Railway bridge BIM model auditing method based on knowledge graph

Abstract

The invention discloses a method for auditing a railway bridge BIM model based on a knowledge graph, and the method comprises the following steps: S1, carrying out the structural processing of railway bridge standard data, and constructing the knowledge graph; s2, information in the BIM model to be audited is extracted and processed; s3, constructing an auditing standard rule base through a Drools rule engine; and S4, auditing is carried out. According to the method, a set of comprehensive auditing rules is formulated based on bridge engineering design specifications, construction standards and experience knowledge in a knowledge graph, the rules are constructed into a rule base, pattern matching is utilized, the rule base is called to audit each bridge component in a BIM model and attributes of the bridge component, and the auditing efficiency is improved. Therefore, automatic and intelligent auditing of the BIM model is realized, auditing efficiency and accuracy are remarkably improved, interference of human factors is reduced, and compliance and reliability of the final BIM model are ensured.

Description

Technical Field

[0001] The present invention relates to the field of construction engineering informatization and intelligence, and in particular to a review method for a railway bridge BIM model based on a knowledge graph. Background Art

[0002] With the widespread application of building information modeling (BIM) technology in the field of railway bridge construction, BIM models have become an important tool for the full life cycle management of engineering project design, construction, operation and maintenance. BIM models not only integrate a large amount of geometric, physical and attribute information, but also realize the visualization, parameterization and collaboration of information, greatly improving the efficiency and accuracy of engineering management.

[0003] Traditionally, the review of railway bridge BIM models mainly relies on manual review. Reviewers mainly rely on design drawings, technical specifications, construction instructions and other documents, combined with their own professional knowledge and experience, to review BIM models item by item. This method is not only time-consuming and labor-intensive, but also prone to inconsistencies and errors in review results due to human factors. In addition, with the continuous updating of design specifications and construction standards, reviewers need to constantly learn and master new knowledge, which undoubtedly increases the difficulty and cost of review work. Summary of the invention

[0004] In order to solve the problems in the background technology, the present invention proposes an efficient, accurate and automated review method for the railway bridge BIM model based on knowledge graph.

[0005] To this end, the present invention adopts the following technical solutions:

[0006] A review method for a railway bridge BIM model based on a knowledge graph includes the following steps:

[0007] S1, structured processing of railway bridge standard data and construction of knowledge graph, including:

[0008] S11 structures the railway bridge standard data to form a structured data set suitable for knowledge graph construction, wherein the railway bridge standard data includes text data in railway bridge design manuals, construction standards, engineering examples, and expert knowledge; the structured data set includes the type and attributes of each bridge component in the railway bridge:

[0009] S12, constructing the structured data set obtained in S11 into a knowledge graph to fully present the properties of each bridge component in the railway bridge, the relationship between the bridge components and the constraints;

[0010] S2, extracting and processing the information in the BIM model to be reviewed, including the following steps:

[0011] S21, extracting the actual size, material properties, connection mode of component connection points and force information of bridge components of each component of the railway bridge in the BIM model to be reviewed;

[0012] S22, calculating a geometric matching degree G, wherein the geometric matching degree G is used to determine the degree to which the actual size conforms to the requirements specified in the knowledge graph;

[0013] S23, calculating a material attribute matching degree M, wherein the material attribute matching degree M is used to determine the degree of consistency between the material attribute and the material attribute in the knowledge graph;

[0014] S24, calculating the rationality R of the component connection point relationship, wherein the rationality R of the component connection point relationship is used to determine the degree of conformity between the relationship between the component connection points and the provisions in the knowledge graph;

[0015] S25, calculating the load distribution rationality L, wherein the load distribution rationality L is used to review the load distribution of the bridge structure in the BIM model;

[0016] S3, determining the audit standard of the BIM model to be audited through the knowledge graph obtained in S1, and then constructing an audit standard rule base through the Drools rule base and the audit standard, wherein the audit standard rule base includes the audit thresholds of G, M, R, and L;

[0017] S4, compares the result obtained in S2 with the audit threshold of S3, and audits the BIM model to be audited.

