Seismic performance analysis and evaluation system of ancient buildings based on BIM modeling

Abstract

The present invention relates to the field of building information technology and discloses a system for analyzing and evaluating the seismic performance of ancient buildings based on BIM modeling. The system includes a building parameter acquisition module for dynamically collecting component material properties, structural connection status, and historical damage parameters, identifying structural weaknesses, and triggering collaborative evaluation instructions; a modal characteristic analysis module and a seismic response simulation module for extracting vibration modal characteristic parameters and seismic wave energy distribution parameters, respectively, to obtain a modal characteristic integrity index and a dynamic stability assessment value; a multi-source fusion judgment module that integrates these indices to generate structural reinforcement or component repair signals; an optimization parameter generation module that matches seismic optimization strategies to generate structural reinforcement and node connection repair parameters; and a damage coupling analysis module and a model iterative update module for monitoring historical damage evolution and closed-loop updating of the BIM model. This system enables accurate evaluation and dynamic optimization of the seismic performance of ancient buildings.

Description

Technical Field

[0001] The present invention relates to the field of building information technology, and in particular to a system for analyzing and evaluating the seismic performance of ancient buildings based on BIM modeling. Background Art

[0002] As an important carrier of historical and cultural heritage, the assessment and protection of the seismic performance of ancient buildings has always been a key challenge in the field of construction engineering. Traditional methods for seismic analysis of ancient buildings have many limitations: the collection of material properties, structural connection status, and historical damage parameters of ancient building components often relies on manual inspection, making dynamic real-time monitoring difficult. In addition, the lack of comprehensiveness and accuracy in data collection makes it impossible to accurately identify structural weaknesses. For example, mortise and tenon joints, a typical structural feature of ancient buildings, have a significant impact on the overall seismic performance due to changes in their looseness and crack propagation. However, traditional methods make it difficult to quantify and dynamically track these parameters.

[0003] Existing technologies lack the ability to integrate and analyze multi-source data during seismic performance assessment. Modal characteristic analysis and seismic response simulation are typically performed independently, failing to collaboratively assess the structural stiffness distribution and dynamic response trends, resulting in low integrity and reliability of the assessment results. Furthermore, insufficient research has been conducted on the evolutionary correlation between historical damage and structural response, failing to fully consider the impact of historical damage parameters such as accumulated settlement and tilt deformation on current seismic performance. This makes the assessment model unable to accurately reflect the actual seismic performance of ancient buildings.

[0004] Traditional seismic assessment systems lack a deep integration with BIM technology, mostly remaining at the model-building level. They lack a closed-loop mechanism for iteratively updating BIM models based on assessment results. Once signals for structural reinforcement or component repair are generated, the meshing accuracy of the BIM model cannot be adjusted in real time. This makes it difficult to effectively verify and provide feedback on the effectiveness of optimization strategies implemented through the model, limiting the dynamic optimization capabilities of seismic analysis.

[0005] With the widespread adoption of BIM technology in the construction sector, integrating it with the seismic performance analysis of historic buildings—realizing intelligent processes throughout the entire process, from data collection and multi-source analysis to simulation and prediction, and optimization feedback—has become a pressing technical challenge. Existing systems lack specialized analysis modules for the unique structural features of historic buildings (such as mortise and tenon joints) and historical damage characteristics, making them unable to meet the high-precision requirements of seismic protection for historic buildings. Summary of the Invention

[0006] The purpose of the present invention is to provide a system for analyzing and evaluating the seismic performance of ancient buildings based on BIM modeling to solve the problems raised in the above background technology.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a system for analyzing and evaluating the seismic performance of ancient buildings based on BIM modeling, the system comprising:

[0008] The building parameter acquisition module is used to dynamically collect the component material properties, structural connection status and historical damage parameters of the target ancient building, obtain the ancient building structural status parameter set, identify and analyze the structural weak links based on the ancient building structural status parameter set, generate seismic abnormality signals, trigger the collaborative assessment instructions based on the generated seismic abnormality signals, and execute the modal characteristic analysis module and the earthquake response simulation module based on the triggered collaborative assessment instructions;

[0009] The modal characteristic analysis module is used to extract the vibration modal characteristic parameters of the overall structure of the target ancient building, quantitatively evaluate the structural stiffness distribution state, and obtain the modal characteristic integrity index;

[0010] The earthquake response simulation module 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 assessment value;

[0011] The multi-source fusion judgment module is used to receive the modal characteristic integrity index and dynamic stability assessment value, conduct collaborative analysis on the seismic performance of ancient buildings, and generate structural reinforcement signals and component repair signals;

[0012] The optimization parameter generation module is used to receive structural reinforcement signals and component repair signals, match seismic optimization strategies, and generate structural reinforcement parameters and node connection repair parameters.

[0013] Preferably, the identification and analysis of structural weaknesses includes:

[0014] By dynamically collecting the material property parameters of the target ancient building components, the deviation percentage from the standard strength is calculated and marked as the material strength anomaly;

[0015] Extract the looseness of the mortise and tenon joints and the crack expansion degree from the connection state parameters of the target ancient building structure, calculate the geometric synthetic vector modulus of the two, and mark it as the connection defect characteristic value;

[0016] The accumulated settlement value and tilt deformation in the historical damage parameters are collected and normalized and weighted to obtain the comprehensive historical damage index.

