CN110750830A - Wood structure ancient building health state assessment method based on normal cloud model - Google Patents
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Abstract
The invention discloses a wood structure ancient building health state assessment method based on a normal cloud model, which comprises the following steps: designing an organization mode of an ancient building structure model; collecting relevant data of the current situation of the historic building; performing spatial clustering, structure extraction and model reconstruction based on a multi-constraint knowledge rule base according to the ancient building structure model organization mode and the related data; rebuilding a spatial calculation model driven based on a knowledge rule, and converting the spatial calculation model into a first finite element analysis model; and respectively carrying out quantitative calculation and analysis based on the first finite element analysis model, carrying out uncertain row evaluation based on the cloud model, and outputting an evaluation result. The method is based on a self-designed health state evaluation modeling process, combines qualitative estimation and accurate quantification in summarizing an ancient building health state index evaluation system and determining a standard cloud model, and effectively solves the important uncertainty problem under the guidance of an ancient building safety evaluation standard.
Description
Technical Field
The invention relates to the technical field of building monitoring, in particular to a wood structure ancient building health state assessment method based on a normal cloud model.
Background
The protection of cultural heritage can strengthen common memory of the country, establish national self-confidence and inherit to display national culture, and is a great requirement of the country, the wood structure ancient architecture is used as a material cultural heritage crystal unique to China and even the world, and is influenced by external loads such as climate change, human activities, earthquakes and the like, internal factors such as wood aging, fatigue and the like for hundreds of years or even thousands of years, and the safety performance is continuously reduced, so that the evaluation of the whole health state of the wood structure is very important. However, the evaluation level of the health state of the wooden ancient building is higher, the existing problems of the ancient building can be ignored, safety accidents are caused, and the loss which is difficult to recover is caused; otherwise, economic waste can be caused by adopting excessive reinforcement precautionary measures.
Why is the structural status of the wooden structure historic building not correctly evaluated? On one hand, because ancient architecture structures in China are various in form and complex in structure, existing structure analysis objects are not clear, and on the more important hand, because of the limitation of detection conditions and the related requirements of cultural heritage protection, partial components cannot be detected by using instruments, or even if the detection is possible, equipment precision problems exist, so that large measurement errors exist, so-called 'grey information' or 'poor information' greatly hinder the normal development of the safety evaluation work of the ancient architectures of the existing wood structures.
The key points of the method are that a comprehensive and effective evaluation mode is not adopted, accurate cognition on multiple dimensions, multiple visual angles and multiple granularities of the ancient building entity is lacked, and particularly, a fine modeling scheme for the structural characteristics of the ancient building entity, multi-source massive spatial data model organization and systematic research on a comprehensive evaluation means of the wood structure under the action of randomness and fuzziness are lacked.
From the specification of the ancient building safety assessment industry, the current standards mainly comprise a civil building reliability identification standard (GB50292-2015) [12], "a first part of an ancient building structure safety identification technical specification, namely a wood structure (DB11/T1190.1-2015) [13] and an ancient building wood structure maintenance and reinforcement technical specification (GB 50165-92) and the like, the specifications are usually qualitatively identified as a main specification and quantitatively identified as an auxiliary specification, and detection is generally carried out in a sampling and observation mode, so that the problem that part of components cannot be detected or cannot be accurately and quantitatively detected exists; from the ancient building evaluation and analysis method, an analytic hierarchy process, a gray fuzzy analysis method, a dead load experiment evaluation method, a gray whitening weight function clustering method, a damage condition index method and the like are generally adopted, the contents of the evaluation of the ancient building safety quantitative indexes are less, and the safety of the whole structure of the ancient building cannot be completely and efficiently evaluated.
The spatial data model is the basis for spatial data expression and analysis. In the last three decades, scholars at home and abroad propose more than 20 three-dimensional space data models aiming at the research of various three-dimensional space objects. The method is still one of the challenging research subjects in the field of structural engineering until now.
In summary, no model is designed according to the national important requirement of wood structure ancient building health assessment, and no comprehensive and efficient ancient building health assessment scheme is provided.
