A BIM-based construction method and system for historical building models

Abstract

The present invention relates to the technical field of building information modeling, and specifically provides a method and system for constructing a historical building model based on BIM, which includes the following steps: obtaining spectral reflectance data on the surface of building components, setting a detection range, extracting spectral features, integrating to form time-series data, and obtaining spectral feature parameters of the components. In the present invention, through the detailed analysis of spectral reflectance, this solution precisionizes the aging assessment of components, avoids subjective judgment errors, improves accuracy, uses the mean square error and curve fitting techniques to finely quantify the aging process, reduces assessment errors, combines dynamic mechanical analysis, incorporates environmental factors to comprehensively evaluate building stability, optimizes structural safety prediction, geometric adaptation analysis improves component matching accuracy, reduces errors, optimizes the reconstruction effect, enhances the geometric and mechanical accuracy of the building model, and improves the practicality and reliability of the model through systematic data integration.

Description

Technical Field

[0001] The present invention relates to the technical field of building information modeling, and particularly to a method and system for constructing a historical building model based on BIM. Background Art

[0002] The technical field of building information modeling includes aspects such as building structure modeling, construction process simulation, and building operation and maintenance management. The core lies in constructing a digital model of a building through computer technology and integrating multi-dimensional information such as geometric information, material properties, construction processes, and maintenance data on this basis to support the whole life cycle management of the building. Building information modeling involves multiple links such as three-dimensional modeling, data storage, and information interaction, and realizes functions such as information sharing, optimized design, construction assistance, and maintenance through constructing a visual and digital building model. In recent years, building information modeling has gradually been combined with historical building protection and cultural heritage digitization to enhance the research, management, and reproduction capabilities of traditional buildings.

[0003] Among them, the method for constructing a historical building model based on BIM refers to using building information modeling technology to digitally model historical buildings. This method covers aspects such as the geometric form reconstruction of historical buildings, structural information analysis, building material data collection, and cultural feature annotation, and combines means such as oblique photography, laser scanning, and three-dimensional modeling to obtain building appearance data. Subsequently, the obtained data is sorted and stored through digital processing means, and building components are classified, labeled, and associated according to the historical building information model. Finally, combined with virtual reality visualization technology, the model construction and information integration of historical buildings are realized to support research and subsequent applications.

[0004] The existing technology relies on geometric form reconstruction and construction process simulation, and it is difficult to conduct fine-grained analysis on the aging state of building materials, resulting in difficulty in evaluating the continuous change trend of component performance during the long-term use of the building. The aging assessment method based on vision or single mechanical simulation is difficult to capture the gradual process of material aging, resulting in the aging judgment being limited by the obviousness of surface changes, affecting the long-term prediction of structural durability. The structural mechanics analysis fails to fully consider the continuous influence of environmental factors and lacks the long-term accumulation of environmental load and foundation change data, resulting in uncertainty in predicting the change of structural forces. Component matching mainly relies on geometric form similarity and fails to combine material properties and splicing relationships, resulting in insufficient matching accuracy of some components and affecting the structural consistency of the overall building model. During the building model reconstruction process, although geometric data can achieve refined expression, there is a lack of analysis of the correlation between material aging and structural force characteristics, making it difficult for the model to comprehensively reflect the long-term stable state of the building and affecting the accuracy of building maintenance and safety assessment. Summary of the Invention

[0005] The object of the present invention is to solve the drawbacks existing in the prior art, and to propose a method and system for constructing a historical building model based on BIM.

[0006] To achieve the above object, the present invention adopts the following technical solutions: A method for constructing a historical building model based on BIM, comprising the following steps:

[0007] S1: Obtain the spectral reflectance data of the surface layer of building components, set the detection range, extract spectral features, integrate to form time series data, and obtain the spectral feature parameters of the components;

[0008] S2: Based on the spectral feature parameters of the components, calculate the change in absorptance, analyze the mean square deviation of spectral data, combine with the aging model to divide the aging grade, and obtain the aging grade index of the building components;

[0009] S3: Use the aging grade index of the building components to analyze the axial force, shear force, and bending moment of the load-bearing components, combine with the foundation settlement, wind load, and seismic influence, evaluate the mechanical equilibrium state, calculate the change in bearing capacity under the influence of aging, deduce the structural deformation trend, and obtain the building structure form offset trend value;

[0010] S4: According to the building structure form offset trend value, calculate the geometric parameters of the components, screen the splicing relationship, and compare the shape features with the style database to obtain the shape adaptation parameters of the building components;

[0011] S5: Call the shape adaptation parameters of the building components, extract the building geometric information from the BIM database, adjust the docking relationship, optimize the structure, and establish the building model reconstruction steps.

[0012] As a further solution of the present invention, the spectral feature parameters of the components include spectral absorptance eigenvalue, spectral boundary change point, and spectral time series data. The aging grade index of the building components includes aging classification threshold, spectral offset amount, and material decay rate. The building structure form offset trend value includes structural stability offset amount, force balance change value, and shape deformation prediction parameter. The shape adaptation parameters of the building components include geometric matching degree, component splicing adaptability, and style feature comparison result. The building model reconstruction steps include component docking adjustment, geometric structure optimization, and building overall data integration.

[0013] As a further solution of the present invention, the specific steps for obtaining the spectral reflectance data of the surface layer of building components, setting the detection range, extracting spectral features, integrating to form time series data, and obtaining the spectral feature parameters of the components are as follows:

[0014] S101: Obtain the spectral reflectance data of the surface layer material of the building components, set the detection range, identify the wavelength interval and resolution, call the set range to measure the spectral reflectance, and organize the data to form spectral reflectance curve data;

[0015] S102: Based on the spectral reflectance curve data, extract the absorptance of the absorption peaks and the corresponding wavelength values, calculate the difference in absorptance between adjacent absorption peaks, screen the boundary points with a change amplitude greater than the set threshold, obtain the spectral curve boundary change point data, calculate the overall average absorptance, integrate the characteristic absorption information of the spectral curve, and obtain the spectral characteristic absorption parameters;

[0016] S103: Call the spectral characteristic absorption parameters, sort the spectral parameters according to the time series, calculate the characteristic changes between time series points, extract the change range and stable interval, and integrate to form the component spectral characteristic parameters.

