A highway asphalt pavement construction data analysis processing system

Abstract

The application relates to the technical field of intelligent construction of road engineering, and discloses a highway asphalt pavement construction data analysis processing system. The system creates a material state vector containing static attributes, dynamic states and process histories, carries out digital modeling on asphalt mixture and anchors the asphalt mixture to a three-dimensional coordinate of a pavement, adopts a heat transfer model, and updates and forwardly simulates a predicted temperature of a target vector at a future interception time of a road roller. Meanwhile, the system calculates a dynamic compactability window according to compaction history and material types, compares the predicted temperature with the window, generates feedforward control instructions of standard, priority or waiting operation, and converts the feedforward control instructions into visual guidance to be sent to a vehicle-mounted terminal, so that prospective control is realized. The application realizes the change of construction control from passive lag to active feedforward, improves the fineness of a compaction process, and establishes a reliable digital quality tracing mechanism.

Description

Technical Field

[0001] This invention relates to the field of intelligent construction technology for road engineering, specifically to a data analysis and processing system for highway asphalt pavement construction. Background Technology

[0002] The compaction quality of highway asphalt pavement is a key factor determining its service life and road performance, and the core of compaction work lies in the precise control of the temperature of the asphalt mixture.

[0003] In current construction practice, the selection of compaction timing relies on the field experience of roller operators and handheld temperature measuring devices. This control method inherently has a lag. Operators typically only assess the temperature after arriving at the work area, by which time the temperature of the asphalt mixture has already begun to decay, causing them to miss the theoretically optimal compaction window when making a decision. Due to the lack of forward-looking prediction of temperature decay trends, construction control is passive, making it difficult to proactively and in advance plan the optimal compaction path and timing, thus affecting the accuracy and initiative in selecting the construction timing.

[0004] Furthermore, existing process control uses fixed, empirical temperature ranges as compaction standards. However, these standards, when formulated, failed to fully consider the material properties of different asphalt mixtures (such as gradation type and modifier type) and the differentiated temperature window requirements of different compaction stages (such as initial compaction and secondary compaction). This uniform, non-adaptive standard limits the level of precision in construction, making it difficult to dynamically adjust for specific working conditions. Consequently, it affects the scientific and precise nature of the compaction effect and fails to meet the process requirements of different materials and different compaction stages.

[0005] Furthermore, in terms of construction data recording and management, traditional methods rely on discrete, non-integrated manual records or simple equipment logs. This data lacks a strong correlation with the road surface's geographical location, leading to data fragmentation and making it difficult to form a comprehensive and interconnected view of the construction process. When quality defects such as localized segregation or insufficient compaction occur later in the road surface process, it is impossible to trace the macroscopic defects back to the microscopic process parameters (such as compaction temperature and number of rolling passes) at that specific location during construction. This results in unclear quality responsibility and hinders subsequent process improvement and optimization, making quality retrospective analysis lack accurate data support. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides a data analysis and processing system for highway asphalt pavement construction, which solves the problems of delayed timing selection, lack of forward-looking guidance, non-adaptive process standards, and lack of accurate data support for quality backtracking in existing compaction operation control.

[0007] To solve the above-mentioned technical problems, the present invention provides a highway asphalt pavement construction data analysis and processing system, comprising:

[0008] The data acquisition and preprocessing module is configured to acquire equipment status data from construction equipment, acquire environmental data from environmental sensors, and perform data cleaning and spatiotemporal alignment operations.

[0009] The material state vector instantiation and management module is configured to create material state vector instances based on a preset unit mass. The material state vector instance has a static attribute set, a dynamic state set, a process history set, and an associated environment slice.

[0010] The spatiotemporal evolution analysis and state update module is configured to anchor the material state vector instance to the three-dimensional coordinates of the road surface, and iteratively update the average temperature of the material state vector instance in the dynamic state set based on the physical model and the environmental data.

[0011] The feedforward control decision generation module is configured to predict the future trajectory of the road roller, predict the predicted temperature of the target material state vector instance on the future trajectory at the interception time, calculate the dynamic compactability window of the target material state vector instance by querying a preset compaction parameter library, and generate feedforward control commands based on the comparison between the predicted temperature and the dynamic compactability window.

[0012] The human-machine interaction and command issuance module is configured to receive the feedforward control command and convert the feedforward control command into a control signal or visual guidance information and issue it to the roller vehicle terminal.

