Construction compaction quality monitoring system and method based on high-precision positioning of beidou

Abstract

This invention provides a system and method for monitoring the compaction quality of airport construction based on BeiDou high-precision positioning, belonging to the field of road construction technology. It includes a hardware subsystem and a software subsystem. The hardware subsystem acquires BeiDou positioning data and transmits it to the software subsystem, acquires sensor data, obtains fused data, transmits and displays the data in real time, and transmits input commands to the roller control system to execute compaction commands. The software subsystem acquires the initial compaction path based on the transmitted BeiDou positioning data, acquires a construction strategy based on the fused data, uses an interpolation algorithm to acquire supplementary compaction commands, transmits the dynamic construction commands and supplementary compaction commands to the hardware subsystem, generates a construction quality report, and provides visual feedback. This invention solves the problems of poor real-time performance, limited accuracy, difficulty in data sharing, insufficient quality control, resource waste, and low security in existing airport construction compaction quality monitoring systems.

Description

Technical Field

[0001] This invention belongs to the field of road construction technology, and in particular relates to an airport construction compaction quality monitoring system and method based on Beidou high-precision positioning. Background Technology

[0002] During airport construction, especially in the earthwork filling phase, monitoring the compaction quality is a crucial step in ensuring construction quality. Traditional compaction quality monitoring methods mainly rely on manual operation and basic measuring tools, with low levels of informatization and automation. Currently, airport construction compaction quality monitoring technology has the following main drawbacks:

[0003] Poor real-time performance: There is a time delay in the collection and processing of compaction data, making real-time monitoring impossible;

[0004] Limited accuracy: Relying on manual measurement and recording limits accuracy and can easily lead to error accumulation;

[0005] Data sharing difficulties: The phenomenon of information silos is serious, and data sharing and collaboration between different construction teams and management departments are not smooth;

[0006] Inadequate quality control: The lack of continuous monitoring and early warning mechanisms means that quality problems are often only discovered in the later stages.

[0007] Resource waste: Due to the lack of effective data support, resource allocation is often not optimized, resulting in waste of materials and manpower;

[0008] Safety issues: Construction in complex environments or in severe weather conditions lacks effective monitoring methods, posing safety hazards.

[0009] Existing technologies utilize BeiDou high-precision positioning (up to centimeter-level) and Geographic Information System (GIS) to monitor parameters such as compaction trajectory, speed, and vibration frequency in real time, and aid construction with a visual interface, as exemplified by the application of the Zhonghaida BeiDou intelligent compaction system at Shenzhen Airport. However, this system suffers from insufficient data fusion, integrating only positioning and basic construction parameters while neglecting multi-dimensional environmental data such as meteorological and soil moisture content, leading to delayed adjustments in compaction strategies. Furthermore, the BeiDou signal is susceptible to interference in complex environments (such as strong vibrations or tunnels), causing positioning drift, as seen in the Ezhou Huahu Airport system. Moreover, the system has a low level of intelligence, relying primarily on manual sampling and experience-based judgment, and cannot achieve real-time quality monitoring across the entire cross-section.

[0010] Existing technologies utilize 5G communication, BeiDou positioning, and intelligent algorithms to achieve unmanned operation of rolling mills; however, such technologies suffer from a lack of standardization, with inconsistent data interfaces between different brands of equipment, leading to difficulties in cross-system collaboration; at the same time, their environmental adaptability is poor, and preset programs are unable to cope with sudden working conditions (such as equipment failure or sudden weather changes), requiring manual intervention for adjustment.

[0011] Existing technologies integrate BeiDou positioning, sensor data (compaction degree, vibration values), and Building Information Modeling (BIM); however, this technology suffers from data silos, with data from various subsystems (positioning, sensors, and BIM) scattered and lacking in-depth fusion analysis. Furthermore, impact compaction equipment is energy-intensive and noisy, failing to meet green construction requirements; a certain brand of impact roller exhibits such problems.

[0012] Existing technologies rely on manual operation or mechanical control with fixed parameters; such technologies are inefficient, have high labor costs, and the compaction quality depends on subjective experience, which can easily lead to unevenness. At the same time, they lack data recording functions, making it difficult to optimize the construction process.

[0013] While the aforementioned existing technologies have made some progress in positioning accuracy and unmanned operation, they still suffer from core defects such as insufficient multi-source data fusion, limited real-time performance, low level of intelligence, and lack of standardization, making it difficult to meet the needs of airport compaction operations for high-precision collaboration, dynamic optimization, and green construction. Summary of the Invention

[0014] To address the aforementioned shortcomings in existing technologies, this invention provides an airport construction compaction quality monitoring system and method based on BeiDou high-precision positioning, which solves the problems of poor real-time performance, limited accuracy, difficulty in data sharing, insufficient quality control, resource waste, and low security in existing airport construction compaction quality monitoring.

[0015] To achieve the above objectives, the technical solution adopted by the present invention is as follows: On the one hand, the present invention provides an airport construction compaction quality monitoring system based on Beidou high-precision positioning, including: a hardware subsystem and a software subsystem;

[0016] The hardware subsystem is used to acquire BeiDou positioning data and transmit the BeiDou positioning data to the software subsystem, acquire sensor data and fuse the BeiDou positioning data and sensor data to obtain fused data, transmit and display the data in real time, and transmit the input dynamic construction instructions to the road roller control system to execute the compaction instructions.

[0017] The software subsystem is used to obtain the initial compaction path and optimize it in real time based on the transmitted Beidou positioning data, predict the compaction degree based on the fused data, obtain the construction strategy and transmit dynamic construction instructions to the hardware subsystem, obtain the supplementary compaction instructions using the interpolation algorithm, input the supplementary compaction instructions to the hardware subsystem, generate a construction quality report and provide visual feedback.

