CN117171842A - Urban slow-moving bridge health monitoring and digital twin system - Google Patents
Urban slow-moving bridge health monitoring and digital twin system Download PDFInfo
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Abstract
The invention relates to a health monitoring and digital twin system for an urban slow-moving bridge, which comprises a live-action model module, a BIM modeling module, a full life cycle operation and maintenance management module, an edge equipment module, a digital twin foundation module, a digital twin data conversion and optimization module and a digital twin application module, wherein information transfer interaction can be realized among the modules. The method comprises the following steps: building a BIM three-dimensional information model of the slow bridge structure; establishing a live-action model of the slow-moving bridge and the surrounding geographical hydrologic environment; constructing a digital twin base layer, and converting and optimizing digital twin data; an intelligent operation and maintenance management platform based on a digital twin body is built. The digital twin system is based on bridge construction, operation maintenance stage structure state monitoring information acquisition, structure load working condition real-time acquisition, data processing and analysis, and remote macroscopic control of construction site conditions and construction period progress is realized through regular updating of a live-action model.
Description
Technical Field
The invention relates to the technical fields of intelligent construction, intelligent construction and intelligent operation maintenance of constructional engineering, in particular to the field of construction and operation monitoring of bridge engineering, in particular to an application tool and an implementation method of intelligent construction operation monitoring of bridges, and particularly relates to a health monitoring and digital twin system of urban slow bridges.
Background
The development and innovation of bridge engineering technology are promoted by the advent of the digitization age with informatization and intellectualization characteristics, and strategic emerging industry technologies such as BIM, internet of things, digital twin, unmanned aerial vehicle live-action modeling, edge equipment and the like are necessarily fused with bridge engineering, so that the industrialization, the digitization and the intellectualization upgrading of the bridge are promoted from multiple dimensions such as intelligent design, intelligent construction, intelligent operation and maintenance and the like.
BIM technology is a product of the building industry's compliant age. The concept of the Internet of things is proposed in 1999, namely, all articles are connected with the Internet through information sensing equipment such as radio frequency identification and the like, so that intelligent identification and management are realized. The internet of things technology originates in the media field and is the third revolution of the information technology industry, any object is connected with a network according to a agreed protocol through information sensing equipment, and the object exchanges information and communicates through an information transmission medium so as to realize the functions of intelligent identification, positioning, tracking, supervision and the like. The digital twin concept was first explicitly proposed by NASA in the united states, and the meaning thereof is to highly accurately establish a digital information model corresponding to things in the real world, and perform operations such as real description, simulation, prediction and evaluation. The digital twin technology is expected to be a bridge for interaction and co-fusion of the physical world and the digital world. However, the digital twin technology is mainly applied to the industrial high-precision industry in the field of bridge engineering and still needs to be improved. The unmanned aerial vehicle live-action modeling is a three-dimensional model of an objective reduction reality scene, has the characteristics of individuation, materialization, structuring and semantezation, forms a three-dimensional model capable of space calculation and comprehensive analysis by fusing a manual modeling technology, an oblique photography technology and a laser radar technology, and presents a three-dimensional data scene result integrating the advantages of various models. Edge computing is an important solution to the problems of high latency, network instability, and low bandwidth in traditional cloud computing (or central computing) modes.
The engineering intelligent construction is based on engineering construction element resource digitalization, takes an engineering construction information model as a carrier, takes automated equipment and Internet of things information technology as means, and realizes auxiliary guidance and decision of overall construction behaviors such as state identification, error analysis, error prediction, evaluation correction, dynamic adjustment and the like under digital chain drive, thereby finally realizing an innovative construction mode of delivering engineering structural products with high precision, high quality and high efficiency. The digital twin technology combines data acquisition of the Internet of things, fully utilizes update and operation history data of a model and a sensor, integrates a multi-disciplinary, multi-physical quantity, multi-scale and multi-probability simulation process, completes mapping of a bridge in a virtual space, realizes understanding of bridge history conditions, evaluation of current operation states and simulation and diagnosis of states and behaviors of the bridge, predicts evolution trend of health conditions and possible diseases and risks (the university of the same aid. A modularized building health monitoring system based on a digital twin platform is 20201276245.9 [ P ]. 2021-02-19).
In summary, the background of the technical development is that the digital twin technology has a huge effect but is complex, and the combination of the internet of things technology and the BIM technology can promote the development of the digital twin technology in the field of engineering construction. For urban slow-moving bridges, the development of intelligent construction technology is also urgent to promote so as to adapt to the development of the industry field age. At present, wireless digital transmission (Zhu Jun, gao Jian, wang Lei) is also adopted for bridge health monitoring, namely a wireless digital transmission device [ P ] for bridge health monitoring, namely CN208985362U,2019-06-14, is adopted, so that the monitoring efficiency of bridge data can be greatly improved, and the superiority of the Internet of things technology is reflected. Therefore, a digital twin system based on BIM+GIS+FEM technology and Internet of things technology needs to be provided for intelligentizing the construction process and operation and maintenance process of the city slow-going bridge.
Disclosure of Invention
In order to solve the problems of reasonable interaction of finite element analysis and Building Information Model (BIM), digital twin system establishment of combining a Shi Gongyun dimension process of a city slow-moving bridge and an Internet of things technology and an intelligent city slow-moving bridge construction process, the invention provides a digital twin system for intelligent city slow-moving bridge intelligent construction and intelligent operation and maintenance, which is used for the intelligent city slow-moving bridge construction process, and comprises a BIM+GIS module, an Internet of things module, a data processing module and a construction simulation module, a digital twin body for large-span steel bridge construction is established based on the BIM+GIS module, the data processing module and the construction simulation module, then the digital twin body part and a physical entity part are subjected to data interaction based on the Internet of things module, the digital twin system is established for city slow-moving bridge construction, and the internal force condition and physical characteristics of prefabricated components in the transportation state, the installation state and the like can be reflected in real time through the data interaction realized by the Internet of things technology, so that the intelligent large-span steel bridge construction process can be realized. Such as a manager may analyze whether the component is acceptable based on a digital twin comparison established in accordance with BIM or the like. Meanwhile, the digital twin system can be simulated in real time to map specific construction and building processes. In addition, the digital twin system can simulate the construction process to be adopted to predict the construction process, so that analysis is performed and scientific decisions are made to guide construction.
The invention is realized at least by one of the following technical schemes.
A health monitoring and digital twin system for urban slow-going bridges comprises a BIM modeling module, a live-action model module, a full life cycle operation and maintenance management module, a digital twin foundation module, a digital twin data conversion and optimization module and a digital twin application module;
the BIM modeling module comprises a unified naming and annotating standard unit for component information design classification, a modeling module for creating complex curved surface components of bridges, a modeling module for creating regular components of bridges and a model conversion module for converting component information among different software;
the live-action model module comprises an unmanned plane module, an apron module, a live-action plug flow module, a three-dimensional reconstruction module and a format conversion module; the unmanned aerial vehicle module is integrated with an RTK positioning and high-resolution camera; the parking apron module realizes the functions of automatic low-power return charge and operation environment perception of the unmanned aerial vehicle, and perceives wind speed, rain and illumination flight environments, so that whether flight conditions are met or not is judged, and automatic operation is realized; the live broadcast plug flow module uses an unmanned plane to monitor in real time, remotely checks the operation live condition at any time, automatically returns and files pictures and video achievements, and is convenient for invoking the pictures to reconstruct three-dimensionally during live-action modeling;
The three-dimensional reconstruction module is used for forming a real-scene model finally by adding photos and coordinates, adding image control points and coordinates thereof, aligning the photos, establishing dense point clouds, generating grids and generating textures, wherein the real-scene model is formed by three-dimensional reconstruction of a multi-angle picture set of a physical entity; the format conversion module converts the live-action model in the OSGB format into the 3D Tiles format.
The full life cycle operation and maintenance management module comprises a 6D BIM initial information unit for comprehensive information application, a comprehensive operation and maintenance information unit for bridge information updating and correction, and a full life cycle information operation and maintenance management module for digital twin application result management;
the digital twin foundation module comprises various sensor units for acquiring the site working condition and bridge reaction information in the construction stage, various sensor units for identifying, tracking and acquiring the load distribution of the slow bridge in real time in the operation and maintenance stage, a wireless communication transmission unit for transmitting information, a data processing unit for processing information and a bridge suspension cable force calculation edge equipment unit;
the digital twin data conversion and optimization module comprises a 6D BIM preliminary information extraction and conversion unit used for containing unit information, a working condition information unit used for finite element structure numerical analysis, a calculation and early warning unit used for calculating structural counter force of the slow bridge under a real-time load working condition, a structural reaction comparison unit used for simulation analysis under different working conditions, a unit parameter and a grid optimization unit;
The digital twin application module comprises a digital twin application module combined with finite element analysis and intelligent analysis, and an information transfer module for digital twin layer application information interaction.
