Quality control method and system for the jacking construction process based on virtual-real scenario mapping

Abstract

The present invention relates to the field of bridge construction automation and intelligence, and particularly relates to a quality control method and system for the jacking construction process based on virtual-real scene mapping. The method includes the following steps: obtaining characteristic data during the bridge jacking construction process; using the characteristic data to build a virtual mapping model of the jacking construction; according to the virtual mapping model, performing dynamic mapping of the state of the jacking construction process and obtaining a dynamic mapping result; based on the dynamic mapping result, obtaining a quality evaluation result of the jacking construction process; and through the quality evaluation result, realizing quality control of the jacking construction process. By introducing virtual-real scene mapping technology, the present invention realizes information fusion and interaction between the virtual and physical spaces driven by data, ensures real-time update and accurate feedback of construction data, provides an intelligent and visual solution for bridge jacking construction, and realizes full-range and whole-process real-time monitoring and management of the construction process quality.

Description

Technical Field

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

[0002] The bridge jacking construction technology 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 large bridge construction. However, the jacking 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 high efficiency, precision, and safety in modern projects.

[0003] In the prior art, the quality control of jacking 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 early warning and difficulty in timely grasping the construction quality. In addition, the traditional plan view, elevation view, and section view are not intuitive in the construction plan, and the detail expression is not comprehensive, making it 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, based on the real construction scene, it is necessary to integrate a limited front-end intelligent perception system through visualization technology to conduct three-dimensional space simulation verification and design optimization on the steel beam jacking operation plan, and realize the digital online intelligent control of the key quality indicators of bridge jacking construction.

[0004] At present, there is not enough research work on the quality control of the bridge jacking construction process, and there is no specific intelligent quality control method for the jacking 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 the jacking 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, jacking displacement, jacking settlement, jacking temperature, main tower inclination deformation, jacking equipment, steel box beam posture status and structural stress data; using the characteristic data to build a virtual mapping model of jacking construction; according to the virtual mapping model, dynamically mapping the jacking construction process status 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 achieved; by quantitatively outputting quality assessment results, an automatic early warning mechanism is formed, which greatly improves the quality control response speed; by feeding back the virtual model to the physical construction, 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; and modifying, adjusting, and reorganizing 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; and by reorganizing the modified data, a feature data set with temporal and spatial correlation is constructed, providing high-precision input for virtual-reality mapping.

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

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

[0010] Optionally, obtaining 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 the update result. By performing standardized discretization processing on the feature data, the present invention realizes the efficient integration and unified management of massive construction monitoring data, and solves the problem of low processing efficiency caused by the chaotic existing data format; by correcting the discrete 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 computational burden of model update is greatly reduced; through the model dynamic update mechanism, the continuous synchronization between the virtual mapping model and the actual construction state is realized, ensuring the timeliness and authenticity of digital twin.

[0011] Optionally, obtaining 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 based on 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 to enter 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 warning model for construction quality based on the quality assessment results; obtaining risk warning information using the risk warning model; establishing a construction quality visualization model based on the risk warning information; and realizing the quality control of the incremental launching construction process through the construction quality visualization model. By establishing a risk 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 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 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 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]

[0016] 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 one time step is a time step variable. The present invention realizes precise dynamic regulation of the quality deviation by constructing a construction parameter adjustment model; 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, intervenes in potential quality problems in advance, and forms a forward-looking quality prevention and control mechanism; through the synergistic effect of multiple parameters, it takes into account the adjustment speed and system stability, avoiding adverse regulation phenomena such as overshoot or oscillation; replaces empirical judgment with digital regulation, greatly improving the scientificity and repeatability of construction parameter adjustment, and providing a standardized technical means for quality control.

[0017] 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 degree of integration, and the information transmission between components 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 quantitative decision-making based on big data; by innovating the dynamic regulation mechanism, it forms a quality closed-loop control chain of monitoring-evaluation-warning-regulation, realizing adaptive correction of construction anomalies and autonomous optimization of process parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] 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;

[0019] Figure 2 is a flowchart of the data backtracking method for the jacking construction process according to an embodiment of the present invention;

[0020] Figure 3 is a flowchart of establishing a virtual mapping model for the jacking construction process according to an embodiment of the present invention;

[0021] 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;

[0022] Figure 5 This is a schematic structural diagram of the quality control system for the jacking construction process based on virtual-real scene mapping according to an embodiment of the present invention.

