Incremental launching construction process quality control method and system based on virtual-real scene mapping

Abstract

The invention relates to the field of bridge construction automation and intelligence, in particular to an incremental launching construction process quality control method and system based on virtual and real scene mapping. The method comprises the following steps: acquiring feature data in a bridge incremental launching construction process; building a virtual mapping model of incremental launching construction by utilizing the feature data; according to the virtual mapping model, dynamic mapping of the incremental launching construction process state is carried out, and a dynamic mapping result is obtained; based on the dynamic mapping result, obtaining a quality evaluation result of the incremental launching construction process; and through the quality evaluation result, realizing quality control of the incremental launching construction process. According to the invention, by introducing a virtual-real scene mapping technology, information fusion and interaction of virtual and physical spaces are realized through data driving, real-time updating and accurate feedback of construction data are ensured, an intelligent and visual solution is provided for bridge incremental launching construction, and all-around and whole-process real-time monitoring and management of construction process quality are realized.

Description

Technical Field

[0001] The present invention relates to the field of bridge construction automation and intelligence, and particularly to a quality control method and system for incremental launching construction process based on virtual-real scene mapping. Background Art

[0002] The incremental launching construction technology of bridges is a mature bridge construction method, which has the advantages of fast construction speed, small site requirements, and little environmental impact, and is widely used in the construction of large bridges. However, the incremental launching construction process is complex, with high requirements for construction precision control, equipment requirements, and safety management. Traditional management means are difficult to meet the construction requirements of modern projects for high efficiency, precision, and safety.

[0003] In the prior art, the quality control of incremental launching construction mainly relies on manual monitoring and offline analysis, which has problems such as complex monitoring, high labor costs, difficult data analysis, poor timeliness, and insufficient online grasp of the construction process, resulting in a lag in safety warning and difficulty in timely mastering the construction quality. In addition, the traditional plan view, elevation view, and section view are not intuitive in the display effect of the construction plan, the detail expression is not comprehensive, and it is difficult to accurately guide the construction; at the same time, the construction site has limited space and dense temporary facilities, which are prone to spatial conflicts, further increasing the difficulty of construction management. Therefore, it is necessary to integrate a limited front-end intelligent perception system through visualization technology based on the real construction scene, conduct three-dimensional space simulation verification and design optimization of the steel beam incremental launching operation plan, and realize the digital online intelligent control of the key quality indicators of bridge incremental launching construction.

[0004] At present, there is not much research work on the quality control of the incremental launching construction process of bridges, and there is no specific intelligent quality control method for the incremental launching construction process based on dynamic mapping of virtual-real scenes. Summary of the Invention

[0005] Aiming at the defects in the prior art, the present invention provides a quality control method and system for incremental launching construction process based on virtual-real scene mapping.

[0006] In the first aspect, the present invention provides a method for quality control of a jacking construction process based on virtual-reality scene mapping, comprising the following steps: obtaining characteristic data during the jacking construction process of a bridge, the characteristic data including main beam stress, support reaction force, jacking displacement, jacking settlement, jacking temperature, main tower inclination deformation, jacking equipment, steel box beam posture state and structural force data; using the characteristic data to build a virtual mapping model of jacking construction; according to the virtual mapping model, dynamically mapping the state of the jacking construction process and obtaining dynamic mapping results; based on the dynamic mapping results, obtaining quality assessment results of the jacking construction process; and achieving quality control of the jacking construction process through the quality assessment results. The present invention realizes digital monitoring of all elements of bridge jacking construction by acquiring characteristic data during the jacking construction process; by building a virtual-reality mapping model, the physical construction scene is mapped to the virtual space in real time, breaking through the limitation of relying on experience judgment in traditional quality control; by dynamically mapping the construction status, millisecond-level identification of construction deviations is realized; by quantitatively outputting quality evaluation results, an automatic early warning mechanism is formed, which greatly improves the quality control response speed; by feeding back the physical construction through the virtual model, the jacking equipment parameter adjustment strategy is optimized, and the construction control accuracy is greatly improved.

[0007] Optionally, the acquisition of characteristic data during the bridge jacking construction process includes: acquiring monitoring data during the bridge jacking construction process; storing the monitoring data in a database, performing process backtracking and data backtracking to obtain problem data; modifying, adjusting and compiling the problem data to obtain characteristic data during the bridge jacking construction process. The present invention achieves comprehensive digital collection of construction status by acquiring bridge jacking construction monitoring data in real time; by establishing a structured database to store monitoring data, it supports second-level retrieval and comparative analysis of historical data, greatly improving data backtracking efficiency; by automatically marking abnormal data, it achieves intelligent identification and modification of problem data; by compiling the modified data, a feature data set with spatiotemporal association is constructed to provide high-precision input for virtual-reality mapping.