Further, the 6D BIM initial information unit comprises bridge live-action model and structure model information (3D), overall progress planning information (4D), engineering quantity and cost information (5D) and structure analysis related information (6D), wherein the structure analysis related information (6D) comprises unit parameters, grid division information, material attribute information, working condition load information, boundary condition processing information and structure surface crack damage information;
the full life cycle information operation and maintenance management module builds an information database of comprehensive operation and maintenance through the collection and fusion of various data, the light weight and the storage standby of the data, uniformly updates and stores multidimensional data in different stages at a server end so as to enable a client to call information, call and access the information at a Web end, and combines the called information with a BIM light weight model to check and output.
The multidimensional information of the 6D BIM initial information unit is added and perfected based on the three-dimensional model information, and the multidimensional information is interacted with the life cycle information operation and maintenance management module after being light.
Further, the digital twin body application module comprises a finite element numerical analysis result calculated according to real-time load working conditions, a working condition bridge reaction database which is used for intelligent analysis and is established by combining historical sample analysis results, a structural damage identification unit based on a convolutional neural network and other effective information units of the digital twin application layer, wherein intelligent prediction comprises the steps of extracting bridge internal force results of different time similar working conditions, analyzing the internal force change condition of key parts of the bridge and predicting the overall internal force distribution condition;
the information transfer module transfers and transmits the information in the digital twin application module to the life cycle information operation and maintenance management module, and further information interaction with the 6D BIM initial information unit is realized through the information checking and outputting unit of the life cycle information operation and maintenance management module.
Further, the rest effective information units of the digital twin application layer comprise updating BIM structure analysis related information according to the optimized finite element model unit and grid parameters, and providing a value range of initial units and grid parameters for sixth-dimension structure analysis information of the 6D BIM initial information unit; according to the comparison and error analysis of various bridge reactions under different working conditions, boundary type selection and boundary simplification, load simulation effectiveness and bridge reaction monitoring arrangement point positions are evaluated on the finite element structure analysis model; and automatically generating preventive maintenance decision and evaluation files of the bridge structure according to the results of finite element analysis and intelligent analysis.
And the intelligent analysis optimizes the boundary conditions, the unit parameters and the grid information of the finite element model through a historical sample analysis result working condition reaction database so as to enable the finite element result to be close to an actual measurement value.
Further, the structural damage identification unit based on the convolutional neural network comprises the following steps:
data collection and preprocessing: collecting a data set containing the structural surface image by the unmanned aerial vehicle close to photography, and preprocessing the data set, wherein the preprocessing comprises the operations of adjusting the size of the image, graying and denoising;
dividing data and setting a network architecture model of CNN: dividing a data set into a training set, a verification set and a test set, and setting the number and the size of convolution layers, an activation function and the types and parameters of pooling layers; training a network: training the CNN by using a training set, and updating network parameters through a back propagation algorithm in the training process to minimize a loss function;
model evaluation: the performance of the network is evaluated by using an independent test data set, the evaluation index is the accuracy, and the super parameter tuning is excellent: according to the performance of the verification set, the network architecture and super parameters including learning rate, batch size and regularization parameters are adjusted;
model test: the performance of the final model was evaluated using the test set.
Further, the bridge suspension cable force calculation edge equipment unit comprises a Digital Twin Operating System (DTOS), an acceleration sensor, a frequency domain data filtering processing and cable force calculation module and a suspension cable stress condition wireless communication transmission unit; a plurality of edge devices are connected through a high-speed data communication protocol to form digital twin edge equipment, and unified management is carried out through a mobile phone client APP, a PC client APP or a digital twin edge equipment wireless remote management platform on a webpage version;
the frequency domain data filtering processing and cable force calculating module collects time domain data of a target cable according to a preset time interval, converts the time domain data into frequency domain data by utilizing a fast Fourier transform method to construct a spectrogram, identifies all peak data in the spectrogram by utilizing a second derivative method, and then calculates the cable force of the target cable by utilizing the peak data.
Further, the calculation and early warning unit for the counter force of the slow-moving bridge structure under the real-time load working condition comprises a cross-camera pedestrian recognition and track tracking module, an anonymous pedestrian weight detection module, a finite element numerical analysis module and result output module, a finite element result error evaluation module and a threshold alarm module;
The cross-camera pedestrian recognition and track tracking module utilizes the time sequence and the spatial relation of the monitoring video to optimally infer a multi-camera network topological graph design and optimize a pedestrian recognition deep learning model, so that a pedestrian recognition function based on the appearance of pedestrians is realized, a dynamic time delay topological network model among the multiple cameras is realized on the basis of the pedestrian recognition deep learning model, a comparatively optimized detection sequence is provided for searching, and the searching blindness is reduced.
Further, the updating iteration implementation process of the unit parameters and the grid optimization unit comprises two layers: the method comprises the steps of carrying out on-site operation and maintenance information updating through a comprehensive operation and maintenance information unit and carrying out unit parameter and grid optimization and iterative updating of unit information through bridge reaction error comparison analysis under different working conditions, wherein the updating content of the comprehensive operation and maintenance information unit comprises on-site working condition information acquisition and importing, various bridge reaction information acquisition and comparison analysis and geometric parameter and material characteristic comprehensive operation and maintenance information obtained through on-site appearance measurement and component test.
The method for realizing the urban slow-moving bridge health monitoring and digital twin system comprises the following steps:
Reconstructing a real model of the bridge and the surrounding environment thereof to reflect a real physical entity;
step two, building a BIM three-dimensional information model of the bridge structure;
step three, constructing a digital twin foundation layer, which specifically comprises the steps of collecting the whole state data of the bridge, and transmitting the data to a data processing unit and carrying out light-weight data processing;
converting and optimizing the digital twin data;
and fifthly, constructing an intelligent operation and maintenance management platform based on a digital twin hierarchical architecture, and particularly realizing information transfer and comprehensive application between the digital twin application module and the full life cycle information operation and maintenance management module through an information transfer module.
Further, the intelligent operation and maintenance management platform is used for layering the digital twin application module, the information transfer module and the full life cycle information operation and maintenance management module, and is particularly divided into a data perception layer, a digital twin body data processing layer, a digital twin body application layer and an intelligent construction and operation and maintenance management layer;
the data perception layer comprises various types of IoT sensors, bridge suspension cable force calculation edge equipment, an RTK positioning technology unmanned aerial vehicle, an environment and bridge structure monitoring module, a man-machine material method loop intelligent identification module and a pedestrian identification and track tracking module;
The digital twin body data processing layer comprises bridge digital twin body modeling, a fine live-action three-dimensional modeling module, field load working condition reaction data, mechanical property detection data and other effective operation and maintenance data, and performs collection, fusion exchange and light-weight preprocessing on the data, and finally establishes an effective information database aiming at different module requirements;
the digital twin application layer comprises a bridge structure digital twin, a BIM system, a GIS system, a finite element simulation system, a comprehensive operation and maintenance management system based on a database, a preventive evaluation system based on intelligent early warning analysis, a maintenance scheme formulation system based on knowledge graph and machine learning, a remainder digital twin expansion application thereof and damage identification of structural surface cracks based on a convolutional neural network;
the intelligent construction and operation management layer comprises three-dimensional models, construction progress information, engineering quantity cost information and multidimensional information of structural analysis which are divided by different information dimensions, planning design, construction management, operation maintenance and other multi-stage information which are divided by different construction stages, and information input and management, collaborative communication of each sub-item, preventive maintenance decision-making and other functional modules;
The output end of the data perception layer is connected with the input end of the digital twin data processing layer, the output end of the digital twin data processing layer is connected with the input end of the digital twin application layer, and the output end of the digital twin application layer is connected with the input end of the intelligent building and operation and maintenance management layer.
Compared with the prior art, the invention has the beneficial effects that:
1. the method has a certain reference value for the deepening application of technologies such as BIM+GIS+FEM models of city slow bridges combined with Internet of things, digital twinning and the like, and makes reference to promotion of industry BIM application.
2. The establishment of the digital twin bodies of the urban slow-moving bridge reflects the construction working conditions of the urban slow-moving bridge in real time, and has important significance for promoting the construction digitization of the urban slow-moving bridge.