Disclosure of Invention
In view of the problems, the invention provides a normal cloud model-based method for evaluating the health state of the wooden ancient architecture, which combines qualitative estimation and accurate quantification and effectively solves the important uncertainty problem under the guidance of the ancient architecture safety evaluation specification.
The invention provides a wood structure ancient building health state assessment method based on a normal cloud model, which comprises the following steps:
designing an organization mode of an ancient building structure model;
collecting relevant data of the current situation of the historic building;
performing spatial clustering, structure extraction and model reconstruction based on a multi-constraint knowledge rule base according to the ancient building structure model organization mode and the related data;
rebuilding a spatial calculation model driven based on a knowledge rule, and converting the spatial calculation model into a first finite element analysis model;
and respectively carrying out quantitative calculation and analysis based on the first finite element analysis model, carrying out uncertain row evaluation based on the cloud model, and outputting an evaluation result.
In one embodiment, the quantitative calculation and analysis, the uncertainty evaluation based on the cloud model, and the evaluation result output respectively comprise:
comparing internal force with deformation and checking bearing capacity by a vibration type decomposition method and a power time-course method to obtain accurate evaluation of natural weathering, earthquake resistance and fire resistance of the historic building timber structure;
converting assessment data of a comment set, accurate quantification and expert qualitative assessment into a cloud model, namely determining digital characteristic values of a standard cloud, an evaluation cloud and a comprehensive cloud; standard cloud digital characteristic value C to be applied to each comment setVi(ExVi，EnVi，HeVi) Calculated by the following formula (1):
(1) in the formula: 1,2, … … 5; x is the number ofimax，ximinThe upper limit value and the lower limit value of each comment set are respectively set; k reflects the linear relation between entropy and super entropy, and k is 0.3;
obtaining expert scores, respectively evaluating m parts by n experts, combining quantitative calculation evaluation result weights, and calculating evaluation cloud digital characteristic values C of all components by adopting formula (2)Ui(ExUi，EnUi，HeUi)；
(2) In the formula: 1,2,. m; j is 1,2,. n; x is the number ofijScoring data for the jth expert for the ith component; s is a sample variance;
comprehensive evaluation of the historic building structure comprehensive cloud and the result comprehensive cloud are obtained by adopting a fuzzy comprehensive evaluation method, a cloud model theory is combined with the fuzzy comprehensive evaluation method, the historic building health state information with randomness and fuzziness is organically processed, and the health state grade is accurately evaluated.
In one embodiment, the evaluation result weight is calculated in combination with quantification, including:
determining the weight of the evaluation index by adopting a combined weighting method: as shown in formula (3):
in the formula, wj' weights calculated for each item by the analytic hierarchy process; w is aj *Weights calculated for the entropy weights; w is ajThe weights obtained by the combined weighting method (j ═ 1,2, …, m).
In one embodiment, the designing the historic building structure model organization mode comprises:
constructing a data structure of the historic building; the data of the data structure is as follows: collecting multi-source fine spatial data and original data collected and sorted by existing data;
designing a conceptual model, a logic model and a physical model;
constructing a spatial index mechanism;
generating an organization mode of the ancient building structure model; the historic building structure model organization mode comprises the following attributes: structural features, material features, structural relationships, geometric relationships, and topological relationships.
In one embodiment, the collecting data related to the current status of the ancient architecture comprises:
and collecting point cloud data, GIS data, BIM data, CAD data, multispectral data, stress wave data, photogrammetric data images and a second finite element model of the ancient building.
In one embodiment, the conceptual model includes: semantic constraints, unit decomposition, geometric expression and model support;
the semantic constraints include: the building comprises a column frame layer, a paving layer, a roof layer and a platform base layer;
the unit decomposition includes: a point unit, a frame unit, a face unit and a body unit;
the geometric representation includes: points, lines, faces and volumes;
the model support comprises: a point cloud model, a B-REP model, a TIN model and a third finite element model.