[0023] Explanation of reference numerals:

[0024] 1. Gantry crane; 2. Steel girder segment; 3. Guide beam; 4. Jacking device; 5. Temporary pier; 6. Deep foundation; 7. Steel girder model. Specific implementation manners

[0025] The following will describe in detail the specific embodiments of the present invention. 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 specifically described to avoid obscuring the present invention.

[0026] Throughout the specification, the reference to "an embodiment", "embodiments", "an example", or "examples" 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 an embodiment", "in embodiments", "an example", or "examples" appearing 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.

[0027] 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, and the method includes the following steps:

[0028] S1. Obtain the characteristic data during the jacking construction process of the bridge, and the characteristic data includes data of the main girder stress, bearing reaction force, jacking displacement, jacking settlement, jacking temperature, main tower inclination deformation, jacking equipment, steel box girder pose state, and structural stress.

[0029] Among them, S1 further includes the following steps:

[0030] S11. Obtain the monitoring data of the main girder stress during the jacking construction process of the bridge.

[0031] In one embodiment, first, according to the structural characteristics and stress conditions of the main girder, determine the key cross-section positions to be monitored, including the beam segments of each span, the mid-span, the 1 / 4 span position, and the positions on both sides of the previous pier when the guiding girder is about to reach the next pier.

[0032] Further, arrange surface strain gauges on each monitoring cross-section, focusing on covering the parts with greater stress, including the bottom plate, web plate of the steel box girder, upper flange of the guiding girder root, and steel pipe piles of the temporary piers.

[0033] Further, install the surface strain gauges to ensure that they are closely attached to the structure surface, and take protective measures to avoid damage during the construction process.

[0034] Further, 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.

[0035] Further, 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 information related to the construction progress and load changes.

[0036] Further, convert the collected strain data into stress data through the material mechanics formula.

[0037] S12. Obtain the monitoring data of the bearing reaction force during the incremental launching construction of the bridge.

[0038] In one embodiment, first, according to the design requirements and construction plan, install stress gauges at the permanent bearings, and arrange pressure sensors on the tops of each pier and temporary pier to ensure that the equipment installation positions are accurate and the connection with the data acquisition system is reliable.

[0039] Further, during the beam lowering stage, monitor the reaction force data of the permanent bearings in real time through the stress gauges, and feedback the data to the monitoring system for analysis in combination with the design values, and adjust the bearing elevation if necessary to ensure uniform stress.

[0040] Further, 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 its dynamic change trend in real time to ensure that the piers and temporary piers are always in a safe stress state.

[0041] S13. Obtain the monitoring data of the incremental launching displacement during the incremental launching construction of the bridge.

[0042] 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 that the equipment is installed stably and the data acquisition system operates normally.

[0043] Furthermore, during the incremental launching construction process, the Beidou positioning technology is used to collect the displacement data of the front end of the falsework in real time. At the same time, the relative position changes between the steel box girder and the bridge tower are monitored by a laser rangefinder to ensure that the data is synchronously uploaded to the monitoring system.

[0044] Furthermore, the displacement data obtained in real time is compared and analyzed with the designed incremental launching trajectory. If the deviation is found to exceed the allowable range, the incremental launching equipment is immediately adjusted or corrective measures are taken.

[0045] Furthermore, the displacement monitoring data is continuously recorded and stored to form a complete incremental launching displacement change curve, providing a basis for construction control and subsequent analysis.

[0046] S14. Obtain the monitoring data of the incremental launching settlement during the bridge incremental launching construction process.

[0047] In one embodiment, first, a total station robot is erected at the dike, and prisms are installed outside each group of steel pipe columns of the assembly platform and the temporary piers to ensure that the measurement point layout is reasonable and the visibility condition is good.