[0013] The data storage and quality backtracking module is configured to store the complete lifecycle data of the material state vector instance and provide a reverse query interface based on geospatial coordinates.

[0014] This invention provides a data analysis and processing system for highway asphalt pavement construction. It has the following beneficial effects:

[0015] 1. This invention predicts the interception time of the road roller on its future trajectory through a feedforward control decision generation module, and uses a heat transfer model to simulate the temperature state of the asphalt mixture at that moment. The feedforward control commands generated based on this prediction result allow the operator to anticipate the suitability of the work area in advance, thereby avoiding missing the optimal compaction window due to delays in on-site judgment and improving the accuracy and initiative in selecting the construction timing.

[0016] 2. This invention uses a dynamic compactability window calculation unit to calculate the dynamically changing compaction temperature window by querying a compaction parameter library based on the process history set (determining the compaction stage) and static attribute set (determining the material type) of the target material state vector. Through adaptive process standards, the compaction operation becomes more scientific and targeted, and can meet the process requirements of different materials and different compaction stages.

[0017] 3. This invention constructs a digital archive of the road surface by anchoring the material state vector to the three-dimensional spatial coordinates of the road surface and storing its complete life cycle data. When quality traceability is required, the quality backtracking analysis unit can quickly locate the specific material state vector instance based on the geographical coordinates through spatial proximity search and retrieve its process history set, thereby realizing rapid traceability from macroscopic quality problems to microscopic process parameters, providing a data foundation for quality assessment and process optimization. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the overall architecture of a highway asphalt pavement construction data analysis and processing system according to the present invention;

[0019] Figure 2 This is an internal logic flowchart of the feedforward control decision generation module of the present invention;

[0020] Figure 3 This is a schematic diagram illustrating the implementation principle of the quality backtracking function of this invention. Detailed Implementation

[0021] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] See attached document Figure 1 This invention provides a data analysis and processing system for highway asphalt pavement construction. The system includes six functional modules: a data acquisition and preprocessing module, a material state vector instantiation and management module, a spatiotemporal evolution analysis and state update module, a feedforward control decision generation module, a human-computer interaction and command issuance module, and a data storage and quality backtracking module.

[0023] The system connects to construction equipment such as mixing plants, transport vehicles, pavers, and road rollers via an IoT communication interface. The data acquisition and preprocessing module is responsible for obtaining real-time status data (such as location, temperature, and speed) from the construction equipment and environmental sensor data (such as ambient air temperature, subgrade temperature, and wind speed), and performing data cleaning and spatiotemporal alignment operations.

[0024] The Material State Vector Instantiation and Management module creates instances of Material State Vectors (MSVs) at the discharge port of the mixing plant based on preset unit volume or mass. Each MSV instance consists of a 5-tuple, whose structure includes: a globally unique identifier; a static attribute set containing invariant parameters such as the density and specific heat capacity of the mixture; a dynamic state set containing the three-dimensional spatial position vector and average temperature of the MSV at a certain moment; a process history set, which is an ordered list of events recording the key process events experienced by the MSV and their related parameters; and an associated environmental slice, which records snapshots of environmental data at key moments, including ambient air temperature, underlying surface temperature, wind speed, and air humidity.

[0025] The spatiotemporal evolution analysis and state update module is responsible for continuously tracking and updating the state of the paved material state vector instances. It precisely anchors the material state vectors to the three-dimensional coordinates of the road surface and iteratively updates their temperature in discrete time steps by coupling a physical model. This temperature update model considers two main factors: first, the heat exchange between the material state vector and the environment, which depends on the temperature difference between the material state vector and the ambient air and the underlying layer; second, the heat conduction between the material state vector and its spatial neighborhood set of material state vectors, which depends on the temperature difference, contact area, and thermal conductivity of the material between the material state vector and its neighboring material state vectors.

[0026] The feedforward control decision generation module is responsible for generating forward-looking control commands based on state prediction. First, it predicts the target area the roller will reach within a preset time period and determines the corresponding set of target material state vectors. Then, it calls the model in the spatiotemporal evolution analysis and state update module to extrapolate the state of the target material state vectors to the predicted arrival time. Finally, the data analysis and processing system, based on the predicted future state and combining the static attributes and process history of the material state vectors, calculates the dynamic compactability window using a function established based on the rheological properties of asphalt materials. This dynamic compactability window defines the optimal set of compaction process parameters under the predicted state, including optimal rolling speed, optimal vibration frequency, and target compaction work.

