CN112734213B - Body-based highway bridge technical condition inspection and evaluation method - Google Patents
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Abstract
The invention discloses a method for checking and evaluating technical conditions of a highway bridge based on a body, which constructs a body knowledge base by introducing bridge engineering basic knowledge, bridge engineering specifications and regular checking data of the highway bridge engineering, combines semantic network rules and semantic query rules, realizes knowledge reasoning, automatically processes bridge disease information, obtains grade scores of the technical conditions of the bridge, realizes automatic evaluation of the technical conditions of the highway bridge, and greatly improves the efficiency and the intelligent level of data processing of the highway bridge.
Description
Technical Field
The invention relates to the technical field of highway bridge maintenance, in particular to a body-based highway bridge technical condition inspection and evaluation method.
Background
The number of the Chinese highway bridges is numerous, and due to the lack of effective support of computer auxiliary tools, the bridge is time-consuming and laborious to check data periodically, and the problems of inaccurate check data, untimely feedback and the like result in the increase of the bridge later maintenance cost. In addition, during data processing, engineering personnel need to search engineering specification standards, but engineering specifications in the field are large in number and wide in content, and the engineering personnel mainly rely on subjective experience of the engineering personnel to finish the work, but the problems of low efficiency, low accuracy and high cost still exist.
In addition to the manual calculation method, there is a method using a Bridge Management System (BMS) in the prior art. Compared with manual processing efficiency, the method for computing the bridge management system is greatly improved, however, the BMS system data processing method lacks intelligence and has no self-learning and reasoning capability. The number of highway bridges is large, and the calculation time cost is increased and the requirement on computer hardware is increased through code calculation.
Disclosure of Invention
The invention provides a body-based highway bridge technical condition checking and evaluating method for overcoming the technical problems.
The invention discloses a body-based highway bridge technical condition checking and evaluating method, which comprises the following steps:
constructing a ontology knowledge base according to knowledge in the field of highway bridge engineering; the highway bridge engineering field knowledge comprises: bridge engineering basic knowledge, bridge engineering specifications and highway bridge engineering periodic inspection data;
defining a plurality of classes, a hierarchy of the classes and attributes of the classes in the ontology knowledge base according to the highway bridge engineering field knowledge, and creating instances of the classes;
defining semantic web rules based on the ontology knowledge base; the semantic web rule includes: bridge disease grade evaluation and deduction value evaluation rules, coefficient and weight reasoning rules and bridge overall technical condition evaluation rules;
defining a semantic query rule; semantic query rules comprising: a bridge overall condition evaluation query rule and a bridge disease cause query rule;
inputting the requirements of inspection and evaluation of the technical condition of the highway bridge, and operating the semantic web rules and the semantic query rules to obtain the parameters of the technical condition of the highway bridge.
Further, the plurality of classes includes: class of bridge structure type and class of structure disease type;
a class of bridge structure types comprising: beam bridges, arch bridges, suspension bridges, and cable-stayed bridges;
a class of structural disease types comprising: upper bearing members, supports, piers, abutment and foundation.
Further, the defining semantic web rules based on the ontology knowledge base includes:
the semantic web rule is a SWRL rule, and the SWRL rule is in the form of:
B 1 ，…，B n →A 1 ，…，A m (1)
wherein A is 1 ，…，A m Is a precondition for SWRL rules; b (B) 1 ，…，B n Is the result of the SWRL rule.
Further, the bridge disease grade evaluation and deduction value evaluation rule comprises: determining a disease grade rule and a deduction point rule;
the coefficient and weight reasoning rules include: determining a component weight rule according to the component number reasoning coefficient rule;
the bridge overall technical condition assessment rule comprises the following steps: calculating a technical condition scoring rule of a component, calculating a technical condition scoring rule of a structure, calculating an overall technical condition scoring rule, and calculating a bridge technical condition rating rule.