In one embodiment, the logic model comprises: member cross-section, member material, member unit and member relationship.
In one embodiment, the source of the data structure includes: a point cloud model, a NURBS model, a CSG model, a 3D-TIN model, and an original finite element analysis model.
In one embodiment, the mechanism for constructing a spatial index comprises: and establishing a QMBB, 3D-R and QMBB tree mixed index formed by the octree, the three-dimensional K-D tree, the quadtree and the minimum bounding box.
In one embodiment, converting the spatial computational model to a first finite element analysis model comprises:
determining a minimum outer packing box of the point cloud according to the space calculation model;
dividing grids and quadrangles according to preset rules;
and optimizing the quadrangle to realize conversion into a first finite element analysis model.
The technical scheme provided by the embodiment of the invention has the beneficial effects that at least:
the wood structure ancient building health state assessment method based on the normal cloud model provided by the embodiment of the invention is based on a self-designed health state assessment modeling process, combines qualitative estimation and accurate quantification in summarizing an ancient building health state index assessment system and determining a standard cloud model, and effectively solves the important uncertainty problem under the guidance of an ancient building safety assessment standard.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a flowchart of a method for evaluating health status of a wood-structure ancient building based on a normal cloud model according to an embodiment of the present invention;
fig. 2 is a schematic diagram of an evaluation index system provided in an embodiment of the present invention.
Fig. 3 is a schematic diagram of a minimum outsourcing box of a three-dimensional point cloud according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of mesh partitioning according to an embodiment of the present invention.
Fig. 5a to 5e are schematic diagrams of different types of quadrilateral divisions according to embodiments of the present invention.
Fig. 6 is a schematic diagram for determining the concavity and convexity of a quadrilateral according to an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The wood structure ancient building health state assessment method based on the normal cloud model provided by the embodiment of the invention is shown in figure 1 and comprises the following steps:
s1, designing an organization mode of the ancient building structure model;
s2, collecting relevant data of the current situation of the historic building;
s3, according to the ancient building structure model organization mode and the related data, based on a multi-constraint knowledge rule base, carrying out spatial clustering, structure extraction and model reconstruction;
s4, reconstructing a spatial calculation model driven based on a knowledge rule, and converting the spatial calculation model into a first finite element analysis model;
and S5, respectively carrying out quantitative calculation and analysis based on the first finite element analysis model, carrying out uncertain row evaluation based on the cloud model, and outputting an evaluation result.
The method is based on original design data of the historic building and structural information such as the whole damage of the current situation of the historic building, and takes the cooperative coupling of the key technologies of the surveying and mapping subject and the civil subject as a means to establish a set of brand-new multidimensional space data model and a structural state analysis model, and endows the historic building entity with the perception calculation capability on the change of the space environment; the first finite element analysis model for comprehensive, complete and accurate analysis can be provided for the subsequent ancient building structure analysis. Based on the first finite element analysis model, qualitative estimation and accurate quantification are combined in summarizing an ancient building health state index evaluation system and determining a standard cloud model, and the important uncertainty problem is effectively solved under the guidance of an ancient building safety evaluation specification.
In one embodiment, the internal force and deformation comparison, bearing capacity checking calculation and the like are carried out by a vibration mode decomposition method and a power time-course method, so that the accurate evaluation of the natural weathering, earthquake resistance, fire resistance and other performances of the historic building timber structure is obtained.
And for the indexes which cannot be accurately evaluated, evaluating by adopting an expert scoring mode, and carrying out comprehensive evaluation on the health state of the historic building by combining the accurate quantitative calculation and analysis indexes and the indexes which cannot be accurately evaluated. Comprehensively analyzing the evaluation factors.
As shown in fig. 2, the wood structure safety evaluation flow and the key points are as follows:
division principle of identification units, subunits and building blocks:
the identification unit is divided into one or a plurality of independent sections according to the structural characteristics of the historic building wood structure and the type of the bearing system, and each section is 1 identification unit. The identification units are divided so as to ensure that the independence and continuity of the structural force transmission system and the mutual influence among the sections are minimum.