[0017] As a further solution of the present invention, based on the component spectral characteristic parameters, calculate the change in absorptance, analyze the mean square error of the spectral data, combine the aging model to divide the aging level, and the specific steps to obtain the building component aging level index are as follows:

[0018] S201: Obtain the component spectral characteristic parameters, select the wavelength points of the spectral curve, calculate the absorptance of the wavelength points, organize the absorptance data, and form the wavelength absorptance distribution data;

[0019] S202: Based on the wavelength absorptance distribution data, analyze the mean square error of the spectral curve, analyze the dispersion degree of the absorptance, calculate the error value of the fitting curve, compare the deviation degree between the curve and the measured data, screen the regions with errors higher than the set threshold, extract the decay characteristics of the spectral curve, and obtain the spectral decay trend parameters;

[0020] S203: Call the spectral decay trend parameters, compare the threshold intervals under different aging levels, screen the spectral parameters that meet the aging level boundaries, divide the aging levels of the components, and obtain the building component aging level index.

[0021] As a further solution of the present invention, using the building component aging level index, analyze the axial force, shear force, and bending moment of the load-bearing components, combine the foundation settlement, wind load, and seismic effects, evaluate the mechanical equilibrium state, calculate the change in bearing capacity under aging effects, deduce the structural deformation trend, and the specific steps to obtain the building structure form offset trend value are as follows:

[0022] S301: Obtain the building component aging level index, analyze the distribution of axial force, shear force, and bending moment of the load-bearing components, analyze the stress conditions of the components, organize the calculation results, and form the load-bearing component stress distribution data;

[0023] S302: Based on the stress distribution data of the load-bearing member, calculate the stress change value of the member under the influence of differential loads, call the data of foundation settlement, wind load and seismic influence, analyze the offset of the environmental factors from the mechanical equilibrium state, screen the members with an offset higher than the set threshold, calculate the change value of the bearing capacity under the influence of aging, extract the stress change range under the action of differential loads, and obtain the mechanical equilibrium offset parameter;

[0024] S303: Call the mechanical equilibrium offset parameter, analyze the stress change trend of the member, calculate the cumulative offset value of the structural form, deduce the structural deformation trend under different aging levels, and obtain the building structural form offset trend value.

[0025] As a further solution of the present invention, the specific formula for calculating the cumulative offset value of the structural form is:

[0026] ;

[0027] where, represents the cumulative offset value of the structural form, represents the X-direction displacement coordinate of the member at the th measurement moment, represents the X-direction coordinate of the member at the initial moment, represents the Y-direction displacement coordinate of the member at the th measurement moment, represents the Y-direction coordinate of the member at the initial moment, represents the Z-direction displacement coordinate of the member at the th measurement moment, represents the bending moment influence factor at the th measurement moment, represents the total number of measurement time steps.

[0028] As a further solution of the present invention, according to the building structural form offset trend value, the specific steps for calculating the geometric parameters of the member, screening the splicing relationship, comparing the morphological characteristics in combination with the style database, and obtaining the building component form adaptation parameter are:

[0029] S401: Obtain the building structural form offset trend value, calculate the main axis direction, proportional parameter and edge curvature of the member, screen the members that meet the morphological measurement standard, organize the calculation results, and form the geometric morphological parameters of the member;

[0030] S402: Based on the geometric morphological parameters of the member, analyze the geometric adaptability of the member, screen the members that meet the splicing relationship, calculate the connection offset of adjacent members, compare the curvature differences of the member edges, screen the pairs of members with a splicing error within the set threshold range, extract the member combinations with a higher adaptability, and obtain the member splicing adaptation parameter;

[0031] S403: Call the component splicing adaptation parameters, combine with the morphological feature data in the style database, calculate the matching degree between the component morphology and the style benchmark, screen the components with a matching degree higher than the set standard, and obtain the building component morphology adaptation parameters.

[0032] As a further solution of the present invention, the specific calculation formula for the matching degree between the building component morphology and the set style benchmark is:

[0033] ;

[0034] where, represents the matching degree between the building component morphology and the set style benchmark, represents the actual morphological parameter value of the th component (such as aspect ratio, height-width ratio, etc.), represents the benchmark morphological parameter value in the style database of the th item, represents the weight coefficient of the th morphological parameter, represents the actual curvature parameter value of the th component, represents the benchmark curvature parameter value in the style database of the th item, represents the adjustment coefficient of the th curvature parameter, represents the total number of morphological parameter items, represents the total number of curvature parameter items.

[0035] As a further solution of the present invention, the specific steps for calling the building component morphology adaptation parameters, extracting building geometric information from the BIM database, adjusting the docking relationship, optimizing the structure, and establishing the building model reconstruction steps are as follows:

[0036] S501: Call the building component morphology adaptation parameters, extract the geometric information of the building components from the BIM database, screen the components that meet the splicing relationship, and organize the data to form a building component geometric information set;

[0037] S502: Based on the building component geometric information set, adjust the component docking relationship, calculate the connection offset of adjacent components, screen the component pairs with the offset within the set threshold range, optimize the component splicing order, adjust the spatial positioning parameters of the structural components, extract the optimized component combination, and obtain the optimized component splicing parameters;

[0038] S503: Call the optimized component splicing parameters, integrate the geometric information of the optimized components, adjust the overall building structure relationship, organize the spatial component data, and establish the building model reconstruction steps.

[0039] A BIM-based historical building model construction system, comprising: a spectral feature extraction module that acquires spectral reflectance data of the surface materials of building components, collects spectral reflectance curves, extracts peak absorption rates, boundary change points, and average absorption rates, integrates spectral features to form time series data, and obtains component spectral feature parameters;

[0040] An aging assessment module, based on the component spectral feature parameters, calculates the absorption rate at wavelength points, analyzes the mean square error and curve fitting error of spectral data, conducts a comparative analysis in combination with an aging model, divides the aging grade threshold, and obtains the aging grade index of building components;

[0041] A mechanical stability analysis module uses the aging grade index of the building components to analyze the axial force, shear force, and bending moment distributions of load-bearing components, calculates the numerical change of component stress, combines foundation settlement, wind load, and seismic effects, evaluates the mechanical equilibrium state through environmental factors, deduces the structural deformation trend, and obtains the building structure form deviation trend value;

[0042] A form matching calculation module calculates the main axis direction, scale parameter, and edge curvature of components according to the building structure form deviation trend value, analyzes geometric adaptability, compares form features in combination with a style database, and obtains the form adaptation parameters of building components;

[0043] A BIM model reconstruction module calls the form adaptation parameters of the building components, extracts building geometric information from the BIM database, adjusts the component docking relationship, optimizes the overall structure, and establishes the building model reconstruction steps.