[0018] The beneficial effects of this invention are as follows: By integrating BeiDou positioning, geographic information system technology, multi-source data fusion, and intelligent decision-making, this invention constructs an airport construction compaction quality monitoring system that achieves integrated management of precise positioning, dynamic optimization, real-time monitoring, and intelligent early warning. This optimizes the real-time performance of airport construction compaction quality monitoring, removes the limitations on accuracy, improves the efficiency of data sharing and the ability of quality control, saves resources, and improves security.

[0019] Furthermore, the hardware subsystem includes: a BeiDou high-precision positioning module, a multi-sensor array module, and a communication interaction module;

[0020] The Beidou high-precision positioning module is used to acquire centimeter-level positioning data of the road roller, fuse and store it through the cloud or edge server to obtain Beidou positioning data, and transmit the Beidou positioning data to the software subsystem;

[0021] The multi-sensor array module is used to monitor vibration frequency and acceleration, surface temperature of the compacted layer, and calculate the thickness of the compacted layer in real time to obtain sensor data;

[0022] The communication and interaction module is used to fuse BeiDou positioning data and sensor data, and upload the fused data to the cloud or edge server to realize data transmission and real-time display. It also transmits the input dynamic construction instructions to the road roller control system to execute the compaction instructions.

[0023] Furthermore, the BeiDou high-precision positioning module includes: a base station and a rover station;

[0024] The base station is deployed around the airport construction area to acquire centimeter-level positioning data of the road roller using a dual-frequency Beidou receiver and real-time dynamic differential technology.

[0025] The mobile station, installed on the top of the road roller's cab, integrates a multi-frequency antenna and inertial measurement elements. It communicates with the base station via a 5G sub-module, transmitting the road roller's centimeter-level positioning data to a cloud or edge server for fusion storage to obtain BeiDou positioning data. The BeiDou positioning data is then transmitted to the software subsystem.

[0026] The beneficial effects of the above-mentioned further solutions are as follows: By using BeiDou high-precision positioning, the present invention improves the high-precision coordination required for airport compaction operations and ensures the positioning accuracy of compaction quality monitoring.

[0027] Furthermore, the multi-sensor array module includes: a vibration sensor, an infrared temperature sensor, and a thickness monitoring submodule;

[0028] The vibration sensor is fixed inside the steel wheel of the road roller and is used to monitor the vibration frequency and acceleration.

[0029] The infrared temperature sensor is installed on the front bracket of the road roller and is used to monitor the surface temperature of the compacted layer.

[0030] The thickness monitoring submodule integrates BeiDou elevation data and a laser rangefinder to calculate the thickness of the compacted layer in real time.

[0031] The beneficial effects of the above-mentioned further solutions are as follows: By integrating multi-source data such as the surface temperature of the compacted layer, the vibration frequency and acceleration of the roller steel wheel, and the thickness of the compacted layer, the present invention can comprehensively perceive the construction status and accurately adjust the construction parameters.

[0032] Furthermore, the communication interaction module includes: a dual-mode communication terminal and an industrial tablet terminal;

[0033] The dual-mode communication terminal is built into the control box of the road roller and is used for data transmission. It consists of a 5G sub-module and a Beidou short message sub-module.

[0034] The industrial tablet terminal is installed on the operator's cab console to display the transmitted data in real time, acquire dynamic construction instructions, and transmit the dynamic construction instructions to the roller control system to execute the compaction instructions.

[0035] The beneficial effects of the above-mentioned further solutions are as follows: the present invention uses a 5G sub-module and a Beidou short message module to ensure data transmission, thereby improving the reliability of communication; and utilizes an industrial tablet terminal to display data in real time, making the construction status more accurate.

[0036] Furthermore, the software subsystem includes: a 3D visualization platform module, an intelligent decision-making module, and a quality assessment and feedback module;

[0037] The three-dimensional visualization platform module is used to generate a digital twin of the construction area based on the transmitted Beidou positioning data, obtain the initial compaction path, update the initial compaction path in response to the roller deviating from the predetermined path, changes in the construction area, or the appearance of obstacles, and display the construction progress and quality status based on visualization.

[0038] The intelligent decision-making module, based on the initial compaction path, generates the optimal compaction path using an improved ant colony algorithm based on fused data and building information model, and predicts the compaction degree using Kalman filter algorithm and long short-term memory neural network to obtain the predicted compaction degree. Based on the predicted compaction degree, the module dynamically optimizes the construction parameters, obtains the construction strategy, obtains dynamic construction instructions, and inputs the dynamic construction instructions to the industrial tablet terminal.

[0039] The quality assessment and feedback module is used to process the predicted compaction degree using the Kriging interpolation algorithm, generate a compaction quality heat map, mark abnormal areas based on the compaction quality heat map, form additional rolling blocks through a density clustering algorithm, obtain additional rolling instructions, input the additional rolling instructions to the industrial tablet terminal in the communication interaction module and the intelligent decision-making module, compare historical data with real-time data, generate a construction quality report and provide visual feedback.

[0040] The intelligent decision-making module, in response to receiving the compaction instruction, updates the construction strategy and optimizes the compaction operation using the updated construction strategy.

[0041] Furthermore, the expression for the predicted compaction degree is as follows:

[0042] ;

[0043] ;

[0044] in, Indicates the current time t The predicted compaction degree Indicates the past n Vibration frequency at each time step , Indicates the past n Crushing speed at each time step , Indicates the past n Compaction at each time step , Indicates the degree of compaction. All represent regression coefficients. This indicates the vibration frequency collected by the vibration sensor. This indicates the compaction speed calculated based on BeiDou positioning data. This indicates the error term.

[0045] The beneficial effects of the above-mentioned further solutions are as follows: This invention achieves full automation of the compaction operation process through Beidou high-precision positioning and intelligent path planning algorithm, eliminates human operation errors, and ensures full coverage of the compaction trajectory without any missed compaction.

