CN113255811B - BIM-based beam bridge multi-source heterogeneous data fusion decision system - Google Patents
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Abstract
The invention discloses a BIM-based beam bridge multi-source heterogeneous data fusion decision system which comprises an operation and maintenance basic data unit, a BIM visual model unit, a disease intelligent acquisition unit, a disease maintenance tracking unit, a technical condition assessment unit, a structure monitoring and early warning unit, a load test analysis unit, a bearing capacity test unit, a maintenance investment decision unit, a virtual reality demonstration unit, a cloud server and a client. Aiming at the decision-making problem of the curing maintenance and reinforcement treatment scheme in the beam bridge curing process, the invention comprehensively applies multi-source heterogeneous data of disease investigation, monitoring and early warning, detection analysis and bearing capacity detection and calculation to make a scientific curing investment scheme and guide scientific curing management.
Description
Technical Field
The invention belongs to the technical field of building information, and particularly relates to a BIM-based beam bridge multi-source heterogeneous data fusion decision system.
Background
In recent years, along with the great development of intelligent traffic, the investigation, monitoring and early warning and the like of bridge diseases are basically informationized and intelligent; however, the data island phenomenon is obvious, and the multi-source heterogeneous data such as basic information, disease information, monitoring detection information and the like are not organically fused, so that the problems of low data utilization efficiency, inaccurate identification of the structural operation state and the like are caused.
The decision-making management platform of the bridge is more common in large-scale bridge management and maintenance; however, as the transportation industry reforms by multi-province, the provincial maintenance investment plan management mode is implemented step by step, the center of gravity of unified maintenance of the provincial bridge is a beam bridge in a common structural form, and a big data-based decision method and a big data-based decision-making platform are the core for solving the problems.
BIM technology rapidly develops in bridge design and construction in recent years, however, due to the fact that the maintenance process is long, units and people are involved, the digitization degree is low, and the phenomenon of data island exists, the technology is rarely applied in the maintenance management process; however, the BIM visual model is used as an information carrier and is applicable to each stage of bridge full life cycle management and control in the technical aspect.
Disclosure of Invention
The invention provides a BIM-based beam bridge multi-source heterogeneous data fusion decision system, which is characterized in that a maintenance investment decision algorithm based on a analytic hierarchy process can realize network-level maintenance priority ordering, fuses business data such as frequent inspection, periodic inspection, load test, bearing capacity assessment and the like, combines actual inspection situation distinction to only consider technical condition assessment of apparent diseases and technical condition assessment of structural deformation, provides scientific support for selection of maintenance and reinforcement treatment, uses a BIM model as a data carrier, uses a VR technology to strengthen expert knowledge of bridge structural diseases and deformation by using a virtual reality scene, can consult various archive parameters, carries out on-line communication discussion, and demonstrates maintenance and reinforcement treatment schemes suggested by a platform, thereby guaranteeing rationality of the overall scheme.
The technical proposal is as follows:
A BIM-based beam bridge multi-source heterogeneous data fusion decision system comprising: the system comprises an operation and maintenance basic data unit, a BIM visual model unit, a disease intelligent acquisition unit, a disease maintenance tracking unit, a technical condition assessment unit, a structure monitoring and early warning unit, a load test analysis unit, a bearing capacity test unit, a maintenance investment decision unit, a virtual reality demonstration unit, a cloud server and a client;
The operation and maintenance basic data unit comprises 'highway bridge and culvert maintenance standard', JTG H11-2004 and annex A bridge basic part content, and is used for calculating annual per kilometer charge, whether a road section is reloaded and whether a large transportation channel is information according to maintenance investment decision;
The BIM visual model unit is used for visually displaying a bridge structure according to the actual size by applying a light-weight technology, converting three-dimensional information of diseases into two-dimensional information for displaying, displaying technical condition assessment grades of different components, displaying a monitoring early warning sensing system and real-time data, displaying a load test load distribution scheme and corresponding structural response, and displaying vibration modes and frequencies acquired by a load test; the three-dimensional information of the disease is converted into two-dimensional information for display, so that structural plane attribution information and coordinate information in disease position description are combined with a BIM model, the structural plane and specific position of the disease in the model are accurately positioned, and roaming viewing is realized;