Further, the technical condition scoring rule of the calculating means includes:
the technical condition score of the component is calculated by formula (2):
where, when x=1, U 1 ＝DP i1 The method comprises the steps of carrying out a first treatment on the surface of the When DP ij ＝100，PMCI l (BMCI l Or DMCI l )＝0；
PMCI l Scoring of the l-member of the i-th class of parts of the superstructure; BMCI l Scoring of the l-member of the i-th class of parts of the substructure; DMCI (digital versatile disc) l Scoring the l member of the deck system class i component; k is the number of types of indicators that the i-th component/member is buckled; u, x and y are introduced variables; i is a component class; DP (DP) ij The deduction value of the j-th detection index of the i-th component l component is obtained.
Further, the technical condition scoring rule of the computing component includes:
the technical condition score of the component is calculated by formula (3):
in PCCI i A score for the i-th class of component of the superstructure;the average value of the scores of all the components of the ith class of parts of the upper structure; PCCI (prestressed concrete cylinder pipe) min A component score value that is the lowest score in the i-th class of component of the superstructure; BCCI (binary coded decimal computing interface) i A score for the i-th class of parts of the substructure; />The average value of the scores of all the components of the ith class of parts of the lower structure; BCCI (binary coded decimal computing interface) min A component score value which is the lowest score value in the i-th component of the lower structure; DCCI (DCCI) i Scoring the class i component of the deck system; />The average value of the scores of all the components of the ith class of components of the bridge deck system; DCCI (DCCI) min The component score value with the lowest score for the ith class of component of the bridge deck system; t is a coefficient that varies with the number of components.
Further, the calculating the technical condition scoring rule of the structure includes:
the technical condition score of the structure is calculated by formula (4):
wherein, SPCI is the technical condition score of the bridge superstructure; the SBCI is a technical condition score of the bridge substructure; BDCI is the technical condition score of the bridge deck system; m is the number of component types of the upper structure/the lower structure/the bridge deck; w (w) i Is the weight of the i-th class of component.
Further, the calculating the overall technical condition scoring rule includes:
the overall state of the art score is calculated by equation (5):
Dr＝DCI×W D +SPCI×W SP +SBCI×W SB (5)
wherein Dr is the score of the overall technical condition of the bridge; w (W) D The weight of the bridge deck system in the full bridge; w (W) SP Weights the superstructure in a full bridge; w (W) SB Is the weight of the substructure in the full bridge.
Further, after the defining the semantic query rule, the method further includes: and checking the consistency of sentences and semantics in the ontology knowledge base, the semantic web rules and the semantic query rules by adopting a Pellet plug-in, and automatically calculating and maintaining the hierarchy of the plurality of classes.
According to the invention, the body knowledge base is constructed by introducing bridge engineering basic knowledge, bridge engineering specifications and highway bridge engineering periodic inspection data, and semantic web rules and semantic query rules are combined, so that knowledge reasoning is realized, bridge disease information is automatically processed, grade scores of bridge technical conditions are obtained, automatic assessment of highway bridge technical conditions is realized, and the efficiency and the intelligent level of highway bridge data processing are greatly improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to the drawings without inventive effort to a person skilled in the art.