[0046] By using Kalman filtering and long short-term memory neural networks for prediction, construction parameters are dynamically optimized to adapt to complex working conditions. By integrating multi-source data acquired by sensors, real-time feedback control is achieved, and construction parameters are automatically adjusted.

[0047] By using the geofencing technology of BeiDou positioning and geographic information system, the location of equipment and its surrounding environment can be monitored in real time, triggering collision warnings and emergency shutdowns, and establishing a real-time safety warning and collaborative operation mechanism.

[0048] By leveraging the two-way linkage between Kriging interpolation and building information modeling, a heat map of the compaction quality of the entire section is generated, replacing traditional spot checks and enabling real-time assessment of the compaction quality of the entire section.

[0049] On the other hand, the present invention provides a method for monitoring the compaction quality of airport construction based on BeiDou high-precision positioning, comprising the following steps:

[0050] S1. Use the Beidou high-precision positioning module to obtain centimeter-level positioning data of the road roller, and transmit the centimeter-level positioning data of the road roller to the cloud or edge server for fusion storage to obtain Beidou positioning data;

[0051] S2. Utilize multiple sensors to acquire sensor data including vibration data of the road roller steel wheel, temperature data of the compacted layer, and thickness data of the compacted layer. Fuse the sensor data with BeiDou positioning data to obtain fused data, and upload the fused data to the cloud or edge server.

[0052] S3. Based on BeiDou positioning data, a digital twin of the construction area is generated using a 3D visualization platform to achieve dynamic visualization of construction progress and quality status, and an initial compaction path is generated. In response to the roller deviating from the predetermined path, changes in the construction area, or the appearance of obstacles, the 3D visualization platform replans the initial compaction path.

[0053] S4. Based on the initial compaction path, obtain the optimal compaction path and predict the compaction degree. Based on the predicted compaction degree, obtain the construction strategy and dynamic construction instructions. Use the Kriging interpolation algorithm to generate a compaction quality heat map and mark abnormal areas to obtain additional compaction instructions. Update the construction strategy through additional compaction instructions to form updated dynamic construction instructions. Compare historical data with real-time data to generate a construction quality report and provide visual feedback.

[0054] S5. Utilize industrial tablet terminals to receive dynamic construction instructions, transmit these instructions to the road roller control system, execute compaction commands, and complete the monitoring of compaction quality during airport construction.

[0055] Further, S4 includes the following steps:

[0056] S401. Based on the initial compaction path, according to the fused data in the cloud or edge server and the building information model, the optimal compaction path is obtained by using the improved ant colony algorithm. The compaction degree is predicted by using the Kalman filter algorithm and the long short-term memory neural network. The construction parameters are dynamically optimized based on the predicted compaction degree to obtain the construction strategy and obtain dynamic construction instructions.

[0057] S402. Using the Kriging interpolation algorithm, the predicted compaction degree is processed to generate a compaction quality heat map. Abnormal areas in the compaction quality heat map are marked and formed into additional rolling blocks through a density clustering algorithm. Additional rolling instructions are obtained and input to the industrial flat panel terminal and intelligent decision module. In response to receiving additional rolling instructions, the construction strategy is updated to form updated dynamic construction instructions. Historical data and real-time data are compared to generate a construction quality report and provide visual feedback.

[0058] The beneficial effects of the above-mentioned further solutions are as follows: This invention integrates BeiDou positioning, sensor data, meteorological information and building information model, optimizes the global construction strategy through edge and cloud collaborative computing, and provides airport construction compaction quality monitoring with real-time performance, high efficiency and high precision.

[0059] Furthermore, the method of obtaining the optimal compaction path using the improved ant colony algorithm specifically involves:

[0060] The construction area is discretized to obtain a construction discrete network, and a set of key nodes is defined, including BeiDou coordinates, building information model priority, and compaction threshold.

[0061] Based on the construction discrete network, according to the set of key nodes, in the initialization stage, the weighted characteristics based on the building information model are assigned to the pheromone concentration, and a heuristic function for fusing distance and compaction difference is constructed.

[0062] Based on the heuristic function of the difference between fusion distance and compaction degree and the pheromone concentration, and combined with the weights of the pheromone and heuristic factor, the dynamic transition probability is obtained. Based on the dynamic transition probability, the path is selected from the set of nodes that meet the construction constraints to obtain the initial path.

[0063] Introduce penalty terms for path length and number of points with substandard compaction, set local updates, and set global updates to only strengthen the edges of the optimal path;

[0064] Based on the initial path, a two-layer pheromone update is performed using local and global updates. In response to excessive time overlap, an exponential decay model is used to apply repulsive pheromones, resulting in a path quality index that includes path length and the number of points with substandard compaction.

[0065] The optimal compaction path is obtained by responding to the maximum number of iterations or the continuous stability of the path quality index.

[0066] The beneficial effects of the above-mentioned further solutions are as follows: By combining Beidou positioning data, building information model and construction constraints, the present invention customizes and optimizes the classic ant colony algorithm to obtain an improved ant colony algorithm and generates the optimal compaction path for the road roller. Attached Figure Description

[0067] Figure 1 This is a system structure diagram of the present invention.

[0068] Figure 2 This is a structural diagram of each layer of the airport construction compaction quality monitoring system in this embodiment.

[0069] Figure 3 This is a data transmission diagram of each module in the airport construction compaction quality monitoring system in this embodiment.

[0070] Figure 4 This is a flowchart of the method in this embodiment. Detailed Implementation

[0071] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0072] Before describing this embodiment, the following terms will be explained:

[0073] GIS: Geographic Information System;

[0074] BIM model: Building Information Model;

[0075] DBSCAN: A density-based clustering algorithm;

[0076] LSTM Neural Network: Long Short-Term Memory Neural Network;

[0077] RTK technology: Real-time dynamic differential technology;

[0078] IMU: Inertial Measurement Unit;

[0079] API: Application Programming Interface;

[0080] GNSS antenna: Beidou external antenna.