The intelligent disease collection unit comprises a structural analysis standard, a position description standard, a characteristic description standard, an image file standard, an evaluation model library and an AI image recognition algorithm, wherein the evaluation model library comprises a component library, a sub-component library and a disease type library;
The disease maintenance tracking unit establishes association relation of different time attribute diseases, is used for only recording the change of disease characteristics during on-site inspection to improve on-site inspection efficiency, and simultaneously realizes the development tracking and prediction of the disease length, width, area and maximum seam width characteristics according to a time axis so as to track and evaluate maintenance measures;
the technical condition assessment unit automatically scores components, parts and parts according to the stability of diseases according to the technical condition assessment standard of highway bridges, JTG T H21-2011, and generates a disease development chart and an assessment report;
The structure monitoring and early warning unit is used for aiming at the beam bridge with low evaluation score of the technical conditions of the upper structure and the lower structure, aiming at the beam bridge, aiming at the structural conditions of the upper structure and the lower structure, arranging deformation, strain and fundamental frequency test elements, monitoring the mechanical behavior change of the structure, and setting an early warning threshold value to early warn abnormal response;
The load test analysis unit is used for capturing a beam bridge with low evaluation score of the rigidity change of the bearing member or the technical condition of part of the upper structure aiming at the structural monitoring and early warning unit, carrying out a load test according to the highway bridge load test procedure JTG/T J21-01-2015, inputting a detection scheme and a result, automatically calculating a check coefficient, and analyzing whether the rigidity of the structure is in a normal range;
the bearing capacity testing unit is used for inputting material condition and state parameter data according to JTG/T J21-2011 and aiming at a girder bridge with structure deflection or deformation and stress overrun according to the highway bridge bearing capacity detection and assessment procedure, and carrying out bridge assessment according to the result of a combined load test analysis unit needing bearing capacity assessment;
The maintenance investment decision unit can automatically calculate the cost according to disease maintenance measures and structural reinforcement treatment measures aiming at maintenance and reinforcement treatment, realize maintenance priority ordering based on a hierarchical analysis method, and automatically generate a reasonable distribution scheme of limited expenses and a reasonable distribution scheme aiming at special targets; the maintenance measures of the disease maintenance are that maintenance methods, unit price and units corresponding to different types of diseases of the beam bridge are set; the structural reinforcement treatment measures are used for setting optional reinforcement treatment schemes, unit price and units of the beam bridge; the maintenance priority ordering is realized based on the analytic hierarchy process, and a priority ordering algorithm is provided;
The virtual reality demonstration unit is used for checking apparent bridge diseases in a roaming manner in virtual reality through VR, monitoring historical data and analysis results, analyzing calculation results of load tests, and material conditions and state parameters, and demonstrating reinforcement treatment schemes adopted by bridge structure plans;
the data cloud server and the client are used for realizing real-time calling of the data stored in the network and friendly interaction with the user through the WEB client and the mobile client.
Preferably, the BIM visual model unit can directly display disease information, structure monitoring points and testing maximum values, load test positions and check coefficients, bridge deck real-time traffic flow and vehicle type classification and other information, distinguish technical condition assessment results of each component by colors, check corresponding electronic files, material conditions and state parameters after clicking specific positions, support VR roaming, and realize demonstration of the rationality of reinforcement treatment scheme of bridge structures in virtual reality environment; the electronic file comprises drawings, report data, such as construction period, operation period, and the like.
Preferably, the disease maintenance tracking unit is used for checking whether all historical diseases are subjected to tracking investigation by adding a field detection completion confirmation function to the data cloud server and the client, marking the slit width test positions on the scene of the key crack diseases, fusing frequent checking and periodic checking information to realize low-frequency monitoring on the development condition of the diseases, and providing data support for judging the change of the stress characteristics of the structure; by tracking and monitoring the cured maintenance diseases, the tracking and evaluation of the maintenance measures are realized, and the good and poor-elimination maintenance measures are recommended.
Preferably, the technical condition assessment unit is used for comprehensively evaluating the disease property after judging according to the disease data of frequent inspection and periodical inspection and the low-frequency monitoring data of the disease maintenance tracking unit.
