A highway maintenance and construction management system based on smart construction sites

Abstract

This invention relates to the field of engineering management data processing and discloses a highway maintenance and construction management system based on a smart construction site. The system includes: a multi-source data synchronous receiving module for parallel access to the positioning trajectories and electronic waybill data streams of operating machinery and material transport vehicles; a kinematic handshake determination module for calculating the speed vector difference between the two vehicles and generating a material supply docking logic locking time window when a preset kinematic coupling threshold is continuously met; a discrete load topology injection module for mapping the discrete load of the waybill to the actual working zone polygon generated by the trajectory within the time window; and a material throughput closed-loop verification module for calculating the ratio of load to working area to inversely determine the paving thickness and verify compliance. This invention utilizes kinematic feature logic to replace physical sensor connections, achieving non-contact closed-loop auditing of the quality of concealed works without hardware modifications, thus solving the regulatory blind spot problem caused by the separation of quantity and shape.

Description

Technical Field

[0001] This invention relates to a highway maintenance and construction management system based on smart construction sites, belonging to the field of engineering management data processing technology. Background Technology

[0002] Current highway pavement maintenance projects involve discrete processes such as milling, paving, and compaction. Project payments are settled based on the qualified work area and actual material consumption. Existing construction management relies on on-site supervision records or trajectory playback from general satellite positioning terminals, using vehicle location data as an auxiliary basis for quantity calculation. Highway maintenance is characterized by wide-area dispersion, multi-section collaboration, and the socialized leasing of operating machinery. The existing management model relying on single-dimensional location data has logical flaws; discrete location points only represent the spatial existence of machinery and cannot distinguish between actual working conditions and ineffective empty movement. This results in a lack of confidence in trajectory-based quantity calculations. Therefore, the industry is introducing vehicle-mounted weighing sensors. Physical sensing devices such as level gauges in hoppers or infrared thermometers determine the operational status through multi-source sensor data fusion. However, relying on hardware integration technology in engineering applications faces marginal cost and maintenance bottlenecks. The high temperature, strong vibration, and dust environment at asphalt construction sites cause precision sensors to drift and fail. In the face of a large number of short-term rental socialized operation vehicles, invasive hardware modification is not economically feasible and is not manageable. The stacking of physical data does not solve the problem of closed-loop verification of management logic. There are information silos between discrete weighing slip data, instantaneous temperature data, and continuous operation trajectories. There is a lack of an inherent verification mechanism for the authenticity of operation quality and engineering quantity based on basic spatiotemporal data logic without relying on dedicated sensors.

[0003] Existing software management strategies have regulatory blind spots. Information systems focus on pre-construction planning and macro-level material allocation, but lack penetrating supervision of micro-level behaviors during the operation process. For example, Chinese invention patent CN120125176A discloses a smart construction site highway construction management system. It establishes a BIM virtual prediction model to allocate monthly, weekly, and daily construction tasks and combines high-altitude inspection terminal to collect roadbed height data to verify construction quality. This system focuses on the selection of material delivery points and optimization of task division and scheduling. In the face of a large number of socialized rental machinery participating in maintenance, the management method based on the preset model is difficult to capture the nonlinear dynamic changes of the construction site in real time. Quality supervision relies on intermittent scanning by external drones and post-event verification by the single physical quantity of height difference. It is difficult to achieve continuous behavior auditing of the entire chain of single-vehicle mixture transportation-paving-compaction. When temperature sensors are lacking, visual or height data are used to reveal hidden quality defects such as temperature segregation of asphalt mixture due to excessive time delay operation.

[0004] Therefore, the technical problem to be solved by this invention is to establish a method for automated auditing of highway maintenance work volume and construction quality data that does not rely on the modification of dedicated physical sensors, but only utilizes basic positioning and general operational data, and achieves this through multi-dimensional spatiotemporal logical operations. Summary of the Invention

[0005] To address the problems mentioned in the background art, the technical solution of the present invention is as follows: A highway maintenance and construction management system based on a smart construction site, the system comprising:

[0006] The multi-source data synchronization receiving module is used to access the first positioning trajectory data stream of the operating machinery, the second positioning trajectory data stream of the associated material transport vehicle, and the electronic waybill data stream of the associated material transport vehicle in parallel under a unified time reference. Both the first positioning trajectory data stream and the second positioning trajectory data stream contain timestamps, geographic coordinates, and instantaneous velocity vectors.

[0007] The kinematic handshake determination module is used to perform vector difference operations within a sliding time window on the first positioning trajectory data stream and the second positioning trajectory data stream. When the difference in velocity vector modulus and the cosine of the velocity vector direction angle between the operating machinery and the associated material transport vehicle simultaneously and continuously meet the preset kinematic coupling threshold, a logical locking time window representing the material supply docking status is generated.

[0008] The discrete load topology injection module is used to extract discrete load values ​​from the electronic waybill data stream in response to the generation of the logical locking time window. It also uses the preset effective working width of the operating machinery to perform geometric buffering and union operations on the first positioning trajectory data stream within the logical locking time window to construct a continuous actual working zone polygon. The discrete load values ​​are then mapped to the actual working zone polygon as attribute parameters.

[0009] The material throughput closed-loop verification module is used to calculate the ratio of discrete load values ​​to the geometric area of ​​the polygon in the actual operation zone based on attribute parameters to obtain the inverted paving thickness. It also performs consistency logic verification on the deviation between the inverted paving thickness and the preset engineering design thickness, and outputs engineering quantity compliance certificate.