[0018] In S11: the bridge component types include beams, columns and piers;

[0019] The bridge component attributes include geometric attributes, force information, standard specification references, component connection point relationships and text classification tags, among which:

[0020] The geometric properties include standard dimensions of bridge components;

[0021] The material properties include strength characteristics, durability, density, corrosion resistance of the bridge components;

[0022] The component connection point relationship is to use the relationship extraction technology to identify the relationship between the bridge components to generate the connection mode between the bridge components;

[0023] The stress information includes standard stress conditions of bridge components;

[0024] The standard specification reference includes extracting the design standard number and specification clause from the text of railway bridge standard data;

[0025] The text classification tagging is to classify different text segments in the railway bridge standard data into design standards, construction specifications or safety regulations through keywords and rule methods.

[0026] In S22, the geometric matching degree G is calculated by the following formula:

[0027]

[0028] Where i is the number of the bridge component; n is the total number of bridge components in the BIM model to be reviewed; v i is the geometric importance weight of bridge component i, 0 <v i ≤1;L M (i) is the actual size of bridge component i in the BIM model to be reviewed; L K (i) is the standard size corresponding to bridge component i in the knowledge graph.

[0029] S23 is specifically:

[0030] The similarity u of the material property k of bridge component i is calculated by the following formula: k (i)

[0031]

[0032] Wherein, i is the number of the bridge component, is the actual value of the kth material property of bridge component i in the BIM model to be reviewed, 1≤k≤4, is the standard value of the kth material property of bridge component i in the knowledge graph;

[0033] Then the similarity M of the material property k of the railway bridge BIM model is calculated by the following formula: k :

[0034]

[0035] Where n is the total number of bridge components in the BIM model to be reviewed, is the material strength importance weight of the kth material property of bridge component i

[0036] The strength characteristic similarity M1, durability similarity M2, density similarity M3 and corrosion resistance similarity M4 were calculated;

[0037] Finally, the material property matching degree M is calculated by summing the similarities of the four material properties using the following formula:

[0038] M=w1.M1+w2.M2+w3.M3+w4.M4;

[0039] Among them: w1, w2, w3, w4 are the importance weights of material strength characteristics, durability, density, and corrosion resistance of the railway bridge BIM model, respectively. <w k ≤1.

[0040] S24 specifically includes the following steps:

[0041] S241, define the connection mode matching function θ(C M (j), C K (j)), the matching function θ(·) is used to quantify the actual component connection point relationship C M (j) and the standard component connection point relationship C in the knowledge graph K (j), where j is the number of the component connection point, θ(·)∈[0,1];

[0042] S242, calculate the rationality R of the component connection point relationship of the BIM model to be reviewed by the following formula:

[0043]

[0044] Where m is the total number of component connection points in the BIM model to be reviewed, z j is the importance weight of the component connection point j, which is determined according to the actual working conditions, 0 <z j ≤1.

[0045] S25 specifically includes the following steps:

[0046] S251, calculate the deadweight of bridge member i by the following formula:

[0047] W i =V i .ρ i .g;

[0048] Wherein, i is the number of the bridge component, V i is the volume of bridge component i, ρ i is the material density of bridge component i, g is the acceleration due to gravity;

[0049] Then calculate the distributed load q of bridge component i according to the following formula: i :

[0050] q i =A i .p;

[0051] Among them, A i is the cross-sectional area of ​​component i, and p is the load per unit area in the design document of the BIM model to be reviewed;

[0052] Import W into the public plugin for Revit iand q i , get the actual force value F of the component M (i);

[0053] S252, calculate the load distribution rationality L of the BIM model to be reviewed by the following formula:

[0054]

[0055] Where n is the total number of bridge components in the BIM model to be reviewed, s i is the load importance weight of bridge component i, which is determined according to the actual working conditions, 0 i ≤1, F M (i) is the actual force value of bridge component i in the BIM model to be reviewed, F K (i) is the standard force value of bridge component i in the knowledge graph.

[0056] Preferably, in S1: the connection mode includes connection relationship, support relationship, dependency relationship, geometric constraint and physical constraint;

[0057] Among them: the connection relationship is the connection method between bridge components; the support relationship is the mechanical dependence relationship between bridge components; the geometric constraint is the geometric relationship between bridge components, including relative position, angle, and alignment; the physical constraint is the load-bearing limit and deformation constraint of the bridge component material that meets the physical properties and design requirements.

[0058] Preferably, in S12, the structured data set is saved as a knowledge graph using the graph database Neo4j.