[0008] Optionally, the construction of the virtual mapping model for incremental launching construction using the feature data includes: using the feature data to establish a main model of bridge incremental launching construction, a temporary structure model, a monitoring point model, and a construction environment model; based on the main model of bridge incremental launching construction, the temporary structure model, the monitoring point model, and the construction environment model, establishing a local virtual mapping primitive model; according to the local virtual mapping primitive model, constructing a virtual mapping primitive model library; through the virtual mapping primitive model library, constructing a virtual mapping model for incremental launching construction, and the virtual mapping model is a virtual mirror of the actual construction environment. The present invention realizes the digital modeling of all elements of the physical construction scenario by establishing a main model of bridge incremental launching construction, a temporary structure model, a monitoring point model, and a construction environment model; supports the rapid call and combination of model components under different working conditions by establishing a virtual mapping primitive model library, greatly improving the overall modeling efficiency; realizes the millisecond-level update of key parameters of the virtual model by dynamically associating the primitive model with real-time monitoring data; predicts the risk of incremental launching trajectory deviation in advance through the two-way interaction between the virtual mirror and the physical environment, greatly improving the prediction accuracy; adapts to various incremental launching scenarios of cable-stayed bridges and arch bridges through the modular expansion ability of the model library, greatly reducing the modeling cost.

[0009] Optionally, the dynamic mapping of the incremental launching construction process state according to the virtual mapping model and obtaining the dynamic mapping result includes: using the feature data to obtain the update result of the virtual mapping model; through the update result, performing the dynamic mapping of the construction process state and obtaining the dynamic mapping result. The present invention realizes the dynamic visual presentation of the construction state by real-time fusing multi-source feature data and the virtual mapping model; establishes a dynamic mapping mechanism through the intelligent iterative update of model parameters, significantly improving the accuracy of construction state evaluation; realizes the millisecond-level interactive feedback between physical construction and digital model through the synchronous mapping technology of virtual and real spaces, providing a real-time decision-making basis for quality control; constructs an early warning system for construction risks through the automatic identification of abnormal states during the dynamic mapping process, greatly reducing the incidence of quality accidents; reveals the structural response mechanism difficult to capture by existing methods through the coupled mapping of construction mechanical behavior and geometric deformation, providing a new perspective for process optimization; forms a traceable quality control evidence chain through the digital reproduction of the full-element construction state, improving the transparency and credibility of project management.

[0010] Optionally, the obtaining of the update result of the virtual mapping model by using the feature data includes: discretizing the feature data to obtain discretized data; correcting the discretized data to obtain cloud monitoring data; extracting key feature data through the cloud monitoring data; and using the key feature data to update the virtual mapping model and obtain an update result. By standardizing and discretizing the feature data, the present invention realizes the efficient integration and unified management of a large amount of construction monitoring data, and solves the problem of low processing efficiency caused by the chaotic existing data format; by correcting the discretized data, the accuracy and reliability of the cloud monitoring data are significantly improved, providing a high-quality data basis for virtual model update; by intelligently extracting and processing the key feature data, the core construction parameters are effectively focused, and the calculation burden of model update is greatly reduced; through the model dynamic update mechanism, the continuous synchronization of the virtual mapping model and the actual construction state is realized, ensuring the timeliness and authenticity of digital twins.

[0011] Optionally, the obtaining of the quality assessment result of the jacking construction process based on the dynamic mapping result includes: obtaining quality assessment parameter data based on the dynamic mapping result; constructing a quality assessment deviation model according to the quality assessment parameter data; obtaining a quality assessment deviation through the quality assessment deviation model; and obtaining the quality assessment result of the jacking construction process according to the quality assessment deviation. Through the multi-dimensional analysis of the dynamic mapping result, the present invention realizes the automatic extraction of construction quality assessment parameters; by constructing an intelligent quality assessment deviation model, a multi-index comprehensive evaluation system covering structural safety and construction accuracy is established; by dynamically tracking the quality assessment deviation, it is beneficial to form a trend map of the evolution of construction quality, providing a scientific basis for process control; by real-time linking quality assessment and construction process, a closed-loop management of monitoring-evaluation-regulation is realized, promoting the construction quality management into a new stage of intelligence.

[0012] Optionally, the quality control of the incremental launching construction process through the quality assessment results includes: establishing a risk early warning model for construction quality based on the quality assessment results; obtaining risk early warning information using the risk early warning model; establishing a construction quality visualization model based on the risk early warning information; and realizing the quality control of the incremental launching construction process through the construction quality visualization model. By establishing a risk early warning model for construction quality, the present invention realizes the transformation of quality risk from passive response to active prevention; through multi-dimensional monitoring and evaluation of the risk early warning model, potential quality hazards in the construction process are accurately identified, significantly improving the predictability and accuracy of risk prevention and control; through the visual presentation and intelligent push of risk early warning information, a multi-party collaborative quality control mechanism is constructed, greatly shortening the problem response and handling time; through the dynamic display function of the construction quality visualization model, real-time monitoring and trend prediction of the quality status are realized, providing an intuitive basis for management decision-making.

[0013] Optionally, the quality control of the incremental launching construction process through the construction quality visualization model includes: determining the components with quality problems through the construction quality visualization model; establishing a construction parameter adjustment model based on the components; obtaining the adjustment results of the construction parameters according to the construction parameter adjustment model; and realizing the quality control of the incremental launching construction process through the adjustment results. By means of the intelligent diagnosis function of the construction quality visualization model, the present invention realizes the automatic identification and positioning of components with quality problems, significantly improving the efficiency and accuracy of defect detection; by correlating and analyzing the parameters of the problem components, a quantitative relationship between construction parameters and quality defects is established, providing a scientific basis for precise regulation; through the intelligent optimization algorithm of the construction parameter adjustment model, an optimal adjustment plan that takes into account both quality and efficiency is automatically generated, changing the existing experience-based decision-making mode; through the real-time feedback and verification mechanism of the adjustment results, the effectiveness of parameter correction and the continuous improvement of construction quality are ensured.