[0017] The material strength anomaly, connection defect characteristic value and historical damage comprehensive index are compared with the preset thresholds respectively. When any parameter exceeds the corresponding threshold, a seismic anomaly signal is generated.

[0018] Preferably, the quantitative evaluation of the structural stiffness distribution state includes:

[0019] By applying pulse excitation and receiving the structural vibration response signal, the modal vibration shape diagram and frequency response curve are generated;

[0020] Extract the main vibration mode participation coefficient and node displacement amplitude from the modal vibration shape diagram, calculate the product of the two and take the inverse to obtain the stiffness continuity coefficient;

[0021] Extract the low-frequency energy proportion and spectrum density from the frequency response curve, calculate the arithmetic mean of the two, and mark it as the frequency domain distribution index;

[0022] The modal characteristic integrity index is obtained by weighted fusion of the stiffness continuity coefficient and the frequency domain distribution index.

[0023] Preferably, the trend prediction of the structural dynamic response state includes:

[0024] Input seismic wave acceleration time history data in real time to extract energy spectrum intensity and spectrum characteristic parameters;

[0025] Construct a dynamic response prediction model, input the energy spectrum intensity into the model for finite element iteration processing, and output the structural failure probability within the future time interval;

[0026] Extract the main frequency component and damping component from the spectrum characteristic parameters, calculate the energy ratio between the two and obtain the spectrum stability factor;

[0027] The structural failure probability is linearly combined with the spectral stability factor to obtain the dynamic stability evaluation value.

[0028] Preferably, the collaborative analysis of the seismic performance of the ancient buildings includes:

[0029] Retrieve material strength abnormality data, set its correction coefficient, and obtain strength impact compensation value through calculation and processing;

[0030] The modal characteristic integrity index, dynamic stability evaluation value and strength impact compensation value are normalized and calculated to generate the seismic performance fusion index;

[0031] A threshold for seismic performance judgment is set. 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.

[0032] Preferably, the matching of seismic optimization strategies includes:

[0033] If a structural reinforcement signal is captured, the overall reinforcement instruction is triggered, and the reinforcement position and cross-section reinforcement parameters of the structural support system are dynamically adjusted according to the instruction to generate structural reinforcement parameters;

[0034] If a component repair signal is captured, the node repair instruction is triggered. According to the instruction, the repair range and stiffness recovery coefficient of the mortise and tenon connection system are optimized and configured to generate the node connection repair parameters.

[0035] Preferably, the system further comprises:

[0036] The damage coupling analysis module is used to monitor the evolutionary correlation between historical damage and structural response, extract the damage growth rate and stress redistribution coefficient, and generate damage coupling assessment values;

[0037] The multi-source fusion determination module further combines the damage coupling assessment value to perform a secondary correction on the seismic performance fusion index.

[0038] Preferably, monitoring the evolutionary correlation between historical damage and structural response includes:

[0039] The historical damage growth rate and dynamic response growth rate are collected through strain sensors, and the difference between the two rates is calculated and the absolute value is taken, which is marked as the damage growth rate difference value;

[0040] Extract stress distribution data of the damaged area and the concentrated area of ​​structural response, calculate the ratio of the maximum stress gradient to the average gradient, and mark it as the stress redistribution coefficient;

[0041] The damage coupling assessment value is generated by weighted summing the damage growth rate difference value and the stress redistribution coefficient.

[0042] Preferably, the system of the present invention further comprises:

[0043] The model iteration and update module is used to adjust the meshing accuracy of the BIM model in real time based on the generated structural reinforcement parameters and node connection repair parameters, and feed back the optimization results to the building parameter acquisition module to form a closed-loop analysis link.

[0044] Preferably, the specific execution process of the model iterative update module includes:

[0045] If the structural reinforcement parameters involve cross-section enhancement adjustments, the mesh density of key components should be increased simultaneously;

[0046] If the node connection repair parameters involve stiffness recovery optimization, the number of elements in the mortise and tenon connection area will be increased simultaneously;

[0047] Input the updated parameters into the building parameter acquisition module and restart the seismic analysis process.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] The BIM-based seismic performance analysis and assessment system for ancient buildings provided by this invention achieves comprehensive and accurate assessment and optimization of their seismic performance through the collaborative work of multiple modules. The building parameter acquisition module dynamically collects component material properties, structural connection status, and historical damage parameters to form a structural state parameter set. By calculating and comparing thresholds for material strength anomalies, connection defect characteristic values, and a comprehensive historical damage index, it accurately identifies structural weaknesses and generates seismic anomaly signals, providing a reliable basis for subsequent analysis. This effectively addresses the issues of incomplete data and poor real-time performance associated with traditional manual inspections.

[0050] The modal characteristic analysis module generates modal vibration shape diagrams and frequency response curves by applying pulse excitation, extracts the stiffness continuity coefficient and frequency domain distribution index, and performs weighted fusion to obtain the modal characteristic integrity index, thereby realizing a quantitative assessment of the structural stiffness distribution state, making up for the shortcomings of traditional methods in stiffness assessment and making the assessment results more scientific.