[0059] Compared with the prior art, the present invention has the following beneficial effects:

[0060] 1. The present invention collects data in related fields such as railway bridge design, construction, and maintenance, and uses the BiLSTM-CRF model to structure the text content of engineering specifications, standards, regulations, and other texts and construct a knowledge graph, thereby realizing a comprehensive and systematic railway bridge engineering knowledge base, and providing a basis for subsequent BIM model review. By using a custom API to interact directly with Revit, BIM model information is extracted and a mapping relationship is established between the entities in the knowledge graph and the information nodes of the BIM model, thereby realizing the effective connection between the BIM model data and the rules and standards in the knowledge graph, and providing the possibility for subsequent BIM model review.

[0061] ​2. The method of the present invention develops a comprehensive set of audit rules based on the bridge engineering design specifications, construction standards and empirical knowledge in the knowledge graph, and constructs these rules into a rule base. By using pattern matching, the rule base is called to audit each bridge component and its attributes in the BIM model, thereby realizing the automated and intelligent audit of the BIM model, significantly improving the audit efficiency and accuracy, reducing the interference of human factors, and ensuring the compliance and reliability of the final BIM model. At the same time, it also provides strong data support for project management and decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0063] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0064] like Figure 1 As shown, the review method of the railway bridge BIM model based on the knowledge graph of the present invention includes the following steps:

[0065] S1, structurally process the railway bridge standard data and construct a knowledge graph, including the following steps:

[0066] S11 structures the railway bridge standard data to form a structured data set suitable for knowledge graph construction, so as to serve as a basis for comparison in BIM model review. Railway bridge standard data includes text data in railway bridge design manuals, construction standards, engineering examples and expert knowledge, specifically:

[0067] Through the combined model of BiLSTM and CRF, the deep analysis and semantic information capture of railway bridge standard data are realized, and the key information is structured. The structured data set includes bridge component types and bridge component attributes;

[0068] Bridge component types include beams, columns, and piers;

[0069] Bridge component properties include geometric properties, force information, standard specification references, component connection point relationships, and text classification tags, among which:

[0070] 1) Geometric properties include the standard dimensions of bridge components, including length, width, and height;

[0071] 2) Material properties include strength, durability, density, and corrosion resistance of bridge components;

[0072] 3) Component connection point relationships use relationship extraction technology to identify the relationship between bridge components to generate the connection method between bridge components. The connection method includes connection relationship, support relationship, dependency relationship, geometric constraint and physical constraint, among which: connection relationship is the connection method between bridge components; support relationship is the mechanical dependency relationship between bridge components; geometric constraint is the geometric relationship between bridge components, including relative position, angle, and alignment; physical constraint is the load-bearing limit and deformation constraint of bridge component materials that conform to physical properties and design requirements.

[0073] 4) Stress information includes standard stress conditions of bridge components;

[0074] 5) Standard specification references include extracting design standard numbers and specification clauses from the text of railway bridge standard data;

[0075] 6) Text classification tagging is to classify different text fragments in the railway bridge standard data into "design standards", "construction specifications" or "safety regulations" through keywords and rule methods, so as to distinguish entries by category in the knowledge graph.

[0076] S12, constructing a knowledge graph for railway bridge engineering:

[0077] The structured data set obtained by S11 is constructed into a knowledge graph to provide a comparison basis for BIM model review. The specific process is as follows:

[0078] First, the bridge component types in S11 are taken as nodes in the knowledge graph, the bridge component attributes are taken as child nodes of the knowledge graph, and the bridge component connection point relationships are taken as edges of the knowledge graph.

[0079] Then, the structured data set will be saved as a knowledge graph using the graph database Neo4j.

[0080] The knowledge graph can efficiently manage bridge component types and attributes. Each node and edge carries specific labels and attribute information for accurate query and fast matching. Using Neo4j's query optimization function, an index structure is built to ensure fast access to standard component data and relationship data during model review.

[0081] The knowledge graph obtained in step S1 is a comprehensive standard data model for railway bridges, which can fully present the properties of bridge components, the relationships between bridge components, and the constraints.

[0082] S2, extract the information in the BIM model to be reviewed and process it:

[0083] Use the custom API to interact directly with Revit to extract the information of the BIM model to be reviewed, including the geometric information, material information, and associated information of the bridge components in the model. The specific steps are as follows:

[0084] S21, edit the API interface used to extract the BIM model data to be reviewed, specifically:

[0085] Installation and project setup: Install Visual Studio and Revit API SDK to extract the actual size, material properties, connection method of component connection points, and force information of bridge components in the BIM model to be reviewed.