[0014] Optionally, the construction parameter adjustment model satisfies the following expression:

[0015] where is the adjustment value of the th construction parameter at the th time step, , , respectively represent the proportional gain, integral gain, and derivative gain, is the quality assessment deviation of the th construction parameter at the th time step, is the th construction parameter at the The quality assessment deviation of each time step, is a time step variable. Through constructing a construction parameter adjustment model, the present invention realizes precise dynamic regulation of the quality deviation; quickly responds to the current quality deviation through the proportional term, significantly improving the immediate adjustment accuracy of construction parameters and ensuring timely correction of quality problems; accumulates historical deviation data through the integral term, effectively eliminating the steady-state error of the system and realizing continuous progressive optimization of construction quality; predicts the deviation change trend through the differential term, intervening in potential quality problems in advance and forming a forward-looking quality prevention and control mechanism; through the collaborative action of multiple parameters, taking into account the adjustment speed and system stability and avoiding the adverse regulation phenomena such as overshoot or oscillation; replacing empirical judgment with digital regulation, greatly improving the scientificity and repeatability of construction parameter adjustment and providing a standardized technical means for quality control.

[0016] In a second aspect, a quality control system for the jacking construction process based on virtual-real scenario mapping provided by the present invention includes an input device, a processor, an output device, and a memory. The input device, the processor, the output device, and the memory are interconnected. Among them, the memory is used to store a computer program, the computer program includes program instructions, the processor is configured to call the program instructions, and the system uses the quality control method for the jacking construction process based on virtual-real scenario mapping. The system provided by the present invention has a high integration degree, and the information transmission between each component is smooth. By constructing a virtual-real linkage digital twin mapping system, it realizes millisecond-level synchronous interaction between the physical construction scenario and the virtual model; by developing an intelligent evaluation algorithm for multi-source data fusion, it establishes a multi-dimensional quality evaluation model covering structural mechanics and geometric accuracy, transforming empirical judgment into a quantitative decision based on big data; by innovating the dynamic regulation mechanism, it forms a quality closed-loop control chain of monitoring-evaluation-warning-regulation, realizing self-adaptive correction of construction anomalies and autonomous optimization of process parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a flowchart of the quality control method for the jacking construction process based on virtual-real scenario mapping according to an embodiment of the present invention; Figure 2 is a flowchart of the data backtracking method for the jacking construction process according to an embodiment of the present invention; Figure 3 is a flowchart of establishing a virtual mapping model for the jacking construction process according to an embodiment of the present invention; Figure 4 is a scene diagram of the jacking construction process according to an embodiment of the present invention; wherein, (a) is a diagram of the actual construction scene, and (b) is a diagram of the virtual mapping scene; Figure 5 is a structural schematic diagram of the quality control system for the jacking construction process based on virtual-real scenario mapping according to an embodiment of the present invention.

[0018] Description of the reference numerals: 1. Gantry crane; 2. Steel beam segment; 3. Guide beam; 4. Jacking device; 5. Temporary pier; 6. Deep foundation; 7. Steel beam model. Detailed implementation manners

[0019] The specific embodiments of the present invention will be described in detail below. It should be noted that the embodiments described here are only for illustrative purposes and are not used to limit the present invention. In the following description, in order to provide a thorough understanding of the present invention, a large number of specific details are set forth. However, it is obvious to those of ordinary skill in the art that the present invention does not have to employ these specific details. In other instances, well-known circuits, software, or methods have not been described in detail in order to avoid obscuring the present invention.

[0020] Throughout the specification, the reference to "one embodiment", "an embodiment", "one example", or "an example" means that the specific features, structures, or characteristics described in connection with the embodiment or example are included in at least one embodiment of the present invention. Thus, the phrases "in one embodiment", "in an embodiment", "one example", or "an example" that appear throughout the specification do not necessarily all refer to the same embodiment or example. In addition, the specific features, structures, or characteristics may be combined in any suitable combination and / or sub-combination in one or more embodiments or examples. In addition, those of ordinary skill in the art should understand that the drawings provided herein are for illustrative purposes only and are not necessarily drawn to scale.

[0021] Please refer to Figure 1 , an embodiment of the present invention provides a quality control method for the jacking construction process based on virtual-real scene mapping. The method includes the following steps: S1. Obtain the characteristic data during the bridge jacking construction process, where the characteristic data includes the data of the main beam stress, bearing reaction force, jacking displacement, jacking settlement, jacking temperature, main tower inclination deformation, jacking equipment, steel box girder pose state, and structural stress.

[0022] Among them, S1 further includes the following steps: S11. Obtain the monitoring data of the main beam stress during the bridge jacking construction process.

[0023] In one embodiment, first, according to the structural characteristics and stress conditions of the main beam, determine the key cross-section positions to be monitored, including the beam segments of each span, the mid-span, the 1 / 4 span positions, and the positions on both sides of the previous pier when the guide beam is about to reach the next pier.