[0027] The human-machine interaction and command issuance module is responsible for converting the optimal set of process parameters calculated by the feedforward control decision generation module into specific control commands, and then sending them to the roller's on-board terminal for display via a wireless communication network. This module is also responsible for receiving and graphically displaying the state of the material state vector, the calculation results of the dynamic compactability window, and data from the entire construction process in real time.

[0028] The data storage and quality backtracking module is responsible for storing the complete lifecycle data of all material state vectors (including static attributes, dynamic state evolution records, process history, and environmental slices). This module provides a geospatial coordinate-based reverse query interface, allowing for the retrieval of complete historical data of the corresponding material state vectors based on the physical location of the road surface after construction is completed. This data is used for causal tracing analysis of quality defects.

[0029] The data acquisition and preprocessing module is responsible for obtaining raw data from diverse and heterogeneous construction stakeholders and converting it into a standardized data format that the system can process internally. This module specifically includes: a construction parameter acquisition unit, an equipment status sensing unit, an environmental information acquisition unit, and a data preprocessing and alignment unit.

[0030] The construction parameter acquisition unit is designed to receive, parse, and store a complete set of static design parameters required for the current asphalt pavement construction from one or more external data sources before the construction begins. These parameters are the foundational data for subsequent material state vector instantiation.

[0031] In one specific implementation, the construction parameter acquisition unit includes a data interface subunit. This data interface subunit is configured to support multiple data import methods to accommodate different design deliverables. For example, the data interface subunit includes a file parser configured to read and parse standardized digital design files, such as files containing road BIM (Building Information Modeling) data (e.g., IFC format), LandXML format road linear and cross-sectional design data files, or spreadsheet files recording mix formulation information (e.g., CSV or XLSX format).

[0032] In another embodiment, the data interface subunit also includes a graphical user interface (GUI) that allows authorized operators to manually enter, verify, or correct key design parameters.

[0033] The static design parameters obtained by the construction parameter acquisition unit from the interface include, but are not limited to:

[0034] Material property parameters: type of asphalt mixture (e.g., AC-25, SMA-13), asphalt grade used in design, design asphalt-aggregate ratio (or asphalt content), and aggregate gradation curve data of the mixture.

[0035] Structural design parameters: the type of paving surface layer for this construction layer (e.g., top layer, intermediate layer), the designed compaction thickness, and the designed width.

[0036] Project and geographic parameters: The unique identifier of the construction project, the start and end chainage information of the construction section, and the corresponding geographic coordinate benchmark.

[0037] After receiving the static design parameters, the construction parameter acquisition unit performs integrity and format checks on the data. Upon successful verification, the construction parameter acquisition unit stores these static design parameters in the database of the data storage and quality backtracking module and establishes an index. These parameters will serve as the sole data source for assigning values ​​to the static attribute sets of material state vector instances when the material state vector instantiation and management module creates such instances.

[0038] The equipment status sensing unit is designed to communicate in real time with sensor networks or vehicle terminals deployed on various key equipment at the construction site through one or more data interfaces in order to continuously acquire dynamic operating status parameters of the equipment.

[0039] In one specific implementation, the device state sensing unit is configured to acquire data from the following device sources:

[0040] Mixing plant: Obtains the discharge temperature of asphalt mixture. and discharge time .

[0041] Transport vehicles: Obtain the real-time location coordinates of the vehicles during transportation. .

[0042] Paver: Obtain high-precision three-dimensional spatial coordinates of the paver. The three-dimensional spatial coordinates are provided by the vehicle-mounted high-precision GNSS / RTK system; the real-time operating speed of the paver is obtained. ; Obtain the temperature of the asphalt mixture at the paver screed. The temperature is measured by an infrared thermometer; and the paving thickness set by the paver is also obtained. .

[0043] Road roller: Obtaining high-precision three-dimensional spatial coordinates of the road roller Obtain the real-time operating speed of the road roller. Obtain the vibration parameters of the road roller, specifically including the vibration frequency. and vibration amplitude ; and to obtain the surface temperature of the road surface in front of or behind the roller. .

[0044] In another embodiment, when intelligent compaction equipment is used in construction, the equipment status sensing unit is also configured to acquire real-time compaction degree measurements output by the roller. .

[0045] The device status sensing unit appends a timestamp, synchronized by the data analysis system, and a unique device identifier to all acquired raw status data. The data is encapsulated into standard data packets and continuously sent to the data preprocessing and alignment unit for subsequent data fusion and processing.

