An ancient building anti-seismic performance evaluation system and method

Abstract

The application discloses an ancient building anti-seismic performance evaluation system and method, comprising: a multi-modal information acquisition terminal arranged at a key structure point of an ancient building to be evaluated, which is used for acquiring a primary information set containing structure geometric appearance data, environmental micro-vibration response data and component physical damage state data; the multi-modal information acquisition terminal is adopted in the application, so that multi-dimensional data such as geometric appearance, damage state, dynamic response and environmental parameters can be synchronously collected, and the limitation of single data is avoided; through a Bayesian parameter identification algorithm and a mortise and tenon joint rotational stiffness dynamic degradation function, a digital twin model is accurately corrected, so that the model is highly fitted with actual working conditions, the error between a calculation frequency and a measured frequency is controlled within 3%, and the vibration mode coincidence degree is not less than 0.9; compared with a traditional experience evaluation method and an ideal model simulation method, the evaluation accuracy is greatly improved.

Description

Technical Field

[0001] This invention relates to the fields of cultural heritage protection, civil engineering structure monitoring, and earthquake engineering technology, specifically to a system and method for evaluating the seismic performance of ancient buildings. Background Technology

[0002] Ancient architecture, especially traditional wooden structures, is a treasure of human civilization. However, throughout history, these buildings have endured severe tests from natural aging, human damage, and earthquakes. Most ancient Chinese buildings employ mortise and tenon joints, bracket sets, and column bases, a structural logic that has historically demonstrated remarkable resilience and earthquake resistance.

[0003] However, existing seismic performance assessments of ancient buildings still face numerous challenges. First, traditional methods rely heavily on expert visual inspection and experience-based judgment, lacking quantitative mechanical data support. Second, existing finite element simulations are often based on idealized component states, neglecting the complexities of internal decay and cracking within wooden components, as well as the time-related degradation of mortise and tenon joint stiffness. Furthermore, ancient buildings are non-renewable resources, making destructive testing impossible. Therefore, obtaining dynamic parameters reflecting the true health status of ancient buildings without destructive testing and establishing accurate seismic assessment models are core technical issues urgently needing to be addressed in the field of preventative conservation of historical buildings.

[0004] Therefore, a seismic performance evaluation system and method for ancient buildings are proposed. Summary of the Invention

[0005] The purpose of this invention is to provide a system and method for evaluating the seismic performance of ancient buildings. This aims to address one of the problems existing in the prior art.

[0006] Firstly, to solve the aforementioned technical problems, this application adopts a technical solution as follows: a seismic performance evaluation system for ancient buildings, comprising: A multimodal information acquisition terminal is deployed at key structural sites of the ancient building to be evaluated to acquire a primary information set containing structural geometry data, environmental micro-vibration response data, and component physical damage data. The distributed collaborative monitoring network includes a high-precision tilt sensor array, a fiber optic strain monitoring unit, wireless triaxial accelerometers deployed on the column bases, mortise and tenon joints and brackets of ancient buildings, ultrasonic sensors and flexible conductive thin film strain gauges, which are used to capture the dynamic response signals of the structure under natural vibration and external excitation in real time. The structural characteristic mapping engine is configured to construct a nonlinear finite element initial model based on the primary information set, and to perform physical performance inversion correction on the initial model using a Bayesian parameter identification algorithm based on the frequency, array type and damping ratio parameters obtained by the collaborative monitoring network, thereby generating a digital twin model that is highly fitted to the actual working conditions. The seismic risk quantification assessment unit is used to apply seismic wave excitation of different fortification intensity levels to the digital twin model, calculate the inter-story drift angle, plastic energy dissipation distribution of components and pull-out displacement of key tenon and mortise joints through time history analysis, and output multi-dimensional seismic performance assessment results in combination with preset damage influence factors.

[0007] In one possible implementation, the distributed collaborative monitoring network employs a two-tiered deployment strategy for sensors, considering both overall modal and local damage characteristics. High-sensitivity accelerometers are installed at the bottom of the load-bearing columns, at the corners, and at the center of the roof ridge of the ancient building to extract overall dynamic parameters; For the decayed areas, cracked areas, and loose joints of the wooden components of ancient buildings, ultrasonic sensors and flexible conductive thin-film strain gauges are interspersed to monitor the expansion rate of the damaged interface in real time.

[0008] In one possible implementation, the structural characteristic mapping engine employs a dynamic degradation function for the rotational stiffness of the tenon and mortise joints during model correction. This function dynamically adjusts the spring stiffness coefficient of the nonlinear connection elements of the tenon and mortise joints in the finite element model based on measured humidity and temperature changes and historical earthquake damage accumulation.

[0009] In one possible implementation, the assessment results include remaining seismic bearing capacity indices, structural collapse early warning thresholds, and a list of reinforcement priorities for specific failed components.

[0010] Secondly, to solve the above-mentioned technical problems, another technical solution adopted in this application is: a method for evaluating the seismic performance of ancient buildings using the aforementioned system, comprising the following steps: S1. Use 3D laser scanning technology to obtain full-area point cloud data of ancient buildings, and combine it with infrared thermal imaging to detect hollowness and insect damage inside wooden components, forming a basic physical state archive. S2. Collect the random environmental vibration response of the ancient building under no artificial excitation by using the micro-motion test method to identify the fundamental frequency of the structure and its first three vibration modes. S3. Based on the data from step S1, establish a structural geometric model and use the vibration frequency identified in step S2 as the target value. By adjusting the material elastic modulus and boundary constraint conditions, the error between the calculated frequency and the measured frequency is controlled within 3%. S4. Input synthetic seismic waves reflecting the site characteristics of the region into the modified model, perform elastoplastic large deformation analysis, and simulate the evolution of the structure from the elastic stage to cracking, instability and even local collapse. S5. Extract key mechanical features during the simulation process, quantify and assess the survival probability of ancient buildings under the target earthquake damage level, and formulate preventive protection plans based on the assessment results.