3. The invention uses the digital twin technology to intelligently build the urban slow-moving bridge, and has great guiding significance for optimizing the bridge building technology. Meanwhile, the method accords with the development direction of future industries, promotes the rapid development of the industries, and has great practical value and economic benefit.
Drawings
FIG. 1 is a schematic block diagram of an embodiment;
FIG. 2 is a flow chart of a system structure for monitoring health of urban slow-moving bridges and digital twinning according to an embodiment;
FIG. 3 is a schematic diagram of a hierarchical architecture of an embodiment digital twin;
FIG. 4 is a schematic diagram of a hierarchy of edge devices according to an embodiment;
fig. 5 is a schematic flow chart of a city slow-moving bridge health monitoring and digital twin method according to an embodiment.
Detailed Description
The invention will be elucidated in more detail below in connection with specific embodiments and with reference to the accompanying drawings. It should be understood that the examples are merely for the purpose of more specifically describing the process of implementing the present invention so as to facilitate understanding by those skilled in the art, and the present invention is not limited thereto. Some simple modifications or improvements are made within the main idea of the invention, which are all within the scope of the invention. In addition, the technical features of the embodiments of the present invention described below may be combined with each other as long as they do not collide with each other.
In the examples of the present invention, the terms "translate," "connect," "transfer," "update," "interact," "implement," and the like are to be construed broadly unless explicitly stated and limited otherwise. For example, the transfer may be a simple transfer of both, or may be an indirect transfer through an intermediary; the interaction may be a direct interaction between two units or an indirect interaction through some technical means. The specific meaning of the terms may be understood as required for various practical situations.
As shown in fig. 1, the urban slow-going bridge health monitoring and digital twin system comprises a BIM comprehensive modeling and information management subsystem and a digital twin technology subsystem based on BIM-GIS-FEM, wherein the BIM comprehensive modeling and information management subsystem comprises a BIM (building information model) modeling module, a live-action model module and a full life cycle operation and maintenance management module; the digital twin technology subsystem based on the BIM-GIS-FEM comprises a digital twin basic module, a digital twin data conversion and optimization module and a digital twin application module.
The BIM modeling module shown in fig. 1 is used for realizing accurate modeling among different types of components of a complex bridge structure, specifically, the BIM modeling module comprises a plurality of comprehensive modeling and conversion software (such as Revit, rhino and 3dx MAX), can be used for modeling by using various three-dimensional digital modeling software according to the requirements of the complex bridge structure, and then the created model is integrated into unified BIM software through model conversion software for subsequent information improvement and comprehensive application;
and unified naming and annotating standards are formulated, so that convenience is provided for unified information management of different components of various modeling software. Different modeling software can directly perform conversion, positioning and butt joint of component models through the model modeling software, and finally, splicing integration and information management of the whole model are realized in a BIM software platform with better comprehensive information management capability and more reasonable engineering applicability.
The making of the unified naming and annotating standard comprises the following steps: and (3) establishing an information classification and coding method for the full-bridge member by using the unit engineering name, the position, the section number, the member category, the detail unit division information and the like, and finally forming a unified standard similar to the layered information management of XX-XX.XX.XX.XX.
The live-action modeling module comprises an unmanned aerial vehicle module, an apron module, a live-action plug flow module, a three-dimensional reconstruction module and a format conversion module. And the unmanned aerial vehicle module is integrated with an RTK positioning and high-resolution camera. The parking apron module realizes the functions of automatic low-power return and charging of the unmanned aerial vehicle and operation environment sensing, and the parking apron senses the flight environments such as wind speed, rain, illumination and the like, so that whether the unmanned aerial vehicle has flight conditions or not is judged, and automatic operation is realized. The live broadcast plug flow module allows the unmanned aerial vehicle to monitor in real time, is convenient for monitoring the operation site on line, and can remotely check the operation live at any time. The pictures and video achievements are automatically returned and archived, so that the pictures are conveniently called to carry out three-dimensional reconstruction during live-action modeling, and the process of inserting and pulling the memory card to transmit the pictures is omitted. The three-dimensional reconstruction process generally comprises the steps of: adding photos and coordinates, adding image control points and coordinates thereof, aligning the photos, establishing dense point clouds, generating grids and textures, and finally forming a live-action model. The live-action model is the result of three-dimensional reconstruction of a multi-angle picture set of a physical entity. The common format of the live-action model is an OSGB format, and the live-action model needs to be converted into a lightweight 3D Tiles format which can be smoothly browsed and operated on a webpage. The format conversion module converts the live-action model in the OSGB format into the 3D Tiles format.
The full life cycle information operation and maintenance management module is used for classifying and storing operation and maintenance management information in the full life cycle process of the bridge, processing related information into a formatted expression mode so as to conveniently interact with 6D BIM (six-dimensional building information model), and displaying the information in real time by referring to a comprehensive information management platform based on webpage weight reduction;
as shown in fig. 1, the full life cycle operation and maintenance management module comprises a 6D BIM initial information unit of an initial design modeling process, a comprehensive operation and maintenance information unit for updating and correcting bridge information, and full life cycle information operation and maintenance management for managing digital twin application results;
the 6D BIM initial information unit comprises bridge three-dimensional model information 3D, overall progress planning information 4D, engineering quantity and cost information 5D and structure analysis related information 6D; the on-site monitoring information and unit parameter optimization information of the model correction process are updated regularly in the construction process; later comprehensive operation and maintenance information and application information from the digital twin functional layer.
The structure analysis related information (6D) comprises unit parameters, grid division information, material attribute information, working condition load information, boundary condition processing information and structural surface crack damage information;
The multidimensional information of the 6D BIM initial information unit is added and perfected based on the three-dimensional model information, and the multidimensional information is interacted with the life cycle information operation and maintenance management module after being light.
The comprehensive operation and maintenance information unit comprises structural geometric information, mechanical property information, inspection test information, assessment decision information and maintenance suggestion information related to geometric parameters and material characteristics. Wherein, the structure geometric information or mechanical property information related to the geometric parameters and material characteristics is used for updating the initial information unit of the 6D BIM; the rest of the effective operation and maintenance information is used for updating the full life cycle information operation and maintenance management module.
The full life cycle information operation and maintenance management module comprises an integrated database building unit, a configuration application server unit, a data calling and feedback unit and an information checking and outputting unit. The comprehensive database unit builds an information database of comprehensive operation and maintenance through the processes of collecting and fusing various stages of data, lightening the data, storing for standby and the like. The information database is uniformly connected to the server side so that a client can carry out information retrieval and access of a background server at the Web side or other customer service terminals, and the retrieved information and the BIM lightweight model are combined to carry out functions of checking, outputting and the like.
The edge equipment unit is a digital twin object and strategy which are used for carrying out modeling, comprehensive perception and real-time prediction on the whole life cycle of civil engineering design, construction and operation and maintenance, is based on the anchoring reference modeling, comprehensive perception and real-time prediction, is based on the E-BIM/E-GIS/E-HIM/E-AIM and a digital twin reference state, dynamic evolution management and predictive operation maintenance decision enabling platform driven by physical/data/knowledge, and realizes operation monitoring-digital twin iterative optimization-structure health condition evolution trend prediction integration and efficient cooperation of the edge end Internet of things based on an edge end reasoning frame and an operation maintenance decision enabling platform of the edge end.
The digital twin foundation module is used for collecting on-site working conditions and various bridge reaction information, carrying out communication transmission, carrying out data preliminary processing and the like, carrying out the processes of collecting, fusing, light-weight processing, data transferring and the like through the data collected by different sensors, providing foundation conditions for building a comprehensive operation and maintenance database, and inputting light-weight effective on-site working condition information into finite element analysis software to carry out bridge reaction analysis under specific load. The method is used for constructing the basis of the digital twin body of the complex bridge structure, and providing a field information source for the digital twin data conversion and optimization module.
The digital twin foundation module comprises various sensor units for collecting site working conditions and bridge reaction information in a construction stage, various sensor units for identifying, tracking and detecting in real time and collecting load distribution of a slow bridge in an operation and maintenance stage, a wireless communication transmission unit for collecting information, a data processing unit for collecting information and a bridge suspension cable force calculation edge equipment unit; the sensor units include sensors of various types.