[0046] The environmental information acquisition unit is designed to acquire key environmental parameters in real time that affect the state vector evolution of materials at and around the asphalt pavement construction site.

[0047] In one specific implementation, the environmental information acquisition unit includes one or more portable weather stations deployed within the construction area. The portable weather stations are configured to integrate multiple sensors, specifically including:

[0048] Atmospheric temperature sensor, used to measure ambient air temperature at construction sites. .

[0049] Anemometers are used to measure wind speeds near the ground surface in construction areas. .

[0050] Humidity sensor, used to measure air humidity .

[0051] In another specific embodiment, the environmental information acquisition unit further includes one or more non-contact temperature sensors. These non-contact temperature sensors (e.g., infrared thermometers) are configured to be mounted at the front of the paver, with their measurement direction facing the surface of the subbase to be paved, for acquiring the surface temperature of the subbase in real time before paving operations commence. .

[0052] The environmental information acquisition unit collects data at a preset time frequency (e.g., once every 30 seconds). , , Parameters, and collect them in real time. Parameters. The environmental information acquisition unit adds a timestamp, uniformly synchronized by the data analysis and processing system, to each set of collected data, forming a standardized environmental data packet, which is then continuously sent to the data preprocessing and alignment unit.

[0053] The data preprocessing and alignment unit is responsible for receiving the raw data stream containing timestamps from the device status sensing unit and the environmental information acquisition unit, and performing data cleaning, time alignment and spatial reference unification processing on it to generate standardized and synchronized data.

[0054] In one specific implementation, the data preprocessing and alignment unit includes a data cleaning subunit. This data cleaning subunit is configured to: first, check the integrity of the received data packets; second, identify and mark abnormal data points exceeding a preset physical range (e.g., temperatures of -100°C or 500°C) using a preset effective value range filter; and finally, fill the marked abnormal data points or temporarily missing data points using a predetermined interpolation algorithm (e.g., linear interpolation or previous value preservation) to ensure the continuity of the data stream.

[0055] The data preprocessing and alignment unit also includes a time alignment subunit. This time alignment subunit uses the unified time synchronization of the data analysis and processing system as a reference to synchronize data from different sensors (e.g., temperature sensors at the mixing plant, paver position sensors, and environmental weather stations) with different sampling frequencies and time delays. In one embodiment, the time alignment subunit uses a resampling algorithm to uniformly process all input data streams to a common, preset discrete time step. superior.

[0056] The data preprocessing and alignment unit also includes a spatial reference alignment subunit. The function of this spatial reference alignment subunit is to align all spatial position vectors (e.g., obtained from the device state sensing unit) Transform from its original coordinate system (e.g., WGS-84 coordinate system) to a unified construction project coordinate system (e.g., the local coordinate system of the construction site).

[0057] In one specific implementation, the spatial reference alignment sub-unit is achieved by applying a preset coordinate transformation matrix. To achieve this conversion, the conversion process is as follows:

[0058] ;

[0059] in, This represents the position vector in the unified construction project coordinate system after transformation; This represents a 4x4 coordinate transformation matrix that contains translation and rotation transformation parameters from the original coordinate system to the project coordinate system. This represents the original homogeneous coordinate position vector received from the sensor.

[0060] The data preprocessing and alignment unit encapsulates the data, which has undergone cleaning, time alignment, and spatial alignment, into standardized data frames and sends them to the matter state vector instantiation and management module, the spatiotemporal evolution analysis and state update module, and the data storage and quality backtracking module.

[0061] The Material State Vector Instantiation and Management module is designed to create and maintain a digital representation of the entire lifecycle of discrete asphalt mixture units, namely the material state vector, and to perform unified tracking and state management of all created material state vector instances.

[0062] The Material State Vector Instantiation and Management module is the core hub connecting construction materials in the physical world with data analysis in the digital world. It receives standardized data from the data acquisition and preprocessing module and provides structured, traceable data objects for the subsequent spatiotemporal evolution analysis and state update module.

[0063] In one specific implementation, the matter state vector instantiation and management module includes: a matter state vector structure definition unit, a matter state vector instantiation unit, and a matter state vector lifecycle management unit.

[0064] The material state vector structure definition unit serves to provide a standardized and unified data structure template for the material state vectors of this invention. This data structure template forms the basis for data organization, tracking, and analysis within the data analysis and processing system.