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a diagram of an architecture of the body system of the present invention;
FIG. 3 is a schematic diagram of annotation properties of classes in the present invention;
FIG. 4 is a schematic diagram of the hierarchy of classes, attributes of the classes, and examples of the classes of the present invention;
FIG. 5 is a schematic diagram of semantic verification of the present invention;
FIG. 6 is a schematic diagram of grammar verification of the present invention;
FIG. 7 is a diagram of parameters of road-bridge engineering evaluation output by the invention in a simulation experiment;
fig. 8 is a diagram of actual evaluation parameters in a road bridge engineering technology inspection report in a simulation experiment.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1, the embodiment provides a method for checking and evaluating technical conditions of a highway bridge based on a body, which comprises the following steps:
101. constructing a ontology knowledge base according to knowledge in the field of highway bridge engineering; knowledge in the field of highway bridge engineering, including bridge engineering basic knowledge, bridge engineering specifications and highway bridge engineering periodic inspection data;
specifically, as shown in fig. 2, the bridge engineering basic knowledge includes bridge classification, bridge structure composition, bridge disease type classification, and the like; bridge engineering specifications comprise a highway bridge technical condition assessment standard and a highway bridge and culvert maintenance specification; the periodic inspection data of highway bridge engineering is mainly data of periodic bridge appearance inspection, the appearance inspection mainly adopts visual inspection of approaching members and combines necessary instruments to carry out comprehensive and detailed inspection on the structure, and the main purpose of the periodic inspection data is to find out the existing defects and diseases of the structure and to record the names, positions, damage degrees and the scope of the parts appearing in the periodic inspection data in detail. Through bridge periodic inspection, a large amount of bridge inspection data is collected, including damage records of bridge deck systems, upper structures and lower structures.
102. Defining a plurality of classes, a hierarchy of the classes and attributes of the classes in an ontology knowledge base according to the knowledge in the field of highway bridge engineering, and creating instances of the classes;
specifically, all the introduced knowledge of the road bridge engineering field is stored in the knowledge base in the form of an OWL ontology. This process is to define classes in the OWL ontology language, but knowledge cannot be represented accurately with the class hierarchy alone, so the properties of the classes are used to link the classes together. There are three main types of attributes in an ontology, object attributes, data attributes and annotation attributes. An object property is a relationship between two individuals. The data attributes connect an individual to an XML schema data type value or RDF literal, i.e., are used to describe the relationship between the individual and the data value. As shown in FIG. 3, annotation properties are used to add information to class, individual, and object (data) properties. Further, individual instances are added to the class hierarchy, a class is first selected, then a specific instance of that class is added, and finally attribute values are appended to the instance. For example, the object attribute "has_damage" may be used to connect individuals of two classes "beam_bridge_structure" and "Damage", the data attribute "top_level" may assign a disease level, the data attribute "max_area" may assign a disease severity level, the instance "Bridge1" belongs to one instance of the Bridge, and so on. The partial categories, attributes and examples established are shown in fig. 4.
The types of the classes defined in the embodiment are classified into a class of bridge structure type and a class of structure disease type; wherein, the classes of bridge structure types are shown in table 1:
TABLE 1
Classes of structural disease types are shown in table 2:
TABLE 2
The ontology development software is mainly Prot g software, which is used for editing ontologies and rules, and many plugins of Prot g can be used for assisting modeling. The Pellet plug-in is an OWL language reasoner for performing semantic consistency check, automatically calculating and helping to correctly maintain the ontology hierarchy. The Class Matrix plug-in can quickly and efficiently add presence constraints to many classes along formulated attributes. The OWLViz plug-in is an ontology visual tree diagram plug-in that allows for visualization of class hierarchies.
103. Defining semantic web rules based on the ontology knowledge base; semantic net rules, including bridge disease grade assessment rules, deduction value assessment rules, coefficient and weight reasoning rules and bridge overall technical condition assessment rules;
specifically, in order to expand flexibility of the ontology and meet the requirements of bridge data processing, tool semantic web rules capable of performing advanced deduction reasoning capability are added on the basis of the ontology, and in the embodiment, the semantic web rules are written in SWRL language. The SWRL rule form is as follows:
B 1 ,...,B n →A 1 ,...,A m (1)
the rule consists of two main parts, the precondition (anticedent) and the result (connequent), which are connected by the symbol "→". B (B) 1 ,...,B n And A 1 ,...,A m Is an element in the SWRL rule and can be in the form of C (x), P (x, y). Where C is a class description and P is an attribute description. x and y are custom variables, have no special meaning, and are used only to represent the meaning of C/P. Both "preconditions" and "results" are aggregates of elements (atoms) that are connected by "≡s". Therefore, the rule is used for simulating the character value to map, and the OWL language is continuously expanded. In addition, SWRL rules also contain built-in elements. The built-in element is the most advanced feature in the semantic web rule language, and can carry out complex semantic reasoning such as mathematical calculation and the like.