The bridge suspension cable force calculation edge equipment unit comprises a Digital Twin Operating System (DTOS), a high-sensitivity acceleration sensor, a frequency domain data filtering processing and cable force calculation module and a suspension cable stress condition wireless communication transmission unit; the wireless communication transmission unit integrated by the edge equipment supports wireless broadband (WIFI) and 5G/4G commercial networks, and can decide which wireless communication mode to adopt for data transmission according to the field operation environment. If the place where the edge equipment is placed is covered by WIFI, the edge equipment is accessed into a field local area network through a field WIFI network, and data is transmitted to a database in the local area network by adopting a File Transfer Protocol (FTP), so that the data can be called into an intelligent operation and maintenance management platform for display. If the place where the edge device is placed is not covered by the local area network, a 5G or 4G commercial network can be used, and an effective SIM card needs to be inserted into the edge device at the moment, and the TCP protocol or the FTP protocol is adopted for data transmission. And a plurality of edge devices are connected through a high-speed data communication protocol to form digital twin edge equipment, and the digital twin edge equipment on the mobile phone client APP, the PC client APP or the webpage version is subjected to unified management through a digital twin edge equipment wireless remote management platform.
The frequency domain data filtering processing and cable force calculating module collects time domain data of a target cable according to a preset time interval, converts the time domain data into frequency domain data by utilizing a fast Fourier transform method to construct a spectrogram, identifies all peak data in the spectrogram by utilizing a second derivative method, and then calculates the cable force of the target cable by utilizing the peak data.
The sensor units mainly comprise temperature sensors and wind speed and direction meters which are arranged at a bridge main span and a bridge tower, static force level meters and fiber bragg grating strain meters which are arranged at the bottom of a bridge main structure control point of the bridge, displacement sensors and acceleration sensors which are arranged at a bridge end supporting position and a bridge pier supporting seat, cable force calculation edge equipment which is arranged on a stay cable or a main cable, infrared induction monitoring cameras which are arranged on the bridge deck and used for identifying pedestrians, pressure sensors which are arranged at a bridge access gate and used for acquiring load sizes, unmanned aerial vehicles and cameras thereof, GNSS sensors which are arranged at the span center and the tower top, and the like.
Specifically, the information collected by various sensors is connected with the data processing unit through the mode of 5G wireless communication by different area forwarding nodes, and the data processing unit integrates, classifies and processes the collected data in a light-weight manner, so that the standardization of a data format is further realized, the applicability of the information is improved, and the rapid input of the site working condition load of finite element analysis and the error comparison of different types of bridge reactions are facilitated. In particular, the cable force computing edge device has data processing capability, and can directly transmit the computing result and the conclusion to the full life cycle operation and maintenance management module in a 5G wireless communication mode.
The digital twin data conversion and optimization module shown in fig. 1 is used for constructing a digital twin corresponding to a real structure. Extracting and converting BIM initial information and finite element model information are realized through a secondary development plug-in, on the basis, error comparison analysis of finite element analysis result bridge reaction and field collected bridge reaction is carried out according to real-time load, and unit parameters and grid optimization information in model conversion are optimized and updated through continuous iteration process until bridge reaction comparison under different working condition loads can meet error conditions.
Specifically, the digital twin data conversion and optimization module comprises a 6D BIM initial information extraction and conversion unit containing unit information, a model and working condition information unit for finite element structure numerical analysis, a calculation and early warning unit for the counter force of a slow bridge structure under a real-time load working condition, various bridge reaction comparison units for simulating an analysis structure under a specific working condition, and a unit parameter and grid optimization unit based on an intelligent optimization algorithm.
And the working condition information unit for numerical analysis of the finite element structure inputs real-time load working conditions of the slow bridge into the finite element model. The structural reaction comparison unit for simulation analysis under specific working conditions is used for determining a series of specific unfavorable load working conditions by the bridge structural expert group, calculating bridge reactions under the unfavorable working conditions and determining a dangerous threshold value of the bridge reactions. And comparing the threshold value with bridge reaction under the real-time load working condition.
And the unit parameters and the grid optimization unit based on the intelligent optimization algorithm optimize the boundary conditions, the unit parameters and the grid information of the finite element model through the historical sample analysis result working condition reaction database so that the finite element result is close to the actual measurement value. The method solves the problems that the Building Information Model (BIM) does not consider the unit parameters and the grid information in the structural simulation analysis, lacks necessary unit parameter optimization and building information model correction processes, and cannot fully and equivalently simulate a real bridge.
The primary information extraction and conversion unit mainly comprises component information and unit information, wherein the component information can be used for updating a 6D BIM primary information unit by directly inputting or adjusting operation and maintenance information such as geometric parameters, material characteristics and the like manually; the unit information is based on unit parameters and grid optimization units of the intelligent optimization algorithm, unit parameter updating and grid optimization are carried out through a loop iteration process, and finally, the model is corrected into a digital twin body consistent with a real bridge structure.
The iterative updating implementation process of the unit parameters and the grid optimization unit comprises two layers, and on a macroscopic layer, the on-site operation and maintenance information modification can be carried out through the comprehensive operation and maintenance information unit, so that the 6D BIM initial information unit and the preliminary information extraction and conversion unit are updated, and the information updating optimization of the finite element junction analysis model is realized; the comprehensive operation and maintenance information unit update content mainly comprises acquisition and import of field working condition information, acquisition and comparison analysis of various bridge reaction information, and comprehensive operation and maintenance information of geometric parameters and material characteristics obtained through field appearance measurement and component test. On the microcosmic level, the finite element result is close to the measured value through comparison and intelligent optimization analysis of various bridge reaction errors under different working conditions. And performing intelligent optimization analysis, namely performing continuous iterative updating on the unit parameters and the grid optimization and related unit information through a historical sample analysis result working condition reaction database.
The unit parameters and the grid optimization unit comprise iterative optimization of preliminary information of unit types, grid types and unit division fineness, the optimized information is transmitted to the digital twin application module for classified storage on the basis of meeting error requirements under different working conditions, and the information can be transmitted to the full life cycle information operation and maintenance management module by means of the information transfer module, so that the structural analysis unit parameters and the grid information contained in the 6D BIM preliminary information unit are guided to be updated.
The calculation and early warning unit for the counter force of the slow-moving bridge structure under the real-time load working condition comprises a cross-camera pedestrian recognition and track tracking module, an anonymous pedestrian weight detection module, a finite element numerical analysis module and result output module, a finite element result error evaluation module and a threshold alarm module.
The anonymous pedestrian weight detection module is arranged at the gate of the entrance and exit of the slow-going bridge, performs anonymous weighing record on the passerby and tracks the pedestrian position in real time. By the method, the real-time load working condition of the slow-moving bridge can be accurately determined at any time, and the load working condition is also applied to a finite element numerical analysis model corresponding to the bridge, so that the real-time bridge reaction is obtained through finite element calculation. And comparing and analyzing the bridge strain calculated by the finite element with the strain value of the embedded strain gauge, evaluating the finite element result error, and verifying the validity and accuracy of the finite element model.
The cross-camera pedestrian recognition and track tracking module utilizes the time sequence and the spatial relation of the monitoring video to optimally infer a multi-camera network topological graph design and optimize a pedestrian recognition deep learning model, so that a pedestrian recognition function based on the appearance of pedestrians is realized, a dynamic time delay topological network model among the multiple cameras is realized on the basis of the pedestrian recognition deep learning model, a comparatively optimized detection sequence is provided for searching, and the searching blindness is reduced.
And the finite element result error evaluation module acquires a reference solution under a specific working condition from the database, namely the numerical value monitored by each sensor on the slow bridge. And comparing the finite element calculation result under the working condition with a reference solution, and adopting error indexes of H1 error (semi-positive definite error) and L2 error (square root error). Only if the error is smaller than a certain user set value, the finite element model can be considered to be effective, and the result can be displayed in the intelligent operation and maintenance management platform. The threshold alert module may monitor particular finite element calculations. The collected real-time load working condition of the slow-moving bridge is applied to the finite element model for calculation, when the specific finite element calculation result, such as bridge deflection and the like, exceeds the standard allowable value, the slow-moving bridge access gate is set to be in a 'out-not-in' state, and meanwhile, the intelligent operation and maintenance management platform sends an alarm message to a specific authority user; when the specific finite element calculation result greatly exceeds the standard allowable value, a slow bridge alarm system is triggered, and the prompt of pedestrians on the bridge to get off the bridge is broadcasted for avoiding danger.
The secondary development plug-ins between Building Information Models (BIM) and finite element structural analysis models mainly relate to any language compatible with NET (such as C#, C++, F#, visual basic. NET, and the like) and development tools integrating multiple computer languages. In addition, there are SDK files provided for the developer and development plug-ins provided by some authorities, including many examples of help files and source code and methods.