[0011] In one possible implementation, in step S1, the method for quantifying the degree of damage to the wooden component is as follows: using an impedance meter to perform a drilling test on the damaged area, establishing a mapping relationship between the impedance curve and the residual density of the wood, and reflecting the residual density in the material property definition of the finite element model.

[0012] In one possible implementation, in step S2, when identifying modal parameters, a frequency domain decomposition algorithm under random environmental excitation is used to extract the damping ratio under the real mode, which is used to evaluate the energy dissipation efficiency of the ancient building's bracket structure.

[0013] In one possible implementation, in step S4, the simulation of the mortise and tenon joint uses a nonlinear element with shear-slip effect, the constitutive model of which considers the plastic deformation caused by the crossgrain compression of the wood and the reduction in effective load-bearing area caused by the tenon withdrawal.

[0014] In one possible implementation, in step S5, the preventative protection scheme includes proactive intervention recommendations for when the structural tilt rate exceeds 1 / 200, and grouting or iron reinforcement schemes for when the relative healthy original stiffness is reduced by more than 30%.

[0015] Thirdly, to solve the above-mentioned technical problems, another technical solution adopted in this application is: an electronic device, including a processor, a memory and a communication interface, wherein the memory stores a computer program, and when the processor executes the computer program, it implements the steps of the above-mentioned method for evaluating the seismic performance of ancient buildings.

[0016] Fourthly, to solve the above-mentioned technical problems, another technical solution adopted in this application is: a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the ancient building seismic performance evaluation method as described above.

[0017] The present invention has the following beneficial effects: 1. This invention employs a multimodal information acquisition terminal to achieve simultaneous acquisition of multi-dimensional data such as geometric shape, damage status, dynamic response, and environmental parameters, avoiding the limitations of single data. Through Bayesian parameter identification algorithm and dynamic degradation function of mortise and tenon joint rotational stiffness, the digital twin model is accurately corrected, making the model highly fit with the actual working conditions. The error between the calculated frequency and the measured frequency is controlled within 3%, and the mode shape coincidence is not less than 0.9. Compared with traditional empirical evaluation methods and ideal model simulation methods, the evaluation accuracy is greatly improved, realizing accurate simulation of "one building, one plan".

[0018] 2. This invention employs non-destructive testing technologies such as micro-motion testing, infrared thermal imaging detection, and micro-drill impedance testing. It can obtain the true health status and dynamic characteristics of the structure without conducting destructive tests on the ancient building, thus avoiding damage to the ancient building during the testing process. It meets the protection requirements of the non-renewable nature of ancient buildings and can be widely applied to the assessment of various precious ancient buildings.

[0019] 3. This invention, through multi-level seismic response simulation, can simulate the failure process of structures under different seismic scenarios, identify potential weak points and collapse risks in advance, and transform the traditional "post-disaster repair" into "pre-disaster intervention". At the same time, based on the assessment results, targeted preventive protection plans and reinforcement priority lists are formulated, providing management departments with scientific decision-making basis, effectively reducing the risk of damage to ancient buildings in earthquakes, and extending the service life of ancient buildings. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a system module diagram of the present invention; Figure 2 This is a schematic diagram of the process of the present invention; Figure 3 This is a schematic diagram of the structure of the electronic device of the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] Figure 2 This is a flowchart illustrating the method for evaluating the seismic performance of ancient buildings according to an embodiment of the present invention. It should be noted that if substantially the same results are obtained, the method of this application is not necessarily identical. Figure 2 The sequence of processes shown is limited. Example 1

[0024] A seismic performance assessment system for ancient buildings includes a multimodal information acquisition terminal, a distributed collaborative monitoring network, a structural characteristic mapping engine, and a seismic risk quantification assessment unit. These units collaborate to form a complete "data acquisition-transmission-processing-assessment" technology system. The specific structure is as follows: Multimodal information acquisition terminal; The multimodal information acquisition terminal is the core of data acquisition, deployed at key structural locations of the ancient building to be evaluated, including load-bearing columns, beams, brackets, mortise and tenon joints, roof ridges, and gable walls. It comprehensively acquires a preliminary information set of the ancient building, providing foundational data for subsequent model construction and evaluation. This terminal integrates multiple acquisition modules to achieve simultaneous acquisition of multi-dimensional information, specifically including: 1. 3D Laser Scanning Module: Utilizing a large-space terrestrial laser scanner, this module performs a panoramic scan of the ancient building using a multi-station stitching method. This generates millimeter-level color point cloud data, accurately acquiring information such as the structural geometry, component dimensions, and spatial relationships of the ancient building. The scanning accuracy is no less than 0.1mm, the station spacing is no more than 15m, and the stitching error is no more than 0.2mm, ensuring the accuracy of the geometric data. After scanning, point cloud data processing software is used to denoise, filter, stitch, and model the original point cloud, generating a 1:1 3D geometric model that clearly presents the overall structure and local details of the ancient building.

[0025] 2. Infrared Thermal Imaging Module: Used to detect hidden damage inside wooden components, including hollow areas, insect infestation, and rot. This module has a temperature resolution of no less than 0.05℃ and a detection distance controlled between 1-5m to avoid interference from ambient temperature, lighting, and other factors. During detection, the infrared thermal imager captures the temperature field distribution on the component surface. Due to the different thermal conductivity characteristics between damaged and intact areas, obvious abnormal areas will form in the temperature field. By analyzing these temperature field anomalies, the location, extent, and degree of hidden damage can be accurately located, and abnormal areas can be marked and numbered, providing a basis for subsequent damage quantification.