[0024] Furthermore, surface strain gauges are arranged at each monitoring section, focusing on covering the parts with greater stress, including the bottom plate, web plate of the steel box girder, upper flange of the root of the guiding girder, and steel pipe piles of the temporary piers.

[0025] Furthermore, install surface strain gauges to ensure their close fit with the structure surface and take protective measures to avoid damage during construction.

[0026] Furthermore, connect the strain gauges to the data acquisition system, set appropriate sampling frequencies and parameters to ensure that the stress change data can be recorded in real time and continuously.

[0027] Furthermore, during the incremental launching construction process, monitor and record the strain data of each monitoring point in real time, and at the same time record the relevant information on the construction progress and load changes.

[0028] Furthermore, convert the collected strain data into stress data through the material mechanics formula.

[0029] S12. Obtain the monitoring data of the bearing reaction force during the incremental launching construction of the bridge.

[0030] In one embodiment, first, according to the design requirements and construction plan, install stress gauges at the permanent bearings and arrange pressure sensors at the tops of each pier and temporary pier to ensure accurate installation positions of the equipment and reliable connection to the data acquisition system.

[0031] Furthermore, during the beam lowering stage, monitor the reaction force data of the permanent bearings in real time through the stress gauges, feedback the data to the monitoring system, analyze it in combination with the design values, and adjust the bearing elevation if necessary to ensure uniform stress.

[0032] Furthermore, during the incremental launching construction process, as the cantilever length changes, continuously collect the bearing reaction force data of the temporary piers and piers through the pressure sensors, and monitor their dynamic change trends in real time to ensure that the piers and temporary piers are always in a safe stress state.

[0033] S13. Obtain the monitoring data of the incremental launching displacement during the incremental launching construction of the bridge.

[0034] In one embodiment, first, install a Beidou positioning device at the front end of the guiding girder and set a laser rangefinder between the steel box girder at the root of the bridge tower and the bridge tower to ensure the stable installation of the equipment and the normal operation of the data acquisition system.

[0035] Furthermore, during the incremental launching construction process, use Beidou positioning technology to collect the displacement data of the front end of the guiding girder in real time, and at the same time monitor the relative position change between the steel box girder and the bridge tower through the laser rangefinder to ensure that the data is uploaded to the monitoring system synchronously.

[0036] Further, compare and analyze the displacement data obtained in real time with the designed jacking trajectory. If it is found that the deviation exceeds the allowable range, immediately adjust the jacking equipment or take deviation correction measures.

[0037] Further, continuously record and store the displacement monitoring data to form a complete jacking displacement change curve, providing a basis for construction control and subsequent analysis.

[0038] S14. Obtain the monitoring data of the jacking settlement during the bridge jacking construction process.

[0039] In one embodiment, first, set up a total station robot at the dike, and install prisms outside each group of steel pipe columns of the assembly platform and the temporary pier to ensure that the measurement point layout is reasonable and the visibility condition is good.

[0040] Further, install inclination sensors and static level gauges on the top of the temporary pier pipe piles to cover the blind area of the total station measurement and form a complete settlement and deviation monitoring system.

[0041] Further, during the jacking process, use the total station robot to automatically track the prism to collect the three-dimensional coordinate data of each measurement point in real time. At the same time, obtain the inclination angle and vertical settlement of the temporary pier through the inclination sensor and the static level gauge.

[0042] S15. Obtain the monitoring data of the jacking temperature during the bridge jacking construction process.

[0043] In one embodiment, first, arrange temperature monitoring points at the key stress-bearing parts of the steel box girder and the main tower. The positions of the monitoring points are consistent with the stress measurement points to ensure that the temperature data can be analyzed corresponding to the stress data.

[0044] Further, use a non-contact infrared temperature tester to quickly scan and measure the surface temperature of the steel box girder. At the same time, directly read the built-in temperature data at the positions where vibrating wire strain gauges or stress sensors have been installed to achieve dual-channel temperature acquisition.

[0045] Further, under each working condition of the jacking construction, synchronously record the temperature values corresponding to the stress measurement points, and focus on the influence of solar radiation temperature difference, day-night temperature difference and seasonal temperature difference on the steel structure.

[0046] S16. Obtain the monitoring data of the inclination deformation of the main tower during the bridge jacking construction process.

[0047] In one embodiment, first, set up observation marking points at a certain height above the ground of the pier column to ensure that the points are stable and convenient for total station visibility measurement.

[0048] Further, arrange a special person to use a high-precision total station to regularly measure the three-dimensional coordinates of the pier column observation points during the jacking construction process and record the spatial position changes of the pier column in real time.

[0049] Furthermore, the coordinate data of each measurement is compared and analyzed with the initial reference value to calculate the longitudinal offset and tilt deformation trend of the pier.

[0050] Furthermore, the deformation monitoring data of the pier column during the entire jacking process is fully recorded to provide a basis for subsequent quality evaluation and construction control.

[0051] S17. Obtain monitoring data of the jacking equipment during the bridge jacking construction process.

[0052] In one embodiment, first, at the three-way jack , , Three axially installed tensile displacement sensors are installed, and stress and displacement sensors are set on the jacking equipment to ensure that each sensor is firmly installed and the signal transmission is normal.