[0051] The earthquake response simulation module inputs seismic wave acceleration time history data in real time, constructs a dynamic response prediction model to output the structural failure probability, and combines the spectrum stability factor to obtain the dynamic stability assessment value, realizing the trend prediction of the structural dynamic response state and providing dynamic prediction capabilities for seismic performance analysis.

[0052] The multi-source fusion judgment module receives the modal characteristic integrity index, dynamic stability assessment value and strength impact compensation value, generates a seismic performance fusion index and compares it with the threshold, accurately generates structural reinforcement or component repair signals, realizes the collaborative analysis of multi-source data, and improves the comprehensiveness and accuracy of the assessment.

[0053] The optimization parameter generation module triggers corresponding instructions according to different signals, dynamically adjusts the parameters of the structural support system or mortise and tenon connection system, generates structural reinforcement parameters and node connection repair parameters, making the optimization strategy more targeted and operational.

[0054] The damage coupling analysis module monitors the evolutionary correlation between historical damage and structural response, extracts the difference in damage growth rate and stress redistribution coefficient to generate a damage coupling assessment value, and performs a secondary correction on the seismic performance fusion index, fully considering the impact of historical damage on current seismic performance and further improving the assessment accuracy.

[0055] The model iteration and update module adjusts the meshing accuracy of the BIM model in real time according to the optimization parameters, improves the modeling accuracy of key components and mortise and tenon connection areas, and feeds back the optimization results to the building parameter acquisition module to form a closed-loop analysis link, realizing a dynamic cycle of the entire process from evaluation to optimization to verification, ensuring the continuous optimization and accuracy of seismic analysis.

[0056] The entire system is based on BIM modeling technology, organically integrating various aspects of the seismic performance analysis of ancient buildings. Through multi-parameter dynamic acquisition, multi-source data fusion, damage evolution analysis and model closed-loop iteration, it significantly improves the accuracy and efficiency of the seismic performance evaluation of ancient buildings, and provides a scientific and systematic technical solution for the seismic protection of ancient buildings, which has important engineering application value and social significance. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is a working principle diagram of the ancient building seismic performance analysis and evaluation system based on BIM modeling according to the present invention;

[0058] Figure 2 Flowchart for quantitative assessment of structural stiffness distribution state;

[0059] Figure 3 Flowchart for structural dynamic response state trend prediction;

[0060] Figure 4 Flowchart for seismic optimization strategy matching. DETAILED DESCRIPTION

[0061] 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.

[0062] 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:

[0063] 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.

[0064] 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.

[0065] 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.

[0066] 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.

[0067] 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.

[0068] Example 1:

[0069] When identifying and analyzing structural weaknesses, a rigorous and systematic process must be followed. Dynamic collection of material property parameters of target ancient building components is carried out. The material property parameters of the components referred to here cover several key aspects, such as the compressive strength, tensile strength, and elastic modulus of wood. During the collection process, professional testing equipment and technology need to be used to ensure that the acquired data is accurate and reliable. For example, for the detection of wood strength, non-destructive testing methods such as stress wave detection can be used to evaluate the strength performance of wood by analyzing the propagation speed and waveform of stress waves in wood. After collecting these parameters, 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. The setting of the standard strength needs to refer to the relevant ancient building material standards and the material performance data of this type of ancient building under normal conditions.

[0070] Extract the mortise and tenon looseness and crack expansion from the connection status parameters of the target ancient building structure. Mortise and tenon connection is a very important connection method in ancient building structures, and the size of its looseness directly affects the stability of the structure. The detection of mortise and tenon looseness can be achieved by measuring the change in the gap between the tenon and the mortise, and using a high-precision displacement sensor for real-time monitoring. As for the crack expansion, it is necessary to regularly observe 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 and crack expansion data, it is necessary to calculate the geometric composite vector modulus of the two. It should be clarified here that the calculation of the geometric composite vector modulus is based on the principle of vector synthesis. The mortise and tenon looseness and crack expansion are taken as the two components of the vector, and its modulus is obtained through vector operation. This modulus is marked as the connection defect characteristic value.

[0071] Collect the cumulative settlement value and tilt deformation value from the historical damage parameters. To obtain the cumulative settlement value, it is necessary to use leveling equipment to set up observation points at key locations of the ancient building, conduct leveling measurements regularly, record the settlement data of each observation point, and accumulate the cumulative settlement value. The tilt deformation value can be obtained by measuring the tilt angle and direction of the main structure of the ancient building through measuring equipment such as total stations. After collecting the cumulative settlement value and tilt deformation value, these two parameters need to be normalized and weighted. The normalization process is to convert parameters of different dimensions into comparable values. The weighted calculation is to assign different weight coefficients according to the importance of these two parameters in identifying weak links in the structure, and obtain the comprehensive index of historical damage through weighted calculation.