[0048] Furthermore, inclination sensors and static level gauges are installed 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.

[0049] Furthermore, during the incremental launching process, the total station robot automatically tracks the prism to collect the three-dimensional coordinate data of each measurement point in real time. At the same time, the inclination angle and vertical settlement of the temporary pier are obtained through the inclination sensors and static level gauges.

[0050] S15. Obtain the monitoring data of the incremental launching temperature during the bridge incremental launching construction process.

[0051] In one embodiment, first, temperature monitoring points are arranged at the key stress-bearing parts of the steel box girder and the main tower. The positions of the monitoring points are consistent with those of the stress measurement points to ensure that the temperature data can be analyzed corresponding to the stress data.

[0052] Furthermore, a non-contact infrared temperature tester is used to quickly scan and measure the surface temperature of the steel box girder. At the same time, the built-in temperature data is directly read at the positions where vibrating wire strain gauges or stress sensors have been installed to achieve dual-channel temperature acquisition.

[0053] Furthermore, under each working condition of the incremental launching construction, the temperature values corresponding to the stress measurement points are synchronously recorded, and key attention is paid to the influence of solar radiation temperature difference, day-night temperature difference and seasonal temperature difference on the steel structure.

[0054] S16. Obtain the monitoring data of the inclination deformation of the main tower during the bridge incremental launching construction process.

[0055] In one embodiment, first, an observation mark point is set at a certain height above the ground on the pier to ensure that the point is stable and convenient for line-of-sight measurement with a total station.

[0056] Furthermore, a dedicated person is arranged to use a high-precision total station to regularly perform three-dimensional coordinate measurements of the pier observation points during the jacking construction process, and record the spatial position changes of the piers in real time.

[0057] Furthermore, the coordinate data of each measurement is compared and analyzed with the initial benchmark value to calculate the longitudinal offset and tilt deformation trend of the pier.

[0058] Furthermore, the deformation monitoring data of the pier columns during the entire jacking process are fully recorded to provide a basis for subsequent quality assessment and construction control.

[0059] S17. Obtain monitoring data of the jacking equipment during the bridge jacking construction process.

[0060] 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 pushing equipment to ensure that each sensor is firmly installed and the signal transmission is normal.

[0061] 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.

[0062] Furthermore, the collected raw data is compiled and processed to generate graphical results of displacement-time curve and thrust-time curve, and compared and analyzed with the design value or control standard.

[0063] 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 device status, find out the cause of data loss and collect additional data.

[0064] Furthermore, the compiled data is subjected to an algorithmic test, and the extracted value is compared with the average value 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.

[0065] 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.

[0066] S18. Obtain monitoring data on the steel box girder posture and structural stress during the bridge jacking construction process.

[0067] 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) benchmark 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.

[0068] 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. At the same time, the laser rangefinder is used to monitor the changes in the lateral distance between the steel box girder and the bridge tower, and the data is synchronously transmitted to the central processing system.

[0069] 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 status data. The jacking equipment has a built-in stress sensor, which is used to obtain structural force data.

[0070] Furthermore, the fused posture data is compared and analyzed with the designed trajectory in real time. If axis offset or elevation abnormality is found, the jacking parameters are immediately adjusted or corrective measures are taken.

[0071] 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.

[0072] S19. Obtain characteristic data during the bridge jacking construction process.

[0073] In one embodiment, the monitoring data is stored in a database, and process and data backtracking are performed to obtain problem data and modify, adjust and reorganize the problem data to obtain characteristic data during the bridge jacking construction process. The data backtracking method of this process is as follows: Figure 2 As shown, Figure 2The process traceback in refers to the full-link verification process of tracing back from the final result data to the original collected data in reverse, and locating the problem link through the closed-loop path of result data - process traceback - data traceback; data traceback 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 process refers to the direct numerical correction of the error data points, such as the deviation correction of the extraction point position, the adjustment process involves the reconfiguration of algorithm parameters, such as the optimization of the line fitting algorithm, and the compilation process is the systematic data reorganization and standardization, such as supplementing the missing curve segments and reconstructing the result list.