[0081] Example 1

[0082] like Figure 1 As shown, the present invention provides an airport construction compaction quality monitoring system based on BeiDou high-precision positioning, comprising: a hardware subsystem and a software subsystem.

[0083] In this embodiment, the airport construction compaction quality monitoring system consists of two parts: a hardware subsystem and a software subsystem. It achieves fully automated control of the compaction operation process through multi-source data fusion and intelligent decision-making. The specific architecture is as follows:

[0084] The hardware subsystem is used to acquire BeiDou positioning data and transmit the BeiDou positioning data to the software subsystem, acquire sensor data and fuse the BeiDou positioning data and sensor data to obtain fused data, transmit and display the data in real time, and transmit the input dynamic construction instructions to the road roller control system to execute the compaction instructions.

[0085] The hardware subsystem includes: a BeiDou high-precision positioning module, a multi-sensor array module, and a communication and interaction module;

[0086] The BeiDou high-precision positioning module consists of a base station deployed around the airport construction area and a mobile station installed on the top of the road roller cab;

[0087] The base station uses a dual-frequency BeiDou receiver and provides centimeter-level positioning correction signals through RTK technology; the mobile station integrates a multi-frequency antenna and an IMU and communicates with the base station through a 5G sub-module.

[0088] In this embodiment, the multi-sensor array module includes: a vibration sensor fixed inside the steel wheel of the road roller, an infrared temperature sensor installed on the front support of the road roller, and a thickness monitoring sub-module integrating Beidou elevation data and a laser rangefinder, which are used to monitor vibration frequency and acceleration, surface temperature of the compacted layer, and calculate the thickness of the compacted layer in real time.

[0089] The communication interaction module consists of a 5G+BeiDou short message dual-mode communication terminal built into the control box of the road roller and an industrial tablet terminal installed on the operator's cab, which is responsible for data transmission and real-time display.

[0090] In this embodiment, the software subsystem is used to obtain the initial compaction path and optimize it in real time based on the transmitted BeiDou positioning data, predict the compaction degree based on the fused data, obtain the construction strategy and transmit dynamic construction instructions to the hardware subsystem, obtain the supplementary compaction instructions using the interpolation algorithm, input the supplementary compaction instructions to the hardware subsystem, generate a construction quality report and provide visual feedback.

[0091] The software subsystem includes: a 3D visualization platform module, an intelligent decision-making module, and a quality assessment and feedback module;

[0092] The three-dimensional visualization platform module adopts a GIS platform, imports the airport BIM model through the API interface, and overlays it with a high-precision GIS map to generate a three-dimensional digital twin. It also has an electronic fence function, which can trigger an audible and visual alarm when a road roller approaches a restricted area.

[0093] The intelligent decision engine uses an improved ant colony algorithm for path planning, supports conflict resolution in multi-machine collaborative operations, and achieves compaction degree prediction by integrating the regression equation of vibration frequency, rolling speed and compaction degree.

[0094] In this embodiment, the improved ant colony algorithm performs path planning as follows:

[0095] The airport construction area is discretized into a grid model, defining parameters including BeiDou coordinates and BIM priority. and compaction threshold The set of key nodes V;

[0096] The initialization phase assigns pheromone concentration Based on the weighted characteristics of BIM priority, a heuristic function is constructed to integrate the differences between distance and compaction degree. Ants are based on dynamic transfer probabilities Select a path from the node set K that satisfies the construction constraints. After the path is completed, perform a two-level pheromone update: the local update introduces the path length. and the number of points where compaction does not meet the standard Penalties; global updates only reinforce the optimal path. The edge;

[0097] For multi-machine collaboration, when the node time overlap exceeds the limit, a repulsive pheromone is applied through an exponential decay model, responding to the maximum number of iterations or path quality indicators. Continuous and stable;

[0098] The expression for initializing the pheromone concentration is as follows:

[0099] ;

[0100] in, Indicates the baseline pheromone concentration. This represents the priority weight coefficient. Indicates BIM priority;

[0101] The expression for the heuristic function is as follows:

[0102] ;

[0103] in, This represents the Euclidean distance calculated using BeiDou coordinates. Indicates key nodes i The BeiDou coordinates are specifically as follows: , Indicates key nodes j The BeiDou coordinates are specifically as follows: , Indicates the sensitivity coefficient to compaction difference. Indicates key nodes i The compaction threshold, Indicates key nodes j The compaction threshold;

[0104] The expression for the state transition function is as follows:

[0105] ;

[0106] in, Indicates time, and Both represent the weights of the pheromone and the heuristic factor. This represents the set of nodes that are currently accessible and satisfy construction constraints (such as not reaching the maximum number of compaction passes). This represents the currently accessible number that satisfies the construction constraints. One node;

[0107] The expression for the local pheromone dynamic update is as follows:

[0108] ;

[0109] in, Indicates the volatility coefficient, and , Represents a constant. Indicates the total path length. This indicates the number of points where the compaction degree does not meet the standard. Indicates the penalty coefficient;

[0110] The expression for the global pheromone dynamic update is as follows:

[0111] , ;

[0112] in, This represents the change in pheromone levels along the optimal path. Indicates the optimal path;

[0113] The expression for the multi-machine collaborative optimization is as follows:

[0114] ;

[0115] in, Indicates the conflict penalty coefficient. Indicates time repetition.

[0116] In this embodiment, a regression model is used to represent the nonlinear relationship between compaction degree and vibration frequency and rolling speed. The expression of the regression model is as follows:

[0117] ;

[0118] in, Indicates the degree of compaction. All of these represent regression coefficients, calibrated using experimental data. This indicates the vibration frequency collected by the vibration sensor. This indicates the compaction speed calculated based on BeiDou positioning data. This represents the error term, characterizing the influence of unmodeled factors.