[0044] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0045] In the present invention, through the detailed analysis of spectral reflectance, the aging assessment of components is refined in this solution, subjective judgment errors are avoided, the accuracy is improved, the aging process is finely quantified using the mean square error and curve fitting techniques, the assessment error is reduced, combined with dynamic mechanical analysis, environmental factors are incorporated to comprehensively evaluate the building stability, the structural safety prediction is optimized, the geometric adaptability analysis improves the component matching accuracy, reduces errors, optimizes the reconstruction effect, enhances the geometric and mechanical accuracy of the building model, and improves the practicability and reliability of the model through systematic data integration. Description of the Drawings

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0047] Figure 1Schematic diagram of the process flow of the present invention;

[0048] Figure 2 Flow chart of step S1 of the present invention;

[0049] Figure 3 Flow chart of step S2 of the present invention;

[0050] Figure 4 Flow chart of step S3 of the present invention;

[0051] Figure 5 Flow chart of step S4 of the present invention;

[0052] Figure 6 Flow chart of step S5 of the present invention;

[0053] Figure 7 System module diagram of the present invention. Detailed implementation manners

[0054] The following describes the technical solutions in the present invention with reference to the accompanying drawings.

[0055] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as an "example" in the present invention should not be construed as being more preferred or more advantageous than other embodiments or design solutions. Rather, the use of the word "example" is intended to present concepts in a specific manner. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one of the two.

[0056] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when their differences are not emphasized, their intended meanings are the same. "(of)", "corresponding", and "corresponding" can sometimes be used interchangeably. It should be noted that when their differences are not emphasized, their intended meanings are the same.

[0057] In the embodiments of the present invention, sometimes subscripts such as W 1 may be written in a non-subscript form such as W1. When their differences are not emphasized, their intended meanings are the same.

[0058] To make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will be described in detail with reference to the accompanying drawings and specific embodiments.

[0059] Please refer to Figure 1 , a method for constructing a historical building model based on BIM, including the following steps:

[0060] S1: Obtain the spectral reflectance data of the surface material of the building component, set the detection range, collect the spectral reflectance curve, extract the peak absorption rate, boundary change points and average absorption rate, integrate the spectral features to form time series data, and obtain the spectral feature parameters of the component;

[0061] S2: Based on the spectral feature parameters of the component, calculate the absorption rate at the wavelength point, analyze the mean square error of the spectral data and the curve fitting error, evaluate the decay trend of the material, conduct a comparative analysis in combination with the aging model, divide the aging grade threshold, and obtain the aging grade index of the building component;

[0062] S3: Use the aging grade index of the building component to analyze the axial force, shear force and bending moment distribution of the load-bearing component, calculate the numerical change of the component stress, combine the foundation settlement, wind load and seismic influence, evaluate the mechanical equilibrium state through environmental factors, calculate the change of the bearing capacity under the influence of aging, deduce the structural deformation trend, and obtain the building structure form offset trend value;

[0063] S4: According to the building structure form offset trend value, calculate the main axis direction, proportional parameter and edge curvature of the component, analyze the geometric adaptability, screen the splicing relationship of the components, compare the shape features in combination with the style database, and obtain the building component shape adaptability parameters;

[0064] S5: Call the building component shape adaptability parameters, extract the building geometric information from the BIM database, adjust the docking relationship of the components, optimize the overall structure, integrate the data, and establish the building model reconstruction steps.

[0065] The spectral feature parameters of the component include spectral absorption rate eigenvalue, spectral boundary change point, and spectral time series data. The aging grade index of the building component includes aging classification threshold, spectral offset amount, and material decay rate. The building structure form offset trend value includes structural stability offset amount, stress balance change value, and shape deformation prediction parameter. The building component shape adaptability parameters include geometric matching degree, component splicing adaptability, and style feature comparison result. The building model reconstruction steps include component docking adjustment, geometric structure optimization, and building overall data integration.

[0066] Please refer to Figure 2 , the specific steps of S1 are:

[0067] S101: Obtain the spectral reflectance data of the surface material of the building component, set the detection range, identify the wavelength interval and resolution, call the measurement of the spectral reflectance within the set range, and organize the data to form spectral reflectance curve data;

[0068] To obtain the spectral reflectance data of the surface material of a building component, it is necessary to first clarify the material type of the building component and select a suitable spectral instrument to detect the target material. First, when setting the detection range, it is necessary to set a reasonable spectral measurement band range according to the material characteristics of the building component, and select the measurement wavelength interval according to the spectral response characteristics of known materials. For example, for concrete materials, their main spectral response interval is concentrated in the visible and near-infrared ranges (400nm - 2500nm), while for metal materials, a higher wavelength range may be required. After setting the wavelength interval, it is necessary to select an appropriate spectral resolution. For example, set the resolution to 10nm, that is, in the range of 400nm - 2500nm, collect the reflectance data every 10nm interval. Then, call the measuring device to measure the spectral reflectance. During the measurement, it is necessary to calibrate the light source intensity to ensure the stability of the incident angle of the measurement beam. For example, fix the light source to irradiate at a 45° angle and use a standard whiteboard for reference calibration. During the measurement process, collect the data of multiple measurement points and calculate their average value to reduce the influence of noise. For example, collect the reflectance data of five points on the surface of the same component and average them to obtain the final spectral reflectance data. Finally, organize the measured data into spectral reflectance curve data. The curve data should include the corresponding relationship between the wavelength and the reflectance, and be output in the form of a data table or a graph to form a spectral reflectance curve.

[0069] S102: Based on the spectral reflectance curve data, extract the absorption rate and the corresponding wavelength value of the absorption peak, calculate the difference in absorption rates between adjacent absorption peaks, screen the boundary points with a change amplitude greater than the set threshold, obtain the spectral curve boundary change point data, calculate the overall average absorption rate, integrate the characteristic absorption information of the spectral curve, and obtain the spectral characteristic absorption parameters;

[0070] Extract the absorption rate and corresponding wavelength values of the absorption peaks. First, obtain the wavelength points with lower reflectivity from the spectral reflectivity data as potential absorption peak positions. Set an absorption rate threshold, such as points with a reflectivity lower than 40% as absorption peak points, and count the wavelength values of these points. For example, in a spectral dataset, the reflectivities at wavelengths 700nm, 1200nm, and 1800nm are 35%, 30%, and 25% respectively. Then these wavelength points can be identified as absorption peak points, and their corresponding absorption rates are 65%, 70%, and 75% respectively. Next, calculate the difference in absorption rates between adjacent absorption peaks. For example, the difference in absorption rates between 700nm and 1200nm is 70% - 65% = 5%, and the difference in absorption rates between 1200nm and 1800nm is 75% - 70% = 5%. Set a change threshold, such as 5%, and screen the boundary points with a change amplitude greater than the set threshold to obtain the data of the boundary change points of the spectral curve, that is, extract the wavelength points with prominent changes in absorption rate. For example, if the change in absorption rate of a certain data point reaches 8%, it is stored as a boundary change point in the dataset. Calculate the overall average absorption rate. The method is to calculate the average of all absorption rate data, such as (65% + 70% + 75%) / 3 = 70%. Then integrate the characteristic absorption information of the spectral curve, record the wavelengths, absorption rates, and their changes of all absorption peaks. Finally, obtain the spectral characteristic absorption parameters, including information such as absorption peak wavelength, absorption rate, and absorption rate change, and output them as a set of characteristic parameters.