The data information conversion type of the secondary development plug-in mainly comprises geometric information such as component unit size, coordinate position and the like; material characteristics such as elastic modulus, poisson ratio, density and strength; the finite element analysis adopts the type and the size of the unit and the type and the fineness of the grid division. The geometric information and the material characteristics can be updated in stages through the field data acquisition of the comprehensive operation and maintenance information unit or the synchronous component test method; the unit parameters and the grid optimization unit realize optimization through the processes of error comparison of the bridge reaction of finite element analysis results and the bridge reaction actually measured on site, unit information adjustment and loop iteration.
The conversion of the 6D BIM initial information unit adopts a method of generating a command stream by adopting a secondary development plug-in, and adopts a form of directly adding or modifying related parameters in finite element software in the model iterative correction process, so that correction processing step information and solution analysis result information in the finite element software can be led out into a file in a specific format in a command stream mode, thereby facilitating data transfer and interaction of later application.
As shown in fig. 1, the digital twin application module comprises a digital twin application module combining finite element analysis and intelligent analysis and an information transfer module for digital twin layer application information interaction. The information transfer module transfers and transmits the information in the digital twin application module to the life cycle information operation and maintenance management module, and further information interaction with the 6D BIM initial information unit is realized through the information checking and outputting unit of the life cycle information operation and maintenance management module.
The digital twin body application module mainly comprises a finite element numerical analysis result calculated in real time according to an actual load, a working condition bridge reaction database which is used for intelligent analysis is created by combining a historical sample analysis result, an intelligent prediction and safety evaluation unit is performed by combining the database, a structural damage identification unit based on a convolutional neural network, other effective information units of a digital twin application layer and the like, the bridge reaction database under various working conditions is established by combining a historical sample, intelligent application and analysis of the database are performed by means of an intelligent optimization algorithm, and bridge reaction prediction and safety evaluation and other application layer effective information management can be performed on the twin structure. The digital twin application module exploits the fusion application between the digital twin hierarchical architecture and the finite element numerical analysis, and is further connected with the full life cycle information operation and maintenance management module through the information transfer module, thereby providing an architecture foundation for realizing full life cycle intelligent operation and management of the bridge.
The structural damage identification unit based on the convolutional neural network comprises the following steps:
data collection and preprocessing: collecting a data set containing the structural surface image by the unmanned aerial vehicle close to photography, and preprocessing the data set, wherein the preprocessing comprises the operations of adjusting the size of the image, graying and denoising;
dividing data and setting a network architecture model of CNN: dividing a data set into a training set, a verification set and a test set, and setting the number and the size of convolution layers, an activation function and the types and parameters of pooling layers; training a network: training the CNN by using a training set, and updating network parameters through a back propagation algorithm in the training process to minimize a loss function;
model evaluation: the performance of the network is evaluated by using an independent test data set, the evaluation index is the accuracy, and the super parameter tuning is excellent: according to the performance of the verification set, the network architecture and super parameters including learning rate, batch size and regularization parameters are adjusted;
model test: the performance of the final model was evaluated using the test set.
The other effective information units of the digital twin application layer comprise updating BIM structure analysis related information according to the optimized finite element model unit and grid parameters, and providing a value range of initial units and grid parameters for sixth-dimension structure analysis information of the 6D BIM initial information unit; according to the comparison and error analysis of various bridge reactions under different working conditions, boundary type selection and boundary simplification, load simulation effectiveness and bridge reaction monitoring arrangement point positions are evaluated on the finite element structure analysis model; and automatically generating preventive maintenance decision and evaluation files of the bridge structure according to the results of finite element analysis and intelligent analysis.
And the intelligent analysis optimizes the boundary conditions, the unit parameters and the grid information of the finite element model through a historical sample analysis result working condition reaction database so as to enable the finite element result to be close to an actual measurement value. The method solves the problems that the Building Information Model (BIM) does not consider the unit parameters and the grid information in the structural simulation analysis, lacks necessary unit parameter optimization and building information model correction processes, and cannot fully and equivalently simulate a real bridge.
The transfer interaction of the digital twin application module, the full life cycle information operation and maintenance management module and the 6D BIM initial information is carried out by means of various format information conversion files, and the transfer interaction mainly comprises a command stream file which is extracted and generated by a secondary development plug-in and meets the specific requirements of a finite element analysis software parameterized design language, an inp file which is used in a model correction preprocessing stage, a res file stored by solving result data, an animation file and the like. The implementation of the related functions of the digital twin application module needs to be combined with various technical principles, and mainly relates to the establishment of a sample database, the prediction of bridge reaction combined with an intelligent optimization algorithm, the intelligent expansion application, the development of a comprehensive information display platform and the like.
Specifically, the intelligent operation and maintenance management platform based on the digital twin application module is integrated with a hard-software foundation of the digital twin body, and mainly comprises a data sensing layer, a digital twin body data processing layer, a digital twin application layer, and an intelligent building and operation and maintenance management layer. The data sensing layer comprises multi-dimensional data acquisition of various types of sensors and classified storage and transmission of different data sources; the digital twin body data processing layer is used for carrying out relevant processing on the acquired data on the basis of bridge digital twin body modeling, including data collection, interactive fusion, light weight, derivation analysis and the like, so as to construct an information comprehensive database; the digital twin application layer comprises a bridge structure digital twin body, a BIM system, a GIS system, a finite element simulation system, a comprehensive operation and maintenance management system based on a database, an intelligent early warning evaluation system and a remainder digital twin expansion application thereof; the intelligent construction and operation management layer is based on the expansion application of the digital twin fusion platform, and can display multidimensional data in a modularized manner and realize full life cycle management.
The invention provides higher requirements on modeling accuracy, carries out iterative optimization of unit parameters and grid information on the model, and continuously updates the bridge information model by combining comprehensive operation and maintenance information, mainly aims to construct a more real digital twin body, and provides practical guarantee for carrying out real-time finite element analysis, establishing a more reliable historical information database, and carrying out bridge safety assessment and bridge reaction prediction according to specific natural disasters or structural diseases. Through unmanned aerial vehicle oblique photography and application of close-up photography, fine live-action modeling is conducted on a site bridge, damage identification is conducted on a site bridge structure, operation and maintenance personnel are helped to timely find out easily damaged parts, and corresponding maintenance measures or construction schemes are timely provided.
The following describes a method for a digital twin body of a bridge structure based on BIM-GIS-FEM by taking a slow-going bridge of a certain city as an embodiment with reference to FIG. 2, which comprises the following steps.
Step one, periodically reconstructing a live-action model of a bridge and surrounding environments thereof, wherein the method comprises the following steps:
a. five-direction oblique photography and close-up photography. Five-direction oblique photography is used for building a coarse model, and close-up photography is used for building a fine model. In the construction stage, long-distance five-direction oblique photography is periodically carried out so as to intuitively monitor project progress; and in the operation and maintenance stage, taking a coarse model obtained by five-direction oblique photography as a basis, performing close-up photography, and monitoring the health condition of each structural component of the bridge.
Step two, building a BIM three-dimensional information model of the bridge, which comprises the following steps:
b. information design classification of bridge components: and carrying out preliminary classification on bridge components according to the complexity, and carrying out unified management by combining component information classification and coding standards. The component information comprises geometric dimensions, coordinate positions, elastic modulus, poisson ratio, density, strength material characteristics and the like; and building a bridge component model by adopting BIM modeling software which accords with the traditional building industry drawing style and engineering personnel operation habit.