In the embodiment, three SWRL rules are established aiming at the inspection and evaluation of the technical condition of the highway bridge, wherein the SWRL rules are bridge disease grade evaluation and deduction value evaluation rules, coefficient and weight reasoning rules and bridge overall technical condition evaluation rules respectively; wherein, the bridge disease grade evaluation and deduction value evaluation rules shown in the table 3 comprise a disease grade rule determination and a deduction point rule determination; coefficients and weight reasoning rules as shown in Table 4, including reasoning coefficient rules based on the number of components, determining component weight rules; the overall technical condition evaluation rules of the bridge shown in table 5 include a technical condition scoring rule of a computing component, a technical condition scoring rule of a computing part, a technical condition scoring rule of a computing structure, a computing overall technical condition scoring rule, and a computing bridge technical condition rating rule.
TABLE 3 Table 3
| Rule 1 | Determining disease grade/level |
| Rule1 -1 | Hole(？H)^max_area(？H,？Ha)^swrlb:lessThanOrEqual(？Ha,0)->level(？H,1) |
| Rule1 - | Hole(？H)^max_area(？H,？Ha)^swrlb:greaterThan(？Ha,0)^swrlb:lessThanOrEqual(？ Ha,0.5)->level(？H,2) |
| Rule1 -3 | Hole(？H)^max_area(？H,？Ha)^swrlb:greaterThan(？Ha,0.5)^swrlb:lessThanOrEqual(？ Ha,1)->level(？H,3) |
| Rule1 -4 | Hole(？H)^max_area(？H,？Ha)^swrlb:greaterThan(？Ha,1)->level(？H,4) |
| Rule 2 | Determination of the Point of deduction/DP |
| Rule2 -1 | Hole(？H)^top_level(？H,？Htl)^level(？H,？Hl)^swrlb:equal(？Htl,4)^swrlb:equal(？ Hl,1)->DP(？H,"0"^^xsd:int) |
| Rule2 -2 | Hole(？H)^top_level(？H,？Htl)^level(？H,？Hl)^swrlb:equal(？Htl,4)^swrlb:equal(？ Hl,2)->DP(？H,"25"^^xsd:int) |
| Rule2 -3 | Hole(？H)^top_level(？H,？Htl)^level(？H,？Hl)^swrlb:equal(？Htl,4)^swrlb:equal(？ Hl,3)->DP(？H,"40"^^xsd:int) |
| Rule2 -4 | Hole(？H)^top_level(？H,？Htl)^level(？H,？Hl)^swrlb:equal(？Htl,4)^swrlb:equal(？ Hl,4)->DP(？H,"50"^^xsd:int) |
TABLE 4 Table 4
| Rule 1 | Inferring a coefficient t from the number of components n |
| Rule1- 1 | Bridge_structure(？B)^n(？B,？Bn)^swrlb:equal(？Bn,1)->t(？B,100000000000000) |
| Rule1- 2 | Bridge_structure(？B)^n(？B,？Bn)^swrlb:equal(？Bn,10)->t(？B,8.1) |
| Rule1- 3 | Bridge_structure(？B)^n(？B,？Bn)^swrlb:equal(？Bn,20)->t(？B,6.6) |
| Rule1- 4 | Bridge_structure(？B)^n(？B,？Bn)^swrlb:equal(？Bn,30)->t(？B,5.4) |
| Rule1- 5 | Bridge_structure(？B)^n(？B,？Bn)^swrlb:equal(？Bn,40)->t(？B,4.9) |
| Rule1- 6 | Bridge_structure(？B)^n(？B,？Bn)^swrlb:equal(？Bn,50)->t(？B,4.4) |
| Rule1- 7 | Bridge_structure(？B)^n(？B,？Bn)^swrlb:equal(？Bn,60)->t(？B,4.0) |
| Rule1- 8 | Bridge_structure(？B)^n(？B,？Bn)^swrlb:equal(？Bn,70)->t(？B,3.6) |
| Rule1- 9 | Bridge_structure(？B)^n(？B,？Bn)^swrlb:equal(？Bn,80)->t(？B,3.2) |
| Rule1- 10 | Bridge_structure(？B)^n(？B,？Bn)^swrlb:equal(？Bn,100)->t(？B,2.5) |
| Rule1- 11 | Bridge_structure(？B)^n(？B,？Bn)^swrlb:greaterThanOrEqual(？Bn,200)->t(？B,2.3) |
| Rule 2 | Determining the weight w of each component |
| Rule2- 1 | Super_w(？P)->w1(？P,0.7)^w2(？P,0.18)^w3(？P,0.12) |
| Rule2- 2 | Sub_w(？B)->w4(？B,0.02)^w5(？B,0.01)^w6(？B,0.3)^w7(？B,0.3)^w8(？B,0.28)^w9(？B, 0.07)^w10(？B,0.02) |
| Rule2- 3 | Deck_w(？D)->w11(？D,0.4)^w12(？D,0.25)^w13(？D,0.1)^w14(？D,0.1)^w15(？D,0.1)^ w16(？D,0.05) |
TABLE 5