[0053] Furthermore, during the jacking construction process, the displacement data of the jack in three directions and the corresponding jacking force data are collected in real time to ensure that the data are synchronously recorded in the monitoring system. The displacement data includes jacking displacement, correction displacement and jacking displacement data.

[0054] Furthermore, the collected raw data are compiled and processed to generate graphical results of displacement-time curve and thrust force-time curve, and compared and analyzed with design values ​​or control standards.

[0055] Furthermore, check whether the various curves generated during the data compilation process are complete. If a certain type of curve is found to be missing, immediately check the sensor log records and equipment status, find out the cause of data loss and supplement the collection.

[0056] Furthermore, the compiled data are subjected to an algorithmic check, and the extracted values ​​are compared with the average values ​​of the five-minute monitoring data. If the difference exceeds the allowable range of the specification, the rationality of the extraction principle, the selection of extraction points or the original data is checked.

[0057] Furthermore, the execution status of each link of data compilation is recorded in detail in the log. If a link fails, the reason is marked and reprocessed until the data quality meets the requirements. The final compiled data will be used for construction control and decision analysis.

[0058] S18. Obtain monitoring data on the posture status and structural stress of the steel box girder during the bridge jacking construction process.

[0059] In one embodiment, first, a global navigation satellite system (GNSS) locator is installed on both sides of the front end of the steel box girder and the front end of the guide beam, and a real-time dynamic differential measurement (RTK) reference point is set near the construction area to form a GNSS monitoring network consisting of three measuring points. At the same time, laser rangefinders are installed on the inner sides of the two tower limbs of the bridge tower to ensure that the equipment installation position is accurate and the signal reception is stable.

[0060] Furthermore, during the jacking construction process, the GNSS locator is used to collect the plane position and elevation data of the steel box girder in real time, and the laser rangefinder is used to monitor the change in the lateral distance between the steel box girder and the bridge tower, and the data is synchronously transmitted to the central processing system.

[0061] Furthermore, an adaptive weighted fusion algorithm is used to perform multi-sensor data fusion processing on the posture signals collected by GNSS, laser rangefinder and jacking equipment to eliminate signal distortion caused by vibration and noise interference factors and obtain more accurate steel box girder posture state data. The jacking equipment has a built-in stress sensor, which is used to obtain structural force data.

[0062] Furthermore, the fused posture data is compared and analyzed with the designed trajectory in real time. If axis deviation or elevation abnormality is found, the jacking parameters are immediately adjusted or corrective measures are taken.

[0063] Furthermore, the changing trends of posture status and structural force data are continuously recorded and analyzed to provide a reliable basis for construction safety control and subsequent processes.

[0064] S19. Obtain characteristic data during the bridge pushing construction process.

[0065] In one embodiment, the monitoring data is stored in a database, and the process and data are backtracked to obtain the problem data and modify, adjust and reorganize the problem data to obtain the characteristic data during the bridge jacking construction process. The data backtracking method of this process is as follows: Figure 2 As shown, Figure 2 The process backtracking in the article refers to the full-link verification process of tracing back from the final result data to the original collected data, and locating the problem link through the closed-loop path of result data-process backtracking-data backtracking; data backtracking specifically refers to the special verification operation of tracing back the original data source along the data processing chain for the identified abnormal data. In practical applications, after the monitoring data is stored in the database, the modification processing refers to the direct numerical correction of the erroneous data points, such as the position correction of the extraction point, the adjustment processing involves the reconfiguration of the algorithm parameters, such as the optimization of the linear fitting algorithm, and the compilation processing is the systematic data reorganization and standardization, such as supplementing the missing curve segments and rebuilding the results list.

[0066] The advantage of the method steps lies in using the backtracking process to discover problem data and finally extracting a characteristic data set that reflects the true state of the bridge incremental launching construction, providing quality-verified basic data for construction control.

[0067] S2. Use the characteristic data to build a virtual mapping model for incremental launching construction.

[0068] In one embodiment, please refer to Figure 3 , Figure 3 is the flow chart for establishing the virtual mapping model of incremental launching construction. First, build the main model of bridge incremental launching construction, the temporary structure model, the monitoring point model, and the construction environment model. The main model of bridge incremental launching construction includes the upper structure model and the lower structure model. The establishment process of the construction environment model is as follows: collect field data through on-site survey and UAV aerial survey technology, establish a real-scene model with accurate Geographic Information System (GIS) information, and use spatial triangulation calculation to reproduce the real construction environment, that is, obtain the construction environment model.

[0069] Further, establish a local virtual mapping primitive model, which includes but is not limited to the bored pile, pier, main beam, cross beam, stay cable, walking incremental launching machine, incremental launching platform, temporary pier, slideway beam, and monitoring point virtual mapping primitive model; Further, build a virtual mapping primitive model library according to the local virtual mapping primitive model; Specifically, use the computer-aided design software MicroStation V8i to perform intelligent solid modeling on each component of the cable-stayed bridge, such as bored piles, piers, main beams, and cross beams, classify and store them as independent model primitives, and support parametric adjustment to meet different design requirements.

[0070] Further, establish the construction equipment and temporary facility models, including the walking incremental launching machine, incremental launching platform, gantry crane, and temporary pier, to ensure that the models can dynamically simulate the incremental launching construction process, such as jacking, pushing, and falling actions and the working states of auxiliary facilities.

