quarter to ensure the durability of the repair effect.

[0060] The real-time monitoring of damage coupling analysis relies on the reasonable layout of the sensor network. At key parts of this hall, such as eaves columns, beam frame joints, and brackets, strain sensors, displacement sensors, and acceleration sensors are arranged. The sampling frequency of the sensors is determined according to the natural vibration frequency of the structure. For example, when the natural vibration frequency is 10 Hz, the sampling frequency is set to 100 Hz to ensure that the dynamic response of the structure can be captured. The data acquisition system needs to have a wireless transmission function to transmit real-time data to the central server for remote monitoring and analysis.

[0061] During the process of model iteration and update, the adjustment of the BIM model needs to be synchronized with the actual on-site construction. For example, when the installation of the steel supports for the gable columns is completed on-site, the position, size, and connection method of the supports need to be updated in the BIM model to ensure that the model is consistent with the actual structure. When the updated model is analyzed for seismic resistance again, the changes in various parameters before and after reinforcement need to be compared and analyzed. For example, the modal characteristic integrity index increases from 0.55 to 0.70, and the dynamic stability evaluation value increases from 0.60 to 0.68. Although specific data verification is not involved, the optimization effect can be judged through the relative change trend of the parameters, providing a reference for the seismic reinforcement of similar ancient buildings in the future.

[0062] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device.

[0063] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made therein without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An ancient building seismic performance analysis and evaluation system based on BIM modeling, characterized in that Including: A building parameter acquisition module, which is used to dynamically collect the component material properties, structural connection status and historical damage parameters of the target ancient building, obtain the structural state parameter set of the ancient building, identify and analyze the weak structural links based on the structural state parameter set of the ancient building, generate seismic anomaly signals, trigger cooperative evaluation instructions according to the generated seismic anomaly signals, and execute a modal feature analysis module and a seismic response simulation module according to the triggered cooperative evaluation instructions; A modal feature analysis module, which is used to extract the vibration modal feature parameters of the overall structure of the target ancient building, quantitatively evaluate the structural stiffness distribution state, and obtain the modal feature integrity index; A seismic response simulation module, which is used to extract the seismic wave energy distribution parameters of the target ancient building, predict the trend of the structural dynamic response state, and obtain the dynamic stability evaluation value; A multi-source fusion determination module, which is used to receive the modal feature integrity index and the dynamic stability evaluation value, conduct cooperative analysis on the seismic performance of the ancient building, and generate a structural reinforcement signal and a component repair signal; An optimization parameter generation module, which is used to receive the structural reinforcement signal and the component repair signal, match the seismic optimization strategy, and generate the structural reinforcement parameters and the node connection repair parameters.

2. The ancient building seismic performance analysis and evaluation system based on BIM modeling according to claim 1, wherein The identification and analysis of the weak structural links include: By dynamically collecting the component material property parameters of the target ancient building, calculating the deviation percentage from the standard strength, and marking it as the material strength anomaly degree; Extracting the mortise and tenon looseness and crack expansion degree in the structural connection state parameters of the target ancient building, calculating the geometric synthesis vector modulus of the two, and marking it as the connection defect characteristic value; Collecting the settlement cumulative value and the inclination deformation amount in the historical damage parameters, performing normalized weighted calculation, and obtaining the historical damage comprehensive index; Comparing the material strength anomaly degree, the connection defect characteristic value and the historical damage comprehensive index with the preset thresholds respectively, and generating a seismic anomaly signal when any parameter exceeds the corresponding threshold.

3. The ancient building seismic performance analysis and evaluation system based on BIM modeling according to claim 1, characterized in that The quantitative evaluation of the structural stiffness distribution state includes: By applying a pulse excitation and receiving the structural vibration response signal, generating a modal vibration mode diagram and a frequency response curve; Extracting the main vibration mode participation coefficient and the node displacement amplitude from the modal vibration mode diagram, calculating the product of the two and taking the reciprocal to obtain the stiffness continuity coefficient; Extracting the low-frequency band energy ratio and the spectral density from the frequency response curve, calculating the arithmetic mean of the two, and marking it as the frequency domain distribution index; Performing weighted fusion on the stiffness continuity coefficient and the frequency domain distribution index to obtain the modal feature integrity index.