[0026] 3. Impedance Testing Module: An impedance meter is used to quantitatively detect the degree of damage to wooden components. A micro-drilling method is employed, where the impedance meter probe is slowly drilled into the component at a controlled speed of 1 mm / s. The drilling depth is determined based on the component's dimensions, not exceeding one-third of the component's cross-sectional thickness to avoid damage. During the test, the impedance meter collects the impedance values ​​in real time as the probe drills in, establishing a mapping relationship between the impedance curve and the residual density of the wood. By analyzing changes in impedance values, the degree of decay and residual strength of the wood are quantitatively assessed. At least three points are tested at each damaged area, and the average value is taken as the residual density value for that area to ensure the reliability of the test results.

[0027] 4. Environmental Monitoring Module: This module collects environmental parameters from the ancient building site in real time, including temperature, humidity, and atmospheric pressure, with a sampling interval of 10-30 seconds. Changes in environmental parameters affect the mechanical properties of the wood and the stiffness of the mortise and tenon joints; therefore, real-time monitoring and recording are necessary to provide data support for subsequent model correction and stiffness degradation analysis. This module has data storage capabilities, storing at least one year of environmental monitoring data for easy traceability and analysis.

[0028] Distributed collaborative monitoring network; A distributed collaborative monitoring network is used to capture the dynamic response signals of ancient buildings under natural vibration and external excitation in real time, providing dynamic data for structural characteristic identification and model correction. This network adopts a two-layer layout strategy of "overall modal and local damage," combining multiple high-precision sensors to achieve synchronous monitoring of the overall dynamic characteristics and local damage status of the structure, specifically including: 1. High-precision tilt sensor array: Used to monitor the tilt status and angle changes of ancient building structures. Deployed at key locations such as the tops of load-bearing columns, roof ridges, and gable walls, the deployment density is determined based on the building's scale, generally one sensor every 5-8 meters, with at least two sensors at corners to form cross-monitoring and ensure comprehensive data. The sensor's measurement range is ±30°, with an accuracy of no less than 0.001°. It can collect real-time tilt angle change data and, by analyzing these changes, determine if the structure has potential tilting, instability, or other hidden dangers.

[0029] 2. Fiber Bragg Grating Strain Monitoring Unit: Used to monitor strain changes in structural components, this unit is deployed on the surface of critical load-bearing components such as beams, columns, and brackets. It employs an adhesive mounting method, allowing it to conform to the curved surfaces of components and adapt to the complex shapes of ancient buildings. The strain measurement range of this unit is -3000με to 3000με, with an accuracy of no less than 1με. It can acquire strain data of components in real time during the stress process, analyze the stress state and damage of components through strain changes, and promptly detect problems such as cracking and deformation.

[0030] 3. Wireless Triaxial Accelerometer: Used to collect vibration response signals from the structure, deployed at the column bases, mortise and tenon joints, and bracket sets of ancient buildings. These are critical nodes for the structure's seismic resistance, and vibration response best reflects the structure's dynamic characteristics. The accelerometer's measurement range is ±5g, and the sampling frequency is adjustable between 10Hz and 1000Hz, flexibly set according to monitoring needs. During micro-motion testing, the sampling frequency is set to 256Hz to ensure the capture of weak vibration signals. Furthermore, the accelerometer uses wireless transmission, avoiding damage to the ancient building from wiring, and is waterproof, dustproof, and resistant to electromagnetic interference, adapting to the complex environmental conditions at ancient building sites.

[0031] 4. Auxiliary Monitoring Unit: This unit includes ultrasonic sensors and flexible conductive thin-film strain gauges, which are interspersed in the decayed areas, cracked areas, and loose joint areas of the wooden components to monitor the propagation rate of the damaged interfaces in real time. The ultrasonic sensors have a detection depth of no less than 50 mm, allowing them to penetrate the component surface and detect the propagation of internal cracks. The flexible conductive thin-film strain gauges can conform to the curved surface of the component to monitor the opening and closing degree and propagation rate of cracks in real time, with a propagation rate monitoring accuracy of no less than 0.01 mm / d. By monitoring the damage propagation, the damage development trend of the structure can be predicted.

[0032] All sensors in the distributed collaborative monitoring network are connected through a data acquisition unit. The data acquisition unit has data storage, preprocessing and transmission functions. It can transmit the collected dynamic response data to the structural characteristic mapping engine in real time. The transmission method adopts 5G or wired Ethernet with a transmission rate of no less than 100Mbps and has data encryption function to prevent data leakage and loss.

[0033] Structural feature mapping engine; The structural characteristic mapping engine is the core of model building and correction. It is configured to construct a nonlinear finite element initial model based on the primary information set acquired by the multimodal information acquisition terminal. Then, it combines the dynamic response parameters acquired by the distributed collaborative monitoring network and uses a Bayesian parameter identification algorithm to invert and correct the initial model, generating a digital twin model that highly fits the actual working conditions. The specific implementation process is as follows: 1. Construction of the Initial Nonlinear Finite Element Model: Based on the 3D geometric model generated by 3D laser scanning, and combined with residual data obtained from infrared thermal imaging and impedance testing, a nonlinear finite element initial model is constructed in ANSYS or Midas finite element analysis software. In the model, wooden components are simulated using solid elements or beam elements, with appropriate element types selected based on the size, shape, and stress characteristics of the components; mortise and tenon joints are simulated using nonlinear connection elements, considering the shear-slip effect and rotational stiffness of the mortise and tenon joints; the bracket structure is simulated using composite elements to recreate its complex stress mechanism; the foundation uses an elastic constraint model to simulate the connection state between the column base and the foundation. Simultaneously, based on the residual wood density obtained from impedance testing, the material properties of the wooden components in the model, such as elastic modulus, Poisson's ratio, and density, are corrected to ensure that the model can reflect the actual residual state of the components.