The technical condition score of the component is calculated by formula (2):
where, when x=1, U 1 ＝DP i1 The method comprises the steps of carrying out a first treatment on the surface of the When DP ij ＝100，PMCI l (BMCI l Or DMCI l )＝0；PMCI l Scoring of the l-member of the i-th class of parts of the superstructure; BMCI l Scoring of the l-member of the i-th class of parts of the substructure; DMCI (digital versatile disc) l Scoring the l member of the deck system class i component; k is the number of types of indicators that the i-th component/member is buckled; u, x and y are introduced variables; i is a component class; DP (DP) ij The deduction value of the j-th detection index of the i-th component l component is obtained.
The technical condition score of the component is calculated by formula (3):
in PCCI i A score for the i-th class of component of the superstructure;the average value of the scores of all the components of the ith class of parts of the upper structure; PCCI (prestressed concrete cylinder pipe) min A component score value that is the lowest score in the i-th class of component of the superstructure; BCCI (binary coded decimal computing interface) i A score for the i-th class of parts of the substructure; />The average value of the scores of all the components of the ith class of parts of the lower structure; BCCI (binary coded decimal computing interface) min A component score value which is the lowest score value in the i-th component of the lower structure; DCCI (DCCI) i Scoring the class i component of the deck system; />The average value of the scores of all the components of the ith class of components of the bridge deck system; DCCI (DCCI) min The component score value with the lowest score for the ith class of component of the bridge deck system; t is a coefficient that varies with the number of components.
The technical condition of the structure is the technical condition of the upper structure or the lower structure or the bridge deck system of the bridge, and the technical condition score of the structure is calculated by the formula (4):
wherein, SPCI is the technical condition score of the bridge superstructure; the SBCI is a technical condition score of the bridge substructure; BDCI is the technical condition score of the bridge deck system; m is the number of component types of the upper structure/the lower structure/the bridge deck; w (w) i Is the weight of the i-th class of component.
The overall state of the art score is calculated by equation (5):
Dr＝DCI×W D +SPCI×W SP +SBCI×W SB (5)
wherein Dr is the score of the overall technical condition of the bridge; w (W) D The weight of the bridge deck system in the full bridge; w (W) SP Weights the superstructure in a full bridge; w (W) SB Is the weight of the substructure in the full bridge.
104. Defining a semantic query rule; semantic query rules comprising: a bridge overall condition evaluation query rule and a bridge disease cause query rule;
specifically, the query of the ontology is implemented through the semantic query language SQWRL. SQWRL is a SWRL-based language from which the bridge engineer can obtain the desired results when the requirements are entered as SQWRL language through the Prot g query interface. As shown in table 6, the defined semantic query rules include: and the bridge overall condition evaluation query rule and the bridge disease cause query rule.