A subunit refers to a member or combination of members that can alone assume a particular function in an ancient building timber structure. The sub-units are divided so as to ensure the integrity of the components and the continuity of a force transmission system. The structure can be divided into three types of foundation foundations, upper bearing wood frames and an enclosure structure according to the stress characteristics by the division of the subunits.
A building block refers to a basic identification unit which can be further subdivided in a subunit, and can be a single piece or an assembly. The division of the components preferably satisfies the following requirements:
1) the independent column foundation is 1 component based on a single foundation of 1 column; the strip foundation should be 1 member in 1 natural compartment, 1 axis length.
2) The wall body should be 1 layer high, 1 axis length of 1 nature room is 1 component.
3) The column should be 1 layer high with 1 member.
4) The beam, purlin, rafter, purlin, joist, etc. should be 1 span, 1 as 1 member.
5) The panel should have 1 component in 1 natural compartment area.
The safety grade classification principle of the authentication unit, the sub-unit and the component is as follows:
the safety grade of the identification unit is preferably divided into the bearing capacity and the stability of the whole structure, whether the weak part affects the whole safety and the like, the safety grade of the sub-unit is preferably divided into the bearing capacity and the completeness of the component, and the safety grade of the component is preferably divided into the bearing capacity, the deformability, the damage condition and the like of the component.
The proposed historic building timber structure safety rating hierarchy criteria are shown in table 1.
TABLE 1 Wood Structure ancient building safety grading Standard
Table 1 Classification standard of ancient timber buildings safetygrades
In one embodiment, the step S4 of converting the spatial calculation model into the first finite element analysis model includes the steps of:
1 determining the minimum envelope of a point cloud
The bounding box is also called an external minimum rectangle, and is an algorithm for solving an optimal bounding space of a discrete point set, and common bounding box algorithms include an AABB bounding box, a bounding sphere, a directional bounding box OBB and a fixed-direction convex hull FDH. Fig. 3 is a schematic diagram of a minimum outsourcing box of a three-dimensional point cloud.
2 dividing grid
The mesh size is set according to the point cloud resolution, assuming that the point cloud resolution is 1mm, the mesh resolution can be set to 2mm, and when the length of the mesh cannot be exactly divided into complete meshes, the remaining small meshes are retained, as shown in fig. 4 below.
3 dividing quadrangle
After the grids are divided, the point clouds are randomly distributed in each grid, and the connecting points and the grid vertexes form a quadrangle. Due to the uneven distribution of the point clouds in the individual nets, the following situations may arise:
3.1 there is only one point in the grid
3.2 there are two points in the grid
3.3 three points in the grid
3.4 four points in the grid
3.5 multiple points in the grid
When there are four uniformly distributed points in the grid, a regular quadrilateral is most easily divided, as shown in fig. 5a, so for the first three cases, a point-complementing rule is made to complement the points in the grid into four points. And (3) calculating the normal direction of the grid, and drawing a plane perpendicular to the normal direction through known points in the normal direction, adding points into the plane as shown in the following figure 5b, wherein the distances between the points are consistent as much as possible, and dividing the quadrangle by adopting the method of figure 5 a.
If there are multiple points in the grid, the point cloud in each grid is fitted with a BUNBS surface, and there are fewer points in each grid, and the fitting is faster, just like the vertices of a quadrilateral, as shown in fig. 5 c.
For four points in the grid, the distribution of the points is judged, when the four points are distributed uniformly, the quadrangle can be directly divided, if the points are concentrated or dispersed near the grid boundary, for example, if the side length of the quadrangle is directly divided to be too short in fig. 5d and 5e, the quadrangle is fitted by using a NURBS curved surface.