[0034] 2. Dynamic Response Parameter Extraction: Vibration response data collected by the distributed collaborative monitoring network is preprocessed, including filtering, denoising, and stability testing, to remove environmental noise and interference signals and extract the structure's dynamic parameters, including natural frequencies, mode shapes, and damping ratios. Natural frequencies and mode shapes reflect the overall modal characteristics of the structure, while the damping ratio reflects the structure's energy dissipation capacity. These parameters are the core target values ​​for model correction.

[0035] 3. Bayesian Parameter Identification Algorithm Correction: Using the extracted dynamic parameters as target values, the Bayesian parameter identification algorithm is employed to inversely correct the parameters of the initial finite element model. The constants to be corrected include the elastic modulus E of the wood, the rotational stiffness K of the tenon-and-mortise joint, and the foundation constraint stiffness. By adjusting these parameters, the dynamic parameters calculated by the model are made to be consistent with the measured parameters. The Bayesian parameter identification algorithm calculates the posterior probability distribution of the constants to be corrected using prior probability distributions and likelihood functions. It iterative calculations are used to find the optimal parameter combination, with at least 5000 iterations to ensure that the error between the calculated frequency and the measured frequency of the corrected model is controlled within 3%, and the mode shape coincidence ratio (MAC value) is not less than 0.9, enabling the model to accurately reflect the actual structural characteristics and dynamic response of the ancient building.

[0036] 4. Dynamic Degradation Correction of Tenon-Mortar Joint Rotational Stiffness: During model correction, a "Dynamic Degradation Function for Tenon-Mortar Joint Rotational Stiffness" is introduced. This function dynamically adjusts the spring stiffness coefficients of the nonlinear connection elements in the finite element model based on measured temperature and humidity changes and historical earthquake damage accumulation. This allows the model to simulate the degradation characteristics of tenon-mortar joint stiffness over time and with environmental changes. The core logic of this dynamic degradation function is as follows: The rotational stiffness of the tenon-mortar joint at time t is obtained by combining the initial rotational stiffness with multi-factor correction. The initial rotational stiffness is calibrated based on the component dimensions and wood strength. The correction process considers four key factors: historical earthquake damage accumulation, service life, environmental humidity, and environmental temperature. The historical earthquake damage accumulation coefficient is determined based on historical earthquake damage records of ancient buildings, with a value range of 0.05-0.2. The ratio of service life to design service life (generally 500 years) is combined with the time influence index (value range 0.8-1.2, depending on wood aging). The following parameters are used to determine the effect of stiffness on the mortise and tenon joint: the ratio of measured relative humidity to standard relative humidity (50%), combined with the humidity influence index (range 0.3-0.7, determined based on wood humidity tests); the ratio of measured temperature to standard temperature (20℃), combined with the temperature influence index (range 0.1-0.3, determined based on wood temperature tests); and the dynamic adjustment of the stiffness of the mortise and tenon joint through the comprehensive correction of the above multiple factors, thereby improving the model's fit and evaluation accuracy.

[0037] Seismic risk quantitative assessment unit; The seismic risk quantification assessment unit is used to perform multi-level seismic response simulations on the modified digital twin model, quantitatively assess the seismic performance of ancient buildings, and output multi-dimensional assessment results and targeted reinforcement recommendations. The specific implementation process is as follows: 1. Seismic Wave Excitation Input: Based on the seismic motion parameter zoning map of the area where the ancient building to be evaluated is located, synthetic seismic waves reflecting the site characteristics of the region are generated. This includes multiple sets of seismic waves at different fortification intensity levels: 6, 7, 8, and 9 degrees. Each level corresponds to different peak ground accelerations and seismic durations, ensuring that the simulation results can reflect the response characteristics of the ancient building under different seismic scenarios. Simultaneously, historical seismic wave data can be input according to actual needs to improve the realism and relevance of the simulation.

[0038] 2. Elastoplastic Large Deformation Analysis: Synthetic seismic waves were input into the corrected digital twin model, and the Newmark-β method was used for elastoplastic large deformation analysis with a time step of 0.01 s. The entire process of the structure from the elastic stage to cracking, instability, and even partial collapse was simulated. During the analysis, key mechanical characteristics such as inter-story drift angles, plastic energy dissipation distribution of components, pull-out displacement of critical tenon joints, and stress-strain of components were monitored in real time, recording the failure process and failure mode of the structure.

[0039] 3. Quantitative Assessment of Seismic Performance: Based on pre-defined damage impact factors, the key mechanical characteristics monitored are analyzed to quantitatively assess the seismic performance of the ancient building. The damage impact factors are set according to the component type, degree of damage, and structural location, with a value range of 0.1-0.9. The damage impact factors for core load-bearing components have higher values, while those for secondary components have lower values. The assessment results include three core components: (1) Remaining seismic bearing capacity index: It is expressed as the bearing capacity reserve coefficient, with a value range of 0-2. It is calculated through structural reliability analysis. When the value is greater than or equal to 1.2, it is judged to have good seismic resistance; when the value is between 0.8 and 1.2, it is judged to have basically met the requirements for seismic resistance, but regular monitoring is required; when the value is less than 0.8, it is judged to have insufficient seismic resistance, and reinforcement measures need to be taken immediately.

[0040] (2) Structural collapse warning threshold: including inter-story drift angle threshold, tenon and mortise joint pull-out displacement threshold and component plastic energy dissipation threshold. The inter-story drift angle collapse warning threshold for wooden frame ancient buildings is 1 / 100, the tenon and mortise joint pull-out displacement threshold is 5mm, and the component plastic energy dissipation threshold is determined according to the component type. When the monitored value exceeds the warning threshold, it is determined that the structure has a risk of collapse and the emergency warning mechanism needs to be activated.

[0041] (3) Reinforcement priority list: The components are ranked according to their importance coefficient, failure probability and reinforcement difficulty. The importance coefficient is set according to the component's role in the structure and ranges from 0.7 to 1.0. The importance coefficient of the core load-bearing component is 1.0. The failure probability is calculated by elastic-plastic simulation analysis. The reinforcement difficulty is determined according to the component's location, size, degree of damage and construction conditions. The priorities are ranked from high to low to provide the management department with a scientific basis for maintenance and reinforcement decisions.