Preferably, the maintenance investment decision unit aims at maintenance and reinforcement treatment, wherein the maintenance is supported by taking disease information which is frequently checked and regularly checked as basic data, and is directly supported by taking the calculation result of the technical condition assessment unit, and the maintenance basic data unit is fused for intelligent auxiliary decision; the reinforcement treatment is based on frequent inspection and regular inspection of apparent diseases, and a structure monitoring and early warning unit and a load test analysis unit are integrated to realize mid-span deflection assessment and structure deflection assessment; when the technical condition assessment structure of the component is controlled by mid-span deflection and structural deflection, fusing the material condition and state parameter data of the bearing capacity testing unit to carry out bearing capacity detection; the maintenance investment decision unit follows the following general idea: the reinforcement treatment priority is higher than that of maintenance; bridges with general and lower structure technical condition grades of four, five or upper structure grade of five must be treated; the maintenance investment decision unit establishes a maintenance priority evaluation index system based on an analytic hierarchy process, wherein the maintenance priority evaluation index system comprises two types of safety indexes and importance indexes; wherein, the security index includes: classifying annual per kilometer charge, route grade, bridge position and bridge length; the importance index includes: technical condition evaluation total score, upper structure evaluation score, lower structure evaluation score, bridge deck system evaluation score, operation period, special structure bridge, annual frequent check times, whether to load road sections, and whether to transport large transportation channels; the annual per kilometer charge amount, the route grade, the bridge position, the bridge length classification, the operation years, the bridges with special structures, the annual frequent check times, whether the road sections are overloaded and whether the large transportation channels are all obtained from the operation and maintenance basic data unit; the technical condition evaluation total score, the upper structure evaluation score, the lower structure evaluation score and the bridge deck system evaluation score are all obtained from the technical condition evaluation unit;
The maintenance investment decision unit determines the weight as an importance index of 0.33 and a safety index of 0.67 according to an expert investigation method; annual per kilometer charge amount 0.58, route grade 0.26, bridge position 0.11, bridge length classification 0.05; technical condition evaluation total score 0.13, upper structure evaluation score 0.23, lower structure evaluation score 0.11, bridge deck system evaluation score 0.03, operation period 0.07, special structure bridge 0.04, annual frequent check times 0.05, whether heavy load road section 0.10, and whether large transportation channel 0.24.
Preferably, the maintenance investment decision unit determines the value of the selected decision parameter according to a 5-scale method, and the method specifically comprises the following steps:
The decision index of the charge per kilometer is valued: 5- [2.5 ], in +++). 4- [2.0, 2.5), 3- [1.5, 2.0), 2- [1.0, 1.5), 1- [0, 1.5);
Route grade decision index value: 5-expressway, 4-primary road, 3-secondary road, 2-tertiary road and 1-quaternary road;
Bridge position decision index takes value: 5-main bridge, 4-auxiliary road bridge, 3-ramp bridge, 2-overpass bridge and 1-others;
Bridge length classification index value: 5-super bridge, 4-big bridge, 3-middle bridge and 2-small bridge;
The technical condition evaluation total score decision index takes the value: 5- [60, 80), 3- [80, 95), 1- [95, 100];
the upper structure evaluation score decision index takes the value: 5- [40, 60), 4- [60, 80), 2- [80, 95), 1- [95, 100];
lower structure evaluation score decision index value: 5- [60, 80), 3- [80, 95), 1- [95, 100];
Bridge deck system evaluation score decision index value: 5- [0, 40), 4- [40, 60), 3- [60, 80), 2- [80, 95), 1- [95, 100];
the operation year decision index takes value: 5- [0, 30), 4- [20, 30), 3- [10, 20), 4- [5, 10), 5- [0, 5;
the decision index of the bridge with the special structure takes the value: 5-special structural bridges, 1-conventional structural bridges;
frequent checking times decision index value: 5-0,4- [0, 12), 3- [12, 24), 2- [24, 36), 1- [36 ] the number of the components, +++).
Whether the decision index of the heavy load road section takes the value: 5-is a heavy load road section, 1-is a non-heavy load road section;
Whether the decision index of the large transportation channel takes the value: 5-large piece transportation channel, 1-non-large piece transportation channel.
Further, the maintenance investment decision unit supports the specified decision index not to participate in the evaluation, and the specific maintenance target comprises: the technical conditions of the overall upper structure of the higher road network bridge are equally divided, the number of the lower bridges is equal to or less than the number of the lower bridges, and the length of the lower bridges is equal to or less than the number of the lower bridges.