4 quadrilateral division rule:
4.1 convexo-concave nature divided into convex quadrangles;
judging the convexity and concavity of the quadrangle through the quality of the triangle, wherein the quality of the triangle ABC can be measured by the following formula a:
assuming a1, a2, a3, a4 are the a values of the four triangles and a1> a2> a3> a4, the deformation factor β of the quadrilateral can be represented by the following equation:
when the tetragon ABCD is identified in a counterclockwise trend, it is a triangle when 0< β <1 is a convex tetragon, and β <0 is a concave tetragon, and β is 0, as shown in fig. 6.
4.2 side length: the side length is moderate, the maximum and minimum value of the side length is set, and the quadrangle is divided in the range
4.3 boundary: connecting mesh vertices within boundaries
Calculating the normal direction of the point cloud, determining the boundary of the point cloud, and calculating the included angle between the normal direction of the boundary point cloud and the grid vertex α, when α is greater than 90 degrees, judging the boundary to be inside, and when α is less than 90 degrees, judging the boundary to be outside;
5 optimization quadrangle
The quality of the quadrilateral grid is measured by two indexes
1 unit internal angle: the more cells with an internal angle close to 90 degrees, the better the grid quality
2 rule node (node with the number of surrounding cells being 4): the more regular nodes in the grid, the better the grid quality
Structured grids are ideal grids, but only apply to regularly shaped areas. For any geometric shape, an unstructured grid is usually formed, the quality is difficult to guarantee, the initial grid needs to be optimized, a topological optimization method is adopted, the number of irregular nodes in the grid is reduced, the grid form is close to that of the structured grid, and the quality of the grid is improved.
The area grid repartitioning method roughly comprises the following processes: two irregular nodes are selected, the shortest path of the two nodes is used as a skeleton, and a regular grid unit only containing one irregular node is regenerated through region growing to replace an original grid. Therefore, the number of irregular nodes is gradually reduced, and the grid quality is continuously optimized.
In one embodiment, in step S5, the performing the quantitative calculation and analysis, the performing the uncertainty evaluation based on the cloud model, and outputting the evaluation result respectively includes:
comparing internal force with deformation and checking bearing capacity by a vibration type decomposition method and a power time-course method to obtain accurate evaluation of natural weathering, earthquake resistance and fire resistance of the historic building timber structure;
converting assessment data of a comment set, accurate quantification and expert qualitative assessment into a cloud model, namely determining digital characteristic values of a standard cloud, an evaluation cloud and a comprehensive cloud; standard cloud digital characteristic value C to be applied to each comment setVi(ExVi，EnVi，HeVi) Calculated by the following formula (1):
(1) in the formula: 1,2, … … 5; x is the number ofimax，ximinThe upper limit value and the lower limit value of each comment set are respectively set; k reflects the linear relation between entropy and super entropy, and k is 0.3;
obtaining expert scores, respectively evaluating m parts by n experts, combining quantitative calculation evaluation result weights, and calculating evaluation cloud digital characteristic values C of all components by adopting formula (2)Ui(ExUi，EnUi，HeUi)；
(2) In the formula: 1,2,. m; j is 1,2,. n; x is the number ofijScoring data for the jth expert for the ith component; s is a sample variance;
and finally, comprehensively evaluating the historic building structure comprehensive cloud and the result comprehensive cloud, wherein the two clouds are obtained by adopting a fuzzy comprehensive evaluation method, the historic building evaluation index systems with different structure styles are possibly different, the specific weight and the algorithm are determined after experimental verification, the cloud model theory is combined with the fuzzy comprehensive evaluation method, the historic building health state information with randomness and fuzziness is organically processed, and the health state grade is accurately evaluated.