[0010] Preferably, the kinematic handshake determination module is specifically used for: extracting the velocity vectors of the operating machinery and the associated material transport vehicle at the same sampling moment; calculating the Euclidean distance between the two velocity vectors as the velocity vector modulus difference, and calculating the inverse cosine of the dot product of the two velocity vectors as the angle between the velocity vector directions; and determining the velocity vector modulus difference only when it is lower than a certain number of consecutive preset sampling points. And the angle between the velocity vector directions is lower than When this happens, the logic locks the time window.

[0011] Preferably, the system further includes a trajectory adaptive correction module, used to perform coordinate calibration on the first positioning trajectory data stream before the discrete load topology injection module constructs the actual working polygon. Specifically, the trajectory adaptive correction module is used to: calculate the trajectory curvature distribution sequence of the first positioning trajectory data stream and obtain the pre-stored design curvature distribution sequence of the road design centerline; perform cross-correlation matching operation on the trajectory curvature distribution sequence and the design curvature distribution sequence to determine the longitudinal mileage mapping relationship of the first positioning trajectory data stream relative to the road design centerline; based on the longitudinal mileage mapping relationship, construct an optimization function with lateral offset as the variable and minimizing the variance of the normal distance from the trajectory point to the road design centerline as the objective, and solve for the correction translation vector; and use the correction translation vector to perform a rigid coordinate transformation on the first positioning trajectory data stream.

[0012] Preferably, the material throughput closed-loop verification module is specifically used to close the corresponding polygonal area of ​​the actual working zone after accumulating a preset number of logical locking time windows, and calculate the inverse paving thickness according to the following formula: ,in, To invert and spread the thickness, The cumulative number of associated material transport vehicles, For the first Discrete load values ​​of a number of associated material transport vehicles. This represents the geometric area of ​​the polygonal region in the actual operation. This is the preset standard density of asphalt mixture.

[0013] Preferably, the system also includes a time-series performance verification module for performing implicit process quality backtracking. Specifically, the time-series performance verification module is used to obtain the first timestamp of the actual working polygon generated by the operating machinery, and the second timestamp of the compaction polygon that is spatially overlapping with the actual working polygon generated by the subsequent road rolling machinery; obtain the real-time environmental meteorological parameters of the work site, and calculate the maximum allowable operation time delay threshold under the current real-time environmental meteorological parameters based on the pre-stored asphalt mixture thermodynamic cooling model; calculate the time difference between the second timestamp and the first timestamp; when the time difference exceeds the maximum allowable operation time delay threshold, mark the corresponding spatially overlapping area as a time-sensitivity abnormal area, and remove the time-sensitivity abnormal area from the engineering quantity compliance certificate.

[0014] Preferably, the system further includes a vibration feature cleaning module, which is used to preprocess the first positioning trajectory data stream before the kinematic handshake determination module performs calculations. Specifically, the vibration feature cleaning module is used to acquire vibration frequency data collected by the built-in acceleration sensor of the vehicle terminal of the operating machinery; perform spectrum analysis on the vibration frequency data to identify whether there is a main frequency component that conforms to the preset mechanical operation characteristics; when it is detected that the vibration frequency data lacks a main frequency component, the first positioning trajectory data stream displays that the operating machinery is in a moving state, and the data in the corresponding time period is marked as invalid idle data and discarded.

[0015] Preferably, when constructing the actual work zone polygon, the discrete load topology injection module is also used to perform polygon Boolean operations, including: obtaining the geofence data of the pre-stored road design patch; calculating the area of ​​the intersection region between the actual work zone polygon and the road design patch, and the area of ​​the overflow region of the actual work zone polygon that exceeds the road design patch; only the area of ​​the intersection region is used as the effective work area, and the overflow region area is marked as invalid loss.

[0016] Preferably, the system also includes a multi-machine collaborative logic interlock module for verifying the integrity of construction procedures. Specifically, the multi-machine collaborative logic interlock module is used to: search for the existence of initial compaction trajectory polygons, intermediate compaction trajectory polygons, and final compaction trajectory polygons that have a spatial enclosure relationship with the actual work zone polygons within the same road design patch; verify whether the generation time of the initial compaction trajectory polygons, intermediate compaction trajectory polygons, and final compaction trajectory polygons strictly follows the preset process sequence logic; if any procedure trajectory polygon is missing or the process sequence logic is reversed, the generation of the engineering quantity compliance certificate is frozen.

[0017] Preferably, the system also includes an anomaly tracing index module, used to respond to anomalies where the inverted paving thickness exceeds the deviation tolerance. Specifically, the anomaly tracing index module is used to: use a timestamp index based on a logically locked time window to reverse lock the specific material transport vehicle identifier and the corresponding electronic waybill data stream that caused the anomaly; generate a quality traceability report containing the specific material transport vehicle identifier, the logically locked time window, and the anomaly inverted paving thickness value, and associate the quality traceability report with the attribute database of the polygon in the actual operation area.