[0119] To improve real-time performance, Kalman filtering is introduced into the regression equation to dynamically optimize the parameters and dynamically correct the model expression:

[0120] ;

[0121] in, Indicates the first The estimated regression coefficients at time t. Represents the Kalman gain matrix. This represents the real-time measured value of compaction obtained through sensors or the test pit method. The observation matrix is ​​represented by... The design matrix constituted;

[0122] By integrating historical construction data, an LSTM neural network is further used to construct a time-series prediction model. The expression of the prediction model is shown below:

[0123] ;

[0124] in, Indicates the current time t The predicted compaction degree Indicates the past n Vibration frequency at each time step , Indicates the past n Crushing speed at each time step , Indicates the past n Compaction at each time step .

[0125] In this embodiment, the quality assessment and feedback module generates a full-surface compaction quality distribution map based on the Kriging interpolation algorithm, marks abnormal areas, and forms additional compaction blocks using the DBSCAN clustering algorithm, then pushes additional compaction instructions; assuming a known set of measuring points... , Indicates the measured data points. n This represents the total number of measured data points and the corresponding compaction degree of the compaction degree observation. The expression for the core formula of Kriging interpolation is as follows:

[0126] ;

[0127] in, Represents the spatial coordinates of the point to be predicted. The point to be predicted in the regression model representing the degree of compaction The degree of compaction, The weights are represented by the weights, which are solved through an optimization problem. The expression for the optimization problem is as follows:

[0128] ;

[0129] ;

[0130] Based on the semi-mutation function, the solution takes the following form:

[0131] ;

[0132] in, This represents the semivariogram, characterizing spatial correlation. Represents the Lagrange multipliers. Indicates the first i Spatial location of each measured data point Indicates the first j Spatial location of each measured data point Indicates the coordinates of the point to be interpolated;

[0133] The semi-variogram model, using a Gaussian model, is expressed as follows:

[0134] ;

[0135] in, The semivariogram is the semivariogram between pairs of data points. This represents the distance between pairs of data points, indicating spatial distance. This refers to the nugget effect, i.e., random noise. This represents the sill value, i.e., the total spatial variability. This indicates the range, i.e., the distance at which the correlation disappears.

[0136] In this embodiment, as Figure 3 As shown, the hardware collaborative workflow is as follows: After the road roller starts, the Beidou mobile station receives the differential signal from the base station and calculates the high-precision position coordinates by combining it with IMU data; the vibration sensor and temperature sensor synchronously collect construction parameters and transmit them to the industrial tablet terminal; the thickness monitoring submodule integrates Beidou elevation data and a laser rangefinder to calculate the thickness of the compacted layer in real time and upload it to the industrial tablet terminal; in the communication interaction module, the dual-mode communication terminal and the 5G submodule upload data to the cloud server, and the Beidou short message module is used for emergency communication in areas without network access.

[0137] In this embodiment, regarding the software control logic, the GIS 3D visualization platform generates the initial compaction path and dynamically optimizes it; the dynamic optimization can be performed based on the real-time location information of the road roller and the construction progress.

[0138] In the GIS 3D visualization platform, if the road roller deviates from the predetermined path, the construction area changes, or obstacles block the way, the GIS platform can quickly replan the path to ensure the continuity and efficiency of the compaction operation.

[0139] In this embodiment, the intelligent decision-making module analyzes sensor data in real time and adjusts construction parameters, specifically as follows:

[0140] The intelligent decision-making module analyzes vibration frequency, rolling speed, surface temperature of the compacted layer, and thickness data collected by a multi-sensor array in real time. It uses a Kalman filter algorithm to suppress noise in parameters such as vibration frequency and rolling speed, and combines a Long Short-Term Memory (LSTM) network to predict the compaction degree in real time. When the predicted compaction degree is lower than a set threshold, the intelligent decision-making module dynamically optimizes construction parameters such as vibration frequency, rolling speed, and number of rolling passes based on the compaction degree prediction model and the current construction conditions, and obtains a construction strategy. The adjusted construction parameters (optimized construction parameters) are used to guide the roller control system to perform corresponding operations, drive the hydraulic motor and steering mechanism, and achieve a more accurate and efficient compaction effect.

[0141] The intelligent decision-making module is also based on an improved ant colony algorithm. It dynamically adjusts the compaction path of the road roller according to the real-time location of the road roller, the coordinates of the construction restricted area, and the conflict area of ​​multi-machine collaborative operation, so as to ensure the efficiency and precision of the construction process and improve the compaction quality.

[0142] The quality assessment module compares historical and real-time compaction data, uses the Kriging interpolation algorithm to generate a full-area compaction quality heat map, marks abnormal areas where the compaction degree is lower than a set threshold, and forms additional compaction blocks through the DBSCAN clustering algorithm. The additional compaction command is pushed to the industrial tablet terminal and simultaneously sent back to the intelligent decision engine to update the global construction strategy, dynamically optimize subsequent compaction operations, ensure the uniformity and stability of construction quality, and compares historical and real-time data to generate and provide feedback on the construction quality report.

[0143] To achieve real-time monitoring and feedback, this invention uses a GIS 3D visualization platform to display the construction progress and quality status in real time; it issues early warnings for abnormal areas and pushes out instructions for re-rolling, ensuring that the construction quality meets the standards.

[0144] In this embodiment, as Figure 2 As shown, the airport construction compaction quality monitoring system based on Beidou high-precision positioning of the present invention adopts a three-layer architecture, which clearly divides the hardware layer, communication layer and software layer.

[0145] Hardware layer: Includes Beidou high-precision positioning module, multi-sensor array module and industrial tablet terminal. Beidou high-precision positioning module and multi-sensor array module are responsible for collecting high-precision positioning and multi-sensor data, and transmitting them to the communication layer through industrial tablet terminal.