[0086] S22, calculate the geometric matching degree G:

[0087] The geometric consistency of the BIM model to be reviewed is calculated by formula (1). G is used to verify whether the actual size of the bridge components in the BIM model to be reviewed meets the design standards and ensure the accuracy of the precision and position of each bridge component:

[0088]

[0089] Where i is the bridge component number, n is the total number of bridge components in the BIM model to be reviewed, and v i is the geometric importance weight of bridge component i (0 <v i ≤1), L M (i) is the actual size of bridge component i in the BIM model to be reviewed, L K (i) is the standard size corresponding to bridge component i in the knowledge graph.

[0090] The closer the value of the geometric matching degree G is to 1, the higher the geometric accuracy is, and the more the geometric structure of the BIM model to be reviewed conforms to the standard.

[0091] S23, calculate the material property matching degree M:

[0092] Calculate the material matching degree of the BIM model to be reviewed. M is used to check whether the actual material properties of the components in the railway bridge BIM model are consistent with the standard material properties specified in the knowledge graph. The material properties include strength characteristics, durability, density, and corrosion resistance. The steps are as follows:

[0093] First, the material properties are quantified, where:

[0094] The data of strength characteristics are the compressive strength values ​​of component materials (unit: MPa);

[0095] Durability data is quantified by standard durability levels or expected service life;

[0096] The density data is the density value of the component material (unit: kg / m3);

[0097] The corrosion resistance data is quantified by dividing the material's corrosion resistance grade A and grade B into numerical values: grade A = 1, grade B = 2.

[0098] Then define the material similarity function and obtain the material similarity u of material property k of bridge component i: k (i), as in formula (2):

[0099]

[0100] in, is the actual material property value of the kth bridge component i in the BIM model to be reviewed, 1≤k≤4, and the material properties are strength, durability, density and corrosion resistance. is the kth standard material property of bridge component i in the knowledge graph. The smaller the difference, the higher the k The closer (i) is to 1, the higher the similarity of the material property k of bridge component i is.

[0101] Calculate the material property k similarity M of the railway bridge BIM model k , as shown in formula (3):

[0102]

[0103] in, is the material strength importance weight of the kth material property of bridge component i

[0104] The strength characteristic similarity M1, durability similarity M2, density similarity M3 and corrosion resistance similarity M4 are calculated.

[0105] The similarities of the four material properties are added together to calculate the material property matching degree M, as shown in formula (4):

[0106] M=w1.M1+w2.M2+w3.M3+w4.M4 (4)

[0107] Among them: w1, w2, w3, w4 are the importance weights of the material strength characteristics, durability, density, and corrosion resistance of the railway bridge BIM model (0 <w k ≤1). The closer the M value is to 1, the higher the matching degree of material properties.

[0108] S24, calculate the rationality of the relationship between the connection points of the components R:

[0109] Analyze the connection node information between the components of the BIM model to be reviewed, check the connection method, and compare the actual connection method with the design specification requirements.

[0110] Determine the degree of conformity between the connection points of the bridge components and those specified in the knowledge graph to ensure the reliability of the connections between the components. The steps are as follows:

[0111] S241, define the connection mode matching function θ(C M (j), C K (j)), the matching function is used to quantify the actual component connection point relationship C M (j) and the standard component connection point relationship C in the knowledge graph K (j), where j is the number of the component connection point, θ(·)∈[0,1].

[0112] Specifically, if the actual connection method is exactly the same as the standard connection method, then θ(C M (j), C K (j))=1; if the actual connection mode is not exactly the same as the standard connection mode, but it can be considered to be an acceptable alternative in some scenarios, θ can be set to a specific value between 0 and 1 according to the acceptability to reflect "partial match"; if the actual connection mode is completely different from the standard connection mode and does not meet the design specifications, then θ(C M (j), C K (j))=0.

[0113] To facilitate calculation, a component connection method quantification table is established, which contains possible connection method combinations and their corresponding matching values. The following table is shown:

[0114] Table 1 Quantification table of matching of connection modes of railway bridge BIM model components

[0115]

[0116]

[0117] S242, calculate the rationality R of the connection point relationship of the BIM model component to be reviewed, as shown in formula (5):

[0118]

[0119] Where m is the total number of component connection points in the BIM model to be reviewed, z j is the importance weight of the component connection point j, which is determined according to the actual working conditions, (0 <z j ≤1). The closer the value of R is to 1, the more the component connection point relationship conforms to the standard.