[0018] Preferably, the multi-source data synchronization receiving module is also used to access the enhanced positioning data stream based on the differential positioning base station. The system also includes a signal confidence weighting module, used to monitor the carrier phase calculation status of the enhanced positioning data stream in real time. When the carrier phase calculation status is detected as a fixed solution, the weight of the enhanced positioning data stream is set to the first weight; when the carrier phase calculation status is detected as a floating-point solution or a single-point solution, the weight of the enhanced positioning data stream is reduced and fusion correction is performed using trajectory data calculated based on inertial navigation. Compared with the prior art, the beneficial effects of the present invention are:

[0019] 1. This invention establishes a dynamic geometric mapping model between discrete positioning data and continuous work surfaces. Based on the mechanical work width, it performs buffering and union operations on the construction trajectory sequence after state cleaning to reconstruct a two-dimensional actual work zone polygon. Based on the reconstructed polygon and the pre-set road design patch, it performs spatial Boolean operations to calculate the geometric coverage and locate missed work or boundary-crossing areas. The data processing logic transforms the audit of highway maintenance engineering quantities from relying on manual on-site monitoring or discrete point tracking to geometric topological relationship calculation and verification. It establishes an automated mechanism for generating compliant engineering quantity settlement vouchers based on mechanical physical motion trajectories, solving the technical gap that discrete trajectory data cannot be directly converted into closed engineering quantity vouchers.

[0020] 2. This invention establishes a logical coupling between material supply and construction consumption based on kinematic feature matching. By calculating the synchronization of the velocity vector and heading angle between the material transport vehicle and the paving machinery within the same time window, it identifies the physical docking status, responds to docking events, injects discrete load data from electronic waybills into the polygonal attributes of the continuous operation zone, calculates the material distribution rate per unit area, and constructs quantitative quality conservation constraints between the logistics data flow and the construction trajectory flow. It enables reverse auditing of average paving thickness and material consumption through data calculation, identifies abnormal working conditions where geometric coverage is compliant but material input is insufficient, and uses logical deduction to achieve control over hidden dimensions of the project.

[0021] 3. This invention achieves retrospective auditing of compaction quality through temporal environmental differential logic. It extracts the timestamp difference of the spatially overlapping area between the paving and rolling polygons, introduces real-time environmental meteorological parameters from the work site, dynamically generates a cooling time window threshold based on the thermodynamic decay law of materials, compares the actual operation time lag with the dynamic threshold, logically determines the temperature state of the compaction area, and marks the area exceeding the time lag as a process failure. It transforms the physical quality control requirements of asphalt temperature into calculable temporal logical constraints, and uses general positioning data and meteorological data to achieve automated verification of the timeliness of the entire road surface process, avoiding blind spots in quality supervision caused by the lack of comprehensive temperature detection methods. Attached Figure Description

[0022] Figure 1 This is a flowchart illustrating the closed-loop audit logic for construction quality based on multi-source data fusion, as described in this invention.

[0023] Figure 2 This is a comparison of the errors of the trajectory adaptive correction algorithm of the present invention under different road alignments;

[0024] Figure 3 This is a diagram illustrating the full-link architecture of the system that integrates data cleaning and logical topology construction in this invention. Detailed Implementation

[0025] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0026] This invention provides a highway maintenance and construction management system based on a smart construction site, including a multi-source data synchronous receiving module, a vibration feature cleaning module, a trajectory adaptive correction module, a kinematic handshake judgment module, a discrete load topology injection module, a material throughput closed-loop verification module, and a temporal performance verification module. Each module performs data interaction and logical interlocking based on a unified spatiotemporal reference. The multi-source data synchronous receiving module receives the positioning data stream of the operating machinery and, in conjunction with the vibration feature cleaning module, performs logical screening of the effective operating status. The system constructs a sequence containing the positioning coordinates of the operating machinery. Instantaneous velocity sequence and the triaxial acceleration sequence collected by the accelerometer built into the vehicle terminal. Composite data frames, processor for The data undergoes a Fast Fourier Transform (FFT) to convert the time-domain signal into a frequency-domain power spectrum. The system operates within a preset mechanical natural vibration frequency range, i.e. to Within the specified range, check if there are any background noise values ​​exceeding a preset threshold. The main frequency component, when the presence of the main frequency component is detected, and Within the preset effective operating speed range, i.e. to At that time, the system marks the data at the current timestamp as valid job data; otherwise, it marks it as invalid idle data and discards it, generating a cleaned sequence of valid job trajectories. The trajectory adaptive correction module is for A rigid registration based on geometric features is performed to correct positioning drift. This module relies on the consistency between the curvature distribution of the construction trajectory and the design curvature distribution of the road centerline. Perform second-order differential calculations on the coordinate sequence to generate a trajectory curvature distribution sequence. And retrieve the design curvature distribution sequence of the road centerline for the corresponding road segment from the engineering database. The system and Perform cross-correlation calculations and determine the longitudinal mapping deviation of the trajectory sequence on road mileage by searching for the peak position of the cross-correlation function. After completing the vertical alignment, the system is built with a horizontal offset. The processor uses the Levenberg-Marquardt algorithm to solve an optimization function with the objective of minimizing the variance of the normal distance from the trajectory point to the design centerline, taking the independent variable as the variable. This algorithm yields the globally optimal correction translation vector, which is then used to... A rigid coordinate transformation is performed on all coordinate points to generate a calibrated trajectory sequence. .