[0074] The advantage of the method steps lies in using the traceback process to discover the problem data, and finally extracting the characteristic data set reflecting the true state of the bridge incremental launching construction, providing the quality-verified basic data for construction control.

[0075] S2. Use the characteristic data to build a virtual mapping model for incremental launching construction.

[0076] 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, construct 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 the field data through on-site reconnaissance 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 actual construction environment, that is, obtain the construction environment model.

[0077] Furthermore, establish a local virtual mapping primitive model, which includes but is not limited to the virtual mapping primitive models of bored piles, bridge piers, main girders, cross beams, stay cables, walking incremental launching machines, incremental launching platforms, temporary piers, slideway girders, and monitoring points;

[0078] Furthermore, construct a virtual mapping primitive model library according to the local virtual mapping primitive model;

[0079] Specifically, use the computer-aided design software MicroStation V8i to perform intelligent solid modeling on the components of the cable-stayed bridge, such as bored piles, bridge piers, main girders, and cross beams, classify and store them as independent model primitives, and support parametric adjustment to meet different design requirements.

[0080] Furthermore, establish the models of construction equipment and temporary facilities, including walking incremental launching machines, incremental launching platforms, gantry cranes, and temporary piers, to ensure that the models can dynamically simulate the incremental launching construction process, such as the lifting, pushing, and falling actions and the working states of the auxiliary facilities.

[0081] Further, integrate the basic element model of the monitoring point, locate the monitoring point in the virtual mapping model and simulate its morphological changes, providing a visual data interface for the construction process monitoring.

[0082] Further, integrate all basic element models into the virtual mapping model library. Through the secondary development function of Pro / Toolkit in the 3D design software Creo2.0, extract the model product and manufacturing information, analyze the geometric features, automatically generate the measurement program and the measuring point planning path, and realize the model-driven intelligent measurement.

[0083] Further, dynamically build the virtual mapping model, that is Figure 3 the virtual scene model of the bridge incremental launching construction in

[0084] Note that the virtual mapping model is a high-precision digital 3D 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, the real-time two-way mapping between the physical entity and the virtual model is realized. Its core is to construct a virtual mirror completely synchronized with the real construction environment through geometric modeling, parametric design, dynamic simulation and data integration, for the visualization, simulation, monitoring and automatic control of the construction process.

[0085] The advantage of this method is that by building the virtual mapping model, the 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.

[0086] S3. According to the virtual mapping model, perform the dynamic mapping of the incremental launching construction process state and obtain the dynamic mapping result.

[0087] 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 the gantry crane 1, steel beam segment 2, nose girder 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 the digital model, such as the steel beam model 7, to simulate and monitor the actual construction process to achieve the intelligent construction management; Figure 4 In (a) and (b), through the combination of virtual and real, it reflects the collaborative application of the actual construction and digital technology.

[0088] In one embodiment, the feature data obtained in step S1 is integrated into the virtual mapping model in real time through an interface or plug-in. Custom-developed middleware is used to link the feature data with the virtual mapping model, and an automatic update mechanism is set up to enable the virtual mapping model to dynamically adjust according to real-time data. In this way, the virtual mapping model can always reflect the actual status of the construction and realize dynamic mapping of the virtual scene.

[0089] Furthermore, the dynamic mapping process of the virtual scene is presented through mathematical relationships.

[0090] Specifically, each type of data in the feature 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 time series Therefore, the following relationship exists:

[0091]

[0092] in, for The first feature data in the moment Class data, is the discretized feature data Class data, is the sampling time step, is the sampling interval. Noise or delay may occur during the transmission of discretized data.

[0093] Furthermore, using the transfer function For the above discretized time series data Correction is performed to obtain more accurate cloud monitoring data, satisfying the following relationship:

[0094]

[0095] in, For the Cloud-like monitoring data, is the transfer function, Indicates the Transmission noise or delay error of discretized data, is the sampling time step, is the discretized feature data Class data.

[0096] Furthermore, multi-dimensional filtering 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:

[0097]

[0098] Among them, 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 sampling time step.