[0071] S103: Call the spectral characteristic absorption parameters, sort the spectral parameters according to the time series, calculate the characteristic changes between time series points, extract the change range and stable interval, and integrate them to form the spectral characteristic parameters of the component;

[0072] Sort the spectral parameters according to the time series. First, establish a time series dataset, arrange the spectral characteristic parameters measured at different time points in chronological order. For example, the absorption rates corresponding to t1, t2, and t3 are 68%, 72%, and 69% respectively. Then calculate the characteristic changes between time series points, calculate the change value of the absorption rate for each adjacent time point. For example, the change value from t1 to t2 is 72% - 68% = 4%, and the change value from t2 to t3 is 69% - 72% = 3%. Extract the change range and stable interval. For example, if the set change threshold is ±3%, then the data points from t2 to t3 belong to the stable interval, and the data points from t1 to t2 belong to the change interval. Finally, integrate them to form the spectral characteristic parameters of the component, including time series absorption rate change data, stable interval, and change amplitude data. Finally, obtain the spectral characteristic parameter set of the component.

[0073] Please refer to Figure 3 , the specific steps of S2 are as follows:

[0074] S201: Obtain the spectral characteristic parameters of the component, select the wavelength points of the spectral curve, calculate the absorptivity at the wavelength points, organize the absorptivity data, and form the wavelength-absorptivity distribution data;

[0075] Select the wavelength points of the spectral curve. First, screen out the key wavelength points from the spectral characteristic parameter set. For example, for concrete materials, select the wavelength points at the main absorption peak positions of 700 nm, 1200 nm, and 1800 nm, and ensure that these wavelength points cover the main spectral characteristic region. Then, calculate the absorptivity at the wavelength points. For each selected wavelength point, calculate the absorptivity based on its spectral reflectivity data. The absorptivity calculation method is the reflectivity. For example, if the reflectivity of a certain material at 700 nm is 35%, then its absorptivity is calculated as 1 - 0.35 = 0.65, that is, the absorptivity is 65%. Repeat this calculation step to obtain the absorptivity data of all selected wavelength points. Next, organize the absorptivity data. Arrange all the calculated absorptivity values according to the wavelength points to form an absorptivity data set. For example, 700 nm corresponds to an absorptivity of 65%, 1200 nm corresponds to an absorptivity of 70%, and 1800 nm corresponds to an absorptivity of 75%. The organized data can be stored as a table or an array. Finally, form the wavelength-absorptivity distribution data. The complete wavelength-absorptivity distribution data should include the absorptivity of each wavelength point and be presented in the form of a data table or a graph so that it can be used for subsequent spectral characteristic analysis to obtain the complete wavelength-absorptivity distribution data.

[0076] S202: Based on the wavelength-absorptivity distribution data, analyze the mean square deviation of the spectral curve, analyze the dispersion degree of the absorptivity, calculate the error value of the fitting curve, compare the deviation degree between the curve and the measured data, screen out the regions with errors higher than the set threshold, extract the decay characteristics of the spectral curve, and obtain the spectral decay trend parameters;

[0077] Analyze the mean square error of the spectral curve. First, calculate the square of the deviation between the absorption rate at each wavelength point and the mean value, and then calculate the average value. For example, if the absorption rates at three wavelength points of a component are 65%, 70%, and 75%, the mean value is (65% + 70% + 75%) / 3 = 70%. Calculate the square of the deviation for each point, such as (65% - 70%)² = 25, (70% - 70%)² = 0, (75% - 70%)² = 25. The mean square error is calculated as (25 + 0 + 25) / 3 = 16.67. Next, analyze the dispersion degree of the absorption rate, and evaluate whether there are large fluctuations in the absorption rate data through the mean square error value. If the mean square error is less than 10, it indicates that the data is relatively concentrated. If the mean square error is greater than 20, it indicates that the absorption rate data fluctuates greatly. Subsequently, calculate the error value of the fitting curve, which is the difference between the actually measured absorption rate and the absorption rate calculated by the fitting curve. For example, if the absorption rates calculated by the fitting curve at 700 nm, 1200 nm, and 1800 nm are 64%, 71%, and 76% respectively, the errors are |65% - 64%| = 1%, |70% - 71%| = 1%, |75% - 76%| = 1% respectively. Then, compare the deviation degree between the curve and the measured data, set a deviation threshold, such as 2%, and screen out the regions with errors higher than the threshold. For example, if the error calculated at a certain wavelength point is 3%, the data at this wavelength point is screened out as a region with a large deviation. Next, extract the decay characteristics of the spectral curve, record the wavelength points and the error change trends in all regions with large deviations, and summarize the spectral decay trend. Finally, obtain the spectral decay trend parameters, which include information such as the wavelength points in the regions with large deviations, the error amplitude, and the error change trends, and output them as a spectral decay trend parameter set.

[0078] S203: Call the spectral decay trend parameters, compare the threshold intervals under different aging levels, screen out the spectral parameters that meet the aging level boundaries, divide the aging levels of the components, and obtain the aging level indicators of the building components;

[0079] Compare the threshold intervals under different aging levels. First, set the error thresholds for different aging levels. For example, set the error threshold for mild aging to 0% - 2%, the error threshold for moderate aging to 2% - 5%, and the error threshold for severe aging to above 5%. Then, screen the spectral parameters that meet the aging level boundaries. For the error value at each wavelength point, determine the aging level interval it belongs to. For example, if the error value at a certain wavelength point is 1.5%, then this point belongs to the mild aging level; if the error value at a certain wavelength point is 3.2%, then it belongs to the moderate aging level; if the error value at a certain wavelength point is 6.0%, then it belongs to the severe aging level. Next, divide the aging levels of the components, count the proportion of aging levels at all wavelength points, and determine the overall aging level of the component based on the highest proportion level. For example, if 70% of the wavelength points in the spectral data of a certain component belong to the moderate aging level, then it is determined that the overall aging level of this component is moderate aging. Finally, obtain the aging level index of the building component, which includes the aging level, error range, proportion situation, etc., and output the complete aging level evaluation result.