[0042] 4. Development of Preventive Protection Plans: Based on the quantitative assessment results, targeted preventive protection plans will be developed to address the structural weaknesses and potential risks, specifying the reinforcement locations, materials, construction techniques, and acceptance standards. For example, for areas where the structural tilt exceeds 1 / 200, proactive intervention measures such as temporary supports and foundation reinforcement will be developed; for mortise and tenon joints where the stiffness reduction exceeds 30%, epoxy resin grouting reinforcement or stainless steel clamp reinforcement solutions will be developed; for severely rotten or cracked wooden components, replacement and repair measures will be developed to ensure the feasibility and effectiveness of the plans. Example 2

[0043] Based on the above system, such as Figure 2 As shown, to solve the above-mentioned technical problems, based on Embodiment 1, another technical solution adopted in this application is: This invention also provides a method for evaluating the seismic performance of ancient buildings, comprising the following steps: S1. On-site digital reconstruction and preliminary investigation; The core of this step is to obtain complete physical state data of the ancient building, providing a foundation for subsequent model building and evaluation. The specific operations are as follows: 1. Preliminary preparation: Before conducting on-site surveys, collect historical data on the ancient buildings to be assessed, including the building's age, structural type, repair records, and historical earthquake damage records, to understand the basic situation and potential risks of the ancient buildings; at the same time, prepare equipment such as 3D laser scanners, infrared thermal imagers, impedance meters, and environmental monitoring instruments, and debug the equipment to ensure that it is working properly; delineate the survey area and set up safety warning signs to avoid damage to the ancient buildings during construction.

[0044] 2. 3D Laser Scanning: A multi-station stitching method is used to perform a panoramic scan of the ancient building. During scanning, the laser scanner is placed at different stations, ensuring that each station covers an area of ​​the ancient building and that there is sufficient overlap between adjacent stations (overlap rate not less than 30%) to guarantee stitching accuracy. The scan data is monitored in real time during the scanning process to avoid missing key parts. For complex parts such as brackets and mortise and tenon joints, the scan density is increased to ensure that their details are clearly captured. After scanning, the raw point cloud data is imported into data processing software for noise reduction, filtering, stitching, and modeling to generate a 1:1 3D geometric model, annotating the dimensions and positions of the components.

[0045] 3. Detection of Hidden Damage: Infrared thermal imagers are used to inspect wooden components at a distance of 1-5 meters. Instrument parameters are adjusted to ensure clear imaging of the temperature field. During inspection, the instrument is moved at a constant speed along the length of the component, comprehensively inspecting key areas such as beams, columns, brackets, and mortise and tenon joints. The location, range, and temperature difference of abnormal temperature areas are recorded. For areas with abnormal temperature fields, a micro-drilling test is performed using an impedance meter. The drilling speed is controlled at 1 mm / s, and the drilling depth does not exceed 1 / 3 of the component's cross-sectional thickness. At least three points are tested in each abnormal area, and the impedance value at each point is recorded. A mapping relationship between the impedance curve and the residual density of the wood is established to quantitatively assess the degree of damage.

[0046] 4. Establishment of Basic Physical Condition Archives: The 3D model generated by 3D laser scanning, infrared thermal imaging detection records, impedance test data, environmental monitoring data, etc., are organized and archived to form a basic physical condition archive of the ancient building. The archive includes text descriptions, data tables, pictures, 3D models, etc., and clarifies the location, degree of damage, material properties, etc. of the components, providing basic data for subsequent model construction and evaluation.

[0047] It is important to note that traditional on-site surveys can only provide qualitative descriptions such as "insect-infested" or "rotten," while this invention quantifies the degree of damage through impedance testing. For example, if an impedance test shows that a load-bearing column has a 30% hollow core, the moment of inertia of that column segment will be multiplied by 0.7 during subsequent modeling, and the elastic modulus of the wood will be corrected to 0.65 of that of intact wood. This ensures that the model can accurately reflect the actual damage state of the component and avoids model errors caused by qualitative descriptions.

[0048] S2. Dynamic characteristics measured in practice; The core of this step is to acquire dynamic response data of the ancient building, identify the modal parameters of the structure, and provide target values ​​for model correction. The specific operations are as follows: 1. Sensor Deployment: Following a two-tiered layout strategy of "overall modal and local damage," high-precision tilt sensors, fiber optic strain monitoring units, and wireless triaxial accelerometers are deployed at key locations of the ancient building. Specifically, wireless triaxial accelerometers are deployed at column bases, mortise and tenon joints, and bracket sets, with the number determined based on the building's scale, generally no fewer than 16, forming a monitoring network. High-precision tilt sensors are deployed at the tops of load-bearing columns, roof ridges, and gable walls. Fiber optic strain monitoring units are deployed on the surfaces of key load-bearing components such as beams and columns. Ultrasonic sensors and flexible conductive thin-film strain gauges are deployed in damaged areas. After deployment, the sensors are debugged to ensure normal operation and stable data transmission.

[0049] 2. Micro-motion Test: The micro-motion test method is used to collect background noise response data of the ancient building under no artificial excitation. The test time is selected between 11:00 PM and 5:00 AM the following day, when background noise is lowest, avoiding external interference such as traffic and human activity. Each test lasts no less than 30 minutes, and the sampling frequency is set to 256Hz to ensure the capture of weak vibration signals. During the test, environmental monitoring data, including temperature and humidity, are recorded simultaneously for subsequent data correction.