4. The ancient building seismic performance analysis and evaluation system based on BIM modeling according to claim 1, characterized in that, The trend prediction of the structural dynamic response state includes: Real-time input of the seismic wave acceleration time history data, and extracting the energy spectrum intensity and the spectral characteristic parameters; Constructing a dynamic response prediction model, inputting the energy spectrum intensity into the model for finite element iterative processing, and outputting the structural failure probability in the future time interval; Extracting the main frequency component and the damping component in the spectral characteristic parameters, calculating the energy ratio of the two to obtain the spectral stability factor; Performing a linear combination of the structural failure probability and the spectral stability factor to obtain the dynamic stability evaluation value.

5. The ancient building seismic performance analysis and evaluation system based on BIM modeling according to claim 1, characterized in that, The cooperative analysis of the seismic performance of the ancient building includes: Retrieve the abnormal strength data of the materials, set its correction coefficient, and obtain the strength influence compensation value through calculation and processing; Normalize the values of the modal feature integrity index, dynamic stability evaluation value, and strength influence compensation value to generate the seismic performance fusion index; Set the seismic performance determination threshold. If the fusion index is lower than the threshold, generate a structure reinforcement signal; if it is higher than the threshold, generate a component repair signal.

6. The ancient building seismic performance analysis and evaluation system based on BIM modeling according to claim 1, characterized in that, The seismic optimization strategy matching includes: If a structure reinforcement signal is captured, trigger the overall reinforcement instruction, dynamically adjust the reinforcement position and cross-section enhancement parameters of the structure support system according to the instruction, and generate the structure reinforcement parameters; If a component repair signal is captured, trigger the joint repair instruction, optimize the repair range and stiffness recovery coefficient of the mortise and tenon connection system according to the instruction, and generate the joint connection repair parameters.

7. The ancient building seismic performance analysis and evaluation system based on BIM modeling according to claim 1, characterized in that It also includes: A damage coupling analysis module for monitoring the evolutionary correlation between historical damage and structural response, extracting the damage propagation rate and stress redistribution coefficient, and generating a damage coupling evaluation value; The multi-source fusion determination module further corrects the seismic performance fusion index by combining the damage coupling evaluation value.

8. The ancient building seismic performance analysis and evaluation system based on BIM modeling according to claim 7, characterized in that The monitoring of the evolutionary correlation between historical damage and structural response includes: Collect the historical damage propagation rate and dynamic response growth rate through strain sensors, calculate the rate difference between the two and take the absolute value, which is marked as the damage propagation rate difference value; Extract the stress distribution data of the damaged area and the structural response concentration area, and statistically calculate the ratio of the maximum stress gradient to the average gradient, which is marked as the stress redistribution coefficient; Perform weighted summation on the damage propagation rate difference value and the stress redistribution coefficient to generate the damage coupling evaluation value.

9. The ancient building seismic performance analysis and evaluation system based on BIM modeling according to claim 1, characterized in that, It also includes: A model iterative update module for real-time adjusting the mesh division accuracy of the BIM model according to the generated structure reinforcement parameters and joint connection repair parameters, and feeding back the optimization result to the building parameter acquisition module to form a closed-loop analysis link.

10. The ancient building seismic performance analysis and evaluation system based on BIM modeling according to claim 9, characterized in that, The specific execution process of the model iterative update module includes: If the structure reinforcement parameters involve cross-section enhancement adjustment, synchronously increase the mesh density of key components; If the joint connection repair parameters involve stiffness recovery optimization, synchronously increase the number of elements in the mortise and tenon connection area; Input the updated parameters into the building parameter acquisition module and restart the seismic analysis process.

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