[0080] Please refer to Figure 4 , and the specific steps of S3 are as follows:

[0081] S301: Obtain the aging level index of the building component, analyze the axial force, shear force, and moment distribution of the load-bearing component, analyze the force condition of the component, organize the calculation results, and form the stress distribution data of the load-bearing component;

[0082] Analyze the axial force, shear force, and bending moment distribution of load-bearing components. First, for specific components such as reinforced concrete beams or steel structure columns, extract their aging grade data, and combine with the structural dimensions and load distribution to calculate the axial force. When calculating the axial force, it is necessary to consider the vertical load borne by the component and its own gravity. For example, for a concrete column with a cross-sectional size of 300mm×300mm and a vertical load of 150kN, the calculated axial force value is 150kN. Next, calculate the shear force. The shear force comes from the influence of horizontal loads or support reactions. For example, if the component is subjected to a wind load of 5kN / m and the column height is 3m, the shear force calculation is 5kN / m×3m = 15kN. Subsequently, calculate the bending moment distribution. The bending moment is usually determined by the load and the length of the acting arm. For example, if the acting point of the wind load is 1.5m from the bottom of the column, the bending moment calculation is 15kN×1.5m = 22.5kN·m. To analyze the stress state of the component, it is necessary to compare the calculated axial force, shear force, and bending moment, and determine whether they exceed the allowable range of the material design. For example, if the axial bearing capacity of the concrete column is 200kN, the shear bearing capacity is 25kN, and the bending moment bearing capacity is 30kN·m, then the current calculated values are all within the limit. Organize the calculation results, associate all the stress calculation values with the component aging grade data, and store them in the database according to the numbers of different components to form a complete stress distribution data of the load-bearing components. Finally, output a stress distribution dataset including axial force, shear force, bending moment, and the corresponding aging grade.

[0083] S302: Based on the stress distribution data of load-bearing components, calculate the stress change values of components under the influence of differential loads, call the data of foundation settlement, wind load, and seismic influence, analyze the offset of environmental factors on the mechanical equilibrium state, screen the components with an offset higher than the set threshold, calculate the change value of the bearing capacity under the influence of aging, extract the stress change range under the action of differential loads, and obtain the mechanical equilibrium offset parameter;

[0084] Calculate the stress change values of components under the influence of differential loads. First, obtain the stress calculation values of components under different loads. For example, under normal service loads, the stress in a certain beam section is 10MPa, and after the action of the wind load, the stress increases to 15MPa. Then the stress change value is calculated as 15MPa - 10MPa = 5MPa. Call the data of foundation settlement, wind load, and seismic influence, and extract the influence of each environmental factor on the structural stress. For example, the additional bending moment caused by foundation settlement is calculated as M = Δ×E×I / L, where Δ is the settlement amount, E is the material elastic modulus, I is the cross-sectional moment of inertia, and L is the component length. If a certain column has a settlement of 5mm, E = 3×10 4 MPa, I = 8×10 6 ,L = 3m, then M = 5mm×3×10 4 MPa×8×10 6 / 3m = 400 kN·m, analyze the offset of the mechanical equilibrium state caused by environmental factors. Compare the force change values caused by each environmental factor with the original force value, and calculate the offset. For example, if the moment change caused by settlement is 400 kN·m and the original moment is 22.5 kN·m, then the offset is calculated as 400 kN·m - 22.5 kN·m = 377.5 kN·m. Screen the components with offsets higher than the set threshold. If the set offset threshold is 100 kN·m, then this component is determined to be a target component with a greater impact. Calculate the change value of the bearing capacity under the influence of aging. Through the material properties of the component, calculate its remaining bearing capacity. For example, if the original bearing capacity is 500 kN·m and it is reduced to 450 kN·m under the influence of aging, then the change value of the bearing capacity is calculated as 500 kN·m - 450 kN·m = 50 kN·m. Extract the stress change range under different loadings, and count the stress change intervals of the component under various loadings. For example, if the maximum stress change value of a component is 5 MPa and the minimum stress change value is 1 MPa, then the stress change range is 1 MPa - 5 MPa. Finally, obtain the mechanical equilibrium offset parameter, which includes the stress change value, the influence amount of environmental factors, the change value of the bearing capacity, and the stress change range, and output the complete set of mechanical equilibrium offset parameters.

[0085] S303: Invoke the mechanical equilibrium offset parameter, analyze the stress change trend of the component, calculate the cumulative offset value of the structural form, deduce the structural deformation trend under different aging levels, and obtain the offset trend value of the building structural form;

[0086] The specific formula for the cumulative offset value of the structural form is:

[0087] ;

[0088] Among them, represents the cumulative offset value of the structural form, represents the X-direction displacement coordinate of the component at the th measurement moment, represents the X-direction coordinate of the component at the initial moment, represents the Y-direction displacement coordinate of the component at the th measurement moment, represents the Y-direction coordinate of the component at the initial moment, represents the Z-direction displacement coordinate of the component at the th measurement moment, represents the bending moment influence factor at the th measurement moment, represents the total number of measurement time steps.

[0089] Formula Represents the cumulative offset value of the structural form, including the displacement amounts of the X, Y, and Z coordinate axes and the bending moment influence factor influence.

[0090] and respectively represent the displacement coordinate and the initial coordinate of the component in the X direction at the th measurement moment. These values are obtained through real-time monitoring by precise displacement sensors. For example, in building monitoring, the sensor accuracy can reach 0.01 mm. Assume that the initial X coordinate of a certain monitoring point is 200.00 mm at the first measurement moment, and the displacement coordinate in the X direction becomes 200.05 mm at the next measurement moment.

[0091] and represent the same measured values but in the Y direction. These coordinates are also obtained through measurement by high-precision equipment. Set an actual measurement, is 150.00 mm, is 150.02 mm.

[0092] represents the displacement in the Z direction and is obtained by the same method. Assume is 100.00 mm.

[0093] is the bending moment influence factor, and this parameter is calculated by the structural engineer based on the loading test. If the component under consideration has experienced medium bending moments during the test, can be set to 0.05.

[0094] According to the above settings, the formula for the calculation example is:

[0095] ;

[0096] Further expand the calculation:

[0097] ;

[0098] ;

[0099] ;

[0100] This calculation result shows that after the superposition of the measurement moments, the cumulative offset of the structure under the influence of the bending moment reaches nearly 100 mm. This shows the possible deformation amount that the structure may experience and is an important indicator for the safety monitoring and maintenance of building structures.