[0072] The material strength anomaly, connection defect characteristic value, and historical damage comprehensive index are compared against preset thresholds. These thresholds are determined based on the type, age, structural form, and relevant standards of the ancient building. When any parameter exceeds the corresponding threshold, a seismic anomaly signal is generated. For example, if the material strength anomaly exceeds the preset threshold, it indicates a significant anomaly in the component material's strength, potentially affecting the structure's seismic performance. In this case, a seismic anomaly signal is generated so that appropriate measures can be taken promptly. Throughout the entire process, data collection accuracy and calculation accuracy must be strictly controlled at every stage to ensure reliable identification and analysis of structural weaknesses, providing a strong basis for subsequent seismic performance analysis and assessment. However, it should be noted that in actual operations, various complex situations may arise, requiring appropriate adjustments and optimization of the detection methods and calculation processes to ensure the effectiveness and accuracy of the identification and analysis. Furthermore, the collected data must be regularly reviewed and verified to ensure its timeliness and reliability, thereby better serving the seismic performance analysis and assessment of ancient buildings.

[0073] Example 2:

[0074] When conducting a quantitative assessment of the structural stiffness distribution state, a systematic operating process must be followed to ensure the accuracy and reliability of the assessment results. Pulse excitation is applied to the target ancient building structure. The application of this excitation requires the selection of an appropriate position and strength. Usually, it is performed at key components or nodes based on the structural characteristics of the ancient building to simulate the stress state of the structure under actual vibration conditions. At the same time, the structural vibration response signal is received by sensors arranged at key locations of the structure. These sensors must have high sensitivity and precise acquisition capabilities to capture subtle changes in the structural vibration process in real time. Based on the received response signal, professional data analysis software is used to generate modal vibration shape diagrams and frequency response curves. The modal vibration shape diagram can intuitively display the deformation form of the structure during the vibration process, while the frequency response curve reflects the response characteristics of the structure at different frequencies.

[0075] The main vibration mode participation coefficient and the node displacement amplitude are extracted from the modal vibration shape diagram. The main vibration mode participation coefficient characterizes the contribution of each order vibration mode to the overall vibration of the structure. This parameter can be obtained by analyzing and calculating the modal vibration shape diagram. The node displacement amplitude refers to the displacement of each node of the structure during the vibration process. It is necessary to select representative nodes in the modal vibration shape diagram for measurement and recording. After obtaining these two parameters, calculate the product of the two and take the inverse to obtain the stiffness continuity coefficient. The calculation process here needs to strictly follow the mathematical operation rules 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 the coefficient, the more uniform the distribution of the structural stiffness. Otherwise, it means that there is a sudden change or discontinuity in the stiffness distribution.

[0076] The low-frequency energy percentage and spectrum density are extracted from the frequency response curve. The low-frequency energy percentage refers to the ratio of the energy contained in the low-frequency band (the specific frequency range is usually determined based on the structural characteristics of the ancient building) to the total energy in the frequency response curve. This parameter is obtained by integrating the frequency response curve and performing energy analysis. The spectrum density describes the density of the spectrum distribution on the frequency axis and can be calculated by counting the number and distribution of peaks in the spectrum. The arithmetic mean of the two is calculated and labeled as the frequency domain distribution index. The frequency domain distribution index can reflect the energy distribution characteristics of the structure within the frequency domain and is of great significance for evaluating the dynamic characteristics of the structure.

[0077] The stiffness continuity coefficient and the frequency domain distribution index are weighted and fused to obtain the modal characteristic integrity index. During the weighted fusion process, it is necessary to reasonably determine the weight coefficient based on the importance of these two parameters to the evaluation of the structural stiffness distribution state. The determination of the weight coefficient usually needs to be combined with the characteristics of the ancient building structure, engineering experience and related 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 characteristic integrity index, the more complete the modal characteristics of the structure and the better the stiffness distribution state. Conversely, it means that there are certain problems with the structural stiffness distribution, which may affect its seismic performance.

[0078] Throughout the entire quantitative assessment process, strict control over operational standards and data accuracy is crucial at every stage. For example, the application force and location of the pulse excitation require detailed calculation and planning to avoid damage to the ancient building structure. Sensor placement must be rational to ensure comprehensive and accurate reception of the structural vibration response signals. Data extraction and calculation must utilize scientific methods and tools to mitigate the influence of human error. Furthermore, the assessment results require multiple verification and comparisons, combining historical data with the actual condition of the ancient building to comprehensively assess whether the structural stiffness distribution meets the requirements. If any anomalies are detected in the assessment results, the entire assessment process must be promptly reviewed and corrected to ensure that the resulting modal integrity index accurately reflects the structural stiffness distribution, providing a reliable basis for seismic performance analysis and assessment of the ancient building. Furthermore, in practical applications, the assessment process and parameters must be appropriately adjusted and optimized based on the characteristics and requirements of each ancient building to enhance the applicability and effectiveness of the assessment.

[0079] Example 3:

[0080] When predicting the trend of the structural dynamic response state, it is necessary to use rigorous processes and scientific methods to analyze the response of ancient buildings under earthquakes. Real-time input of seismic wave acceleration time history data is required. This data must be obtained through professional seismic monitoring equipment or authoritative seismic databases, covering seismic wave samples of different magnitudes, epicenter distances, and spectral characteristics to simulate a variety of earthquake conditions. After the data is input, the energy spectrum intensity and spectrum characteristic parameters are extracted with the help of signal processing technology. The energy spectrum intensity reflects the distribution of seismic wave energy in different frequency bands, which can be obtained by performing spectral analysis on the acceleration time history and calculating the energy accumulation value of each frequency band; the spectrum characteristic parameters include the main frequency component, the damping component, etc. The main frequency component can be determined by identifying the frequency corresponding to the spectrum peak, and the damping component needs to be comprehensively evaluated in combination with the structural material properties and historical vibration test data.