TABLE 6
The newly built ontology needs to be verified, including verification of correctness of ontology semantics and grammar.
(1) Semantic verification: to ensure the specification of the built ontology, the lexical relations in the us bridge inspection standards are text analyzed using AntConc corpus analysis software, and each concept incorporated into the ontology knowledge base is analyzed and evaluated. Taking bridge "extraction" as an example, the corpus collocation extracted from the antconco corpus is shown in fig. 5. (2) grammar validation: and checking consistency of all sentences and defined semantics in the ontology by adopting a Pellet plug-in, and automatically calculating and maintaining the hierarchical structure of the ontology class. The result of the examination is shown in fig. 6, the inference engine does not make any error during the operation, and the result (yellow position) is correctly deduced. The semantic and grammar verification is completed, and the established ontology can be used.
105. Inputting the requirements of inspection and evaluation of the technical condition of the highway bridge, and operating the semantic web rules and the semantic query rules to obtain the parameters of the technical condition of the highway bridge.
Specifically, the specific operation of the body system is illustrated by simulation experiments.
Simulation experiment:
the bridge is an automobile channel 12 positioned on the expressway of the G7 line of China, and the center pile number is K2626+164. The bridge is built in 2013, the full width of the bridge deck is 28m, and the full length of the bridge is 15.5m.
The method specifically realizes the inspection and evaluation of the technical condition of the highway bridge through the body system as follows:
(1) Calculating the disease grade and the deduction value: the bridge 0# and 1# bridge abutment have pitted surfaces, and the maximum area is 0.4m 2 The area was manually added to the body, and the disease level was automatically calculated according to rule 1 and rule 2 of table 3, and the calculation was performed by the calculation of the score, and the level (disease level) and DP (score) values were output.
(2) Calculating the technical condition score of the bridge component: first, the t value (coefficient according to the number of components, which can be inferred from rule 1 of table 4) is manually input. And then sequentially reasoning to obtain component scores of each abutment according to rule 1 of table 5, outputting BMCI (component condition score) values, and reasoning to obtain scores of the whole abutment components according to rule 2, and outputting BCCI (lower component technical condition score) values.
(3) Calculating the technical condition score of the bridge substructure: in this step, the weight of each component of the bridge (coefficient changing with the bridge type, obtained by reasoning according to rule 2 in table 4) is defined into the ontology, the condition score of the bridge structure is deduced by the operation rule 3, and the SBCI (lower structure technical condition score) value is output.
(4) And similarly, repeating the steps to obtain the technical condition scores of the bridge superstructure and the bridge deck system, and outputting SPCI (superstructure condition score) and BCI (bridge deck system condition score) values.
(5) And (3) operating the rule 4 and the rule 5 to calculate the overall technical condition score and grade of the bridge, and outputting Dr (score) and Dj (grade) values.
As shown in fig. 7, the values of the bridges Dr and Dj are 94.61 and 2, respectively. The above values are compared with the actual value of the bridge, fig. 8, with an accuracy of 100%.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.