[0099] Furthermore, using the key features, update the state of each component of the virtual mapping model, so that the virtual mapping model can reflect the actual construction progress in real time; the update of the component state at a specific time step involves the adjustment of local component parameters, and its update expression is as follows:

[0100]

[0101] Among them, 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 feature parameter corresponding to the influence coefficient matrix of the key features of the th component, representing the local sensitivity of the virtual-real mapping, is the total number of components.

[0102] Furthermore, visually display the update changes in the virtual mapping model through a visualization tool.

[0103] It should be noted that the parameter data in the above update expression is named virtual mapping data.

[0104] S4. Based on the dynamic mapping result, obtain the quality evaluation result of the jacking construction process.

[0105] In one embodiment, convert the feature parameter into a quality evaluation parameter , and the content of its quality evaluation includes the deformation, axis change and stress distribution of the main girder. The quality evaluation parameter satisfies the following expression:

[0106]

[0107] Among them, is the mapping function for mapping the feature parameter in the cloud monitoring data into a quality evaluation parameter, is the feature parameter, is a quality assessment parameter.

[0108] Further, a preset standard index , compare the quality assessment parameter with the preset standard index to obtain a quality assessment result.

[0109] Specifically, establish a quality assessment deviation model, and the quality assessment deviation model satisfies the following expression:

[0110]

[0111] where is and comparison deviation.

[0112] Further, judge whether the construction quality meets the design requirements by the magnitude of, and obtain an evaluation result of the construction quality.

[0113] Specifically, set the normal range threshold .

[0114] If , the construction quality is normal;

[0115] If , the construction quality is abnormal.

[0116] S5. Through the quality assessment result, realize the quality control of the incremental launching construction process.

[0117] In one embodiment, based on the quality assessment result, establish a risk warning model for construction quality, obtain risk warning information, and the risk warning model satisfies the following expression:

[0118]

[0119] where is the risk warning value, is the deviation, [[ID=6)) is the normal range threshold of construction quality.

[0120] If )]], then issue risk 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;

[0121] If , then do not issue risk warning information.

[0122] ​Further, based on the risk warning information, a construction quality visualization model is established, and quality problems are displayed in a visual manner in the virtual mapping model. The construction quality visualization model satisfies the following expression:

[0123]

[0124] where 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 warning value, is the visualization function.

[0125] Further, based on the construction quality visualization model, the construction parameters that need to be adjusted in the problem components are determined.

[0126] Further, a feedback control algorithm is used to adjust the construction parameters.

[0127] Specifically, first, the control system is set as a proportional-integral-derivative controller.

[0128] Further, a construction parameter adjustment model is established. The construction parameter adjustment model is as follows:

[0129]

[0130] where 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.

[0131] Further, based on the adjustment parameter , the construction equipment adjusts its operations in real time. For example, based on the deviation calculation result, the jacking speed is adjusted to control the stress distribution of the main girder; the pressure of the jack is adjusted to change the force distribution of the jack to ensure the stability of the structure; by adjusting the height of the pier, the overall stability of the structure is maintained.

[0132] Furthermore, 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 a deviation exceeding 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 real-time reports to record the construction status, evaluation results, control inputs, and any generated warning information.

[0133] Furthermore, through the method of integrating multi-source quality data and statistical analysis, automatically archive 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.

[0134] Please refer to Figure 5 , Figure 5 FIG. is a schematic structural diagram of a quality control system for the jacking construction process based on virtual-real scene 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 scene mapping described above.

[0135] 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, collect key parameters in real time, and the key parameters include main girder stress, bearing reaction force, jacking displacement, settlement, temperature, and main tower deformation parameters; second, obtain the operating status of construction equipment; third, monitor the impact of environmental factors on construction quality; fourth, transmit the original data to the processor for modeling and analysis.