[0120] S25, calculate the rationality of load distribution L:

[0121] Compare the stress information of each component in the overall bridge structure extracted by S21 with the design load distribution requirements, calculate the deviation between the actual stress of each component and the design standard stress, and review the load distribution of the bridge structure in the BIM model to ensure the stability and safety of the overall structure. The steps are as follows:

[0122] S251, calculate the actual load data based on the geometric data and material properties, and calculate the deadweight of bridge component i, as shown in formula (6):

[0123] W i =V i .ρ i .g (6)

[0124] Among them, V i is the volume of bridge component i, ρ i is the material density of bridge component i, and g is the acceleration due to gravity.

[0125] Calculate the distributed load q on bridge component i i , as shown in formula (7):

[0126] q i =A i .p (7)

[0127] Among them, A i is the cross-sectional area of ​​component i, and p is the load per unit area in the design document.

[0128] Using the Revit plug-in Autodesk Robot Structural Analysis, the calculated self-weight W of bridge component i is i and the distributed load q i Import,

[0129] And according to the structural conditions, the model is subjected to stress simulation. Through mechanical analysis, the actual stress value F of the component is obtained. M (i) S252, calculate the load distribution rationality L of the BIM model to be reviewed, as shown in formula (8):

[0130]

[0131] Among them, s i is the load importance weight of bridge component i, which is determined according to the actual working conditions, 0 i ≤1, F M (i) is the actual force value of bridge component i in the BIM model to be reviewed, F K (i) is the standard force value of bridge component i in the knowledge graph.

[0132] ​The closer the value of load distribution rationality L is to 0, the smaller the deviation between the actual force result value and the standard force value, indicating that the load distribution is more reasonable.

[0133] S3, builds an audit standard rule base through the Drools rule engine:

[0134] First, the review standard of the BIM model to be reviewed is determined through the knowledge graph obtained from the railway bridge standard data in S1;

[0135] Logically formalize the audit standards into a computer-understandable format (logical expression, rule template or scripting language), and import it into the Drools rule engine to build a complete audit standard rule base, ensuring that the expression of the rules is both accurate and efficient, so that the Drools rule engine can automatically manage, store and call the audit standards in the audit standard rule base;

[0136] The audit standard rule base includes audit thresholds of G, M, R, and L.

[0137] S4, conduct review:

[0138] The result obtained by S2 is compared with the audit threshold of S3, and the BIM model to be audited is audited.

Claims

1. A method for reviewing a railway bridge BIM model based on a knowledge graph, characterized in that: The following steps are involved: S1, structured processing of railway bridge standard data and construction of knowledge graph, including: S11 structures the railway bridge standard data to form a structured data set suitable for knowledge graph construction, wherein the railway bridge standard data includes text data in railway bridge design manuals, construction standards, engineering examples, and expert knowledge; the structured data set includes the type and attributes of each bridge component in the railway bridge: S12, constructing the structured data set obtained in S11 into a knowledge graph to fully present the properties of each bridge component in the railway bridge, the relationship between the bridge components and the constraints; S2, extracting and processing the information in the BIM model to be reviewed, including the following steps: S21, extracting the actual size, material properties, connection mode of component connection points and force information of bridge components of each component of the railway bridge in the BIM model to be reviewed; S22, calculating a geometric matching degree G, wherein the geometric matching degree G is used to determine the degree to which the actual size conforms to the requirements specified in the knowledge graph; S23, calculating a material attribute matching degree M, wherein the material attribute matching degree M is used to determine the degree of consistency between the material attribute and the material attribute in the knowledge graph; S24, calculating the rationality R of the component connection point relationship, wherein the rationality R of the component connection point relationship is used to determine the degree of conformity between the relationship between the component connection points and the provisions in the knowledge graph; S25, calculating the load distribution rationality L, wherein the load distribution rationality L is used to review the load distribution of the bridge structure in the BIM model; S3, determining the audit standard of the BIM model to be audited through the knowledge graph obtained in S1, and then constructing an audit standard rule base through the Drools rule base and the audit standard, wherein the audit standard rule base includes the audit thresholds of G, M, R, and L; S4, compares the result obtained in S2 with the audit threshold of S3, and audits the BIM model to be audited.