[0027] The kinematic handshake determination module and the discrete load topology injection module construct a material audit mechanism based on supply and demand coupling. The kinematic handshake determination module is connected in parallel to the calibration trajectory sequence of the paving machinery. Trajectory sequence of associated material transport vehicles and in the sliding time window Real-time calculation of the velocity vectors of the two vehicles and The system's physical docking determination logic is set as follows: when the difference in the magnitudes of the velocity vectors of the two vehicles... Less than the relative static threshold And the angle between the velocity vectors Less than the parallel threshold When a material supply docking event occurs, the system determines that a corresponding logical locking time window has been generated. In response to The discrete load topology injection module extracts the discrete load values ​​of the material transport vehicle from the electronic waybill system. At the same time, obtain the paver's position. Effective working width within the time period The system During the time period trajectory point execution The geometric buffer operation is performed to buffer the radius, and a Boolean union operation is performed on the generated micro-facets to construct the actual operating zone polygon corresponding to the train. and will The attribute parameters are injected into the polygon data structure; the material throughput closed-loop verification module performs inversion calculations based on the injected attribute parameters, and the system calculates the actual working zone polygon generated by a single material supply docking based on the principle of mass conservation. geometric area And according to the formula Calculate the inversion paving thickness ,in The preset standard density parameter for asphalt mixtures has a value of [value missing]. The system will With respect to the design thickness specified in the engineering design documents Compare and calculate the deviation rate. ,like Exceeding the tolerance threshold The system generates a material audit anomaly report containing the truck number, paving time, and deviation value, and links it to the electronic file for that road section. The time-series performance verification module uses the differential logic of spatiotemporal polygons to perform a full-domain backtracking of the timeliness of compaction operations. This module identifies the first timestamp of the paving operation polygon generated within the same work area. The second timestamp generated by the polygon of subsequent roller operation The system accesses real-time environmental meteorological parameters from the work site, including atmospheric temperature. With wind speed It also calls a pre-set asphalt mixture thermodynamic cooling model to calculate the maximum allowable operating time delay under the current environment. The cooling model is set at for and When it is less than level 3, for ;exist for hour, for The system calculates the actual operation time delay. And perform verification on the grid cells in the overlapping areas, for Greater than Areas with abnormal timeliness are marked as such and identified with specific color patches on the visualized engineering electronic map to guide core sampling operations during subsequent quality acceptance.

[0028] Example 1: In highway maintenance construction scenarios located in high-altitude mountainous areas with drastic terrain, the satellite positioning signal experiences nonlinear multipath drift due to mountain obstruction. Furthermore, the transportation of asphalt mixtures relies entirely on rented vehicles without dedicated weighing and position sensors. Under these conditions, traditional on-site monitoring faces challenges such as the inability to verify the amount of concealed work in real time and the difficulty in accurately locating the work surface in complex terrain. To address the technical problem of geometric distortion of the work surface caused by positioning signal drift, the trajectory adaptive correction module, based on a defined rigid registration procedure, corrects the received noisy valid work trajectory sequence. The processor performs calibration operations based on curvature features, calculating the second derivative of the trajectory points to generate a sequence of trajectory curvature distributions. And compared with the pre-stored design curvature distribution sequence of the road centerline for this section. By performing cross-correlation matching, the system leverages the rigid invariance of road geometry features to solve for lateral offsets. The optimization function for variables determines and applies a global correction translation vector, thereby accurately mapping the drift trajectory data to the coordinate system of the design patch without increasing differential positioning hardware, thus building a high-confidence spatial benchmark for subsequent engineering quantity calculations.

[0029] Building upon the solution to spatial positioning accuracy issues, and addressing the disconnect between logistics and construction data caused by the lack of IoT sensing devices for socialized vehicles, the kinematic handshake determination module and the discrete load topology injection module establish a logical connection using the kinematic characteristics of multi-vehicle collaboration. When a material transport vehicle approaches the paving machinery for unloading operations, the system analyzes the velocity vector data of both vehicles in parallel. When the difference in the velocity vector modulus between the two vehicles... Less than and included angle Less than The state in the sliding time window When the internal condition persists, the system determines that the physical material supply connection has been established and locks the time window. In response to this logical event, the system directly retrieves the discrete load value from the electronic waybill of the material transport vehicle. And injected as an attribute parameter into the paver. Based on the effective working width within the time period The generated actual job has polygons This allows for the precise mapping of discrete logistics quality data to continuous construction geometry data. Based on this mapping, the material throughput closed-loop verification module and the time-series performance verification module further perform logical inversion and compliance auditing on the quality of concealed works. The system calculates the actual operation area polygon... geometric area and using the formula The system calculates the average paving thickness for the area, directly identifying any thickness violations caused by insufficient material input. Simultaneously, the system incorporates real-time atmospheric temperature data. With wind speed The maximum permissible operation time delay was calculated using a thermodynamic cooling model of asphalt mixture. and the actual operation time delay Perform grid-by-grid comparison for Exceeding The system automatically marks the area as a temperature segregation risk zone. This embodiment demonstrates how the system can achieve dual closed-loop control of quantity and quality in highway maintenance projects through logical operations on multi-source spatiotemporal data without contact or hardware modification.

[0030] Example 2: This example aims to verify the actual performance and boundary conditions of the system of the present invention in performing engineering quantity auditing and quality backtracking under non-ideal signal environments and in the absence of dedicated sensors. The test platform is a 2.0-kilometer-long maintenance construction section of a secondary mountain highway. This section is adjacent to a steep mountain on one side, and there are satellite signal blockages and multipath effects. The test objects include an asphalt paver and five material transport trucks operating in a cycle. Neither the operating machinery nor the material transport vehicles are equipped with contact connection sensors or high-precision weighing equipment. They are equipped with a civilian-grade GNSS positioning module that outputs NMEA-0183 format data through a general serial port. The nominal horizontal positioning accuracy is 2.5 meters CEP, and the data sampling rate is 1Hz. As a comparison with the true value, a total station is deployed on the test site to perform millimeter-level tracking measurement of the construction trajectory, and the actual load data of each vehicle is recorded by the electronic weighbridge that has been certified by the national metrology. The test also examines the threshold value of the velocity vector modulus difference, a core parameter in the kinematic handshake judgment module. The setting follows the following engineering decision-making logic: the determination of this parameter is limited by the velocity noise floor of the GNSS receiver in a dynamic environment. Micro-vibration interference during paver operation The essence of the technical trade-off lies in balancing the stability of the material supply status lock with the interference rejection rate of nearby non-operating vehicles. Based on the Doppler velocity measurement principle, the civilian GNSS module... Usually in to The interval, in order to comply with the 3-Sigma statistical criterion and reserve a vibration tolerance, is set as follows: and ,in The minimum relative speed for non-connecting vehicles is determined based on pre-test data from the field. This represents the optimal operating point for this parameter under current hardware conditions.