[0065] In one specific implementation, the matter state vector structure definition unit defines each matter state vector. Defined as a quintuple, its formal representation is as follows:

[0066] ;

[0067] in:

[0068] This is a globally unique identifier. It is assigned when the matter state vector is instantiated and is used to uniquely index and track the matter state vector instance throughout its entire lifecycle.

[0069] This is a static attribute set. This static attribute set contains physical and chemical properties that remain unchanged from the time the matter's state vector is generated. In one embodiment, this static attribute set... At least including: material gradation type Material density Specific heat capacity and thermal conductivity .

[0070] This is a dynamic state set. This dynamic state set describes the matter state vector at time [time]. The variable states. In one implementation, this dynamic state set... At least includes: the matter state vector at time t. Three-dimensional spatial position vector The three-dimensional spatial position vector is defined in the construction project coordinate system of the data preprocessing and alignment unit; and the material state vector is defined at time... average temperature .

[0071] This is a process history set. The process history set is a time-ordered list of events used to record all key process events experienced by this material state vector instance since its generation. In one implementation, The structure is Each process event Each of these is a data structure, which must contain at least one event type. (For example, "mixing completed", "start paving", "initial compaction") (The exact timestamp of the event) and process parameter data related to the event. (e.g., roller speed or vibration frequency).

[0072] This is a snapshot of the associated environment. This associated environment slice is used to store local environmental data snapshots collected at specific key moments in the lifecycle of the material state vector (e.g., instantiation moment or paving and anchoring moment). In one implementation, this associated environment slice... At least including: ambient air temperature Surface temperature of the underlying layer near-surface wind speed and air humidity .

[0073] The material state vector structure definition unit provides this data structure template to the material state vector instantiation unit as a unified basis for creating all material state vector instances.

[0074] The material state vector instantiation unit is designed to continuously create material state vector instances at the starting point of the construction process (i.e., the discharge port of the mixing plant) based on the data structure template provided by the material state vector structure definition unit.

[0075] In one specific implementation, the matter state vector instantiation unit is configured to receive a data stream from the data acquisition and preprocessing module in real time. Specifically, it receives:

[0076] The batching plant discharge data from the equipment status sensing unit includes the discharge temperature. Discharge time and discharge rate ;

[0077] Transport vehicle identifier associated with this batch of material output from the equipment status sensing unit. ;

[0078] From the environmental information collection unit, in Environmental data, including ;

[0079] Static attributes related to this construction from the construction parameter acquisition unit, including , .

[0080] The instantiation unit of the matter state vector contains a trigger subunit and an assignment subunit.

[0081] The trigger subunit is configured based on a preset matter state vector per unit mass. This triggers the instantiation operation. The trigger subunit responds to the received output rate. Perform integration to calculate the cumulative output mass since the last instantiation. :

[0082] ;

[0083] in, Indicates from arrive The cumulative quality of time; Indicates the time when the previous material state vector instance was created; Indicates in Quality flow rate at any given moment; This represents the definite integral operation, which means that the integral will be performed on the definite integral. arrive The cumulative mass within this time interval Perform cumulative summation.

[0084] when At that time, the trigger subunit is at the discharge moment Trigger the instantiation event of the matter state vector and reset it. (For example ) and update .

[0085] When the instantiation event is triggered, the assignment sub-unit is activated to create and populate a new material state vector instance. The filling process is as follows:

[0086] Field: Generates a globally unique identifier and assigns it to .

[0087] Fields: Static attributes obtained from construction parameter acquisition units and will Mass as an instance of the matter state vector Deposit, jointly fill .

[0088] Field: Use discharge time The data is used to populate the initial dynamic state. Specifically, the average temperature is set. Set initial position It is a non-spatial identifier, that is This indicates that the state vector of the substance is in a transport state.

[0089] Field: The first process event that created this material state vector. The structure of this process event is as follows: and store it in .

[0090] Field: Discharge time obtained from the environmental information acquisition unit Environmental data And populate using that data snapshot .

[0091] The instantiation unit of the matter state vector is completed After creation and population, the material state vector instance is output to the material state vector lifecycle management unit for subsequent state tracking.

[0092] The lifecycle management unit for matter state vectors is responsible for receiving matter state vector instances created by the matter state vector instantiation unit and managing their dynamic state sets throughout the entire lifecycle of the matter state vector. and process resume collection Continuous updates and maintenance are required.

[0093] In one specific implementation, the matter state vector lifecycle management unit maintains a registry of active matter state vector instances. When a matter state vector instance is created, its initial position... Set as a non-space identifier The management unit places the material state vector instance in the "in transit" state.