[0081] A dynamic response prediction model is constructed based on finite element analysis. A refined structural calculation model must be established based on 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. The extracted energy spectrum intensity is input into the model for finite element iteration. During the iteration process, factors such as material nonlinearity, geometric nonlinearity, and contact nonlinearity must be considered. The dynamic equation of the structure under the action of seismic waves is solved using a step-by-step integration method, and the probability of structural failure within a future time interval is output. The calculation of the failure probability requires the definition of structural failure criteria, such as component stress exceeding the yield strength and node displacement exceeding the allowable limit. The failure probability of the entire structure is determined by statistically analyzing the percentage of units that meet the failure criteria.

[0082] The dominant frequency component and damping component of the spectral characteristic parameters are extracted, and their energy ratio is calculated to derive the spectral stability factor. The dominant frequency component reflects the frequency at which the main energy of the seismic wave is concentrated. If it is close to the natural frequency of the structure, it is likely to induce resonance. The damping component reflects the structure's ability to dissipate vibration energy. The energy ratio calculation requires first normalizing the energies corresponding to the dominant frequency component and the damping component. This factor is then derived from the numerical ratio of the two. This factor can be used to measure the stability of the seismic wave spectral characteristics. The closer the ratio is to 1, the more stable the spectral characteristics are and the more predictable the structural dynamic response is.

[0083] The dynamic stability assessment value is obtained by linearly combining the structural failure probability and the spectral stability factor. The linear combination process requires determining the weight coefficients of the two. The weight coefficients must be determined based on the historical building's importance, structural form, and seismic fortification objectives. These weight coefficients can be determined through expert evaluation or statistical analysis of historical earthquake damage data. For example, for historical buildings in high-intensity fortification areas, the weight of the structural failure probability can be appropriately increased to highlight the focus on structural safety. The dynamic stability assessment value comprehensively reflects the structural failure risk under the action of seismic waves and the impact of spectral characteristics on the response, providing a quantitative basis for seismic performance assessment.

[0084] Throughout the trend prediction process, accurate data input is fundamental. The sampling frequency, duration, and amplitude of seismic acceleration time history data must meet regulatory requirements to avoid biased prediction results due to data errors. Model construction must fully consider the structural complexity of ancient buildings, such as the mechanical simplification of special structures like brackets and caissons. Model accuracy should be verified through on-site dynamic testing when necessary. Finite element iterative calculations require appropriate control of the time step and convergence accuracy to ensure both computational efficiency and reliability. Furthermore, comparative analysis of prediction results under different seismic wave conditions is necessary to identify the dynamic response characteristics of the structure under the most unfavorable conditions, providing a targeted basis for subsequent seismic optimization. For complex ancient building complexes, a multiscale modeling approach can be considered, embedding refined models of key nodes within the macrostructural model to balance computational efficiency and accuracy. Furthermore, a verification mechanism for prediction results should be established, regularly comparing predicted data with actual earthquake monitoring data or shaking table test results. Model parameters and prediction methods should be continuously optimized to enhance the accuracy and reliability of trend predictions.

[0085] Example 4:

[0086] When conducting a collaborative analysis of the seismic performance of ancient buildings, a comprehensive assessment must be achieved through multi-dimensional data fusion and quantitative processing. Taking a Qing Dynasty wooden pavilion as an example, the material strength anomaly data of the ancient building was retrieved. This data comes from the wood strength test of major components such as columns and beams by the building parameter acquisition module. For example, the test found that the compressive strength of the wood of its eaves columns was 15% lower than the standard value. This value is the material strength anomaly. Then, a correction coefficient is set. The determination of the correction coefficient needs to take into account the degree of material aging, environmental corrosion factors, etc. By combining expert experience with historical data, a correction coefficient of 0.8 is set for the material strength anomaly of the eaves column. After calculation and processing, the strength impact compensation value is obtained. That is, through the calculation of the material strength anomaly and the correction coefficient, the compensation amount for the impact on the seismic performance of the structure is obtained.

[0087] The modal integrity index obtained from the modal characteristic analysis module, the dynamic stability assessment value obtained from the seismic response simulation module, and the aforementioned strength impact compensation value are normalized. Taking this pavilion as an example, the modal integrity index is 0.72, reflecting its structural stiffness distribution; the dynamic stability assessment value is 0.65, reflecting the structural dynamic response trend under earthquake action; and the strength impact compensation value is calculated to be 0.18. During normalization, these three values ​​are uniformly mapped to the [0, 1] interval to eliminate the impact of dimensional differences and generate a seismic performance fusion index. Specifically, a specific normalization algorithm is used to convert 0.72, 0.65, and 0.18 into comparable values, which are then weighted to obtain a fusion index. In this example, the fusion index is assumed to be 0.61.