Claims (3)
1. The method for checking and evaluating the technical condition of the highway bridge based on the body is characterized by comprising the following steps of:
constructing a ontology knowledge base according to knowledge in the field of highway bridge engineering; the highway bridge engineering field knowledge comprises: bridge engineering basic knowledge, bridge engineering specifications and highway bridge engineering periodic inspection data;
defining a plurality of classes, a hierarchy of the classes and attributes of the classes in the ontology knowledge base according to the highway bridge engineering field knowledge, and creating instances of the classes;
defining semantic web rules based on the ontology knowledge base; the semantic web rule is a SWRL rule, and the SWRL rule is in the form of:
B 1 ，...，B n →A 1 ，...，A m (1)
wherein A is 1 ，...，A m Is a precondition for SWRL rules; b (B) 1 ，...，B n Is the result of SWRL rules;
the SWRL rules include: bridge disease grade evaluation and deduction value evaluation rules, coefficient and weight reasoning rules and bridge overall technical condition evaluation rules;
the bridge disease grade evaluation and deduction value evaluation rule comprises the following steps: determining a disease grade rule and a deduction point rule;
the coefficient and weight reasoning rules include: reasoning coefficient rules and determining component weight rules according to the number of components;
the bridge overall technical condition assessment rule comprises the following steps: calculating a technical condition scoring rule of a component, a technical condition scoring rule of a calculating part, a technical condition scoring rule of a calculating structure, a general technical condition scoring rule and a bridge technical condition grading rule;
a technical condition scoring rule for the computing component comprising: the technical condition score of the component is calculated by formula (2):
where, when x=1, U 1 ＝DP i1 The method comprises the steps of carrying out a first treatment on the surface of the When DP ij ＝100，PMCI l =0 or BMCI l =0 or DMCI l ＝0；
PMCI l Scoring of the l-member of the i-th class of parts of the superstructure; BMCI l Scoring of the l-member of the i-th class of parts of the substructure; DMCI (digital versatile disc) l Scoring the l member of the deck system class i component; k is the number of types of indicators that the i-th component/member is buckled; u, x and y are introduced variables; i is a component class; DP (DP) ij A deduction value of a j-th detection index of the i-th component l component;
the technical condition scoring rule of the computing component includes: the technical condition score of the component is calculated by formula (3):
in PCCI i A score for the i-th class of component of the superstructure;the average value of the scores of all the components of the ith class of parts of the upper structure; PCCI (prestressed concrete cylinder pipe) min A component score value that is the lowest score in the i-th class of component of the superstructure; BCCI (binary coded decimal computing interface) i A score for the i-th class of parts of the substructure; />The average value of the scores of all the components of the ith class of parts of the lower structure; BCCI (binary coded decimal computing interface) min A component score value which is the lowest score value in the i-th component of the lower structure; DCCI (DCCI) i Scoring the class i component of the deck system; />The average value of the scores of all the components of the ith class of components of the bridge deck system; DCCI (DCCI) min The component score value with the lowest score for the ith class of component of the bridge deck system; t is a coefficient that varies with the number of components;
the technical condition scoring rule of the computing structure comprises: the technical condition score of the structure is calculated by formula (4):
wherein, SPCI is the technical condition score of the bridge superstructure; the SBCI is a technical condition score of the bridge substructure; BDCI is the technical condition score of the bridge deck system; m is the number of component types of the upper structure/the lower structure/the bridge deck; w (w) i Weights for the i-th class of components;
the calculating the overall technical condition scoring rule includes: the overall state of the art score is calculated by equation (5):
Dr＝BDCI×W BD +SPCI×W SP +SBCI×W SB (5)
wherein Dr is the score of the overall technical condition of the bridge; w (W) BD The weight of the bridge deck system in the full bridge; w (W) SP Weights the superstructure in a full bridge; w (W) SB Weights the substructure in the full bridge;
defining a semantic query rule; semantic query rules comprising: a bridge overall condition evaluation query rule and a bridge disease cause query rule;
inputting the requirements of inspection and evaluation of the technical condition of the highway bridge, and operating the semantic web rules and the semantic query rules to obtain the parameters of the technical condition of the highway bridge.
2. The method of claim 1, wherein the plurality of classes comprises:
class of bridge structure type and class of structure disease type;
a class of bridge structure types comprising: beam bridges, arch bridges, suspension bridges, and cable-stayed bridges;
a class of structural disease types comprising: upper bearing members, supports, piers, abutment and foundation.
3. The method for checking and evaluating the technical condition of the highway bridge based on the body according to claim 1, wherein after the defining of the semantic query rule, the method further comprises:
and checking the consistency of sentences and semantics in the ontology knowledge base, the semantic web rules and the semantic query rules by adopting a Pellet plug-in, and automatically calculating and maintaining the hierarchy of the plurality of classes.
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