Further, the maintenance investment decision unit has the following specific algorithm:
Aiming at the more positive maintenance expense S Ⅱ for bridge maintenance with obvious disease affecting operation safety, the method comprises the following reasonable distribution of reinforcement, and meets the following requirements: the technical conditions are bridges of four classes and five classes, and bridges with upper structure scores lower than 40 points or lower structure scores lower than 60 points in the bridges of three classes must be maintained;
assuming the total number of bridges in the road network is n, and the set is A; the method is a special structure bridge and an extra large bridge, and the evaluation results are four types and five types, namely a set A 1; four and five types of bridges, except a 1, are set a 2; the bridge is a bridge with a special structure and an extra large bridge, and the three cases are evaluated as intersections A 3; three types of bridges, except for a 3, are set a 4; the special structure bridges and extra large bridges except A 1、A3 are set A 5; other cases are set a 6;
The maintenance priority of each set is A 1＞A2＞(A3、A4)＞A5＞A6, wherein A 1、A2 needs to be repaired, A 3 needs to be repaired, A 4 needs to be repaired (partial bridges possibly exist in the set with higher priority than A 3), the total investment cost S Ⅱ.A5、A6 can be repaired or not repaired, and the total investment cost is conditional maintenance cost S I (used for bridge maintenance without obvious disease influence on operation safety);
Assuming that the number of elements in set a i is x i(xi ≡0), i=1 to 6, The element (bridge) is a ij, the maintenance cost of bridge a ij is s ij, and the maintenance state is c ij (when the value is 1, it is determined that maintenance is not performed, and when the value is 0). Bridge maintenance cost in set A i is/>The curing is performed as follows:
to determine the maintenance state c ij of the element in A 3、A4, performing maintenance priority evaluation index calculation according to the decision index level and weight; the weight of the index P y is W y, y is the number of the decision index, and the value of each decision index P y of the bridge a ij is P y-ij. The maintenance priority grade of the bridge a ij is I ij＝20∑Wypy-ij, and the value range is 0-100; when the designated decision index does not participate in the evaluation, the introduced decision index P y uses the state parameter d y (when the participation evaluation value is 1 and the non-participation evaluation value is 0), y is the decision index number, the initial weight is W 0-y, and the weight is calculated
The element maintenance priority scores in A 3、A4 are J 1,J2 and … … in sequence from the top to the bottom, the corresponding maintenance cost is s 1,s2 and … …, when the requirements are metWhen the bridge maintenance state corresponding to J △ is 1 (delta=1-m), and the maintenance state of other elements in a 3、A4 is 0;
for maintenance priority evaluation index calculation considering special requirements, the following parameters are introduced for a concrete bridge a ij for the convenience of calculation:
score contribution index:
Or (b)
Representing the ratio of the cost required for scoring the overall (superstructure) technical condition of the bridge a ij to the average level of all three types of bridges in the road network for every 1 point improvement; d r-ij is the overall technical status score for bridge a ij, SPCI r-ij is the superstructure technical status score for bridge a ij;
the quantitative contribution index:
representing the ratio of the expense required for maintaining the bridge a ij to the average level of all three types of bridges in the road network;
Length contribution index:
Representing the ratio of the expense required for maintaining the bridge a ij per linear meter to the average level of all three types of bridges in the road network;
Setting a specific maintenance target participation coefficient as e α、eβ、eγ, wherein the value of the specific maintenance target participation coefficient is 1 when the maintenance target needs to be met, and the specific maintenance target participation coefficient is 0 when the maintenance target is not needed; the maintenance priority score for bridge a ij is calculated as:
Iij＝20[1+min{Wy}(eααij+eββij+eγγij)]∑Wypy-ij
Preferably, the virtual reality demonstration unit supports the bridge to be reinforced and treated, intuitively knows the operation condition of the bridge at any time and any place, refers to electronic archives, and performs voice discussion in a platform to simulate the scene of expert on-site demonstration.
The beam bridge multi-source heterogeneous data fusion decision method and the platform based on BIM provided by the invention have the following advantages:
(1) The maintenance investment decision algorithm based on the analytic hierarchy process can realize the network-level maintenance priority ordering, and support the intelligent generation of maintenance expense allocation schemes under the conventional targets and the special targets;
(2) The method integrates business data such as frequent inspection, periodic inspection, load test, bearing capacity evaluation and the like, combines the technical condition evaluation of only considering apparent diseases and the technical condition evaluation of considering structural deformation in the distinction of actual inspection conditions, and provides scientific support for the selection of maintenance and reinforcement treatment;
(3) The BIM model is used as a data carrier, the VR technology is applied to strengthen the knowledge of experts on bridge structure diseases and deformation in a virtual reality scene, various file parameters can be referred to, on-line communication discussion is developed, the maintenance and reinforcement treatment scheme suggested by the platform is demonstrated, and the rationality of the overall scheme is ensured.
Drawings
FIG. 1 is an overall block diagram of a BIM-based beam bridge multi-source heterogeneous data fusion decision system;
FIG. 2 is a general step implementation diagram of a BIM-based beam bridge multi-source heterogeneous data fusion decision system.
Detailed Description
In order to enable those skilled in the art to better understand the technical scheme of the invention, the following describes the multi-source heterogeneous data fusion decision system of the girder bridge based on BIM in detail by combining the embodiment. The following examples are only illustrative of the present invention and are not intended to limit the scope of the invention.