[0146] Communication layer: Data is uploaded to the cloud in real time via 5G module, and Beidou short message service + emergency communication support is integrated to realize data interaction and control command transmission;

[0147] Software layer: Based on a GIS 3D visualization platform, it provides functions such as electronic fence monitoring, intelligent decision-making, and predictive early warning, and also supports applications such as BIM model linkage and quality assessment;

[0148] The airport construction compaction quality monitoring system based on BeiDou high-precision positioning is a closed-loop system that integrates hardware acquisition, communication transmission, and software analysis, focusing on positioning, data processing, and intelligent applications.

[0149] In this embodiment, as Figure 3As shown, after the airport construction compaction quality monitoring system is launched, the Beidou high-precision positioning module acquires centimeter-level positioning data of the road roller in real time, transmits it to the cloud or edge server for fusion and storage, and then sends it to the GIS 3D visualization platform to generate a digital twin of the construction area. This enables dynamic visualization of construction progress and quality status within the GIS 3D visualization platform. Simultaneously, a multi-sensor array collects data on the vibration of the road roller's steel wheel, the temperature and thickness of the compacted layer, and uploads this data to the cloud after fusion with Beidou positioning data, providing data support for intelligent decision-making. The intelligent decision engine generates the optimal compaction path based on real-time data and the BIM model, dynamically adjusts conflict areas in multi-machine collaborative operations, uses Kalman filtering and LSTM neural networks to predict compaction degree, and outputs dynamic construction instructions to the industrial tablet terminal. Operators can monitor and interact in real time, and the industrial tablet terminal then transmits the dynamic construction instructions to the road roller control system to execute the compaction operation. The quality assessment and feedback module uses the Kriging interpolation algorithm to generate a compaction quality heat map, marking abnormal areas and... The DBSCAN clustering algorithm forms compaction blocks, and compaction instructions are pushed to the operator interface while simultaneously being fed back to the intelligent decision engine to update the construction strategy. During construction, if the roller approaches a restricted area or safety distance threshold, the electronic fence function of the GIS 3D visualization platform triggers an alarm and sends an emergency stop command. All interactive data is stored in the cloud-based construction management database for subsequent analysis and optimization. In terms of communication, the 5G submodule ensures data transmission, the BeiDou short message submodule enables redundant communication of key instructions in extreme environments, and the industrial tablet terminal supports manual input of instructions by the operator. After verification by the edge computing node, the instructions are synchronously updated to the cloud-based decision-making and GIS 3D visualization platform, ensuring the flexibility and robustness of system control. The entire system achieves closed-loop management of "data acquisition → fusion analysis → decision control → quality feedback." Each module, with the cloud as the core and edge computing nodes as local processing units, forms a hierarchical and collaborative intelligent monitoring network, achieving high-precision dynamic optimization control of airport compaction construction quality.

[0150] Example 2

[0151] In this embodiment, as Figure 4 As shown, this invention provides a method for monitoring the compaction quality of airport construction based on BeiDou high-precision positioning. The specific steps are as follows:

[0152] S1. Use the Beidou high-precision positioning module to obtain centimeter-level positioning data of the road roller, and transmit the centimeter-level positioning data of the road roller to the cloud or edge server for fusion storage to obtain Beidou positioning data;

[0153] S2. Utilize multiple sensors to acquire sensor data including vibration data of the road roller steel wheel, temperature data of the compacted layer, and thickness data of the compacted layer. Fuse the sensor data with BeiDou positioning data to obtain fused data, and upload the fused data to the cloud or edge server.

[0154] S3. Based on BeiDou positioning data, a digital twin of the construction area is generated using a 3D visualization platform to achieve dynamic visualization of construction progress and quality status, and an initial compaction path is generated. In response to the roller deviating from the predetermined path, changes in the construction area, or the appearance of obstacles, the 3D visualization platform replans the initial compaction path.

[0155] In this embodiment, S4, based on the initial compaction path, the optimal compaction path is obtained, and the compaction degree is predicted. Based on the predicted compaction degree, a construction strategy is obtained, dynamic construction instructions are generated, and a compaction quality heat map is generated using the Kriging interpolation algorithm, and abnormal areas are marked to obtain a supplementary compaction instruction. The construction strategy is updated based on the supplementary compaction instruction to form an updated dynamic construction instruction. Historical data and real-time data are compared to generate a construction quality report and provide visual feedback. The specific steps are as follows:

[0156] S401. Based on the initial compaction path, according to the fused data in the cloud or edge server and the building information model, the optimal compaction path is obtained by using the improved ant colony algorithm. The compaction degree is predicted by using the Kalman filter algorithm and the long short-term memory neural network. The construction parameters are dynamically optimized based on the predicted compaction degree to obtain the construction strategy and obtain dynamic construction instructions.

[0157] S402. Using the Kriging interpolation algorithm, the predicted compaction degree is processed to generate a compaction quality heat map. Abnormal areas in the compaction quality heat map are marked and formed into additional rolling blocks through a density clustering algorithm. Additional rolling instructions are obtained and input to the industrial flat panel terminal and intelligent decision module. In response to receiving additional rolling instructions, the construction strategy is updated to form updated dynamic construction instructions. Historical data and real-time data are compared to generate a construction quality report and provide visual feedback.

[0158] In this embodiment, the process of obtaining the optimal compaction path using the improved ant colony algorithm is as follows:

[0159] The construction area is discretized to obtain a construction discrete network, and a set of key nodes is defined, including BeiDou coordinates, building information model priority, and compaction threshold.

[0160] Based on the construction discrete network, according to the set of key nodes, in the initialization stage, the weighted characteristics based on the building information model are assigned to the pheromone concentration, and a heuristic function for fusing distance and compaction difference is constructed.