In one embodiment, the current methods for determining the weight of the evaluation index can be divided into subjective weighting and objective weighting. The core of the subjective weighting method is that a plurality of experts carry out weighting on the importance of each index according to experience, the expert knowledge is fully utilized, the actual situation is reflected to a certain extent, but the subjectivity is strong. The objective weighting method is based on objective information reflected by equipment indexes, determines the weight among all characteristic parameters and strictly avoids the influence of artificial subjective factors. However, the weights determined by such methods are completely dependent on objective data, and the correlation between the indexes cannot be considered sufficiently, and sometimes the obtained weights are completely different from the importance of the evaluation indexes themselves. Therefore, the reasonable weighting method should weight the decision index based on the internal rules of objective information and expert experience, so as to achieve the objective and subjective unification. Therefore, the method has the advantages of 2 weighting methods, makes up the defects of the 2 weighting methods, and is more scientific and accurate in weight value. The analytic hierarchy process is an effective method for objectively describing human subjective judgment, and is most widely applied to a subjective weighting method. The entropy weight method is an objective weighting method, and uses the original data of an evaluation object as a basis, and determines the relevance between evaluation indexes by calculating the information entropy between the evaluation indexes to obtain the weight with objective significance. Therefore, in this embodiment, an analytic hierarchy process and an entropy weight process are selected, and a multiplicative integration method is used to construct a combined empowerment as shown in formula (3):
in the formula uj' weights calculated for each item by the analytic hierarchy process;wj *weights calculated for the entropy weights; w is ajThe weights obtained by the combined weighting method (j ═ 1,2, …, m).
A normal cloud model similarity measurement technology: obtaining standard cloud C through computingV(ExV，EnV，HeV) And after the cloud C (Ex, En, He) is synthesized, a normal cloud generator is adopted to establish a membership cloud model, and the similarity mu is obtained through the following steps: generating a normal random number En' ═ NORM (En, He)2) And xi＝NORM(Ex，En′i 2) N, calculating xiIn standard cloud CV(ExV，EnV，HeV) Degree of certainty in
With a degree of certainty muiX ofiCalled a cloud droplet in the domain, all the cloud droplets constitute a cloud, which is a characterization of the concept. And repeating the steps, and taking the average value to obtain the similarity. A plurality of cloud droplets form a universal normal mathematical mapping image which is a scalable, non-definite boundary and elastic cloud image and completes mutual mapping between qualitative and quantitative.
In specific implementation, for example, representative ancient building multi-source spatial data across the country are collected, a large number of experiments and algorithm tests are carried out on the basis of deep research of a data processing theory, automatic extraction experiments of component geometry and topological information are carried out by combining existing CAD/BIM/GIS and other data, and reusability of a graph identification rule is verified; carrying out a seamless conversion algorithm experiment from a building structure point cloud model, an NURBS model or an irregular triangulation network model to a structure finite element analysis model, building an experiment platform by combining a C + + and other object-oriented programming languages and a developed three-dimensional modeling system, carrying out mining experiments on various regular behaviors and attributes, and verifying the applicability of cross-discipline analysis model conversion; carrying out a real-site investigation experiment according to the safety detection standard of the conventional timber structure ancient building structure, designing different types of experimental researches such as an ultrasonic detection experiment, a monotonous loading experiment and the like, carrying out deeper research on stress performances such as bending and shearing of mortise and tenon joints, single timber frames and an integral large timber structure by combining finite element simulation and theoretical analysis, and evaluating the structural mode and the dynamic characteristic of the timber structure ancient building; the method is characterized in that a main structural component evaluation experiment is specially designed for ancient buildings of different styles, the weight influence of the main structural component brought into an evaluation system is verified, the existing GIS/BIM/CAD/CAE commercial software, a self-made experiment prototype system and visualization conditions are comprehensively utilized, and a primary and secondary clear multi-level index evaluation system is constructed.
The wood structure ancient building health state evaluation method based on the normal cloud model provided by the invention has a deep mathematical basis by adopting a multistage mixed three-dimensional space indexing mechanism, a fine three-dimensional model reconstruction algorithm, a finite element analysis method, a power time course analysis, cloud model evaluation and other theories. Starting from obtaining ancient building space data by using a high-precision space-time surveying and mapping sensor, carrying out the work of seamless conversion from a point cloud or NURBS model to a finite element analysis model, establishment of a normal cloud model evaluation system, structural analysis and health monitoring of space data in a typical experiment area and the like by taking the integrated coupling of the surveying and mapping subject and the civil subject as constraint and taking methods such as multi-level mixed space index design and construction, multi-level organization of space data, construction of a wood structure NURBS model and the like as means.