[0094] The material state vector lifecycle management unit is configured to perform a paving anchoring operation. This paving anchoring operation transforms the material state vector instance from a transported state to an anchored state. In one embodiment, the material state vector lifecycle management unit receives high-precision three-dimensional spatial coordinates of the paver from the data acquisition and preprocessing module in real time. paver identifier and learned that with the A queue of associated material state vector instances.

[0095] When a matter state vector instance exist When a time is spread out, the matter state vector lifecycle management unit performs the following updates:

[0096] Calculate the anchoring coordinates of the state vector of this substance. The anchoring coordinates are based on the paver's position at... GNSS / RTK position vector at time And a preset geometric offset vector for the paver, representing the distance from the GNSS antenna to the actual landing point of the asphalt mixture (e.g., the rear edge of the screed). :

[0097] ;

[0098] in, It is an instance of the state vector of this matter. Anchored coordinates in the construction project coordinate system; It is the paver in GNSS / RTK position vector at time; It is the geometric offset vector of the paver.

[0099] renew dynamic state set , and The value from Modified to Subsequently, the state vector instance of this matter... Fields remain as constant.

[0100] renew Process resume collection Add a new process event to the list. The structure of this process event is as follows: : Staggered paving : : .

[0101] The material state vector lifecycle management unit is also configured to perform process event logging operations. This unit receives real-time data from the equipment state sensing unit, including the roller's high-precision three-dimensional spatial coordinates. The compaction width of the road roller and roller process parameters .

[0102] At any moment The material state vector lifecycle management unit performs a spatial query to identify the set of all material state vector instances that have been rolled by the roller and are in an anchored state. :

[0103] ;

[0104] in, Indicates in A set of material state vector instances that are constantly covered by the road roller; Represents an instance of an anchored matter state vector; express anchor coordinates ; express High-precision three-dimensional spatial coordinates of the road roller at all times; Indicates calculation and A function of the shortest spatial distance between them; This indicates the compaction width of the road roller.

[0105] For the set of instances of matter state vectors Each instance of the matter state vector in The material state vector life cycle management unit is located in its process history set. Additional events in China The structure of this event is as follows: .

[0106] The Material State Vector Lifecycle Management Unit manages the latest state of all Material State Vector instances. and It provides real-time updates to the spatiotemporal evolution analysis and state update module and the data storage and quality backtracking module.

[0107] The spatiotemporal evolution analysis and state update module is designed to receive physical space anchored material state vector instances provided by the material state vector lifecycle management unit, and continuously calculate, update and predict the dynamic state (especially temperature) of the material state vector instances based on thermodynamic physical models and real-time environmental and process data.

[0108] Spatiotemporal evolution analysis and state update are the core computing engines for realizing feedforward control decisions, providing data processing and analysis systems with the ability to predict future states.

[0109] In one specific implementation, the spatiotemporal evolution analysis and state update module specifically includes: a spatiotemporal anchoring unit, a thermophysical model unit, and a state iteration update unit.

[0110] The spatiotemporal anchoring unit functions to receive an instance of a matter state vector that is in an anchored state from the matter state vector lifecycle management unit, and to set the anchoring coordinates of that matter state vector instance. The indexes are converted into a unified, discretized three-dimensional spatial grid model of the road surface, thereby establishing topological neighborhood relationships between material state vector instances.

[0111] In one specific implementation, the spatiotemporal anchoring unit first defines an orthogonal three-dimensional mesh covering the entire construction area. The three-dimensional mesh From the coordinates of the grid origin and the vector that defines the size of the mesh cell Determined:

[0112] ; ;

[0113] in, Representing a 3D mesh Coordinates of the grid origin in the construction project coordinate system; They are Coordinate components on the X, Y, Z axes; Represents the size vector of a mesh cell; These are the length, width, and height of the grid cell on the X, Y, and Z axes, respectively.

[0114] The spatiotemporal anchoring cell contains a grid index calculation sub-cell. When the spatiotemporal anchoring cell receives an instance of the matter state vector... and its anchoring coordinates At that time, the grid index computation subcell performs the following calculations to determine the material state vector instance. Belonging to the grid index :

[0115] ; ; ;

[0116] in, These represent instances of the matter state vector in the three-dimensional mesh. Discrete indices in the X, Y, and Z directions; Anchor coordinates representing instances of matter state vectors Components on the X, Y, and Z axes; Represents the coordinates of the grid origin. The amount; Indicates the size of the grid cell. The amount; This represents the floor function.