Step three, a realization process of the digital twin basic module comprises the following steps:
c. and (3) data acquisition: in order to collect the whole state data of the bridge, main control points of the slow-moving bridge in a certain city are determined, and related sensors are arranged according to actual requirements. The bridge comprises a temperature sensor and a wind speed and direction meter which are arranged at a bridge main span and a bridge tower, a static level gauge and a fiber bragg grating strain gauge which are arranged at the bottom of a bridge main structure control point bridge deck, a displacement sensor and an acceleration sensor which are arranged at a bridge end supporting part and a bridge pier supporting seat, cable force calculation edge equipment which are arranged on a main cable and a pull rod, a GNSS sensor which is arranged at a span center and a tower top, an infrared sensing monitoring camera which is arranged on the bridge deck and used for pedestrian recognition, a pressure sensor which is arranged at a bridge access gate and used for acquiring load size, an unmanned aerial vehicle and a camera with the unmanned aerial vehicle, and the like.
d. And (3) data transmission: the information collected by various sensors is transferred to the data processing unit through different area forwarding nodes, wherein the on-site working condition load information and various bridge reaction information can be remotely transmitted to the data processing unit through a wireless communication mode; the cable force calculation edge equipment can remotely transmit the calculated cable force or the suspension cable safety condition to the full life cycle operation and maintenance management module in a wireless communication mode.
e. And (3) data processing: the volume of various information from field collection is numerous, and the information needs to be integrated, classified and light-weight processed to improve the practicability of the information. The embodiment suggests that the compression algorithm is adopted as a light-weight means, and deviation detection processing and compression filtering simplification are carried out on the time sequence continuous variable, so that the actual trend of the data can be accurately reflected, and the storage space of the information data can be greatly reduced. The bridge information after the data light weight processing comprises real-time working condition load information for finite element numerical analysis, on-site various bridge reaction information for comparing with numerical analysis results under specific working conditions, related operation and maintenance information for perfecting and updating bridge BIM information and the like. The integrated taxonomies are the storage of specific different types of data into different databases for the convenience of later data analysis and recall.
Step four, the basic process of the digital twin data exchange and optimization module comprises the following steps:
f. secondary development plug-in applications based on BIM3D APIs: the data interaction function of the BIM3D API can be used for users to carry out secondary development application, and mainly comprises the following steps: obtaining geometric figure and related parameter data of a component, creating or modifying model elements, creating UI plug-ins which can be used for rapidly realizing repeated operation commands, realizing functions of model information sharing and the like. The C# language with more excellent operation capability and language characteristics can be selected as much as possible for secondary development of the plug-in unit, and a proper development tool is selected according to the matching requirement of BIM3D software. The command stream file corresponding to the finite element software NERAP is converted by deriving geometric information (component size and coordinate positioning), physical information (elastic modulus, poisson ratio, material density and the like), unit information (unit type and shape, grid type, division fineness and the like) and boundary condition processing information of the model in sequence. In the scheme, a txt output format is defined by adopting a NERAP version command stream standard, and a txt document containing information necessary for finite element analysis is finally generated.
g. Cell parameters and grid optimization of the finite element model: because the information such as the geometric parameters and the material characteristics of the bridge structure are continuously changed, the related operation and maintenance data are required to be updated regularly and reflected in the building information model in time, so that the secondary development plug-in unit can be used for repeatedly converting the BIM related information and updating the finite element model. On the basis, the bridge reaction results of finite element numerical analysis under different working conditions and errors between the bridge reactions actually measured on site are compared, and the combination optimization analysis is carried out by setting variables such as unit parameters, grid types and the like and combining an intelligent optimization algorithm, so that the variable value range meeting the bridge reaction error requirements under various working conditions is finally determined. Different unit types (such as various entities, rods, beams, plates and shell units) can be selected according to different model depth requirements, and the simulation ranges applicable to the unit types are different; for the selection of the grid type and the grid size, the entity unit can select tetrahedrons and hexahedrons with different node numbers, whether the grid size is reasonable or not can be judged by adjusting the stress strain value change range of the control part after the grid fineness is adjusted twice, and if the stress strain value change is within 5%, the fineness value is considered to be relatively reasonable.
h. Finite element model modification and analysis result data transfer: because the iterative process of unit parameter and grid optimization needs to repeatedly modify the related parameters for a plurality of times, if the unit related information of the building information model is obviously not convenient enough, the model modification can be realized by adopting a method of directly modifying the unit related parameters in finite element software NERAP. Through the optimization process of model geometric information, unit information and related topological information, a more accurate and reliable digital twin model is generated and load simulation analysis is carried out, so that error comparison and analysis are carried out on the displacement bridge reaction under the load of a specific working condition. The preprocessing related information input by the finite element model and the model analysis post-processing result information can be led out through a command stream built-in by finite element software NERAP to generate inp files which can be called by other safety calculation analysis modules; and the solving result is stored in a res file, so that the bridge full life cycle operation and maintenance management module can be used for calling and reconstructing data of the three-dimensional model stress or displacement cloud picture and displaying the data on a platform. When the geometric information, topological information and structural analysis related information (such as cell grid, material property, working condition load, boundary processing and the like) of the bridge need to be changed, an updated inp file and an updated res file can be generated to cover the last output result.
And fifthly, constructing an intelligent operation and maintenance management platform based on the digital twin body.
As shown in fig. 2, the digital twin application module can realize information transfer through the information transfer module and the full life cycle information operation and maintenance management module, and the digital twin application module is used for realizing an intelligent function target; the full life cycle information operation and maintenance management module has the functions of collecting, fusing, storing, standby, calling, checking, interactive expansion and the like of various data; the information transfer module is used for exchanging the application information of the digital twin layer. The three modules can be utilized to perform layered fusion, an intelligent fusion platform based on a digital twin body is built, and further intelligent operation and maintenance management of full life cycle information of the whole bridge project is realized. As shown in fig. 3, an intelligent operation and maintenance management platform is built on the basis of a hierarchical architecture of a digital twin body, and the platform is integrated with a hardware and software foundation of the digital twin body and mainly comprises a data perception layer, a digital twin body data processing layer, a digital twin application layer and an intelligent construction and operation and maintenance management layer.
i. A data perception layer and a digital twin volume data processing layer: the data perception layer can comprehensively perceive and collect the region to be detected aiming at different information sources and mainly comprises various types of IoT sensors, a suspension cable force calculation edge device, an RTK positioning technology unmanned plane, a pedestrian recognition and track tracking module, a man-machine material method loop intelligent recognition module and a ship; the environment and bridge structure monitoring module is based on an environment detector and a point cloud scanning of a large-scale unmanned aerial vehicle, and mainly detects the internal and external environment of a bridge and the construction condition of a main structure, wherein the environment and bridge structure monitoring module comprises the air quality of the surrounding environment, the temperature or humidity change of the periphery of the bridge, the sunshine time under different climatic conditions and the real-time construction progress of the bridge structure; the man-machine material method ring intelligent recognition module is based on a biological characteristic recognition technology and a satellite positioning technology, and is used for intelligently recognizing and rapidly positioning personnel, equipment and raw materials entering and exiting a construction site, so that evaluation analysis and overall management are carried out on relevant construction method standards and environmental influence conditions; the pedestrian recognition and track tracking module can make full use of the time sequence and the space relation of the monitoring video to optimally infer a network topological graph of the multiple cameras, and has the main functions of realizing the pedestrian recognition function based on the appearance of pedestrians by designing and optimizing a deep learning model for pedestrian recognition, and realizing a dynamic time delay topological network model among the multiple cameras on the basis of the model to provide an optimized detection sequence for searching, so that the blindness of searching is reduced; the digital twin body data processing layer is based on bridge digital twin body modeling, and is used for carrying out collection, fusion and exchange and light-weight pretreatment on comprehensively perceived data, and finally an effective information database is established according to different module requirements. The specific implementation process of the data perception layer and the digital twin data processing layer is described in the second step and the third step, and the basic implementation process of the intelligent operation and maintenance management platform based on the digital twin hierarchical architecture is introduced below.
j. Digital twin application layer: the digital twin application layer is based on a digital twin application module, and integrates and analyzes the received data preprocessing layer information according to the hard software implementation requirements of the related functions of the module. The digital twin application layer takes the digital twin body of the bridge structure as an application main body, and can realize the comprehensive operation and maintenance management system, the preventive evaluation system, the maintenance scheme formulation system, the digital twin expansion function and the like which comprise a BIM system, a GIS system, a finite element analog simulation system, a database-based comprehensive operation and maintenance management system and the like.