[0050] 3. Data Preprocessing: The collected vibration response data is imported into data processing software for preprocessing. First, a combination of low-pass and high-pass filtering is used to remove high-frequency noise and low-frequency interference, retaining the vibration signal of the structure. Then, stationarity and normality tests are performed on the data to ensure its validity. Finally, Fourier transform is performed on the data to convert the time-domain signal into a frequency-domain signal, preparing for modal parameter identification.

[0051] 4. Modal Parameter Identification: A frequency domain decomposition (FDD) algorithm under random environmental excitation is used to analyze the preprocessed frequency domain signal and extract modal parameters such as the structure's natural frequencies, mode shapes, and damping ratios. The frequency resolution of the FDD algorithm is no less than 0.01 Hz, and the damping ratio identification accuracy is no less than 0.1%. During the identification process, the fundamental frequency and its first three mode shapes are the focus. The fundamental frequency reflects the overall stiffness of the structure, the mode shapes reflect the vibration pattern, and the damping ratio reflects the energy dissipation capacity of the structure. For example, the measured fundamental frequency of a Ming and Qing dynasty wooden palace is 1.25 Hz, while the finite element calculation based on ideal material properties is 1.60 Hz. This significant difference reveals that the palace has loose joints or material aging, providing a clear direction for subsequent model correction. Simultaneously, the energy dissipation efficiency of the bracket system is evaluated through the damping ratio. When the damping ratio is greater than 5%, the energy dissipation efficiency of the bracket system is considered good; when the damping ratio is less than 3%, the bracket system is considered to have looseness or damage, requiring close monitoring.

[0052] S3, Digital Twin Model Construction and Revision; The core of this step is "correcting the model through measurement," which involves constructing a digital twin model that closely matches the actual working conditions. The specific steps are as follows: 1. Geometric Model Construction: Based on the 3D laser scanning model generated in step S1, a geometric model of the ancient building is constructed using ANSYS or Midas finite element analysis software. Appropriate element types are selected according to the structural type of the ancient building; for example, beam elements are used for wooden columns and beams, nonlinear connection elements are used for brackets and mortise and tenon joints, and elastic constraint elements are used for the foundation. During the construction process, the model is strictly constructed according to the measured dimensions to ensure that the geometric model is consistent with the actual structure. Simultaneously, based on the damage data obtained in step S1, damaged components in the model are marked and processed.

[0053] 2. Initial Model Parameter Settings: Based on the type of wood, degree of damage, and environmental conditions of the ancient building, the material properties and boundary constraints of the initial model are set. Parameters such as the elastic modulus, Poisson's ratio, and density of the wood are corrected based on the residual density of the wood obtained from impedance testing. For severely damaged components, the elastic modulus and density are appropriately reduced. The boundary constraints simulate the connection state between the column base and the foundation. An elastic constraint model is used, and the constraint stiffness is set based on the field survey results to ensure that the model can reflect the actual boundary conditions.

[0054] 3. Initial Model Modal Analysis: Modal analysis is performed on the constructed nonlinear finite element initial model to calculate the model's natural frequencies, mode shapes, damping ratios, and other modal parameters. These parameters are then compared with the measured modal parameters identified in step S2 to analyze the errors between the two. If the error between the calculated and measured frequencies exceeds 3%, or the mode shape coincidence ratio (MAC value) is less than 0.9, the model needs to be corrected.

[0055] 4. Bayesian Parameter Identification and Correction: A Bayesian parameter identification algorithm is used to inversely correct the constants to be corrected in the model. These constants include the elastic modulus E of the wood, the rotational stiffness K of the mortise and tenon joint, and the foundation constraint stiffness. Measured modal parameters are used as target values. Through iterative calculation, the optimal parameter combination is found to make the modal parameters calculated by the model consistent with the measured parameters. The number of iterations is no less than 5000. After each iteration, the error between the calculated and measured values ​​is calculated until the error is controlled within 3% and the mode shape coincidence (MAC value) is no less than 0.9. It is important to emphasize that during the correction process, the values ​​of the constants to be corrected must conform to the physical properties of the wood to avoid unrealistic parameter values, achieving a "regression to physical meaning" and avoiding random computer-generated values. This ensures that the corrected model truly reflects the structural characteristics of the ancient building.

[0056] 5. Dynamic correction of mortise and tenon joint stiffness: The "dynamic degradation function of rotational stiffness of mortise and tenon joint" is introduced. Based on the environmental monitoring data and historical earthquake damage records obtained in steps S1 and S2, the rotational stiffness of the mortise and tenon joint at different times is calculated. The spring stiffness coefficient of the nonlinear connection unit in the model is dynamically adjusted so that the model can simulate the degradation characteristics of the stiffness of the mortise and tenon joint with time and environmental changes, and further improve the model's fitting degree.

[0057] S4, Multi-level Seismic Response Simulation; The core of this step is to simulate the response process of ancient buildings under different earthquake scenarios and identify weak points in the structure. The specific operation is as follows: 1. Seismic Wave Selection and Generation: Based on the seismic motion parameter zoning map of the area where the ancient building to be evaluated is located, the fortification intensity level of the area is determined, and synthetic seismic waves reflecting the site characteristics of the area are generated. The peak ground acceleration, duration, and spectral characteristics of the synthetic seismic waves are strictly determined according to the requirements of the "Code for Seismic Design of Buildings" (GB 50011-2010). Each fortification intensity level corresponds to at least three different sets of seismic waves to ensure the reliability of the simulation results. Simultaneously, historical seismic wave data (such as the Wenchuan earthquake and the Yushu earthquake) can be input according to actual needs to simulate the structural response under extreme earthquake scenarios.

[0058] 2. Simulation Parameter Settings: Import the corrected digital twin model into the finite element analysis software and set the simulation parameters. The Newmark-β method is used for elastoplastic large deformation analysis, with a time step of 0.01 s. The analysis duration is no less than the duration of the seismic wave to ensure a complete simulation of the structure's seismic response process. Simultaneously, a failure criterion is set. Based on the mechanical properties of wood and the structural characteristics of ancient buildings, parameters such as yield stress and ultimate strain of the components are set. When the stress or strain of a component exceeds the set value, the component is considered to have failed.