[0101] Please refer to Figure 5 for the specific steps of S4:

[0102] S401: Obtain the offset trend value of the building structure form, calculate the principal axis direction, proportion parameter, and edge curvature of the component, screen the components that meet the form measurement criteria, organize the calculation results, and form the geometric form parameters of the components;

[0103] Calculate the principal axis direction, proportion parameter, and edge curvature of the component. First, extract the geometric center coordinates of the component. According to the length direction and the maximum axial dimension of the component, calculate its principal axis direction. For example, for a beam, its length direction is set as the X-axis, and the cross-section height direction is set as the Y-axis, then the principal axis direction can be defined as the X-axis. Next, calculate the proportion parameter. By measuring the length, width, and height of the component, calculate their proportional relationship. For example, a certain component is 3m long, 0.3m wide, and 0.5m high, then its proportion parameter calculation is length-width ratio = 3m / 0.3m = 10, height-width ratio = 0.5m / 0.3m = 1.67. Then, calculate the edge curvature of the component. Extract multiple points on the boundary curve and calculate the change in the tangent slope of adjacent points. For example, for two adjacent points (x1, y1) and (x2, y2) on the edge curve y = f(x) of a certain component, calculate its tangent slope k = (y2 - y1) / (x2 - x1), and then calculate the curvature κ = |d²y / dx²| / (1 + (dy / dx)²)^(3 / 2). If the edge heights of a certain component at x = 1m and x = 2m are 0.3m and 0.35m respectively, then the curvature calculation is κ = |0.05 / (1 + 0.5²)^(3 / 2)|. Screen the components that meet the form measurement criteria. Compare the calculated proportion parameter and curvature value with the set standard value. If the length-width ratio error is within the range of ±5%, and the edge curvature error is less than 0.01, then the component meets the measurement criteria. Organize the calculation results, store the calculated principal axis direction, proportion parameter, and curvature data, and classify them according to the component number. Finally, form the geometric form parameters of the components.

[0104] S402: Based on the geometric form parameters of the components, analyze the geometric adaptability of the components, screen the components that meet the splicing relationship, calculate the connection offset of adjacent components, compare the curvature differences of the component edges, screen the pairs of components with splicing errors within the set threshold range, extract the component combinations with higher adaptability, and obtain the component splicing adaptability parameters;

[0105] First, obtain the geometric shape data of all components, calculate the dimensional differences between adjacent components. For example, if the length, width, and height of adjacent component A are 3m, 0.3m, and 0.5m respectively, and the length, width, and height of component B are 3.1m, 0.3m, and 0.5m respectively, then the dimensional differences are calculated as ΔL = |3.1m - 3m| = 0.1m, ΔW = |0.3m - 0.3m| = 0m, ΔH = |0.5m - 0.5m| = 0m. Screen the components that meet the splicing relationship, set the splicing error threshold. For example, if the length error is less than 0.2m, the width error is less than 0.05m, and the height error is less than 0.05m, then it is determined that components A and B can be spliced. Calculate the connection offset of adjacent components, obtain the connection edge coordinates of the two components. For example, if the center point of the connection edge of component A is (1.5m, 0.25m) and the center point of the connection edge of component B is (1.55m, 0.25m), then the offset is calculated as ΔX = |1.55m - 1.5m| = 0.05m, ΔY = |0.25m - 0.25m| = 0m. Compare the curvature differences at the edges of the components, calculate the curvature change at the splicing boundary. For example, if the edge curvature of component A is 0.02 and the edge curvature of component B is 0.025, then the curvature difference Δκ = |0.025 - 0.02| = 0.005. Screen the pairs of components with splicing errors within the set threshold range. If the set curvature error threshold is 0.01, then A and B can be spliced. Extract the component combinations with higher adaptability, count the component combinations that meet the splicing conditions, and record parameters such as the offset and curvature change at the splicing boundary. Finally, obtain the component splicing adaptation parameters.

[0106] S403: Invoke the component splicing adaptation parameters, combine with the morphological feature data in the style database, calculate the matching degree between the component morphology and the style benchmark, screen the components with a matching degree higher than the set standard, and obtain the building component morphology adaptation parameters;

[0107] The specific calculation formula for the matching degree between the building component morphology and the set style benchmark is:

[0108] ;

[0109] Among them, represents the matching degree between the building component morphology and the set style benchmark, represents the numerical value of the actual morphological parameter of the th component (such as length-width ratio, height-width ratio, etc.), represents the numerical value of the benchmark morphological parameter in the th item in the style database, represents the weight coefficient of the th morphological parameter, represents the numerical value of the actual curvature parameter of the th component, represents the The numerical value of the reference curvature parameter in the item style database represents the adjustment coefficient of the th curvature parameter, represents the total number of shape parameter items,

[0110] The formula calculates the matching degree between the shape of the building component and the set style reference. This matching degree is obtained by comparing the differences between the actual shape parameters of the component and the shape parameters of the style reference, and weighting according to the importance of each parameter.

[0111] Calculation of shape parameters:

[0112] represents the th actually measured shape parameter, such as the length-width ratio. If the actual length of the component is 300 cm and the width is 100 cm, then the length-width ratio of

[0113] is 3.0.

[0114] is the weight of this shape parameter, set according to the design importance. For the length-width ratio, the weight may be 1.5.

[0115] Calculation of curvature parameters:

[0116] and are the actually measured and reference curvature parameters respectively. Set to 0.02 (unitless), while is set to 0.015.

[0117] is the adjustment coefficient of the curvature, which can be set to 2.0 according to the sensitivity of the curvature change.

[0118] Example: Assume that there are two shape parameters and one curvature parameter in the system for comparison. Shape parameters: actual length-width ratios of 3.0 and 4.0, reference ratios of 2.5 and 3.5, weights of 1.5 and 2.0. Curvature parameter: actual curvature of 0.02, reference curvature of 0.015, adjustment coefficient of 2.0.

[0119] Calculation process:

[0120] ;

[0121] ;

[0122] ;

[0123] ;

[0124] The result shows that the given component has a style matching score of 0.5825. A lower score indicates a significant difference between the actual component form and the set style benchmark, and it may be necessary to further adjust the design or select different components to better conform to the predetermined style.

[0125] Please refer to Figure 6 , and the specific steps of S5 are as follows:

[0126] S501: Invoke the building component form adaptation parameters, extract the geometric information of the building components from the BIM database, screen the components that meet the splicing relationship, and organize the data to form a building component geometric information set;

[0127] Extract the geometric information of the building components from the BIM database. First, retrieve the building component data in the BIM database to obtain the length, width, height, and edge curvature parameters of each component. For example, the length, width, and height of a certain component are 3m, 0.3m, and 0.5m respectively, and the edge curvature is 0.02. Then, screen the components that meet the splicing relationship, extract the geometric form parameters of all components, compare the component dimensions, curvatures, and the offset of the connecting edges, and set the splicing threshold. If the length, width, and height error is less than ±5cm and the curvature error is less than 0.01, it is determined that the component can be spliced. For example, the size of component A is 3m × 0.3m × 0.5m, and the size of component B is 3.02m × 0.3m × 0.5m, with errors ΔL = 0.02m, ΔW = 0m, ΔH = 0m, meeting the splicing conditions. After organizing the data of the components that meet the splicing relationship, finally output a building component geometric information set including component numbers, dimension parameters, curvature parameters, and splicing adaptation relationships.