[0031] During the test, the system operated at full load. The multi-source data synchronous receiving module received the original positioning data streams from the paver and the material transport vehicle in real time. To simulate extreme working conditions and verify the effectiveness of the algorithm, the received original coordinate sequences were... Active superposition of standard deviations Gaussian white noise was used to simulate severe signal drift. The experimental design incorporated a multi-dimensional control system: Control group 1 used only raw GPS data and followed conventional measurement methods without trajectory correction and kinematic handshake logic; the present invention's sample group fully enabled trajectory adaptive correction and supply-demand coupling audit logic; and the out-of-range control group relaxed the velocity vector difference threshold to... The system operates under various conditions to verify the rationality of parameter boundaries. It performs streaming processing on the input data stream. In the sample group of this invention, the trajectory adaptive correction module extracts the curvature distribution characteristics of the noisy trajectory, matches it with the curvature sequence of the design centerline through cross-correlation calculations, calculates the correction translation vector, and performs a rigid transformation on the coordinates. The kinematic handshake judgment module monitors the synchronization of the velocity vector within the sliding time window. When it detects that the difference between the velocity vectors of the paver and the material transport vehicle is consistently lower than a certain value, it will correct the error. And the included angle is less than At that time, the logic locks the time window and sets the waybill weight. (Irregular measured values) are injected into the polygon of the work zone generated during this period.

[0032] Referring to Table 1, under strong noise interference, the area calculation error of control group 1 is as high as [missing information]. Due to the lack of supply and demand coupling logic, the inversion thickness cannot be calculated. This invention uses geometric feature registration to suppress area calculation errors within [a certain range]. It successfully outputs an inversion thickness that is highly consistent with the design value, with an error of only [missing information]. It is worth noting that the data from the out-of-range control group shows an inflection point in nonlinear performance: when the threshold drops from... Increase to At that time, although the coverage of physical docking increased slightly, the inversion thickness error deteriorated sharply. This is because an overly wide threshold incorrectly identifies several instances of material transport vehicles waiting on the side or following at low speed as material supply events, resulting in materials being incorrectly injected into the wrong working area, thus logically diluting the calculated thickness.

[0033] Table 1: Comparative Experimental Data on the Effectiveness of Quantity Auditing under Different Parameter Settings

[0034]

[0035] The test results confirm that, without the need to deploy expensive differential base stations and dedicated weighing sensors, high-precision engineering quantity auditing can be achieved by relying on basic positioning data and the geometric kinematic dual verification logic constructed in this invention, even in environments with strong interference. In particular, the setting of the velocity vector coupling threshold has a clear performance boundary. An excessively large threshold will lead to the loss of the specificity of the logic connection, thereby compromising the closed-loop accuracy of material auditing.

[0036] Example 3: This example combines Figures 1 to 3 This document describes a highway maintenance and construction management system based on a smart construction site, such as... Figure 1As shown, the logical flow of this system begins with the positioning trajectory and vibration data generated by the operating machinery, as well as the positioning trajectory and electronic waybill generated by the associated material transport vehicle. These raw data are fed into the multi-source data synchronous receiving module for parallel access, and then diverted to the vibration feature cleaning module to remove invalid empty data based on frequency domain analysis. At the same time, the data enters the trajectory adaptive correction module to perform rigid coordinate transformation based on curvature distribution. The processed data enters the kinematic handshake judgment module to calculate the vector difference and generate the material supply docking logic locking time window. The discrete load topology injection module maps the waybill load to the actual working zone polygon. The polygon attributes are verified by the material throughput closed-loop verification module to invert the paving thickness and perform consistency logic verification. On the other hand, the time series performance verification module performs maximum allowable operation time delay threshold backtracking. Finally, the outputs of both are combined to generate an engineering quantity compliance certificate containing thickness inversion and timeliness marking.

[0037] like Figure 2 As shown, the vertical axis represents the positioning error in meters (m). The legend distinguishes between the error before and after calibration. The horizontal axis covers three typical scenarios: straight road sections, curved road sections, and complex road sections. In straight road sections, the error before calibration was 3m, which decreased to 1m after calibration. In curved road sections, the error before calibration rose to nearly 6m, but remained around 1m after calibration. In complex road sections, the error before calibration soared to over 8m, but could still be suppressed to within 2m after calibration. Figure 3 As shown in the diagram, the system architecture is geared towards generating automated audit vouchers for engineering quantity and quality compliance verification. The multi-source sensing access section on the left covers mechanical and vehicle positioning trajectory streams, electronic waybill data streams, and enhanced positioning and inertial navigation fusion data. These input data streams undergo signal confidence weighting, trajectory adaptive correction based on curvature registration, and vibration feature cleaning based on FFT in the data cleaning and correction branch below. Then, they enter the logical topology construction stage in the upper branch, sequentially performing kinematic handshake judgment based on vector difference, discrete load topology injection, and polygon reconstruction of the actual operation area. Finally, in the closed-loop audit inversion branch on the right, quality tracing is performed through anomaly tracing index, time series performance verification is performed through thermodynamic model, and material throughput closed-loop verification is performed, thereby completing the closed-loop data processing of the entire chain.