Example 1
As shown in fig. 2, the operation of the beam bridge multi-source heterogeneous data fusion decision system based on BIM provided by the present invention includes 14 steps:
s1: the operation and maintenance basic data of the road network bridge are maintained by using a WEB or mobile client;
s2: building a BIM model according to the actual structural size of the bridge, evaluating the construction members to be divided according to the technical condition, and associating the construction period, operation period and other drawing, report and other data in the electronic file;
S3: the intelligent collection of the new disease found on site and the characteristic development record of the disease found in the past are carried out through the mobile client, and the record of whether the disease which is maintained and maintained is continuously developed is also included;
S4: according to the collected apparent diseases, carrying out intelligent assessment on the technical conditions to obtain the technical condition assessment grades of each component, part, position and overall;
S5: according to the technical condition rating, dividing the bridge into three types, namely a bridge which only needs maintenance, a bridge which possibly needs reinforcement treatment and a bridge which needs reinforcement treatment;
s6: developing a structural deflection test and a load test analysis (or structural monitoring and early warning) aiming at a bridge which possibly needs reinforcement treatment, wherein the structural deflection test focuses on permanent deflection of the structure, and the load test analysis (or structural monitoring and early warning) focuses on the response of the structure under the load;
S7: judging according to the deflection and deformation of the structure and stress conditions, and when the deflection and the deformation are not over-limited, indicating that the disease of the structure only affects the durability; when one of the two is out of limit, the stress performance of the structure is inconsistent with the design state, and diseases can have irreversible influence on the overall rigidity and the section rigidity of the structure;
S8: aiming at the condition that both the two are judged to not exceed the limit in the step S7, maintenance expense calculation is carried out;
S9: and (3) carrying out bearing capacity assessment on the bridge which is judged to be out of limit and has to be reinforced and treated in the step (S7), wherein the method comprises the following steps of:
S9-1: detecting material conditions and state parameters, and executing according to the highway bridge bearing capacity detection and assessment procedure (JTG/T J21-2011);
s9-2: performing bridge structure checking, and automatically executing according to the highway bridge bearing capacity checking and evaluating procedure (JTG/T J21-2011);
S10: judging whether the bearing capacity meets the requirement, executing S8 when the bearing capacity meets the requirement, and executing S11 when the bearing capacity does not meet the requirement;
S11: selecting a reinforcement treatment scheme according to the bearing capacity checking condition, and performing the menstruation fee calculation;
S12: the bridge and the expenses to be maintained and reinforced are comprehensively and preliminarily determined, and the maintenance priority ranking under the limited expenses is carried out by adopting a hierarchical analysis method in combination with the conventional management and maintenance targets and the special management and maintenance targets;
s13: expert demonstration of developing a maintenance investment plan comprising the steps of:
S13-1: the BIM model synchronizes disease, deformation, deflection, material conditions and state parameter data;
s13-2: expert refers to the related data and the electronic archive data in the BIM through VR virtual reality technology;
s13-3: carrying out on-line technical demonstration, and mainly aiming at a strengthening scheme adopted by a bridge needing strengthening treatment;
s14: and repairing and editing the maintenance investment scheme according to the online technical demonstration result.
The invention provides a BIM-based beam bridge multi-source heterogeneous data fusion decision method and a BIM-based beam bridge multi-source heterogeneous data fusion decision platform, wherein a maintenance investment decision algorithm based on a analytic hierarchy process can achieve network-level maintenance priority ordering, a visual BIM model is used as a multi-source heterogeneous data carrier, full life cycle data fusion can be applied to the research and selection of maintenance and reinforcement treatment schemes, and VR virtual reality is applied to expert demonstration processes, so that scientific maintenance decisions based on big data analysis for the beam bridge are achieved.
While the present invention has been described in detail with reference to the embodiments, the present invention is not limited to the above-described embodiments, and various changes can be made without departing from the spirit of the present invention within the knowledge of those skilled in the art, and the present invention shall also be considered as the scope of the present invention.