2. The method for reviewing the railway bridge BIM model based on the knowledge graph according to claim 1 is characterized in that: In S11: The bridge component types include beams, columns and piers; The bridge component attributes include geometric attributes, force information, standard specification references, component connection point relationships and text classification tags, among which: The geometric properties include standard dimensions of bridge components; The material properties include strength characteristics, durability, density, corrosion resistance of the bridge components; The component connection point relationship is to use the relationship extraction technology to identify the relationship between the bridge components to generate the connection mode between the bridge components; The stress information includes standard stress conditions of bridge components; The standard specification reference includes extracting the design standard number and specification clause from the text of railway bridge standard data; The text classification tagging is to classify different text segments in the railway bridge standard data into design standards, construction specifications or safety regulations through keywords and rule methods.

3. The audit method of the railway bridge BIM model based on the knowledge graph according to claim 2 is characterized in that: In S22, the geometric matching degree G is calculated by the following formula: Where i is the number of the bridge component; n is the total number of bridge components in the BIM model to be reviewed; v i is the geometric importance weight of bridge component i, 0 <v i ≤1;L M (i) is the actual size of bridge component i in the BIM model to be reviewed; L K (i) is the standard size corresponding to bridge component i in the knowledge graph.

4. The method for reviewing the railway bridge BIM model based on the knowledge graph according to claim 2 is characterized in that: S23 is specifically: The similarity u of the material property k of bridge component i is calculated by the following formula: k (i) Wherein, i is the number of the bridge component, is the actual value of the kth material property of bridge component i in the BIM model to be reviewed, 1≤k≤4, is the standard value of the kth material property of bridge component i in the knowledge graph; Then the similarity M of the material property k of the railway bridge BIM model is calculated by the following formula: k : Where n is the total number of bridge components in the BIM model to be reviewed, is the material strength importance weight of the kth material property of bridge component i The strength characteristic similarity M1, durability similarity M2, density similarity M3 and corrosion resistance similarity M4 were calculated; Finally, the material property matching degree M is calculated by summing the similarities of the four material properties using the following formula: M=w1.M1+w2.M2+w3.M3+w4.M4; Among them: w1, w2, w3, w4 are the importance weights of material strength characteristics, durability, density, and corrosion resistance of the railway bridge BIM model, respectively. <w k ≤1.

5. The method for reviewing the railway bridge BIM model based on the knowledge graph according to claim 2 is characterized in that: S24 specifically includes the following steps: S241, define the connection mode matching function θ(C M (j), C K (j)), the matching function θ(·) is used to quantify the actual component connection point relationship C M (j) and the standard component connection point relationship C in the knowledge graph K (j), where j is the number of the component connection point, θ(·)∈[0,1]; S242, calculate the rationality R of the component connection point relationship of the BIM model to be reviewed by the following formula: Where m is the total number of component connection points in the BIM model to be reviewed, z j is the importance weight of the component connection point j, which is determined according to the actual working conditions, 0 <z j ≤1.

6. The method for reviewing the railway bridge BIM model based on the knowledge graph according to claim 2 is characterized in that: S25 specifically includes the following steps: S251, calculate the deadweight of bridge member i by the following formula: W i =V i .r i .g; Wherein, i is the number of the bridge component, V i is the volume of bridge component i, ρ i is the material density of bridge component i, g is the acceleration due to gravity; Then calculate the distributed load q of bridge component i according to the following formula: i : q i =A i .p; Among them, A i is the cross-sectional area of ​​component i, and p is the load per unit area in the design document of the BIM model to be reviewed; Import W into the public plugin for Revit i and q i , get the actual force value F of the component M (i); S252, calculate the load distribution rationality L of the BIM model to be reviewed by the following formula: Where n is the total number of bridge components in the BIM model to be reviewed, s i is the load importance weight of bridge component i, which is determined according to the actual working conditions, 0 i ≤1, F M (i) is the actual force value of bridge component i in the BIM model to be reviewed, F K (i) is the standard force value of bridge component i in the knowledge graph.​ 7. The method for reviewing the railway bridge BIM model based on the knowledge graph according to claim 2 is characterized in that: In S1: the connection mode includes connection relationship, support relationship, dependency relationship, geometric constraint and physical constraint; Among them: the connection relationship is the connection method between bridge components; the support relationship is the mechanical dependence relationship between bridge components; the geometric constraint is the geometric relationship between bridge components, including relative position, angle, and alignment; the physical constraint is the load-bearing limit and deformation constraint of the bridge component material that meets the physical properties and design requirements.

8. The method for reviewing the railway bridge BIM model based on the knowledge graph according to claim 2 is characterized in that: In S12, the structured data set is saved as a knowledge graph using the graph database Neo4j.

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