The specific process comprises the following steps: the development of the operation and maintenance management system mainly relates to the steps of script language selection, server development, database construction and the like. The embodiment suggests that a MySQL database with free open sources is built as a full life cycle operation and maintenance information database by combining historical samples of bridge reactions under different working conditions based on initial information of the 6D BIM, on-site comprehensive operation and maintenance information and effective information transferred by a digital twin application module; apache with open source codes and supporting cross-platform application is adopted in a high-configuration computer as Web server software, so that related information can be conveniently browsed and inquired on different mobile devices; PHP (Hypertext preprocessor) is selected as a script language for Web development, and the PHP language supports most operating systems and databases. Based on the development combination of PHP, apache and MySQL, project development, specific function design of dynamic websites and the like can be carried out on a Windows operating system, and finally a comprehensive operation and maintenance management system based on a database is built. The main content of the preventive evaluation system comprises intelligent prediction and safety evaluation of structural bridge reaction and effective identification of structural damage parts, and mainly relates to knowledge bases such as intelligent optimization algorithm, modal parameter identification, structural damage identification and the like. The maintenance scheme system mainly comprises automatic generation maintenance measures or construction schemes and the like, and mainly relates to knowledge bases such as machine learning, knowledge graph construction and the like. The implementation case suggests that a method of setting corresponding design variables and objective functions based on res result files is adopted, mapping relations between different structural parameters or material properties and other change parameters and deformation of various structural parts are established, intelligent optimization algorithms (such as deep learning CNN) are adopted to predict bridge reactions of bridge structures under specific working conditions, and finite element analysis results are used for verifying parameter setting rationality and deformation prediction accuracy. The deep learning CNN is mainly used for processing data of a grid-like structure, and has remarkable advantages for analyzing and identifying real-time information with time sequences and image data. And (3) adopting limit control methods of reasonable ranges of different bridge reaction variables to comprehensively evaluate the safety, applicability and durability of the prediction result of the structural bridge reaction, and generating an automatic report, maintenance measures, construction suggestions and evaluation reports. Based on the structural damage identification process of the bridge reaction actually measured on site, the embodiment suggests a detection method for firstly designing a modal parameter extraction method to obtain a modal parameter identification model and then identifying structural damage according to the modal parameter. The detection method can identify the damage part of the structure and calculate the damage index, then judge the severity of the damage of the structure according to the damage index, further obtain a related detection report of the damage of the structure, and generate a preventive maintenance decision and a health evaluation report of the bridge structure.
On the basis of perfect correction of the digital twin body, the structural bridge reaction under the load of the on-site working condition can be accurately analyzed in real time by a finite element numerical simulation method, which is the basic function of 'real-time perception' of the digital twin body; establishing a bridge reaction database under different working conditions by combining historical samples, wherein the database is a basic function of 'reference modeling' of a digital twin body; the intelligent prediction and the safety assessment are carried out by combining a database and an intelligent optimization algorithm, which is the basic function of 'accurate prediction' of the digital twin body. When bridge operation and maintenance information or bridge structure mechanical property parameters monitored on site change, such as geometric dimension errors of components, material property changes, structure newly-added diseases, support changes and the like, the information is reflected to the updating process of BIM system information through manual information input modes such as component detail adjustment, material elastic modulus and rigidity adjustment, component connection mode, space position adjustment and the like, and then a finite element analysis model is regenerated through a conversion mode of a secondary development plug-in; for the change of operation and maintenance information such as field working conditions, structural boundary conditions and the like, corresponding load application and boundary unit adjustment can be directly carried out through finite element software NERAP, and finally, the information meeting specific conditions is transmitted to a comprehensive operation and maintenance system for storage application through a unit parameter optimization process of loop iteration.
k. Intelligent building and operation management layer: the intelligent construction and operation and maintenance management layer can carry out comprehensive information interaction fusion with the digital twin application layer, fully combines the advantages of computer hardware and software and application development, and builds a digital twin fusion platform meeting the operation and maintenance management requirements of the whole life cycle. The digital twin fusion platform comprises information modules of different stages of planning design, construction management, operation maintenance and the like, integrates information modules of different dimensions of a 3D building model, 4D construction progress, 5D engineering quantity cost, 6D structure analysis and the like, and exploits the modules of information input management of each department, collaborative design and communication of each sub-item and the like.
The information system construction and implementation process of the digital twin fusion platform mainly comprises the steps of invoking a database and developing functions of a management platform, wherein the related functions of the management platform can be developed through a network editing technology, the acquisition, storage and analysis of data are realized through a database system development technology, the light-weight processing of a bridge BIM model and the convenient display at a Web end are realized through an API technology, the light-weight three-dimensional model is combined with multi-dimensional information of each stage, and the maximum application of visual information is pursued. The embodiment suggests that a Browser/Server (Browser/Server) network system architecture is adopted, PHP network programming is used to develop basic application of a digital twin intelligent operation and maintenance management platform BIM-MAG through unified HTML and Javascript language, mySQL database system development technology is used to realize data acquisition, storage and analysis, and the method is combined with BIM models which are light-weighted through technologies such as WebGL and the like, so that multidimensional data in different stages are finally stored in a Server end in a unified mode. The client can send requests to a background server in a domain name mode through Web ends of different devices and carry out specific information retrieval and access, and the system can store basic engineering information, operation and maintenance management information and analysis result information on the server so as to enable the client to carry out various operations, multidimensional browsing and personalized processing on a BIM-MAG management platform. The basic system framework is divided into a Web layer, a business function layer and a data access layer, wherein the Web layer supports the operations of information inquiry, information input management and the like of a user; the business function layer is used for implementing business and data rules and is mainly responsible for processing and realizing business functions; the data access layer is used for integrating and storing data information and is responsible for accessing and calling a database, and mainly comprises entity three-dimensional model information in a bridge design construction stage, various monitoring information in a bridge operation and maintenance stage, result information of digital twin application analysis and the like.
In addition, a plurality of expansion functions can be developed on the basis of the intelligent operation and maintenance management platform BIM-MAG, and the method mainly comprises the following steps: the visual system comprises a scene loading function, a hierarchical browsing function, an object access function, a searching function and other query functions, a multiple control effect and animation demonstration function aiming at different objects, and various visual functions such as visual angle control through a camera, interface data dynamic display, a temperature and humidity cloud image, a particle effect image and the like. The digital twin intelligent operation and maintenance management platform aiming at the large-span complex bridge structure is built, so that the integration and application of the information technology of full life cycle management are facilitated, and the development of the construction industry from simple three-dimensional informatization to twin digitization is promoted.
It will be readily understood by those skilled in the art that the foregoing description of a large span shaped tower hybrid girder suspension bridge is merely a preferred embodiment of the present invention, and is not intended to limit the present invention, but rather to make various modifications, equivalent substitutions or improvements within the spirit and principles of the present invention, all falling within the scope of the present invention.
Claims (10)
1. A city slow-going bridge health monitoring and digital twin system is characterized in that: the system comprises a BIM modeling module, a live-action model module, a full life cycle operation and maintenance management module, a digital twin basic module, a digital twin data conversion and optimization module and a digital twin application module;
The BIM modeling module comprises a unified naming and annotating standard unit for component information design classification, a modeling module for creating complex curved surface components of bridges, a modeling module for creating regular components of bridges and a model conversion module for converting component information among different software;
the live-action model module comprises an unmanned plane module, an apron module, a live-action plug flow module, a three-dimensional reconstruction module and a format conversion module; the unmanned aerial vehicle module is integrated with an RTK positioning and high-resolution camera; the parking apron module realizes the functions of automatic low-power return charge and operation environment perception of the unmanned aerial vehicle, and perceives wind speed, rain and illumination flight environments, so that whether flight conditions are met or not is judged, and automatic operation is realized; the live broadcast plug flow module uses an unmanned plane to monitor in real time, remotely checks the operation live condition at any time, automatically returns and files pictures and video achievements, and is convenient for invoking the pictures to reconstruct three-dimensionally during live-action modeling;
the three-dimensional reconstruction module is used for forming a real-scene model finally by adding photos and coordinates, adding image control points and coordinates thereof, aligning the photos, establishing dense point clouds, generating grids and generating textures, wherein the real-scene model is formed by three-dimensional reconstruction of a multi-angle picture set of a physical entity; the format conversion module converts the live-action model in the OSGB format into a 3D Tiles format;
The full life cycle operation and maintenance management module comprises a 6D BIM initial information unit for comprehensive information application, a comprehensive operation and maintenance information unit for bridge information updating and correction, and a full life cycle information operation and maintenance management module for digital twin application result management;
the digital twin foundation module comprises various sensor units for acquiring the site working condition and bridge reaction information in the construction stage, various sensor units for identifying, tracking and acquiring the load distribution of the slow bridge in real time in the operation and maintenance stage, a wireless communication transmission unit for transmitting information, a data processing unit for processing information and a bridge suspension cable force calculation edge equipment unit;
the digital twin data conversion and optimization module comprises a 6D BIM preliminary information extraction and conversion unit used for containing unit information, a working condition information unit used for finite element structure numerical analysis, a calculation and early warning unit used for calculating structural counter force of the slow bridge under a real-time load working condition, a structural reaction comparison unit used for simulation analysis under different working conditions, a unit parameter and a grid optimization unit;
the digital twin application module comprises a digital twin application module combined with finite element analysis and intelligent analysis, and an information transfer module for digital twin layer application information interaction.