[0128] S502: Based on the building component geometric information set, adjust the component docking relationship, calculate the connection offset of adjacent components, screen the pairs of components with offsets within the set threshold range, optimize the component splicing order, adjust the spatial positioning parameters of the structural components, extract the optimized component combination, and obtain the optimized component splicing parameters;

[0129] First, based on the splicing adaptation parameters of the components, obtain all component combinations that meet the splicing relationship and adjust the splicing order. For example, if component A and component B, and component B and component C meet the splicing conditions, then preferably adjust the order to A - B - C to minimize the splicing error. Calculate the connection offset of adjacent components and extract the splicing point coordinates of two adjacent components. For example, if the center coordinate of the connection point of component A is (1.5m, 0.25m) and the center coordinate of the connection point of component B is (1.55m, 0.25m), then the offset calculation is ΔX = |1.55m - 1.5m| = 0.05m, ΔY = 0m. Screen the pairs of components whose offsets are within the set threshold range. Set the splicing error threshold, such as ΔX ≤ 0.1m, ΔY ≤ 0.05m, then determine that component A and B can be spliced. Optimize the component splicing order and arrange the component combination with the smallest splicing offset in the front. For example, if the offset of component A - B is 0.05m and the offset of component B - C is 0.08m, then keep the order of A - B - C unchanged. Adjust the spatial positioning parameters of the structural components and correct the spatial coordinates of the components according to the splicing offset. For example, if the offset of component B exceeds the set range, then adjust the X coordinate of B to reduce the splicing offset with A to 0.02m. Extract the optimized component combination, store the adjusted splicing data in the database, and finally obtain the optimized component splicing parameters, including the adjusted splicing order, the corrected spatial positioning parameters, and the final connection offset data.

[0130] S503: Call the optimized component splicing parameters, integrate the geometric information of the optimized components, adjust the overall building structure relationship, organize the spatial component data, and establish the building model reconstruction steps;

[0131] First, obtain the length, width, height, splicing point coordinates, and edge curvature data of all components after adjustment, rearrange the component numbers to conform to the optimized splicing order. For example, the component numbers are adjusted from A - B - C to A - C - B to reduce the overall splicing error. Adjust the overall building structure relationship, calculate the connection offset between all components, and correct the spatial coordinates of the components that exceed the threshold. For example, if the splicing offset of component C relative to B is 0.12m, exceeding the set threshold of 0.1m, then adjust the X coordinate of C by 0.02m to reduce the splicing error to 0.1m. Organize the spatial component data, store the spatial coordinates of all optimized components, and summarize the splicing status and adjustment information of each component. Finally, establish the building model reconstruction steps, which include the optimized splicing order, spatial coordinate correction, component adjustment information, and complete building structure relationship data, and output the complete building model reconstruction data set.

[0132] Please refer to Figure 7 , a BIM - based historical building model construction system, including:

[0133] The spectral feature extraction module obtains the spectral reflectance data of the surface material of building components, collects the spectral reflectance curve, extracts the peak absorption rate, boundary change points and average absorption rate, integrates the spectral features to form time series data, and obtains the spectral feature parameters of the components;

[0134] Based on the spectral feature parameters of the components, the aging assessment module calculates the absorption rate at the wavelength points, analyzes the mean square error and curve fitting error of the spectral data, and conducts a comparative analysis in combination with the aging model to divide the aging grade threshold and obtain the aging grade index of the building components;

[0135] Using the aging grade index of the building components, the mechanical stability analysis module analyzes the axial force, shear force and bending moment distribution of the load-bearing components, calculates the numerical value of the stress change of the components, and combines the foundation settlement, wind load and seismic effects to evaluate the mechanical equilibrium state through environmental factors, deduce the structural deformation trend, and obtain the building structure form offset trend value;

[0136] According to the building structure form offset trend value, the form matching calculation module calculates the main axis direction, proportional parameters and edge curvature of the components, analyzes the geometric adaptability, and compares the form features in combination with the style database to obtain the form adaptability parameters of the building components;

[0137] The BIM model reconstruction module calls the form adaptability parameters of the building components, extracts the building geometric information from the BIM database, adjusts the component docking relationship, optimizes the overall structure, and establishes the building model reconstruction steps.

[0138] As described above, it is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A method for constructing a historical building model based on BIM, characterized in that: The following steps are involved: S1: Obtain the surface spectral reflectance data of building components, set the detection range, extract spectral features, integrate to form time series data, and obtain component spectral feature parameters; S2: Based on the spectral characteristic parameters of the component, calculate the change in absorbance, analyze the mean square error of the spectral data, divide the aging grade based on the aging model, and obtain the aging grade index of the building component; S3: using the building component aging grade index, analyzing the axial force, shear force, and bending moment of the load-bearing components, combining foundation settlement, wind load, and earthquake impact, evaluating the mechanical equilibrium state, calculating the change in bearing capacity under the influence of aging, deriving the structural deformation trend, and obtaining the trend value of the building structure morphology deviation; S4: Calculate component geometric parameters according to the building structure morphology deviation trend value, select splicing relationships, compare morphological features with the style database, and obtain building component morphology adaptation parameters; S5: calling the building component morphology adaptation parameters, extracting building geometry information from the BIM database, adjusting the docking relationship, optimizing the structure, and establishing a building model reconstruction step; The specific steps of S3 are: S301: Obtain the aging grade index of the building component, analyze the axial force, shear force and bending moment distribution of the load-bearing component, analyze the stress condition of the component, sort out the calculation results, and form stress distribution data of the load-bearing component; S302: Based on the stress distribution data of the load-bearing components, calculate the stress change value of the components under the influence of differentiated loads, call the foundation settlement, wind load and earthquake impact data, analyze the offset of the mechanical equilibrium state caused by environmental factors, select components with offsets higher than a set threshold, calculate the bearing capacity change value under the influence of aging, extract the stress change range under the action of differentiated loads, and obtain the mechanical equilibrium offset parameter; S303: calling the mechanical equilibrium offset parameter, analyzing the stress change trend of the component, calculating the cumulative offset value of the structural form, deriving the structural deformation trend under the differentiated aging level, and obtaining the building structure form offset trend value; The specific steps of S4 are: S401: Obtain the deviation trend value of the building structure morphology, calculate the main axis direction, proportion parameters and edge curvature of the component, select the components that meet the morphology measurement standard, sort out the calculation results, and form the component geometric morphology parameters; S402: Based on the component geometric morphology parameters, analyze the component geometric adaptability, select components that meet the splicing relationship, calculate the connection offset of adjacent components, compare the curvature difference of component edges, select component pairs whose splicing errors are within a set threshold range, extract component combinations with higher adaptability, and obtain component splicing adaptation parameters; S403: calling the component splicing adaptation parameters, combining the morphological feature data of the style database, calculating the matching degree between the component morphology and the style benchmark, screening components with matching degrees higher than the set standard, and obtaining the building component morphological adaptation parameters.