[0059] 3. Nonlinear Simulation of Mortise and Tenon Joints: Nonlinear elements with shear-slip effects are used to simulate mortise and tenon joints. The constitutive model of this element considers the plastic deformation caused by cross-grain compression of the wood and the reduction in effective load-bearing area due to tenon pull-out. The shear stiffness of the nonlinear element is determined based on the dimensions of the mortise and tenon joint, the strength of the wood, and the assembly clearance. A bilinear strengthening model is used to simulate plastic deformation. The reduction coefficient of the effective load-bearing area is dynamically adjusted according to the tenon pull-out displacement. When the pull-out displacement is greater than 2 mm, the reduction coefficient of the effective load-bearing area begins to decrease linearly until the pull-out displacement reaches 5 mm, at which point the effective load-bearing area is reduced to 50% of the initial value, simulating the failure process of the mortise and tenon joint.

[0060] 4. Simulation Process Monitoring and Data Recording: Initiate seismic response simulation to monitor key mechanical characteristics of the structure in real time, such as inter-story drift angles, plastic energy dissipation distribution of components, pull-out displacement of critical tenon joints, and stress-strain of components. Record the entire process of the structure from the elastic stage to cracking, instability, and even partial collapse. For example, simulate the "compression-reset" process of the dougong (bracket setter) under seismic waves, calculate its equivalent additional damping ratio, and analyze the energy dissipation efficiency of the dougong structure. Through pushover (static elastoplastic) analysis, plot the structure's "capacity spectrum curve" to intuitively reflect the structure's seismic resistance.

[0061] S5. Comprehensive performance evaluation and decision guidance; The core of this step is to quantitatively assess the seismic performance of ancient buildings and formulate targeted preventative protection plans. The specific procedures are as follows: 1. Analysis of key mechanical characteristics: Extract key mechanical characteristics recorded during the simulation in step S4, including inter-story drift angle, plastic energy dissipation distribution of components, pull-out displacement of mortise and tenon joints, stress and strain of components, etc. Combined with the preset damage influence factor, analyze these data to quantitatively evaluate the seismic performance of ancient buildings under different seismic intensity levels.

[0062] 2. Survival Probability Calculation: The Monte Carlo simulation method is used to analyze the structural reliability of ancient buildings and calculate their survival probability under the target earthquake damage level. The simulation is conducted at least 10,000 times. Survival probability is a crucial indicator for evaluating the seismic performance of ancient buildings. A higher survival probability indicates stronger earthquake resistance under that damage level, and vice versa. For example, if an ancient building has a 65% survival probability under a rare 8-degree earthquake, it means there is a 35% chance of damage in that earthquake scenario, requiring reinforcement measures.

[0063] 3. Seismic Performance Rating: Based on the remaining seismic bearing capacity index, structural collapse warning threshold, and survival probability, the seismic performance of ancient buildings is divided into four levels: Excellent (remaining seismic bearing capacity coefficient ≥ 1.2, survival probability ≥ 80%), Good (1.0 ≤ remaining seismic bearing capacity coefficient < 1.2, 60% ≤ survival probability < 80%), Satisfactory (0.8 ≤ remaining seismic bearing capacity coefficient < 1.0, 40% ≤ survival probability < 60%), and Unsatisfactory (remaining seismic bearing capacity coefficient < 0.8, survival probability < 40%). Based on the rating, the seismic performance status and potential risks of the ancient buildings are clearly defined.

[0064] 4. Reinforcement Priority Ranking: Based on the importance coefficient, failure probability, and reinforcement difficulty of the components, the components requiring reinforcement are prioritized. Core load-bearing components (such as load-bearing columns, main beams, and brackets) have the highest priority, followed by secondary components; components with high failure probability and low reinforcement difficulty have higher priority than components with low failure probability and high reinforcement difficulty. After ranking, a reinforcement priority list is generated, providing management with a scientific basis for maintenance and reinforcement decisions.

[0065] 5. Development of Preventive Protection Plans: Based on the seismic performance assessment results and the reinforcement priority list, develop targeted preventive protection plans. The plans must clearly define the reinforcement locations, reinforcement materials, construction techniques, construction period, and acceptance standards to ensure feasibility and effectiveness. For example, for areas where the structural tilt exceeds 1 / 200, temporary supports should be used for reinforcement to prevent further tilting, while the foundation should be grouted to improve its bearing capacity. For tenon-and-mortise joints where the stiffness reduction exceeds 30%, epoxy resin grouting should be used to enhance the connection stiffness of the joints, or stainless steel clamps should be used to wrap them to prevent loosening. For severely rotten or cracked wooden components, replacement with timber of the same material should be used, and the replaced components should undergo anti-corrosion and insect-proofing treatment to ensure their service life. Furthermore, the plans should specify the frequency and content of regular monitoring, establish a long-term monitoring mechanism, track changes in structural performance in real time, and adjust protective measures promptly. Example 3

[0066] like Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present disclosure. It illustrates a structural schematic diagram suitable for implementing the electronic device in the embodiment of the present disclosure. Figure 3 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0067] like Figure 3 As shown, the electronic device includes a processor, a memory, and a communication interface. The memory stores a computer program, and when the processor executes the computer program, it implements the ancient building seismic performance evaluation method of the various embodiments of this disclosure. The electronic device can exchange data with other devices or systems through the communication interface, enabling real-time updates and sharing of data information.