[0071] Further, integrate the monitoring point primitive model, locate the monitoring points in the virtual mapping model and simulate their morphological changes, providing a visual data interface for construction process monitoring.

[0072] Further, integrate all primitive models into the virtual mapping model library, extract the model product and manufacturing information and analyze the geometric features through the Pro / Toolkit secondary development function of the 3D design software Creo2.0, and automatically generate the measurement program and the measuring point planning path to achieve model-driven intelligent measurement.

[0073] Further, dynamically build the virtual mapping model, that is Figure 3The virtual scene model for incremental launching construction of a bridge realizes the full-element digital mapping of the construction environment, bridge structure, equipment actions, and monitoring data, providing real-time simulation and decision-making support for incremental launching construction.

[0074] It should be noted that the virtual mapping model is a high-precision digital three-dimensional model based on the real physical environment and construction process. By digitally replicating the objects, structures, construction equipment, and dynamic processes in the real world 1:1 into the virtual space, real-time two-way mapping between physical entities and virtual models is achieved. Its core is to construct a virtual mirror that is completely synchronized with the real construction environment through geometric modeling, parametric design, dynamic simulation, and data integration, for the visualization, simulation, monitoring, and automated control of the construction process.

[0075] The advantage of this method is that by building a virtual mapping model, real-time interaction between the physical construction environment and the virtual space is realized, ultimately serving the intelligent management and decision-making of the construction process.

[0076] S3. According to the virtual mapping model, perform dynamic mapping of the state of the incremental launching construction process and obtain the dynamic mapping result.

[0077] Please refer to Figure 4 , Figure 4 which is the scene diagram of the incremental launching construction process of the bridge of the present invention. Figure 4 In (a), it represents the actual construction scene, showing various types of equipment and structures used in the incremental launching construction process, including gantry crane 1, steel beam segment 2, guide beam 3, incremental launching device 4, temporary pier 5, and deep foundation 6. Figure 4 In (b), it represents the virtual mapping scene, that is, through a digital model, such as steel beam model 7, to simulate and monitor the actual construction process to achieve the intelligentization of construction management. Figure 4 In (a) and (b), through the combination of virtual and real, it reflects the collaborative application of actual construction and digital technology.

[0078] In one embodiment, the characteristic data obtained in step S1 is integrated into the virtual mapping model in real time through an interface or plug-in; a customized middleware is used to link the characteristic data with the virtual mapping model, and an automatic update mechanism is set so that the virtual mapping model is dynamically adjusted according to real-time data; in this way, the virtual mapping model can always reflect the actual state of the construction and achieve the dynamic mapping of the virtual scene.

[0079] Furthermore, the dynamic mapping process of the virtual scene is presented through a mathematical relationship.

[0080] Specifically, each type of data in the characteristic data represents the specific physical quantity at a certain point in time during the construction process; in order to accurately record and analyze these data at different time nodes, the data is discretized into a time series . Therefore, the following relationship exists:

[0081] where, is the -th type of data in the characteristic data at time is the -th type of data after discretization of the characteristic data, is the time step of sampling, is the sampling interval. During the transmission of discretized data, noise or delay may occur.

[0082] Furthermore, the transfer function is used to correct the above discretized time series data to obtain more accurate cloud monitoring data, satisfying the following relationship:

[0083] where, is the -th type of cloud monitoring data, is the transfer function, represents the transmission noise or delay error of the -th type of discretized data, is the time step of sampling, is the -th type of data after discretization of the characteristic data.

[0084] Furthermore, multi-dimensional filtering processing and feature extraction are performed on the cloud monitoring data to remove noise and extract key features; the mathematical expression of this processing process is as follows:

[0085] where, is the key feature parameter of the -th type of cloud monitoring data, is the multi-dimensional filtering and feature extraction function, is the -th type of cloud monitoring data, is the time step of sampling.

[0086] Further, using the key features, update the component states of the virtual mapping model so that the virtual mapping model can reflect the progress of the actual construction in real time; the update of the component states at a specific time step involves the adjustment of local component parameters, and its update expression is as follows:

[0087] where, is the parameter of the th component at the time step of , is the parameter of the th component at the time step of , is the characteristic parameter corresponding to the influence coefficient matrix of the key features of the rd component, representing the local sensitivity of the virtual-real mapping, is the total number of components.

[0088] Further, visually display the updated changes in the virtual mapping model through a visualization tool.

[0089] It should be noted that the parameter data in the above update expression is named virtual mapping data.

[0090] S4. Based on the dynamic mapping result, obtain the quality evaluation result of the incremental launching construction process.

[0091] In one embodiment, convert the characteristic parameter into a quality evaluation parameter , and the content of the quality evaluation includes the deformation, axis change, and stress distribution of the main girder. The quality evaluation parameter satisfies the following expression:

[0092] where, is a mapping function for mapping the characteristic parameter in the cloud monitoring data into a quality evaluation parameter, is the characteristic parameter, is the quality evaluation parameter.

[0093] Further, preset a standard index , compare the quality evaluation parameter with the preset standard index to obtain the quality evaluation result.