[0136] The processor includes a data preprocessing module, a digital twin modeling engine, a dynamic mapping calculation unit, a quality evaluation and risk warning module, and a parameter optimization decision module, and has the following functions: First, clean and fuse the input data and extract key features; second, construct and update the virtual mapping model; third, calculate the construction status deviation in real time and predict potential risks; fourth, optimize the jacking parameters based on the quality evaluation results; fifth, support edge computing and cloud collaboration to ensure low-latency response.

[0137] The output device includes a visual interaction terminal, an early 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, quality assessment results, and 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.

[0138] 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 data reading and writing at the millisecond level to ensure dynamic model update; second, it stores the data of the entire construction process for retrospective analysis and liability traceability; third, it accumulates typical construction cases to improve the model's self-learning ability.

[0139] 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, it realizes the information fusion and interaction between the virtual and physical spaces driven by data, ensures the real-time update and accurate feedback of construction data, and realizes the full-range 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.

[0140] 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 described in the foregoing embodiments, or perform equivalent replacements for some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions 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 jacking construction process based on virtual-reality scene mapping, characterized in that: The method comprises the following steps: Acquire characteristic data during the bridge jacking construction process, including main beam stress, support reaction force, jacking displacement, jacking settlement, jacking temperature, main tower tilt deformation, jacking equipment, steel box girder posture and structural stress data; Using the characteristic data, a virtual mapping model of the jacking construction is constructed; According to the virtual mapping model, dynamic mapping of the jacking construction process state 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; Through the quality assessment results, the quality control of the jacking construction process is achieved; 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; Modifying, adjusting and compiling the problem data to obtain characteristic data during the bridge pushing construction process; The use of the characteristic data to construct a virtual mapping model of the jacking construction includes: Using the characteristic data, a bridge jacking construction main body model, 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; By using the virtual mapping primitive model library, a virtual mapping model of jacking construction is constructed, wherein the virtual mapping model is a virtual mirror image of the real construction environment; The step of dynamically mapping the state of the jacking construction process and obtaining a dynamic mapping result based on the virtual mapping model includes: Using the feature data, obtaining an update result of the virtual mapping model; Perform dynamic mapping of the construction process status and obtain dynamic mapping results based on the update results; The obtaining of an 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; The cloud monitoring data satisfies the following formula: ， Among them, is the class of cloud monitoring data, is the transfer function, represents the transmission noise or delay error of the class of discretized data, is the sampling time step, is the class of data after discretization of the feature data; Extract key feature data from the cloud monitoring data, including: ， Among them, is the key feature parameter of the nth type of cloud monitoring data, is the multi-dimensional filtering and feature extraction function, is the nth type of cloud monitoring data, is the sampling time step; Using the key feature data, updating the virtual mapping model and obtaining an update result specifically includes: ， in, For the The time step of a component is Parameters when For the The time step of a component is Parameters when is the characteristic parameter Corresponding to The influence coefficient matrix of the key features of each component represents the local sensitivity of the virtual-real mapping. The total number of components.

2. The quality control method for the jacking construction process based on virtual-real scene mapping according to claim 1, wherein The obtaining of a 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 a 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.

3. A quality control method for the jacking construction process based on virtual-real scene mapping according to claim 1, 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; Through the construction quality visualization model, the quality control of the incremental launching construction process is realized.

4. A quality control method for the jacking construction process based on virtual-real scene mapping according to claim 3, characterized in that The realization of the quality control of the incremental launching construction process through the construction quality visualization model includes: Determine the components with quality problems through the construction quality visualization model; Establish a construction parameter adjustment model based on the components; Obtain the adjustment result of the construction parameters according to the construction parameter adjustment model; Realize the quality control of the incremental launching construction process through the adjustment result.

5. The quality control method for the jacking construction process based on virtual-real scenario mapping according to claim 4, wherein, The construction parameter adjustment model satisfies the following expression: ， Among them, 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 quality assessment deviation of the th construction parameter at the th time step, is the time step variable.

6. A quality control system for the jacking construction process based on virtual-real scene mapping. The system uses a quality control method for the jacking construction process based on virtual-real scene mapping according to any one of claims 1 to 5, characterized in that 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, the computer program includes program instructions, and the processor is configured to call the program instructions.

Images