[0088] Next, a threshold is set to determine seismic performance. This threshold is based on factors such as the historic building's protection level and seismic fortification intensity. For example, for a key historic building in an 8-degree fortification zone, the threshold could be set to 0.65. The resulting fusion index is then compared with the threshold. If the fusion index is below the threshold, a structural reinforcement signal is generated; if it is above the threshold, a component repair signal is generated. In this example, the fusion index of 0.61 is below the threshold of 0.65, so a structural reinforcement signal is generated, indicating that the entire structure of the pavilion needs to be reinforced.

[0089] In the collaborative analysis process, the accuracy and integrity of the data are crucial. The detection of material strength anomalies requires the use of non-destructive testing technologies, such as stress wave detection or wood density measurement, to ensure that the ancient building itself is not damaged. Taking the bracket components as an example, the internal defects are detected by a stress wave instrument, and the percentage deviation of the material strength from the standard value is calculated as the material strength anomaly data of the component. The acquisition of the modal characteristic integrity index depends on accurate modal testing. By arranging acceleration sensors on each floor of the pavilion, applying environmental excitation or artificial excitation, collecting structural vibration response signals, generating modal vibration mode diagrams and frequency response curves, and then extracting parameters such as the main vibration mode participation coefficient and node displacement amplitude, the stiffness continuity coefficient and frequency domain distribution index are calculated, and finally weighted fusion is obtained into the modal characteristic integrity index.

[0090] Determining the dynamic stability assessment value requires combining seismic wave input with structural dynamic response analysis. For this pavilion, for example, the acceleration time history data of a typical seismic wave, such as the EICentro wave, corresponding to the local design intensity, is input. A finite element model is used to calculate the structural response to this seismic wave. The energy spectrum intensity and spectral characteristic parameters are extracted, and a dynamic response prediction model is constructed to output the probability of structural failure in the future. The energy ratio of the dominant frequency component to the damping component of the spectral characteristic parameters is simultaneously calculated to obtain the spectral stability factor. A linear combination of these two factors forms the dynamic stability assessment value.

[0091] Collaborative analysis requires considering the coupled effects of multiple parameters. For example, when material strength anomalies are high, even if the modal integrity index and dynamic stability assessment values ​​are at good levels, the strength impact compensation value will lower the seismic performance fusion index, thereby triggering a structural reinforcement signal. Conversely, if material strength anomalies are low, but the modal integrity index indicates uneven structural stiffness distribution, the dynamic stability assessment value will also be affected, and targeted component repair or local reinforcement may be necessary.

[0092] In practice, a data calibration mechanism must also be established. Regular calibration of testing equipment, such as sensor sensitivity calibration and stress wave instrument parameter optimization, is essential to ensure the reliability of collected data. For complex historical structures, such as pavilions with diagonal braces or mezzanines, a more refined layout of testing points is required to avoid missing data. Furthermore, historical monitoring data should be combined to analyze the changing trends of various parameters, such as the annual rate of change in material strength anomaly and the stability of the modal integrity index, to provide a basis for long-term maintenance.

[0093] For example, if subsequent testing reveals increased loosening of the brackets and mortise and tenon joints in this Qing Dynasty timber pavilion, leading to an increase in the connection defect eigenvalue and, in turn, a decrease in the modal integrity index, collaborative analysis will need to re-retrieve relevant data, update the strength impact compensation value, and recalculate the fusion index to determine whether adjustments to reinforcement or restoration strategies are necessary. This dynamic collaborative analysis mechanism can reflect changes in the seismic performance of ancient buildings in real time, providing scientific support for conservation decisions.

[0094] Example 5:

[0095] During the seismic optimization strategy matching process, structural reinforcement or component repair operations must be precisely implemented based on the signals generated by the system, and closed-loop optimization must be achieved by combining damage coupling analysis with a model iteration mechanism. For example, in a Ming Dynasty wooden hall, when the multi-source fusion judgment module generates a structural reinforcement signal, the system automatically triggers an overall reinforcement command. At this point, the reinforcement locations and cross-sectional reinforcement parameters of the structural support system must be dynamically adjusted based on the command. For example, if analysis reveals that the hall's gable columns are tilted due to foundation settlement and the modal integrity index indicates a low stiffness continuity coefficient, additional steel supports will be required around the gable columns. The cross-sectional dimensions of the supports are determined based on the column's bearing capacity requirements, such as 100mm×100mm steel sections connected to the columns with bolts. The spacing of the supports should also be adjusted to ensure uniform stress distribution within the reinforced structure.

[0096] If a component repair signal is captured, such as the looseness of the mortise and tenon joints of the hall's brackets exceeding a preset threshold or a high connection defect characteristic value, a node repair instruction will be triggered. At this point, the repair range and stiffness recovery coefficient of the mortise and tenon joint system need to be optimized. For example, for loose tenons, epoxy resin mortar is used to fill the mortise and tenon gaps. The filling thickness is determined based on the looseness. If the gap is 5mm, the filling layer thickness is controlled at 3-4mm to ensure a tight fit between the tenon and the mortise. At the same time, the bracket components within the repair range are surface treated to remove rotten or weathered layers, and anti-corrosion and insect-proof coatings are applied to improve the durability of the components. The stiffness recovery coefficient needs to be determined through on-site testing, such as using a hammer method to measure the frequency changes of the components before and after repair to evaluate the stiffness recovery effect.