[0068] The processor in the aforementioned electronic device serves as its core, responsible for executing the computer program stored in the memory to implement various functions of the ancient building seismic performance evaluation method. The processor can employ a high-performance multi-core CPU or a dedicated chip to meet the demands of complex calculations and real-time processing. The memory stores the operating system, applications, data, and computer programs. In this embodiment, the memory stores the computer program implementing the ancient building seismic performance evaluation method. The memory can be RAM, ROM, Flash memory, or other types of non-volatile memory. The communication interface connects the electronic device to other devices or networks, enabling data transmission and exchange. In this embodiment, the communication interface supports various communication protocols and interface standards, such as Wi-Fi, Bluetooth, USB, and Ethernet, to meet communication needs in different scenarios.

[0069] For a detailed description of this embodiment, please refer to the corresponding descriptions in the foregoing embodiments, which will not be repeated here. Example 4

[0070] According to embodiments of the present disclosure, a computer-readable storage medium stores a computer program, which, when executed by a processor, implements the functions of the aforementioned methods for evaluating the seismic performance of ancient buildings according to various embodiments of the present disclosure.

[0071] The aforementioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or portable hard drive), media with built-in rewritable non-volatile memory (e.g., memory card), and media with built-in ROM (e.g., ROM cartridge).

[0072] For a detailed description of this embodiment, please refer to the corresponding descriptions in the foregoing embodiments, which will not be repeated here.

[0073] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An ancient building seismic performance evaluation system, characterized in that, include: A multimodal information acquisition terminal is deployed at key structural sites of the ancient building to be evaluated to acquire a primary information set containing structural geometry data, environmental micro-vibration response data, and component physical damage data. The distributed collaborative monitoring network includes a high-precision tilt sensor array, a fiber optic strain monitoring unit, wireless triaxial accelerometers deployed on the column bases, mortise and tenon joints and brackets of ancient buildings, ultrasonic sensors and flexible conductive thin film strain gauges, which are used to capture the dynamic response signals of the structure under natural vibration and external excitation in real time. The structural characteristic mapping engine is configured to construct a nonlinear finite element initial model based on the primary information set, and to perform physical performance inversion correction on the initial model using a Bayesian parameter identification algorithm based on the frequency, array type and damping ratio parameters obtained by the collaborative monitoring network, thereby generating a digital twin model that is highly fitted to the actual working conditions. The seismic risk quantification assessment unit is used to apply seismic wave excitation of different fortification intensity levels to the digital twin model, calculate the inter-story drift angle, plastic energy dissipation distribution of components and pull-out displacement of key tenon and mortise joints through time history analysis, and output multi-dimensional seismic performance assessment results in combination with preset damage influence factors.

2. The ancient building anti-seismic performance evaluation system according to claim 1, characterized in that, The distributed collaborative monitoring network adopts a two-layer layout strategy for sensor deployment, which considers both overall modal and local damage characteristics. High-sensitivity accelerometers are installed at the bottom of the load-bearing columns, at the corners, and at the center of the roof ridge of the ancient building to extract overall dynamic parameters; For the decayed areas, cracked areas, and loose joints of the wooden components of ancient buildings, ultrasonic sensors and flexible conductive thin-film strain gauges are interspersed to monitor the expansion rate of the damaged interface in real time.

3. The seismic performance evaluation system for ancient buildings according to claim 1, characterized in that, The structural characteristic mapping engine employs a dynamic degradation function for the rotational stiffness of mortise and tenon joints during model correction. This function dynamically adjusts the spring stiffness coefficient of the nonlinear connection elements of mortise and tenon joints in the finite element model based on measured humidity and temperature changes and historical earthquake damage accumulation.

4. The seismic performance evaluation system for ancient buildings according to claim 1, characterized in that, The assessment results include remaining seismic bearing capacity indicators, structural collapse early warning thresholds, and a list of reinforcement priorities for specific failed components.

5. A method for evaluating the seismic performance of ancient buildings using the system described in any one of claims 1 to 4, characterized in that, Includes the following steps: S1. Use 3D laser scanning technology to obtain full-area point cloud data of ancient buildings, and combine it with infrared thermal imaging to detect hollowness and insect damage inside wooden components, forming a basic physical state archive. S2. Collect the random environmental vibration response of the ancient building under no artificial excitation by using the micro-motion test method to identify the fundamental frequency of the structure and its first three vibration modes. S3. Based on the data from step S1, establish a structural geometric model and use the vibration frequency identified in step S2 as the target value. By adjusting the material elastic modulus and boundary constraint conditions, the error between the calculated frequency and the measured frequency is controlled within 3%. S4. Input synthetic seismic waves reflecting the site characteristics of the region into the modified model, perform elastoplastic large deformation analysis, and simulate the evolution of the structure from the elastic stage to cracking, instability and even local collapse. S5. Extract key mechanical features during the simulation process, quantify and assess the survival probability of ancient buildings under the target earthquake damage level, and formulate preventive protection plans based on the assessment results.

6. The method for evaluating the seismic performance of ancient buildings according to claim 5, characterized in that, In step S1, the method for quantifying the degree of damage to wooden components is as follows: use an impedance meter to perform a drilling test on the damaged area, establish a mapping relationship between the impedance curve and the residual density of the wood, and reflect the residual density in the material property definition of the finite element model.

7. The method for evaluating the seismic performance of ancient buildings according to claim 5, characterized in that, In step S2, when identifying modal parameters, a frequency domain decomposition algorithm under random environmental excitation is used to extract the damping ratio under the real mode, which is used to evaluate the energy dissipation efficiency of the ancient building's bracket structure.

8. The method for evaluating the seismic performance of ancient buildings according to claim 5, characterized in that, In step S4, the simulation of the mortise and tenon joint uses a nonlinear element with shear-slip effect.

9. The method for evaluating the seismic performance of ancient buildings according to claim 5, characterized in that, In step S5, the preventive protection scheme includes proactive intervention recommendations for when the structural tilt rate exceeds 1 / 200, and grouting or iron reinforcement schemes for when the relative healthy original stiffness is reduced by more than 30%.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method as described in any one of claims 5 to 9.

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