[0117] The spatiotemporal anchoring element will calculate the grid index. With this material state vector instance Unique Identifier The associations are established and stored in a spatial index structure (e.g., a hash table or a three-dimensional array). This spatial index structure is used by other units of the spatiotemporal evolution analysis and state update module (such as the thermophysical model unit) to quickly retrieve the set of spatial neighborhood matter state vectors of any matter state vector instance.

[0118] The state evolution model unit functions as a dynamic state set of instances of a matter state vector. (especially temperature) The evolution of the material state vector instance provides one or more sets of physical governing equations. These equations, based on the principles of heat transfer, describe the heat exchange process between the material state vector instance and adjacent material state vector instances, the underlying layer, and the atmospheric environment after the material state vector instance is anchored to the road surface grid.

[0119] In one specific implementation, the state evolution model element employs a heat transfer model based on the explicit finite difference method. This is for a grid index determined by the spatiotemporally anchored element. Instances of matter state vectors , its in The temperature at that moment was The state evolution model unit calculates its state evolution in Temperature updates in real time :

[0120] ;

[0121] in, express exist Temperature updated in real time; express exist Temperature at any moment; This represents the discrete time step used for iterative calculations; express The quality (from its) In the set ); express Specific heat capacity (from its gather); express The sum of conductive heat between it and all its neighboring material state vector instances; express The heat flux conducted between the substrate and the underlying layer; express Convective heat flux between the exposed surface and the ambient air; express Radiative heat flux between an exposed surface and the environment.

[0122] The state evolution model cells are configured to utilize a grid index established using spatiotemporally anchored cells. ,calculate . yes Rather than in 3D mesh All neighborhood matter state vector instances The sum of the heat conducted between them:

[0123] ;

[0124] in, express In 3D mesh Instance of neighborhood matter state vectors A set; Represents an instance of a neighborhood matter state vector. exist Temperature at any moment; express and The effective thermal conductivity between (this coefficient can be obtained from) and of In the set Export); express and The contact interface area between them (by Sure); express and The distance between the center points (by) Sure); This indicates a summation operation.

[0125] The state evolution model unit is further configured to determine Grid index Does it correspond to the bottom surface of the paving body (e.g.) If so, then Calculated as:

[0126] ;

[0127] in, express Effective thermal conductivity between the substrate and the underlying layer; express Contact area with the underlying layer (by of , (Component determination) express The surface temperature of the underlying layer at time (from of (obtained from a collection or real-time data stream); express The effective heat transfer distance from the center point to the surface of the underlying layer. If If it is not on the bottom surface, then It was set to zero.

[0128] The state evolution model unit is further configured to determine index Does it correspond to the exposed surface of the paving body (e.g.) If so, then and Calculated as:

[0129] ;

[0130] ;

[0131] in, This represents the convective heat transfer coefficient. Based on near-surface wind speed The function, from of Obtain from a collection or real-time data stream; express Surface area exposed to air (by of (Component determination) express Ambient air temperature at any given time; Indicates the emissivity of asphalt materials (from (Set or preset value); This represents the Stefan-Boltzmann constant; Indicates the effective sky temperature (based on) and (Calculated parameters). If If not located on an exposed surface, then and All were set to zero.

[0132] The state evolution model unit provides the complete set of heat transfer control equations to the state iteration update unit as the basis for performing the state (temperature) evolution calculation of the material state vector.

[0133] The process history update unit is responsible for analyzing and summarizing the original and discrete process event sequences recorded by the material state vector lifecycle management unit, and converting them into a structured process history with clear process stage divisions.

[0134] In one specific implementation, the process history update unit receives a material state vector instance. And specifically handle their process resume collection All event types These are the original compaction events. These original compaction events are a set of timestamps. Sorted list .

[0135] The process history update unit includes a compaction pass identification subunit. This compaction pass identification subunit distinguishes different compaction passes by analyzing the time intervals between original compaction events. The execution process is as follows:

[0136] Define the time threshold for the number of passes Initialize the iteration counter and a temporary buffer set used to store all the original events for the current iteration. ; Traverse the original event list For the first in the list One event ( From 1 to ), calculate its relationship with the next event Time difference between The event Add to buffer set ; Determine the time difference Is it greater than the threshold? ,like If so, then one compaction pass is considered complete. Then determine the event. and If it belongs to the same round of crushing, continue to traverse.