[0097] The system also includes a damage coupling analysis module to monitor the evolutionary correlation between historical damage and structural response. For example, strain sensors were used to collect historical damage growth rates and dynamic response growth rates for the temple. For example, if the crack growth rate at the eaves corner was monitored to be 0.2 mm / year and the dynamic response growth rate was 0.15 mm / year, the difference between the two rates was calculated and taken as the absolute value, resulting in a damage growth rate difference of 0.05 mm / year. Simultaneously, stress distribution data was extracted from the damaged area and the concentrated structural response area, and the ratio of the maximum stress gradient to the average gradient was calculated. If the maximum stress gradient was 15 MPa / m and the average gradient was 10 MPa / m, the stress redistribution coefficient would be 1.5. The damage growth rate difference and the stress redistribution coefficient were weighted and summed to generate a damage coupling assessment value. This value was fed back to the multi-source fusion assessment module to perform a secondary correction on the seismic performance fusion index. For example, the original fusion index of 0.6 was adjusted to 0.58 based on the weighting coefficient to more accurately reflect the actual seismic performance of the structure.

[0098] The model iteration and update module needs to adjust the meshing accuracy of the BIM model in real time based on the generated structural reinforcement parameters and node connection repair parameters. For example, when the structural reinforcement parameters involve cross-sectional enhancement adjustments of gable columns, the mesh density of the column components is simultaneously increased, and the original mesh size is refined from 50mm×50mm to 25mm×25mm to more accurately simulate the stress state after reinforcement. If the node connection repair parameters involve the optimization of the stiffness recovery of the bracket arch mortise and tenon joints, the number of elements in the mortise and tenon joint area is increased from 100 to 200 to ensure that the stress changes in the connection parts can be accurately captured during finite element analysis. The updated parameters need to be input into the building parameter acquisition module, and the seismic analysis process is restarted. For example, the modal characteristic analysis is repeated to verify whether the structural stiffness continuity coefficient has increased after reinforcement, or the earthquake response is re-simulated to see whether the dynamic stability assessment value has improved.

[0099] In practice, the triggering of structural reinforcement signals may stem from multi-parameter anomalies. For example, the hall's material strength anomaly indicates a 20% reduction in the compressive strength of the beam's timber, and a historical damage index reaching 0.7 due to foundation settlement. Both exceed preset thresholds. In this case, the overall reinforcement directive must consider both beam reinforcement and foundation elevation. Beam reinforcement can be achieved by wrapping with carbon fiber cloth. The number of wrapping layers is determined based on strength requirements, such as two layers of carbon fiber cloth, each 0.111mm thick. Ensure the overlap length is at least 100mm. Foundation elevation is achieved through staged lifting with jacks, with each lift controlled to 1-2mm to avoid additional stress on the structure.

[0100] Processing component repair signals requires a combination of traditional techniques and modern technology. For example, when repairing cracks in the hall's wooden pillars, traditional patching techniques were first employed. The rotten wood within the cracks was removed, and then dry wood was used to fill the cracks in their proper shape. Modern structural adhesives were then used to bond the components together. The adhesive selected must meet the requirements for the preservation of ancient buildings. For example, if epoxy resin adhesives were used, their viscosity and curing time must meet construction requirements. Regular monitoring of components after repair is required, such as quarterly measurements of crack expansion, to ensure the durability of the repair.

[0101] Real-time monitoring for damage coupling analysis relies on a well-placed sensor network. Strain sensors, displacement sensors, and accelerometers were deployed at key locations within the hall, such as eaves columns, beam joints, and bracket arches. The sensor sampling frequency was determined based on the structure's natural frequency. For example, if the natural frequency was 10 Hz, the sampling frequency was set to 100 Hz to ensure the dynamic response of the structure was captured. The data acquisition system required wireless transmission capabilities to transmit real-time data to a central server for remote monitoring and analysis.

[0102] During the iterative update process of the model, the adjustment of the BIM model needs to be synchronized with the actual on-site construction. For example, after the installation of the steel support of the gable column is completed on site, the position, size and connection method of the support need to be updated in the BIM model to ensure that the model is consistent with the actual structure. When the updated model is subjected to seismic analysis again, it is necessary to compare and analyze the changes in various parameters before and after reinforcement. For example, the modal characteristic integrity index increased from 0.55 to 0.70, and the dynamic stability assessment value increased from 0.60 to 0.68. Although it does not involve specific data verification, the optimization effect can be judged by the relative change trend of the parameters, providing a reference for the subsequent seismic reinforcement of similar ancient buildings.