Claims (8)
1. BIM-based beam bridge multi-source heterogeneous data fusion decision system is characterized by comprising: the system comprises an operation and maintenance basic data unit, a BIM visual model unit, a disease intelligent acquisition unit, a disease maintenance tracking unit, a technical condition assessment unit, a structure monitoring and early warning unit, a load test analysis unit, a bearing capacity test unit, a maintenance investment decision unit, a virtual reality demonstration unit, a cloud server and a client;
The operation and maintenance basic data unit comprises 'highway bridge and culvert maintenance standard', JTG H11-2004 and annex A bridge basic part content, and is used for calculating annual per kilometer charge, whether a road section is reloaded and whether a large transportation channel is information according to maintenance investment decision;
The BIM visual model unit is used for visually displaying a bridge structure according to the actual size by applying a light-weight technology, converting three-dimensional information of diseases into two-dimensional information for displaying, displaying technical condition assessment grades of different components, displaying a monitoring early warning sensing system and real-time data, displaying a load test load distribution scheme and corresponding structural response, and displaying vibration modes and frequencies acquired by a load test; the three-dimensional information of the disease is converted into two-dimensional information for display, so that structural plane attribution information and coordinate information in disease position description are combined with a BIM model, the structural plane and specific position of the disease in the model are accurately positioned, and roaming viewing is realized;
The intelligent disease collection unit comprises a structural analysis standard, a position description standard, a characteristic description standard, an image file standard, an evaluation model library and an AI image recognition algorithm, wherein the evaluation model library comprises a component library, a sub-component library and a disease type library;
The disease maintenance tracking unit establishes association relation of different time attribute diseases, is used for only recording the change of disease characteristics during on-site inspection to improve on-site inspection efficiency, and simultaneously realizes the development tracking and prediction of the disease length, width, area and maximum seam width characteristics according to a time axis so as to track and evaluate maintenance measures;
the technical condition assessment unit automatically scores components, parts and parts according to the stability of diseases according to the technical condition assessment standard of highway bridges, JTG TH21-2011, and generates a disease development chart and an assessment report;
The structure monitoring and early warning unit is used for aiming at the beam bridge with low evaluation score of the technical conditions of the upper structure and the lower structure, aiming at the beam bridge, aiming at the structural conditions of the upper structure and the lower structure, arranging deformation, strain and fundamental frequency test elements, monitoring the mechanical behavior change of the structure, and setting an early warning threshold value to early warn abnormal response;
The load test analysis unit is used for capturing a beam bridge with low evaluation score of the rigidity change of the bearing member or the technical condition of part of the upper structure aiming at the structural monitoring and early warning unit, carrying out a load test according to the highway bridge load test procedure JTG/T J21-01-2015, inputting a detection scheme and a result, automatically calculating a check coefficient, and analyzing whether the rigidity of the structure is in a normal range;
the bearing capacity testing unit is used for inputting material condition and state parameter data according to JTG/T J21-2011 and aiming at a girder bridge with structure deflection or deformation and stress overrun according to the highway bridge bearing capacity detection and assessment procedure, and carrying out bridge assessment according to the result of a combined load test analysis unit needing bearing capacity assessment;
The maintenance investment decision unit can automatically calculate the cost according to disease maintenance measures and structural reinforcement treatment measures aiming at maintenance and reinforcement treatment, realize maintenance priority ordering based on a hierarchical analysis method, and automatically generate a reasonable distribution scheme of limited expenses and a reasonable distribution scheme aiming at special targets; the maintenance measures of the disease maintenance are that maintenance methods, unit price and units corresponding to different types of diseases of the beam bridge are set; the structural reinforcement treatment measures are used for setting optional reinforcement treatment schemes, unit price and units of the beam bridge; the maintenance priority ordering is realized based on the analytic hierarchy process, and a priority ordering algorithm is provided;
The virtual reality demonstration unit is used for checking apparent bridge diseases in a roaming manner in virtual reality through VR, monitoring historical data and analysis results, analyzing calculation results of load tests, and material conditions and state parameters, and demonstrating reinforcement treatment schemes adopted by bridge structure plans;
The cloud server and the client are used for realizing real-time calling of the data stored in the network and friendly interaction with the user through the WEB client and the mobile client;
the maintenance investment decision unit comprises the following specific algorithm:
Aiming at the more positive maintenance expense S Ⅱ, the method is used for bridge maintenance with obvious disease affecting operation safety, comprises reasonable reinforcement distribution, and meets the following necessary conditions: the technical conditions are bridges of four classes and five classes, and bridges with upper structure scores lower than 40 points or lower structure scores lower than 60 points in the bridges of three classes must be maintained;
assuming the total number of bridges in the road network is n, and the set is A; the method is a special structure bridge and an extra large bridge, and the evaluation results are four types and five types, namely a set A 1; four and five types of bridges, except a 1, are set a 2; the bridge is a bridge with a special structure and an extra large bridge, and the three cases are evaluated as intersections A 3; three types of bridges, except for a 3, are set a 4; the special structure bridges and extra large bridges except A 1、A3 are set A 5; other cases are set a 6;
The maintenance priority A 1＞A2＞(A3、A4)＞A5＞A6 of each set, wherein A 1、A2 is required to be repaired, A 3 is required to be repaired, A 4 is required to be repaired, partial bridges in the sets have higher priority than A 3, the total cost S Ⅱ;A5、A6 is input for selective maintenance, and the total cost is input as conditional maintenance cost S Ⅰ for bridge maintenance which has no obvious disease affecting operation safety;
Assuming that the number of elements in set a i is x i,xi ≡0, i=1 to 6, The element bridge is a ij, the maintenance cost of the bridge a ij is s ij, the maintenance state is c ij, the maintenance is determined when the value is 1, the maintenance is not determined when the value is 0, and the bridge maintenance cost in the set A i is/>The curing is performed as follows:
to determine the maintenance state c ij of the element in A 3、A4, performing maintenance priority evaluation index calculation according to the decision index level and weight; the weight of the index P y is W y, y is the number of decision indexes, the value of each decision index P y of the bridge a ij is P y-ij, the maintenance priority score of the bridge a ij is I ij＝20∑Wypy-ij, and the value range is 0-100; when the designated decision index does not participate in the evaluation, the decision index P y is introduced to use the state parameter d y, when the participation evaluation value is 1, the non-participation evaluation value is 0, y is the decision index number, the initial weight is W 0-y, and the weight is calculated
The element maintenance priority scores in A 3、A4 are J 1,J2 and … … in sequence from the top to the bottom, the corresponding maintenance cost is s 1,s2 and … …, when the requirements are metWhen the bridge maintenance state corresponding to J △ is 1, delta=1-m, and the maintenance state of other elements in A 3、A4 is 0;
For maintenance priority evaluation index calculation considering special requirements, the following parameters are introduced for a specific bridge a ij:
score contribution index:
Or (b)
Representing the ratio of the cost required for each 1 point improvement of the technical condition score of the overall upper structure of the bridge a ij to the average level of all three types of bridges in the road network; d r-ij is the overall technical status score for bridge a ij, SPCI r-ij is the superstructure technical status score for bridge a ij;
the quantitative contribution index:
representing the ratio of the expense required for maintaining the bridge a ij to the average level of all three types of bridges in the road network;
Length contribution index:
Representing the ratio of the expense required for maintaining the bridge a ij per linear meter to the average level of all three types of bridges in the road network;
Setting a specific maintenance target participation coefficient as e α、eβ、eγ, wherein the value of the specific maintenance target participation coefficient is 1 when the maintenance target needs to be met, and the specific maintenance target participation coefficient is 0 when the maintenance target is not needed; the maintenance priority score for bridge a ij is calculated as:
Iij＝20[1+min{Wy}(eααij+eββij+eγγij)]∑Wypy-ij.
2. the BIM-based beam bridge multi-source heterogeneous data fusion decision system according to claim 1, wherein the BIM visual model unit can directly display disease information, structure monitoring points and testing maximum values, load test positions and check coefficients, bridge deck real-time traffic flow and vehicle type classification information and distinguish technical condition assessment results of each component by colors, and after clicking specific positions, corresponding electronic files, material conditions and state parameters are checked to support VR roaming, so that the rationality of a reinforcement treatment scheme of a bridge structure is demonstrated in a virtual reality environment; the electronic file comprises construction period, operation period drawings and report data.
3. The BIM-based beam bridge multi-source heterogeneous data fusion decision system is characterized in that the disease maintenance tracking unit is added with a field detection completion confirmation function on a data cloud server and a client to check whether all historical diseases are subjected to tracking investigation, marks a seam width test position on a seam emphasis disease field, fuses frequent checking and periodic checking information to realize low-frequency monitoring of disease development conditions, and provides data support for judging structural stress characteristic changes; by tracking and monitoring the cured maintenance diseases, the tracking and evaluation of the maintenance measures are realized, and the good and poor-elimination maintenance measures are recommended.
4. The BIM-based beam bridge multi-source heterogeneous data fusion decision system according to claim 1, wherein the technical condition assessment unit is used for comprehensively evaluating the disease property after judging according to the disease data of frequent inspection and regular inspection and the low-frequency monitoring data of the disease maintenance tracking unit.