[0161] Based on the heuristic function of the difference between fusion distance and compaction degree and the pheromone concentration, and combined with the weights of the pheromone and heuristic factor, the dynamic transition probability is obtained. Based on the dynamic transition probability, the path is selected from the set of nodes that meet the construction constraints to obtain the initial path.

[0162] Introduce penalty terms for path length and number of points with substandard compaction, set local updates, and set global updates to only strengthen the edges of the optimal path;

[0163] Based on the initial path, a two-layer pheromone update is performed using local and global updates. In response to excessive time overlap, an exponential decay model is used to apply repulsive pheromones, resulting in a path quality index that includes path length and the number of points with substandard compaction.

[0164] The optimal compaction path is obtained by responding to the maximum number of iterations or the continuous stability of the path quality index.

[0165] In this embodiment, the industrial tablet terminal is used to receive dynamic construction instructions, which are then transmitted to the road roller control system to execute the compaction instructions and complete the monitoring of the compaction quality of the airport construction.

Claims

1. An airport construction compaction quality monitoring system based on BeiDou high-precision positioning, connected to a road roller control system, characterized in that, include: Hardware subsystems and software subsystems; The hardware subsystem is used to acquire BeiDou positioning data and transmit the BeiDou positioning data to the software subsystem, acquire sensor data and fuse the BeiDou positioning data and sensor data to obtain fused data, transmit and display the data in real time, and transmit the input dynamic construction instructions to the road roller control system to execute the compaction instructions. The hardware subsystem includes: a BeiDou high-precision positioning module, a multi-sensor array module, and a communication interaction module; The communication interaction module includes: a dual-mode communication terminal and an industrial tablet terminal; The dual-mode communication terminal is built into the control box of the road roller and is used for data transmission. It consists of a 5G sub-module and a Beidou short message sub-module. The 5G submodule is used for the routine transmission of high-bandwidth digital twin data and sensor data. The Beidou short message submodule responds to the interruption of the 5G signal link, automatically takes over and performs redundant transmission of emergency shutdown instructions and key re-rolling instructions in extreme environments, forming a primary and backup collaborative communication mechanism. The industrial tablet terminal is installed on the operator's cab console to display the transmitted data in real time, acquire dynamic construction instructions, and transmit the dynamic construction instructions to the roller control system to execute the compaction instructions. The software subsystem is used to obtain the initial compaction path and optimize it in real time based on the transmitted Beidou positioning data, predict the compaction degree based on the fused data, obtain the construction strategy and transmit dynamic construction instructions to the hardware subsystem, obtain the supplementary compaction instructions using the interpolation algorithm, input the supplementary compaction instructions to the hardware subsystem, generate a construction quality report and provide visual feedback. The software subsystem includes: a 3D visualization platform module, an intelligent decision-making module, and a quality assessment and feedback module; The three-dimensional visualization platform module is used to generate a digital twin of the construction area with real-time physical attributes and electronic fence based on the transmitted Beidou positioning data and fused data, obtain the initial compaction path, and trigger an alarm based on the real-time physical attributes and electronic fence status in the digital twin in response to the road roller deviating from the predetermined path, the construction area changing or obstacles appearing. The initial compaction path is replanned and updated based on this as a decision-making basis. At the same time, the construction progress and quality status are displayed visually. The intelligent decision-making module, based on the initial compaction path, generates the optimal compaction path using an improved ant colony algorithm based on fused data and building information model, and predicts the compaction degree using Kalman filter algorithm and long short-term memory neural network to obtain the predicted compaction degree. Based on the predicted compaction degree, the module dynamically optimizes the construction parameters, obtains the construction strategy, obtains dynamic construction instructions, and inputs the dynamic construction instructions to the industrial tablet terminal. The quality assessment and feedback module is used to perform spatial interpolation processing on the predicted compaction degree using the Kriging interpolation algorithm to generate a full-area surface compaction quality heat map, identify and mark abnormal scattered point areas where the compaction degree is lower than a set threshold, automatically cluster and merge adjacent abnormal scattered points into sheet-like continuous rolling blocks using the DBSCAN density clustering algorithm, and then generate directional rolling instructions for the continuous rolling blocks. The rolling instructions are input to the industrial tablet terminal and intelligent decision-making module in the communication interaction module, and the historical data and real-time data are compared to generate a construction quality report and provide visual feedback. The intelligent decision-making module, in response to receiving the compaction instruction, updates the construction strategy and optimizes the compaction operation using the updated construction strategy.

2. The airport construction compaction quality monitoring system based on BeiDou high-precision positioning according to claim 1, characterized in that, The Beidou high-precision positioning module is used to acquire centimeter-level positioning data of the road roller, fuse and store it through the cloud or edge server to obtain Beidou positioning data, and transmit the Beidou positioning data to the software subsystem; The multi-sensor array module is used to monitor vibration frequency and acceleration, surface temperature of the compacted layer, and calculate the thickness of the compacted layer in real time to obtain sensor data; The communication and interaction module is used to fuse BeiDou positioning data and sensor data, and upload the fused data to the cloud or edge server to realize data transmission and real-time display. It also transmits the input dynamic construction instructions to the road roller control system to execute the compaction instructions.

3. The airport construction compaction quality monitoring system based on BeiDou high-precision positioning according to claim 2, characterized in that, The BeiDou high-precision positioning module includes: a base station and a rover station; The base station is deployed around the airport construction area to acquire centimeter-level positioning data of the road roller using a dual-frequency Beidou receiver and real-time dynamic differential technology. The mobile station, installed on the top of the road roller's cab, integrates a multi-frequency antenna and inertial measurement elements. It communicates with the base station via a 5G sub-module, transmitting the road roller's centimeter-level positioning data to a cloud or edge server for fusion storage to obtain BeiDou positioning data. The BeiDou positioning data is then transmitted to the software subsystem.