[0038] Example 4: Addressing the quality black box problem caused by the mismatch between trajectory drift and the timeliness of temperature control during highway maintenance, this example, based on the aforementioned general architecture, constructs a targeted repair scheme adapted to complex terrain and climate environments by embedding a high-order curvature registration algorithm and a dynamic thermodynamic constraint model. To address the registration challenge of trajectory data under complex alignments, the trajectory adaptive correction module performs a feature matching operation based on discrete curvature sequences. The processor processes the received original trajectory coordinate sequence... The system performs equidistant resampling to generate a discrete point set with a sampling interval of 1.0 meter. Based on the principle of differential geometry, the system calculates the local curvature value of each point in the discrete point set, generating a trajectory curvature distribution sequence that can characterize the geometric fingerprint of the operation trajectory. Simultaneously, the design curvature distribution sequence of the road centerline for the corresponding road segment is extracted from the engineering design database. processor and Perform a sliding window cross-correlation operation and determine the longitudinal mileage deviation of the trajectory sequence relative to the designed route by searching for the hysteresis corresponding to the maximum cross-correlation coefficient. After completing the longitudinal anchoring, construct the structure with lateral offset. and rotation angle To optimize the objective function of the variables, which aims to minimize the sum of squared normal distances from the trajectory point set to the design centerline, the processor uses the Gauss-Newton iterative method to solve this nonlinear least squares problem, calculates the globally optimal rigid transformation matrix, and applies this matrix to accurately map the original drift trajectory to the design coordinate system, eliminating spatial geometric distortion caused by multipath effects. When the design curvature distribution sequence of the road design centerline is of length... If the variance within a 100-meter sliding window is lower than the preset linearity threshold... When the trajectory adaptive correction module pauses the cross-correlation matching calculation, locks the correction translation vector obtained from the most recent curve segment calculation, and uses the locked correction translation vector as a reference. Combined with the heading angle change rate data output by the vehicle inertial navigation unit, it performs linear extrapolation calibration on the coordinates of the trajectory points of the subsequent straight segments. The recursive process continues until the variance of the design curvature distribution sequence is detected to be higher than the linear judgment threshold again, and then the real-time correction logic based on curvature cross-correlation matching is restored.

[0039] To address the issue of determining the compaction effectiveness of asphalt mixtures under varying temperature and high wind conditions, the time-series performance verification module abandons the static threshold lookup method and adopts a dynamic time-delay threshold calculation logic based on thermodynamic differential equations. The system also receives real-time ambient temperature data from the vehicle-mounted meteorological terminal. With wind speed Data stream, combined with the discharge temperature of the asphalt mixture. With the target paving thickness A real-time cooling rate model is constructed based on Newton's law of cooling, and this model defines a cooling rate constant. With wind speed It is positively correlated with thickness. The correlation is negative, and the system dynamically calculates the temperature of the mixture as it drops to the minimum compaction temperature. The required critical time, i.e. the maximum permissible job delay Calculate the maximum allowable job delay. At that time, the cooling rate constant of the thermodynamic cooling model of asphalt mixture Using empirical formulas Calculate, where, To collect real-time wind speed for vehicle-mounted weather terminals, The electronic waybill specifies the preset paving thickness; and To calibrate the thermophysical property constants based on the thermal diffusivity of the mixture, the following example describes modified asphalt concrete. The value is 0.045. The value is set to 0.18. Real-time meteorological parameters are substituted into the formula at preset time intervals, such as 30 seconds, to dynamically update the cooling rate constant of the current grid cell. The result is obtained by solving Newton's equation of cooling. Numerical values, for example, when the wind speed is And the temperature is The system calculates the strong convection sections. The system automatically reduces the time from 15 minutes under standard conditions to 8.5 minutes, calculating the actual operation time delay for each spatial grid cell in the overlapping area of ​​the paving and compaction tracks. When the mesh cell satisfies When the logical condition is met, the system determines that the compaction process in that area meets temperature compliance requirements. Through the above-mentioned algorithm calibration based on physical characteristics and dynamic constraints based on thermodynamic logic, the system identifies three areas in this high-difficulty section where local over-time compaction is caused by mechanical failure. Although these areas appear to be geometrically complete, core sampling verification shows that the average pavement porosity of these areas marked as time-sensitive areas is [value missing]. Higher than normal .

[0040] Example 5: To address the potential parameter compatibility risks that may arise when the system is first deployed in new asphalt materials or special climatic areas, this example establishes a standardized pre-deployment calibration procedure. Before formally conducting the engineering quantity audit, a series of controlled calibration tests are conducted to establish benchmark values ​​for key algorithm parameters, thereby eliminating the impact of environmental differences on audit accuracy. Before the system is connected to the work site, on-site calibration of the GNSS receiver noise floor is performed. The vehicle-mounted positioning terminal to be used is placed in an open area, and static positioning data is continuously collected for no less than one hour. The processor calculates the standard deviation of this static data sequence in the horizontal direction. Based on this, a basic noise threshold was set in the kinematic handshake judgment module. A straight test section of 200 meters in length was selected, and the paver was controlled to travel at a constant speed according to the standard operating speed. At the same time, the material transport vehicle was arranged to perform multiple approach and accompanying actions at different distances and angles. The system recorded the distribution characteristics of the velocity vector difference between the two vehicles during this dynamic process and statistically analyzed the minimum velocity modulus difference under non-handshake accompanying state. ,based on The criterion sets the speed difference threshold for determining supply and demand coupling as follows:

[0041] For the environmental adaptability calibration of the asphalt mixture thermodynamic model, the system performs a correction of the cooling rate constant based on measured data. During the trial paving phase on the first day, three different wind speed periods were selected, and the actual surface temperature of the mixture was measured every 2 minutes using a handheld high-precision infrared thermometer, obtaining no fewer than 3 complete temperature decay curves. The system then incorporated the wind speed data collected on-site. Temperature The measured temperature sequence is input into a pre-set Newtonian cooling model, and the combined cooling rate constant under the current material and environmental combination is obtained by backfitting using the least squares method. The calibrated constant is embedded into the timing performance verification module and used to dynamically calculate the maximum allowable operation delay during subsequent operations. The core parameters, through the aforementioned pre-calibration procedures, enable the system to automatically adapt to engineering environments under different latitudes and longitudes, seasons, and material ratios.

[0042] Example 6: Addressing the issue of deviations in quantity auditing caused by the dynamic uncertainty of the working face's geometric parameters and poor time window adaptability under weak signal conditions during asphalt paving operations in variable-width sections, this example constructs a targeted solution integrating a dynamic mileage lookup mechanism and an adaptive signal confidence adjustment procedure. To mitigate the impact of signal quality fluctuations on the stability of kinematic handshake determination, the kinematic handshake determination module incorporates an adaptive window adjustment procedure based on signal confidence. The processor reads the horizontal accuracy factor output by the GNSS receiver in real time. Data flow, and according to the formula The length of the logical locking time window at the current moment is dynamically calculated, where, As the base time window, The preset adjustment coefficient is used when signal quality deterioration is detected. When the signal strength increases, the system automatically extends the time window to reduce the interference of random noise on the velocity vector difference calculation by increasing the number of sampling points. This ensures that the statistical accuracy of the material supply docking status determination in a weak signal environment is not lower than the preset confidence level. The signal confidence weighting module uses an extended Kalman filter (EKF) framework for data fusion and monitors the carrier phase calculation status of the satellite positioning receiver in real time. When the status flag is a fixed solution, the observation noise covariance matrix is... Variance term of position measurement Set to nominal accuracy value like .

[0043] When the status flag changes to a floating-point solution or a single-point solution, the horizontal precision factor is output in real time. Dynamically adjust the variance term of position measurement, according to the formula Calculation, where To pre-determine the variance inflation coefficient, such as a value of 10.0, the satellite positioning data is reduced by increasing the observation noise covariance value. During the Kalman filter state update phase, the gain weight is adjusted to make the system trajectory output tend towards the inertial navigation prediction value. Addressing the dynamic determinism of the geometric parameters of the variable-width working face, the discrete load topology injection module abandons the static logic of a pre-determined fixed width and instead executes a mileage index lookup mechanism based on the design model. The system utilizes the longitudinal projection mileage of the calibrated trajectory points on the road centerline output by the trajectory adaptive correction module. Using the unique index key to access the pre-stored road design database, the processor extracts the design pavement width corresponding to that mileage point in real time. And as the instantaneous effective working width, it participates in the actual working polygon. Through this dynamic mapping mechanism, the system performs geometric reconstruction operations, locking the area calculation accuracy of the variable-width segment within the geometric constraints of the design model.

[0044] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0045] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A highway maintenance and construction management system based on smart construction sites, characterized in that, The system includes: The multi-source data synchronization receiving module is used to access the first positioning trajectory data stream of the operating machinery, the second positioning trajectory data stream of the associated material transport vehicle, and the electronic waybill data stream of the associated material transport vehicle in parallel under a unified time reference. Both the first positioning trajectory data stream and the second positioning trajectory data stream contain timestamps, geographic coordinates, and instantaneous velocity vectors. The kinematic handshake determination module is used to perform vector difference operations within a sliding time window on the first positioning trajectory data stream and the second positioning trajectory data stream. When the difference in velocity vector modulus and the cosine of the velocity vector direction angle between the operating machinery and the associated material transport vehicle simultaneously and continuously meet the preset kinematic coupling threshold, a logical locking time window representing the material supply docking status is generated. The discrete load topology injection module is used to extract discrete load values ​​from the electronic waybill data stream in response to the generation of the logical locking time window. It also uses the preset effective working width of the operating machinery to perform geometric buffering and union operations on the first positioning trajectory data stream within the logical locking time window to construct a continuous actual working zone polygon. The discrete load values ​​are then mapped to the actual working zone polygon as attribute parameters. The material throughput closed-loop verification module is used to calculate the ratio of discrete load values ​​to the geometric area of ​​the polygon in the actual operation zone based on attribute parameters to obtain the inverted paving thickness. It also performs consistency logic verification on the deviation between the inverted paving thickness and the preset engineering design thickness, and outputs engineering quantity compliance certificate.

2. The highway maintenance and construction management system based on a smart construction site according to claim 1, characterized in that, The kinematic handshake determination module is specifically used for: extracting the velocity vectors of the operating machinery and the associated material transport vehicle at the same sampling moment; calculating the Euclidean distance between the two velocity vectors as the velocity vector modulus difference, and calculating the inverse cosine of the dot product of the two velocity vectors as the angle between their directions; and determining the velocity vector modulus difference only when it is lower than a certain number of consecutive preset sampling points. And the angle between the velocity vector directions is lower than When this happens, the logic locks the time window.