5. The BIM-based beam bridge multi-source heterogeneous data fusion decision system according to claim 1, wherein the maintenance investment decision unit performs maintenance and reinforcement treatment, wherein the maintenance is supported by taking disease information which is frequently checked and periodically checked as basic data, and a technical condition assessment unit calculation result is directly supported, and the fusion operation basic data unit performs intelligent auxiliary decision; the reinforcement treatment is based on frequent inspection and regular inspection of apparent diseases, and a structure monitoring and early warning unit and a load test analysis unit are integrated to realize mid-span deflection assessment and structure deflection assessment; when the technical condition assessment structure of the component is controlled by mid-span deflection and structural deflection, fusing the material condition and state parameter data of the bearing capacity testing unit to carry out bearing capacity detection; the maintenance investment decision unit follows the following general idea: the reinforcement treatment priority is higher than that of maintenance; bridges with general and lower structure technical condition grades of four, five or upper structure grade of five must be treated; the maintenance investment decision unit establishes a maintenance priority evaluation index system based on an analytic hierarchy process, wherein the maintenance priority evaluation index system comprises two types of safety indexes and importance indexes; wherein, the security index includes: classifying annual per kilometer charge, route grade, bridge position and bridge length; the importance index includes: technical condition evaluation total score, upper structure evaluation score, lower structure evaluation score, bridge deck system evaluation score, operation period, special structure bridge, annual frequent check times, whether to load road sections, and whether to transport large transportation channels; the annual per kilometer charge amount, the route grade, the bridge position, the bridge length classification, the operation years, the bridges with special structures, the annual frequent check times, whether the road sections are overloaded and whether the large transportation channels are all obtained from the operation and maintenance basic data unit; the technical condition evaluation total score, the upper structure evaluation score, the lower structure evaluation score and the bridge deck system evaluation score are all obtained from the technical condition evaluation unit;
The maintenance investment decision unit determines the weight as an importance index of 0.33 and a safety index of 0.67 according to an expert investigation method; annual per kilometer charge amount 0.58, route grade 0.26, bridge position 0.11, bridge length classification 0.05; technical condition evaluation total score 0.13, upper structure evaluation score 0.23, lower structure evaluation score 0.11, bridge deck system evaluation score 0.03, operation period 0.07, special structure bridge 0.04, annual frequent check times 0.05, whether heavy load road section 0.10, and whether large transportation channel 0.24.
6. The BIM-based beam bridge multi-source heterogeneous data fusion decision system according to claim 1, wherein the maintenance investment decision unit is characterized in that the selected decision parameters are determined to be valued according to a 5-scale method, and the decision parameters are specifically as follows:
The decision index of the charge per kilometer is valued: 5- [2.5 ], in +++). 4- [2.0, 2.5), 3- [1.5, 2.0), 2- [1.0, 1.5), 1- [0, 1.5);
Route grade decision index value: 5-expressway, 4-primary road, 3-secondary road, 2-tertiary road and 1-quaternary road;
Bridge position decision index takes value: 5-main bridge, 4-auxiliary road bridge, 3-ramp bridge, 2-overpass bridge and 1-others;
Bridge length classification index value: 5-super bridge, 4-big bridge, 3-middle bridge and 2-small bridge;
The technical condition evaluation total score decision index takes the value: 5- [60, 80), 3- [80, 95), 1- [95, 100];
the upper structure evaluation score decision index takes the value: 5- [40, 60), 4- [60, 80), 2- [80, 95), 1- [95, 100];
lower structure evaluation score decision index value: 5- [60, 80), 3- [80, 95), 1- [95, 100];
Bridge deck system evaluation score decision index value: 5- [0, 40), 4- [40, 60), 3- [60, 80), 2- [80, 95), 1- [95, 100];
The operation year decision index takes value: 5- [30, +++ ") and, 4- [20 ] the number of the first and second sets, 30), 3- [10 ], 20), 4- [5, 10), 5- [0, 5);
the decision index of the bridge with the special structure takes the value: 5-special structural bridges, 1-conventional structural bridges;
frequent checking times decision index value: 5-0,4- [0, 12), 3- [12, 24), 2- [24, 36), 1- [36 ] the number of the components, +++).
Whether the decision index of the heavy load road section takes the value: 5-is a heavy load road section, 1-is a non-heavy load road section;
Whether the decision index of the large transportation channel takes the value: 5-large piece transportation channel, 1-non-large piece transportation channel.
7. The BIM-based beam bridge multi-source heterogeneous data fusion decision system according to claim 1, wherein the maintenance investment decision unit supports the decision index not to participate in the evaluation and the specific maintenance target comprises: the technical conditions of the overall upper structure of the higher road network bridge are equally divided, the number of the lower bridges is equal to or less than the number of the lower bridges, and the length of the lower bridges is equal to or less than the number of the lower bridges.
8. The BIM-based beam bridge multi-source heterogeneous data fusion decision system according to claim 1, wherein the virtual reality demonstration unit intuitively knows the operation condition of the bridge at any time and any place aiming at the bridge which needs reinforcement treatment, refers to electronic archives, and performs voice discussion in a platform to simulate the scene of expert on-site demonstration.
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