[0094] Specifically, establish a quality evaluation deviation model, and the quality evaluation deviation model satisfies the following expression:

[0095] where, For and comparison deviation.

[0096] Furthermore, by to determine whether the construction quality meets the design requirements, and obtain the evaluation result of the construction quality.

[0097] Specifically, set the normal range threshold of the construction quality .

[0098] If , the construction quality is normal; If , the construction quality is abnormal.

[0099] S5. Through the quality evaluation result, realize the quality control of the incremental launching construction process.

[0100] In one embodiment, based on the quality evaluation result, establish a risk early warning model for construction quality, obtain risk early warning information, and the risk early warning model satisfies the following expression:

[0101] Wherein, is the risk early warning value, is the deviation, is the normal range threshold of the construction quality.

[0102] If , issue risk early warning information, and the problem components in the virtual mapping model will be marked in the form of colors and charts to remind the construction personnel to take necessary countermeasures; If , do not issue risk early warning information.

[0103] Furthermore, based on the risk early warning information, establish a construction quality visualization model, and display the quality problems in a visual manner in the virtual mapping model. The construction quality visualization model satisfies the following expression:

[0104] Wherein, is the visualization result of the quality problem of the th component, is the construction parameter of the th component at the time step of , is the risk early warning value, is the visualization function.

[0105] Further, based on the construction quality visualization model, determine the construction parameters that need to be adjusted in the problem components.

[0106] Further, use a feedback control algorithm to adjust the construction parameters.

[0107] Specifically, first, set the control system as a proportional-integral-derivative controller.

[0108] Further, establish a construction parameter adjustment model, and the construction parameter adjustment model is as follows:

[0109] Wherein, represents the adjustment value of the th construction parameter calculated according to the deviation at the next time step , which is also called the adjustment parameter, , , respectively represent the proportional gain, integral gain, and derivative gain, is the cumulative sum of deviations, representing the integral of all deviations from the beginning to the th step.

[0110] Further, based on the adjustment parameter , the construction equipment adjusts its operations in real time. For example, based on the deviation calculation result, adjust the jacking speed to control the stress distribution of the main girder; adjust the pressure of the jacks to change the force distribution of the jacks and ensure the stability of the structure; by adjusting the height of the piers, maintain the overall stability of the structure.

[0111] Further, continuously monitor the new construction status and update it in real time through the virtual mapping model and the database to ensure that the construction process is consistent with the design objectives. Each adjustment during the construction process affects the construction status at the next moment. Through the closed-loop control mechanism, continuously evaluate the deviation and adjust the construction parameters to ensure the continuous optimization of the construction quality. When the intelligent decision-making module detects an abnormality or the deviation exceeds the tolerance range, mark the problem area in the virtual mapping model in a visual way and prompt the construction team to take measures. During the construction process, generate a real-time report to record the construction status, evaluation results, control inputs, and any generated warning information.

[0112] Further, through the method of multi-source quality data integration and statistical analysis, automatically file all data and adjustment records to form a construction knowledge base for reference and optimization of future projects. After the construction is completed, conduct a comprehensive evaluation of the entire construction process, analyze the quality qualification rate, construction efficiency, and risk control, and provide data support and optimization suggestions for future construction projects.

[0113] Please refer toFigure 5 , Figure 5 This is a schematic structural diagram of the quality control system for the jacking construction process based on virtual-real scenario mapping in an embodiment of the present invention. The system includes an input device, a processor, an output device, and a memory. The input device, the processor, the output device, and the memory are interconnected. Among them, the memory is used to store a computer program, and the computer program includes program instructions. The processor is configured to call the program instructions, and the system uses the quality control method for the jacking construction process based on virtual-real scenario mapping.

[0114] In this embodiment, the input device includes a sensor array, an industrial camera and a laser scanner, a construction equipment data interface, and an environmental monitoring device, and has the following functions: First, it collects key parameters in real time. The key parameters include main girder stress, bearing reaction force, jacking displacement, settlement, temperature, and main tower deformation parameters. Second, it obtains the operating status of construction equipment. Third, it monitors the influence of environmental factors on construction quality. Fourth, it transmits the original data to the processor for modeling and analysis.

[0115] The processor includes a data preprocessing module, a digital twin modeling engine, a dynamic mapping calculation unit, a quality assessment and risk warning module, and a parameter optimization decision module, and has the following functions: First, it cleans and fuses the input data and extracts key features. Second, it constructs and updates the virtual mapping model. Third, it calculates the construction state deviation in real time and predicts potential risks. Fourth, it optimizes the jacking parameters based on the quality assessment results. Fifth, it supports edge computing and cloud collaboration to ensure low-latency response.

[0116] The output device includes a visual interaction terminal, a warning and alarm device, an automatic regulation execution mechanism, and a report generation system, and has the following functions: First, it displays the virtual mapping model, the quality assessment results, and the risk warning information in real time. Second, it provides visual construction guidance. Third, it triggers automatic or semi-automatic regulation. Fourth, it generates traceable quality control records to support decision-making analysis.

[0117] The memory includes a real-time database, a historical database, a model library, and a knowledge base, and has the following functions: First, it supports millisecond-level data reading and writing to ensure dynamic update of the model. Second, it stores the data of the entire construction process for retrospective analysis and responsibility tracing. Third, it accumulates typical construction cases to improve the model's self-learning ability.