3. The highway maintenance and construction management system based on a smart construction site according to claim 1, characterized in that, The system also includes a trajectory adaptive correction module, which performs coordinate calibration on the first positioning trajectory data stream before the discrete load topology injection module constructs the actual working polygon. Specifically, the trajectory adaptive correction module is used to: calculate the trajectory curvature distribution sequence of the first positioning trajectory data stream and obtain the pre-stored design curvature distribution sequence of the road design centerline; perform cross-correlation matching operation on the trajectory curvature distribution sequence and the design curvature distribution sequence to determine the longitudinal mileage mapping relationship of the first positioning trajectory data stream relative to the road design centerline; based on the longitudinal mileage mapping relationship, construct an optimization function with lateral offset as the variable and minimizing the variance of the normal distance from the trajectory point to the road design centerline as the objective, and solve for the correction translation vector; and use the correction translation vector to perform a rigid coordinate transformation on the first positioning trajectory data stream.

4. The highway maintenance and construction management system based on a smart construction site according to claim 1, characterized in that, The material throughput closed-loop verification module is specifically used to close the corresponding polygonal area of ​​the actual work zone after accumulating a preset number of logical locking time windows, and calculate the inverse paving thickness according to the following formula: ,in, To lay out the thickness for inversion, The cumulative number of associated material transport vehicles, For the first Discrete load values ​​of a number of associated material transport vehicles. This represents the geometric area of ​​the polygonal region in the actual operation. This is the preset standard density of asphalt mixture.

5. A highway maintenance and construction management system based on a smart construction site according to claim 1, characterized in that, The system also includes a timing performance verification module, which is used to perform implicit process quality backtracking. Specifically, the timing performance verification module is used to obtain the first timestamp of the actual working zone polygon generated by the operating machinery, and the second timestamp of the compaction operation polygon that is spatially overlapping with the actual working zone polygon generated by the subsequent road rolling machinery. The system acquires real-time environmental meteorological parameters at the work site and calculates the maximum allowable work delay threshold under the current real-time environmental meteorological parameters based on a pre-stored thermodynamic cooling model of asphalt mixture. Calculate the time difference between the second timestamp and the first timestamp; When the time difference exceeds the maximum allowable operation time delay threshold, the corresponding spatial overlap area is marked as a time-sensitive abnormal area, and the time-sensitive abnormal area is removed from the engineering quantity compliance certificate.

6. The highway maintenance and construction management system based on a smart construction site according to claim 1, characterized in that, The system also includes a vibration feature cleaning module, which is used to preprocess the first positioning trajectory data stream before the kinematic handshake determination module performs the calculation. Specifically, the vibration feature cleaning module is used to obtain vibration frequency data collected by the built-in acceleration sensor of the vehicle terminal of the operating machinery. Perform spectrum analysis on the vibration frequency data to identify whether there is a dominant frequency component that matches the preset mechanical operation characteristics; when the vibration frequency data is found to lack a dominant frequency component, make the first positioning trajectory data stream show that the operating machinery is in a moving state, mark the data of the corresponding time period as invalid idle data and discard it.

7. A highway maintenance and construction management system based on a smart construction site according to claim 1, characterized in that, When constructing the actual work zone polygon, the discrete load topology injection module is also used to perform polygon Boolean operations, including: obtaining the geofence data of the pre-stored road design patch; calculating the area of ​​the intersection region between the actual work zone polygon and the road design patch, and the area of ​​the overflow region of the actual work zone polygon that exceeds the road design patch; only the area of ​​the intersection region is used as the effective work area, and the overflow region area is marked as invalid loss.

8. A highway maintenance and construction management system based on a smart construction site according to claim 1, characterized in that, The system also includes a multi-machine collaborative logic interlock module for verifying the integrity of construction procedures. Specifically, the multi-machine collaborative logic interlock module is used to: search for the existence of initial compaction trajectory polygons, intermediate compaction trajectory polygons, and final compaction trajectory polygons that have a spatial enclosure relationship with the actual work zone polygons within the same road design patch; verify whether the generation time of the initial compaction trajectory polygons, intermediate compaction trajectory polygons, and final compaction trajectory polygons strictly follows the preset process sequence logic; if any procedure trajectory polygon is missing or the process sequence logic is reversed, the generation of the engineering quantity compliance certificate is frozen.

9. A highway maintenance and construction management system based on a smart construction site according to claim 1, characterized in that, The system also includes an anomaly tracing index module, which is used to respond to anomalies where the inverted paving thickness exceeds the deviation tolerance. Specifically, the anomaly tracing index module is used to: use a timestamp index based on a logically locked time window to reverse lock the specific material transport vehicle identifier and the corresponding electronic waybill data stream that caused the anomaly; generate a quality traceability report containing the specific material transport vehicle identifier, the logically locked time window, and the anomaly inverted paving thickness value, and associate the quality traceability report with the attribute database of the polygon in the actual operation area.

10. A highway maintenance and construction management system based on a smart construction site according to claim 1, characterized in that, The multi-source data synchronization receiving module is also used to access the enhanced positioning data stream based on differential positioning base stations. The system also includes a signal confidence weighting module, which is used to monitor the carrier phase calculation status of the enhanced positioning data stream in real time. When the carrier phase calculation status is detected to be a fixed solution, the weight of the enhanced positioning data stream is set as the first weight. When the carrier phase calculation status is detected to be a floating-point solution or a single-point solution, the weight of the enhanced positioning data stream is reduced and the trajectory data calculated based on inertial navigation is used for fusion correction.

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