2. The urban slow-moving bridge health monitoring and digital twinning system for implementing the method of claim 1, which is characterized in that: the 6DBIM initial information unit comprises bridge live-action model and structure model information (3D), overall progress planning information (4D), engineering quantity and cost information (5D) and structure analysis related information (6D), wherein the structure analysis related information (6D) comprises unit parameters, grid division information, material attribute information, working condition load information, boundary condition processing information and structure surface crack damage information;
the full life cycle information operation and maintenance management module builds an information database of comprehensive operation and maintenance through the collection and fusion of various data, the light weight and the storage for standby, uniformly updates and stores multi-dimensional data in different stages at a server end so as to enable a client to call information to be called and accessed at a Web end, and the called information is combined with a BIM light weight model to be checked and output;
the multidimensional information of the 6D BIM initial information unit is added and perfected based on the three-dimensional model information, and the multidimensional information is interacted with the life cycle information operation and maintenance management module after being light.
3. The urban slow moving bridge health monitoring and digital twinning system according to claim 2, characterized in that:
The digital twin body application module comprises a finite element numerical analysis result calculated according to real-time load working conditions, a working condition bridge reaction database which is used for intelligent analysis and is established by combining historical sample analysis results, an intelligent prediction and safety evaluation unit which is combined with the database, a structural damage identification unit based on a convolutional neural network, and other effective information units of a digital twin body application layer, wherein the intelligent prediction comprises the steps of extracting bridge internal force results of different similar working conditions, analyzing internal force change conditions of key parts of the bridge, and predicting overall internal force distribution conditions;
the information transfer module transfers and transmits the information in the digital twin application module to the life cycle information operation and maintenance management module, and further information interaction with the 6D BIM initial information unit is realized through the information checking and outputting unit of the life cycle information operation and maintenance management module.
4. A city slow moving bridge health monitoring and digital twinning system as claimed in claim 3, wherein: the other effective information units of the digital twin application layer comprise updating BIM structure analysis related information according to the optimized finite element model unit and grid parameters, and providing a value range of initial units and grid parameters for sixth-dimension structure analysis information of the 6D BIM initial information unit; according to the comparison and error analysis of various bridge reactions under different working conditions, boundary type selection and boundary simplification, load simulation effectiveness and bridge reaction monitoring arrangement point positions are evaluated on the finite element structure analysis model; automatically generating preventive maintenance decision and evaluation files of the bridge structure according to the results of finite element analysis and intelligent analysis;
And the intelligent analysis optimizes the boundary conditions, the unit parameters and the grid information of the finite element model through a historical sample analysis result working condition reaction database so as to enable the finite element result to be close to an actual measurement value.
5. A city slow moving bridge health monitoring and digital twinning system as claimed in claim 3, wherein: the structural damage identification unit based on the convolutional neural network comprises the following steps:
data collection and preprocessing: collecting a data set containing the structural surface image by the unmanned aerial vehicle close to photography, and preprocessing the data set, wherein the preprocessing comprises the operations of adjusting the size of the image, graying and denoising;
dividing data and setting a network architecture model of CNN: dividing a data set into a training set, a verification set and a test set, and setting the number and the size of convolution layers, an activation function and the types and parameters of pooling layers; training a network: training the CNN by using a training set, and updating network parameters through a back propagation algorithm in the training process to minimize a loss function;
model evaluation: the performance of the network is evaluated by using an independent test data set, the evaluation index is the accuracy, and the super parameter tuning is excellent: according to the performance of the verification set, the network architecture and super parameters including learning rate, batch size and regularization parameters are adjusted;
Model test: the performance of the final model was evaluated using the test set.
6. The urban slow moving bridge health monitoring and digital twinning system according to claim 1, characterized in that: the bridge suspension cable force calculation edge equipment unit comprises a Digital Twin Operating System (DTOS), an acceleration sensor, a frequency domain data filtering processing and cable force calculation module and a suspension cable stress condition wireless communication transmission unit; a plurality of edge devices are connected through a high-speed data communication protocol to form digital twin edge equipment, and unified management is carried out through a mobile phone client APP, a PC client APP or a digital twin edge equipment wireless remote management platform on a webpage version;
the frequency domain data filtering processing and cable force calculating module collects time domain data of a target cable according to a preset time interval, converts the time domain data into frequency domain data by utilizing a fast Fourier transform method to construct a spectrogram, identifies all peak data in the spectrogram by utilizing a second derivative method, and then calculates the cable force of the target cable by utilizing the peak data.
7. The urban slow moving bridge health monitoring and digital twinning system according to claim 1, characterized in that: the calculation and early warning unit for the counter force of the slow-moving bridge structure under the real-time load working condition comprises a cross-camera pedestrian recognition and track tracking module, an anonymous pedestrian weight detection module, a finite element numerical analysis module, a result output module, a finite element result error evaluation module and a threshold alarm module;
The cross-camera pedestrian recognition and track tracking module utilizes the time sequence and the spatial relation of the monitoring video to optimally infer a multi-camera network topological graph design and optimize a pedestrian recognition deep learning model, so that a pedestrian recognition function based on the appearance of pedestrians is realized, a dynamic time delay topological network model among the multiple cameras is realized on the basis of the pedestrian recognition deep learning model, a comparatively optimized detection sequence is provided for searching, and the searching blindness is reduced.
8. The urban slow moving bridge health monitoring and digital twinning system according to claim 1, characterized in that: the updating iteration implementation process of the unit parameters and the grid optimization unit comprises two layers: the method comprises the steps of carrying out on-site operation and maintenance information updating through a comprehensive operation and maintenance information unit and carrying out unit parameter and grid optimization and iterative updating of unit information through bridge reaction error comparison analysis under different working conditions, wherein the updating content of the comprehensive operation and maintenance information unit comprises on-site working condition information acquisition and importing, various bridge reaction information acquisition and comparison analysis and geometric parameter and material characteristic comprehensive operation and maintenance information obtained through on-site appearance measurement and component test.
9. A method for implementing the urban slow moving bridge health monitoring and digital twinning system of claim 1, comprising the steps of:
reconstructing a real model of the bridge and the surrounding environment thereof to reflect a real physical entity;
step two, building a BIM three-dimensional information model of the bridge structure;
step three, constructing a digital twin foundation layer, which specifically comprises the steps of collecting the whole state data of the bridge, and transmitting the data to a data processing unit and carrying out light-weight data processing;
converting and optimizing the digital twin data;
and fifthly, constructing an intelligent operation and maintenance management platform based on a digital twin hierarchical architecture, and particularly realizing information transfer and comprehensive application between the digital twin application module and the full life cycle information operation and maintenance management module through an information transfer module.
10. The urban slow moving bridge health monitoring and digital twinning system according to claim 9, characterized in that: the intelligent operation and maintenance management platform is used for layering the digital twin application module, the information transfer module and the full life cycle information operation and maintenance management module, and is particularly divided into a data sensing layer, a digital twin data processing layer, a digital twin application layer and an intelligent construction and operation and maintenance management layer;
The data perception layer comprises various types of IoT sensors, bridge suspension cable force calculation edge equipment, an RTK positioning technology unmanned aerial vehicle, an environment and bridge structure monitoring module, a man-machine material method loop intelligent identification module and a pedestrian identification and track tracking module;
the digital twin body data processing layer comprises bridge digital twin body modeling, a fine live-action three-dimensional modeling module, field load working condition reaction data, mechanical property detection data and other effective operation and maintenance data, and performs collection, fusion exchange and light-weight preprocessing on the data, and finally establishes an effective information database aiming at different module requirements;
the digital twin application layer comprises a bridge structure digital twin, a BIM system, a GIS system, a finite element simulation system, a comprehensive operation and maintenance management system based on a database, a preventive evaluation system based on intelligent early warning analysis, a maintenance scheme formulation system based on knowledge graph and machine learning, a remainder digital twin expansion application thereof and damage identification of structural surface cracks based on a convolutional neural network;
the intelligent construction and operation management layer comprises three-dimensional models, construction progress information, engineering quantity cost information and multidimensional information of structural analysis which are divided by different information dimensions, planning design, construction management, operation maintenance and other multi-stage information which are divided by different construction stages, and information input and management, collaborative communication of each sub-item, preventive maintenance decision-making and other functional modules;
The output end of the data perception layer is connected with the input end of the digital twin data processing layer, the output end of the digital twin data processing layer is connected with the input end of the digital twin application layer, and the output end of the digital twin application layer is connected with the input end of the intelligent building and operation and maintenance management layer.
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