The modeling research on the objective geometry and position of the ancient building entity in the traditional thought can be promoted to be subjective and objective unified expression of the accurate evaluation requirement of the health state on the uncertainty problem, and particularly:
(1) the method is used for trying to construct a fine-grained and characteristic-rich comprehensive analysis model of the ancient building solid structure for the first time. The method comprises the steps of establishing an ancient building high-precision point cloud model by utilizing multi-source data collected by different surveying and mapping sensors, combining structural information such as the structure geometry, the semantics, the topology, the material characteristics and the mechanical state of an ancient building, carrying out seamless conversion on a wood structure finite element analysis model by utilizing the point cloud model, adopting the thought of reverse engineering and the same geometric analysis technology, reducing the accurate real geometric appearance of a building body, filling the research gap from the geometric information to the structural analysis information conversion, being beneficial to the evaluation of the structural mode and the dynamic characteristics of the whole structure and each component node of the ancient building, and improving the deep fusion capability of the key technology of the surveying and mapping subject and the civil subject in the application fields such as the evaluation of the health state of the ancient building.
(2) And providing a comprehensive scheme for evaluating the health state of the timber structure ancient building by using a normal cloud model theory. The method is characterized in that a normal cloud model theory is introduced into comprehensive evaluation of a complex system for evaluating the overall health state of the ancient building, millimeter-scale quantitative analysis is carried out by utilizing a constructed wood structure fine comprehensive analysis model, influence factors such as natural weathering, structural deformation and material characteristics are added into measurement information by combining expert wisdom described by natural language, a multi-parameter dynamic participation bidirectional cognitive calculation process is formed, a cloud model similarity measurement research aiming at the field of ancient architecture legacy protection is developed, and a borrowable research paradigm is provided for quantitative description-qualitative concept bidirectional mapping for ancient building health state evaluation.
In one embodiment, the organization of the ancient architectural structure model designed in S1 includes three aspects: data structures, historic building structure design, and spatial indexing mechanisms.
Firstly, the method comprises the following steps: a data structure; the method comprises the steps of acquiring original design data of the historic building, multi-source fine space data and original data collected and sorted by existing data; the method can be divided into a point cloud model, a NURBS model, a CSG model, a 3D-TIN model and an original finite element analysis model. Where, for example, the original finite element analysis model is a pattern that is artificially defined or imagined.
Secondly, the method comprises the following steps: designing an ancient building structure; the method comprises the following steps: conceptual models, logical models, and physical models.
Thirdly, the method comprises the following steps: a spatial indexing mechanism; the method comprises the following steps: and the octal tree and the three-dimensional K-D tree, the quadtree and the minimum bounding box form the QMBB, the 3D-R and the QMBB tree mixed index.
Based on the three data, an ancient architectural structure geometric model can be constructed, and the ancient architectural structure geometric model comprises 5 attributes: structural features, material features, structural relationships, geometric relationships, and topological relationships.
The structural characteristics represent the appearance information of the ancient buildings, such as whether the ancient buildings are damaged or not, whether the wall is peeled or not and the conditions of mortise and tenon; material characteristics such as wood type, strength, whether butter is spread or not; a structural relationship representing a connection relationship of the authentication unit, the main member, the general member, and the like; the topological relation represents the connection relation of the column and the beam.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A wood structure ancient building health state assessment method based on a normal cloud model is characterized by comprising the following steps:
designing an organization mode of an ancient building structure model;
collecting relevant data of the current situation of the historic building;
performing spatial clustering, structure extraction and model reconstruction based on a multi-constraint knowledge rule base according to the ancient building structure model organization mode and the related data;
rebuilding a spatial calculation model driven based on a knowledge rule, and converting the spatial calculation model into a first finite element analysis model;
and respectively carrying out quantitative calculation and analysis based on the first finite element analysis model, carrying out uncertain row evaluation based on the cloud model, and outputting an evaluation result.