[0118] The present invention proposes an intelligent quality control method for the jacking construction process based on dynamic mapping of virtual and real scenarios. By introducing virtual-real mapping technology, information fusion and interaction between the virtual and physical spaces are realized through data driving, ensuring real-time update and accurate feedback of construction data, and achieving all-round and whole-process real-time monitoring and management of construction quality. This method overcomes the drawbacks of existing means, improves construction efficiency and safety, and provides an intelligent and visual solution for bridge jacking construction.

[0119] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered by the scope of the claims and the description of the present invention.

Claims

1. A method for quality control of the jacking construction process based on virtual-real scene mapping, characterized in that: The method comprises the following steps: Acquire characteristic data during the bridge jacking construction process, including data on main beam stress, support reaction force, jacking displacement, jacking settlement, jacking temperature, main tower tilt deformation, jacking equipment, steel box beam posture and structural stress; Using the characteristic data, a virtual mapping model of the jacking construction is constructed; According to the virtual mapping model, dynamic mapping of the state of the jacking construction process is performed and a dynamic mapping result is obtained; Based on the dynamic mapping results, obtaining a quality assessment result of the jacking construction process; The quality assessment results are used to achieve quality control of the jacking construction process.

2. According to the method of quality control of the jacking construction process based on virtual-real scene mapping according to claim 1, it is characterized in that: The acquisition of characteristic data during the bridge pushing construction process includes: Obtain monitoring data during bridge jacking construction; The monitoring data is stored in a database, and process and data backtracking are performed to obtain problem data; The problem data are modified, adjusted and reorganized to obtain characteristic data during the bridge jacking construction process.

3. According to the method of quality control of the jacking construction process based on virtual-real scene mapping according to claim 1, it is characterized in that: The method of using the characteristic data to construct a virtual mapping model for top-pushing construction includes: Using the characteristic data, a main model of bridge jacking construction, a temporary structure model, a monitoring point model and a construction environment model are established; Establishing a local virtual mapping primitive model based on the bridge pushing construction main body model, the temporary structure model, the monitoring point model and the construction environment model; Constructing a virtual mapping primitive model library according to the local virtual mapping primitive model; A virtual mapping model of jacking construction is constructed through the virtual mapping primitive model library, and the virtual mapping model is a virtual mirror image of the real construction environment.

4. According to the method for quality control of the jacking construction process based on virtual-real scene mapping according to claim 1, it is characterized in that: The step of dynamically mapping the state of the jacking construction process according to the virtual mapping model and obtaining a dynamic mapping result comprises: Using the feature data, obtaining an update result of the virtual mapping model; Through the update result, the construction process status is dynamically mapped and the dynamic mapping result is obtained.

5. According to the method of quality control of the jacking construction process based on virtual-real scene mapping according to claim 4, it is characterized in that: The obtaining the update result of the virtual mapping model by using the feature data includes: Discretizing the characteristic data to obtain discretized data; Correcting the discretized data to obtain cloud monitoring data; Extracting key feature data through the cloud monitoring data; The virtual mapping model is updated using the key feature data to obtain an update result.

6. According to the method of quality control of the jacking construction process based on virtual-real scene mapping according to claim 1, it is characterized in that: The obtaining of the quality assessment result of the jacking construction process based on the dynamic mapping result includes: Based on the dynamic mapping result, obtaining quality assessment parameter data; Constructing a quality assessment deviation model based on the quality assessment parameter data; Obtaining quality assessment deviation through the quality assessment deviation model; Based on the quality assessment deviation, a quality assessment result of the jacking construction process is obtained.

7. The method for quality control of the jacking construction process based on virtual-real scene mapping according to claim 1 is characterized in that: The quality control of the jacking construction process achieved through the quality assessment results includes: Establishing a risk early warning model for construction quality based on the quality assessment results; Using the risk warning model to obtain risk warning information; Establishing a construction quality visualization model based on the risk warning information; The quality control of the jacking construction process is achieved through the construction quality visualization model.

8. The method for quality control of the jacking construction process based on virtual-real scene mapping according to claim 7 is characterized in that: The quality control of the jacking construction process achieved through the construction quality visualization model includes: Determine components with quality problems through the construction quality visualization model; According to the components, a construction parameter adjustment model is established; According to the construction parameter adjustment model, obtaining the adjustment result of the construction parameter; Through the adjustment results, quality control of the jacking construction process is achieved.

9. The method for quality control of the jacking construction process based on virtual-real scene mapping according to claim 8 is characterized in that: The construction parameter adjustment model satisfies the following expression: ， in, For the The construction parameters are listed in The adjustment value of the time step, , , Represent the proportional gain, integral gain and differential gain respectively, For the The construction parameters are listed in The quality assessment deviation of time steps, For the The construction parameters are listed in The quality assessment deviation of time steps, is the time step variable.

10. A system for quality control of a jacking construction process based on virtual-real scene mapping, the system using a method for quality control of a jacking construction process based on virtual-real scene mapping as claimed in any one of claims 1 to 9, characterized in that: The system includes an input device, a processor, an output device and a memory, wherein the input device, the processor, the output device and the memory are connected to each other, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions.

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