4. The airport construction compaction quality monitoring system based on BeiDou high-precision positioning according to claim 2, characterized in that, The multi-sensor array module includes: a vibration sensor, an infrared temperature sensor, and a thickness monitoring submodule; The vibration sensor is fixed inside the steel wheel of the road roller and is used to monitor the vibration frequency and acceleration. The infrared temperature sensor is installed on the front bracket of the road roller and is used to monitor the surface temperature of the compacted layer. The thickness monitoring submodule integrates BeiDou elevation data and a laser rangefinder to calculate the thickness of the compacted layer in real time.

5. The airport construction compaction quality monitoring system based on BeiDou high-precision positioning according to claim 1, characterized in that, The expression for predicting compaction degree is as follows: in, Indicates the current time t The predicted compaction degree Indicates the past n Vibration frequency at each time step , Indicates the past n Crushing speed at each time step , Indicates the past n Compaction at each time step , Indicates the degree of compaction. All represent regression coefficients. This indicates the vibration frequency collected by the vibration sensor. This indicates the compaction speed calculated based on BeiDou positioning data. This indicates the error term.

6. A method for monitoring the compaction quality of airport construction based on BeiDou high-precision positioning, applied to an airport construction compaction quality monitoring system based on BeiDou high-precision positioning as described in any one of claims 1-5, comprising the following steps: S1. Use the Beidou high-precision positioning module to obtain centimeter-level positioning data of the road roller, and transmit the centimeter-level positioning data of the road roller to the cloud or edge server for fusion storage to obtain Beidou positioning data; S2. Utilize multiple sensors to acquire sensor data including vibration data of the road roller steel wheel, temperature data of the compacted layer, and thickness data of the compacted layer. Fuse the sensor data with BeiDou positioning data to obtain fused data, and upload the fused data to the cloud or edge server. S3. Based on BeiDou positioning data and fused data, a digital twin of the construction area with real-time physical attributes and electronic fence is generated using a 3D visualization platform to achieve dynamic visualization of construction progress and quality status, and an initial compaction path is generated. In response to the road roller deviating from the predetermined path, changes in the construction area, or the appearance of obstacles, an alarm is triggered based on the real-time physical attributes and electronic fence status in the digital twin, and the initial compaction path is replanned and updated based on this as a decision-making basis. S4. Based on the initial compaction path, the optimal compaction path is obtained, and the compaction degree is predicted. Based on the predicted compaction degree, the construction strategy is obtained, dynamic construction instructions are generated, and the Kriging interpolation algorithm is used to perform spatial interpolation processing on the predicted compaction degree to generate a full-area surface compaction quality heat map. Abnormal scattered point areas with compaction degree below a set threshold are identified and marked. The DBSCAN density clustering algorithm is used to automatically cluster and merge adjacent abnormal scattered points into sheet-like continuous supplementary compaction blocks, and then generate directional supplementary compaction instructions for the continuous supplementary compaction blocks. The construction strategy is updated through supplementary compaction instructions to form updated dynamic construction instructions. Historical data and real-time data are compared to generate a construction quality report and provide visual feedback. S5 utilizes an industrial tablet terminal to receive dynamic construction instructions. In response to a 5G signal link interruption, it automatically takes over the transmission of emergency shutdown instructions and critical compaction instructions under extreme conditions through the Beidou short message submodule. It then transmits the dynamic construction instructions to the roller control system, executes the compaction instructions, and completes the monitoring of the compaction quality of airport construction.

7. The airport construction compaction quality monitoring method based on BeiDou high-precision positioning according to claim 6, characterized in that, S4 includes the following steps: S401. Based on the initial compaction path, according to the fused data in the cloud or edge server and the building information model, the optimal compaction path is obtained by using the improved ant colony algorithm. The compaction degree is predicted by using the Kalman filter algorithm and the long short-term memory neural network. The construction parameters are dynamically optimized based on the predicted compaction degree to obtain the construction strategy and obtain dynamic construction instructions. S402. Using the Kriging interpolation algorithm, spatial interpolation processing is performed on the predicted compaction degree to generate a full-area surface compaction quality heat map. Abnormal scattered point areas with compaction degrees below a set threshold are identified and marked. The DBSCAN density clustering algorithm is used to automatically cluster and merge adjacent abnormal scattered points into sheet-like continuous rolling blocks. Then, directional rolling instructions are generated for the continuous rolling blocks. The directional rolling instructions are input to the industrial flat panel terminal and the intelligent decision module. In response to receiving the rolling instructions, the construction strategy is updated to form updated dynamic construction instructions. The historical data and real-time data are compared to generate a construction quality report and provide visual feedback.

8. The airport construction compaction quality monitoring method based on BeiDou high-precision positioning according to claim 7, characterized in that, The optimal compaction path obtained using the improved ant colony algorithm is specifically as follows: The construction area is discretized to obtain a construction discrete network, and a set of key nodes is defined, including BeiDou coordinates, building information model priority, and compaction threshold. Based on the construction discrete network, according to the set of key nodes, in the initialization stage, the weighted characteristics based on the building information model are assigned to the pheromone concentration, and a heuristic function for fusing distance and compaction difference is constructed. Based on the heuristic function of the difference between fusion distance and compaction degree and the pheromone concentration, and combined with the weights of the pheromone and heuristic factor, the dynamic transition probability is obtained. Based on the dynamic transition probability, the path is selected from the set of nodes that meet the construction constraints to obtain the initial path. Introduce penalty terms for path length and number of points with substandard compaction, set local updates, and set global updates to only strengthen the edges of the optimal path; Based on the initial path, a two-layer pheromone update is performed using local and global updates. In response to excessive time overlap, an exponential decay model is used to apply repulsive pheromones, resulting in a path quality index that includes path length and the number of points with substandard compaction. The optimal compaction path is obtained by responding to the maximum number of iterations or the continuous stability of the path quality index.

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