2. The evaluation method of claim 1, wherein the performing the quantitative calculation and analysis, and the performing the uncertainty evaluation based on the cloud model, respectively, and outputting the evaluation result comprises:
comparing internal force with deformation and checking bearing capacity by a vibration type decomposition method and a power time-course method to obtain accurate evaluation of natural weathering, earthquake resistance and fire resistance of the historic building timber structure;
converting assessment data of a comment set, accurate quantification and expert qualitative assessment into a cloud model, namely determining digital characteristic values of a standard cloud, an evaluation cloud and a comprehensive cloud; standard cloud digital characteristic value C to be applied to each comment setVi(ExVi，EnVi，HeVi) Using the following formula(1) And calculating to obtain:
(1) in the formula: 1,2, … … 5; x is the number ofimax，ximinThe upper limit value and the lower limit value of each comment set are respectively set; k reflects the linear relation between entropy and super entropy, and k is 0.3;
obtaining expert scores, respectively evaluating m parts by n experts, combining quantitative calculation evaluation result weights, and calculating evaluation cloud digital characteristic values C of all components by adopting formula (2)Ui(ExUi，EnUi，HeUi)；
(2) In the formula: 1,2,. m; j is 1,2,. n; x is the number ofijScoring data for the jth expert for the ith component; s is a sample variance;
comprehensive evaluation of the historic building structure comprehensive cloud and the result comprehensive cloud are obtained by adopting a fuzzy comprehensive evaluation method, a cloud model theory is combined with the fuzzy comprehensive evaluation method, the historic building health state information with randomness and fuzziness is organically processed, and the health state grade is accurately evaluated.
3. The assessment method of claim 2 wherein the computing of the assessment result weight in conjunction with quantification comprises:
determining the weight of the evaluation index by adopting a combined weighting method: as shown in formula (3):
w 'of'jWeights calculated for the analytic hierarchy process; w is aj *Weights calculated for the entropy weights; w is ajThe weights obtained by the combined weighting method (j ═ 1,2, …, m).
4. The assessment method of claim 1, wherein said designing an ancient architectural structure model organizational scheme, comprises:
constructing a data structure of the historic building; the data of the data structure is as follows: collecting multi-source fine spatial data and original data collected and sorted by existing data;
designing a conceptual model, a logic model and a physical model;
constructing a spatial index mechanism;
generating an organization mode of the ancient building structure model; the historic building structure model organization mode comprises the following attributes: structural features, material features, structural relationships, geometric relationships, and topological relationships.
5. The method of claim 1, wherein collecting data related to the current status of the historic building comprises:
and collecting point cloud data, GIS data, BIM data, CAD data, multispectral data, stress wave data, photogrammetric data images and a second finite element model of the ancient building.
6. The evaluation method of claim 4, wherein the conceptual model comprises: semantic constraints, unit decomposition, geometric expression and model support;
the semantic constraints include: the building comprises a column frame layer, a paving layer, a roof layer and a platform base layer;
the unit decomposition includes: a point unit, a frame unit, a face unit and a body unit;
the geometric representation includes: points, lines, faces and volumes;
the model support comprises: a point cloud model, a B-REP model, a TIN model and a third finite element model.
7. The evaluation method of claim 4, wherein the logic model comprises: member cross-section, member material, member unit and member relationship.
8. The evaluation method of claim 4, wherein the source of the data structure comprises: a point cloud model, a NURBS model, a CSG model, a 3D-TIN model, and an original finite element analysis model.
9. The evaluation method of claim 1, wherein the building a spatial index mechanism comprises: and establishing a QMBB, 3D-R and QMBB tree mixed index formed by the octree, the three-dimensional K-D tree, the quadtree and the minimum bounding box.
10. The evaluation method of claim 1, wherein converting the spatial computational model to a first finite element analysis model comprises:
determining a minimum outer packing box of the point cloud according to the space calculation model;
dividing grids and quadrangles according to preset rules;
and optimizing the quadrangle to realize conversion into a first finite element analysis model.
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