2. The method for constructing a historical building model based on BIM according to claim 1, characterized in that: The component spectral characteristic parameters include spectral absorption rate characteristic values, spectral boundary change points, and spectral time series data; the building component aging grade indicators include aging classification thresholds, spectral offsets, and material decay rates; the building structure morphology offset trend values ​​include structural stability offsets, force balance change values, and morphology deformation prediction parameters; the building component morphology adaptation parameters include geometric matching, component splicing adaptability, and style feature comparison results; the building model reconstruction steps include component docking adjustment, geometric structure optimization, and overall building data integration.

3. The method for constructing a historical building model based on BIM according to claim 1, characterized in that: The specific steps of obtaining the surface spectral reflectance data of building components, setting the detection range, extracting spectral features, integrating to form time series data, and obtaining the spectral characteristic parameters of components are as follows: S101: Acquire spectral reflectance data of the surface material of the building component, set the detection range, identify the wavelength range and resolution, call the set range to measure the spectral reflectance, and organize the data to form spectral reflectance curve data; S102: Based on the spectral reflectance curve data, extract the absorbance and corresponding wavelength value of the absorption peak, calculate the absorbance difference of adjacent absorption peaks, screen the boundary points whose change amplitude is greater than the set threshold, obtain the boundary change point data of the spectral curve, calculate the overall absorbance mean, integrate the characteristic absorption information of the spectral curve, and obtain the spectral characteristic absorption parameters; S103: calling the spectral characteristic absorption parameters, sorting the spectral parameters according to the time series, calculating the characteristic changes between the time series points, extracting the change range and the stable interval, and integrating them to form the component spectral characteristic parameters.

4. The method for constructing a historical building model based on BIM according to claim 1, characterized in that: Based on the spectral characteristic parameters of the component, the specific steps of calculating the change in absorbance, analyzing the mean square error of the spectral data, and dividing the aging grade in combination with the aging model to obtain the aging grade index of the building component are as follows: S201: Acquire the spectral characteristic parameters of the component, select the wavelength point of the spectral curve, calculate the absorptivity of the wavelength point, sort out the absorptivity data, and form wavelength absorptivity distribution data; S202: Based on the wavelength absorption rate distribution data, analyze the mean square error of the spectrum curve, analyze the dispersion degree of the absorption rate, calculate the error value of the fitting curve, compare the deviation degree between the curve and the measured data, screen the area where the error is higher than the set threshold, extract the decay characteristics of the spectrum curve, and obtain the spectrum decay trend parameter; S203: calling the spectral decay trend parameter, comparing the threshold interval under the differentiated aging level, screening the spectral parameters that meet the aging level boundary, dividing the aging level of the component, and obtaining the aging level index of the building component.

5. The method for constructing a historical building model based on BIM according to claim 1, characterized in that: The calculation formula of the cumulative offset value of the structural form is specifically: ； in, represents the cumulative deviation value of the structural morphology, Representative The X-direction displacement coordinates of the component at the measurement moment, Represents the X-direction coordinate of the component at the initial moment, Representative The Y-direction displacement coordinate of the component at the measurement moment, Represents the Y coordinate of the component at the initial moment, Representative The Z-direction displacement coordinates of the component at the measurement moment, Representative The bending moment influence factor at each measurement moment, Represents the total number of measurement time steps.

6. The method for constructing a historical building model based on BIM according to claim 1, characterized in that: The specific calculation formula for the matching degree between the building component form and the set style benchmark is: ； in, Represents the degree of match between the form of the building components and the set style benchmark, Representative The actual morphological parameter value of the item component, Representative The value of the base morphological parameters in the item style database, Representative The weight coefficient of the item shape parameter, Representative The actual curvature parameter value of the item component, Representative The base curvature parameter value in the style database, Representative The adjustment coefficient of the curvature parameter, Represents the total number of morphological parameter items, Represents the total number of curvature parameter items.

7. The method for constructing a historical building model based on BIM according to claim 1, characterized in that: The specific steps of calling the building component morphology adaptation parameters, extracting building geometry information from the BIM database, adjusting the docking relationship, optimizing the structure, and establishing the building model reconstruction step are: S501: calling the building component morphology adaptation parameter, extracting geometric information of the building components from the BIM database, selecting components that meet the splicing relationship, and arranging the data to form a building component geometric information set; S502: Based on the building component geometric information set, adjusting the component docking relationship, calculating the connection offset of adjacent components, selecting component pairs whose offsets are within a set threshold range, optimizing the component splicing sequence, adjusting the spatial positioning parameters of the structural components, extracting the optimized component combination, and obtaining the optimized component splicing parameters; S503: calling the optimized component splicing parameters, integrating the geometric information of the optimized components, adjusting the overall building structure relationship, sorting out the spatial component data, and establishing a building model reconstruction step.

8. A BIM-based historical building model construction system, which is used to execute the BIM-based historical building model construction method according to any one of claims 1 to 7, the system comprising: The spectral feature extraction module obtains the spectral reflectance data of the surface materials of building components, collects the spectral reflectance curve, extracts the peak absorptivity, boundary change points and average absorptivity, integrates the spectral features to form time series data, and obtains the spectral feature parameters of the components; The aging assessment module calculates the absorptivity of the wavelength point based on the spectral characteristic parameters of the component, analyzes the mean square error and curve fitting error of the spectral data, performs comparative analysis in combination with the aging model, divides the aging level threshold, and obtains the aging level index of the building component; The mechanical stability analysis module uses the building component aging grade index to analyze the axial force, shear force and bending moment distribution of the load-bearing components, calculates the stress change value of the components, combines foundation settlement, wind load, earthquake influence, evaluates the mechanical equilibrium state through environmental factors, derives the structural deformation trend, and obtains the trend value of the building structure morphology deviation; The morphology matching calculation module calculates the main axis direction, proportion parameters, and edge curvature of the component according to the deviation trend value of the building structure morphology, analyzes the geometric adaptability, compares the morphological features with the style database, and obtains the morphological adaptation parameters of the building component; The BIM model reconstruction module calls the building component morphology adaptation parameters, extracts building geometry information from the BIM database, adjusts the component docking relationship, optimizes the overall structure, and establishes a building model reconstruction step.

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