[0103] It should be noted that, in this document, relational terms such as first and second, etc., are used only 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 terms "comprises," "includes," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0104] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A BIM-based ancient building seismic performance analysis and evaluation system, characterized by: include: The building parameter acquisition module is used to dynamically collect the component material properties, structural connection status and historical damage parameters of the target ancient building, obtain the ancient building structural status parameter set, identify and analyze the structural weak links based on the ancient building structural status parameter set, generate seismic abnormality signals, trigger the collaborative assessment instructions based on the generated seismic abnormality signals, and execute the modal characteristic analysis module and the earthquake response simulation module based on the triggered collaborative assessment instructions; The modal characteristic analysis module is used to extract the vibration modal characteristic parameters of the overall structure of the target ancient building, quantitatively evaluate the structural stiffness distribution state, and obtain the modal characteristic integrity index; The earthquake response simulation module 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 assessment value; The multi-source fusion judgment module is used to receive the modal characteristic integrity index and dynamic stability assessment value, conduct collaborative analysis on the seismic performance of ancient buildings, and generate structural reinforcement signals and component repair signals; The optimization parameter generation module is used to receive structural reinforcement signals and component repair signals, match seismic optimization strategies, and generate structural reinforcement parameters and node connection repair parameters.

2. The BIM-based seismic performance analysis and evaluation system for ancient buildings according to claim 1 is characterized in that: The identification and analysis of structural weaknesses includes: By dynamically collecting the material property parameters of the target ancient building components, the deviation percentage from the standard strength is calculated and marked as the material strength anomaly; Extract the looseness of the mortise and tenon joints and the crack expansion degree from the connection state parameters of the target ancient building structure, calculate the geometric synthetic vector modulus of the two, and mark it as the connection defect characteristic value; The accumulated settlement value and tilt deformation in the historical damage parameters are collected and normalized and weighted to obtain the comprehensive historical damage index. The material strength anomaly, connection defect characteristic value and historical damage comprehensive index are compared with the preset thresholds respectively. When any parameter exceeds the corresponding threshold, a seismic anomaly signal is generated.

3. The ancient building seismic performance analysis and evaluation system based on BIM modeling according to claim 1 is characterized in that: The quantitative evaluation of the structural stiffness distribution state includes: By applying pulse excitation and receiving the structural vibration response signal, the modal vibration shape diagram and frequency response curve are generated; Extract the main vibration mode participation coefficient and node displacement amplitude from the modal vibration shape diagram, calculate the product of the two and take the inverse to obtain the stiffness continuity coefficient; Extract the low-frequency energy proportion and spectrum density from the frequency response curve, calculate the arithmetic mean of the two, and mark it as the frequency domain distribution index; The modal characteristic integrity index is obtained by weighted fusion of the stiffness continuity coefficient and the frequency domain distribution index.

4. The ancient building seismic performance analysis and evaluation system based on BIM modeling according to claim 1 is characterized in that: The trend prediction of the structural dynamic response state includes: Input seismic wave acceleration time history data in real time to extract energy spectrum intensity and spectrum characteristic parameters; Construct a dynamic response prediction model, input the energy spectrum intensity into the model for finite element iteration processing, and output the structural failure probability within the future time interval; Extract the main frequency component and damping component from the spectrum characteristic parameters, calculate the energy ratio between the two and obtain the spectrum stability factor; The structural failure probability is linearly combined with 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 is characterized in that: The collaborative analysis of the seismic performance of ancient buildings includes: Retrieve material strength abnormality data, set its correction coefficient, and obtain strength impact compensation value through calculation and processing; The modal characteristic integrity index, dynamic stability evaluation value and strength impact compensation value are normalized and calculated to generate the seismic performance fusion index; A threshold for seismic performance judgment is set. 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.

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

7. The ancient building seismic performance analysis and evaluation system based on BIM modeling according to claim 1 is characterized in that: Also includes: The damage coupling analysis module is used to monitor the evolutionary correlation between historical damage and structural response, extract the damage growth rate and stress redistribution coefficient, and generate damage coupling assessment values; The multi-source fusion determination module further combines the damage coupling assessment value to perform a secondary correction on the seismic performance fusion index.

8. The ancient building seismic performance analysis and evaluation system based on BIM modeling according to claim 7 is characterized in that: The monitoring of the evolutionary correlation between historical damage and structural response includes: The historical damage growth rate and dynamic response growth rate are collected through strain sensors, and the difference between the two rates is calculated and the absolute value is taken, which is marked as the damage growth rate difference value; Extract stress distribution data of the damaged area and the concentrated area of ​​structural response, calculate the ratio of the maximum stress gradient to the average gradient, and mark it as the stress redistribution coefficient; The damage coupling assessment value is generated by weighted summing the damage growth rate difference value and the stress redistribution coefficient.

9. The ancient building seismic performance analysis and evaluation system based on BIM modeling according to claim 1 is characterized in that: Also includes: The model iteration and update module is used to adjust the meshing accuracy of the BIM model in real time based on the generated structural reinforcement parameters and node connection repair parameters, and feed back the optimization results to the building parameter acquisition module to form a closed-loop analysis link.

10. The BIM-based seismic performance analysis and evaluation system for ancient buildings according to claim 9 is characterized in that: The specific execution process of the model iterative update module includes: If the structural reinforcement parameters involve cross-section enhancement adjustments, the mesh density of key components should be increased simultaneously; If the node connection repair parameters involve stiffness recovery optimization, the number of elements in the mortise and tenon connection area will be increased simultaneously; Input the updated parameters into the building parameter acquisition module and restart the seismic analysis process.

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