[0137] When a single compaction pass is determined to be complete (i.e.) (Or has already been traversed to the end of the list), the history aggregation subunit of the process history update unit is activated. This history aggregation subunit is applied to the buffer set. All original events are aggregated to generate new, structured compaction events. and perform the following operations:

[0138] Calculate the average process parameters for this compaction pass. For example, calculate the average compaction rate. and average compaction temperature .

[0139] ;

[0140] ;

[0141] in, Represents a buffer set The number of original events; It is a buffer set The original compaction event in; It is an event When it occurs, from its data The roller speed extracted from it; It is an event When it occurs, the instance of the matter's state vector The real-time temperature is calculated by the state evolution model unit; This indicates a summation operation.

[0142] Generate structured events The structure of the event is .in, It is a count counter The current value, It is the timestamp of the last original event in this iteration.

[0143] Newly generated structured events Appended to the instance of the matter state vector Process resume collection middle.

[0144] Clear buffer set and the count counter Increment by one to prepare for identifying the next compaction pass. Through the above operations, the process history update unit transforms the original event stream, which contains a large amount of redundant information, into a concise, clear, and structured process history that includes key process parameters.

[0145] See attached document Figure 2The feedforward control decision generation module functions by generating optimized control commands for the next construction phase in advance, based on the current state and future evolution trend of the material state vector provided by the spatiotemporal evolution analysis and state update module, combined with the real-time movement trajectory of the construction machinery. By predicting future operating conditions, the feedforward control decision generation module achieves a shift from reactive, post-event correction to proactive, pre-event control.

[0146] In one specific implementation, the feedforward control decision generation module includes: a job path and state prediction unit, a dynamic compactability window calculation unit, and a feedforward control command generation unit.

[0147] The operation path and state prediction unit functions to extrapolate the trajectory of construction machinery over a future period based on its current mechanical motion state, and simultaneously predict the thermodynamic state of the material state vector within the area covered by that trajectory at the future operation time. In one specific implementation, the operation path and state prediction unit is configured to set a future time window. (For example, the next 60 seconds). The job path and status prediction unit receives real-time data from the equipment status sensing unit. and The operation path and state prediction unit, based on kinematic extrapolation, calculates the future time of the road roller. (in Predicted location This calculation assumes that the road roller maintains its current motion trend for a short period of time, and the calculation formula is as follows:

[0148] ;

[0149] in, Indicating that road rollers will be used in the future Predicted location at any given time; Indicates the time of the road roller High-precision three-dimensional spatial coordinates; Indicates the time of the road roller Real-time operation speed; It represents the time offset from the current moment to the future.

[0150] Based on the predicted trajectory, the task path and state prediction unit is further configured to perform future space collision detection. This task path and state prediction unit identifies future time windows. The set of all material state vector instances that will be crushed by the road roller is denoted as the task set. For each instance of the material state vector in the set of tasks to be performed. The operation path and state prediction unit calculates the interception time when the road roller is expected to reach the location of the material's state vector. .

[0151] ;

[0152] in, This represents an instance of the material state vector expected to arrive at the road roller. The moment of interception at the location; Represents an instance of a matter state vector The anchor coordinates (from its) (state set); Indicates the time of the road roller High-precision three-dimensional spatial coordinates; Indicates the time of the road roller Real-time operation speed; This represents the Euclidean norm (used to calculate distance or speed).

[0153] After determining the interception time Subsequently, the task path and state prediction unit calls the physical equations of the state evolution model unit to process the material state vector instance. From time Interception time The temperature evolution is rapidly simulated forward to obtain the state vector of the matter at the interception time. Predicted temperature .

[0154] To meet real-time requirements, the prediction calculation uses the Euler integral method for discretization estimation:

[0155] ;

[0156] in, Represents a predicted instance of a matter state vector. At the moment of interception Temperature; Represents an instance of a matter state vector The known temperature at the current moment; Represents the number of simulation steps, by Sure; Indicates the time step for the prediction calculation; Representing the heat transfer equation ( The temperature change rate function (i.e., cooling rate, usually a negative value) is derived from the comprehensive analysis. Represents the set of environmental parameters ( In prediction calculations, it is usually assumed that... The internal structure remains unchanged.

[0157] The job path and status prediction unit will calculate the interception time. and predicted temperature The set of pending tasks Output to the optimal compaction time window discrimination unit.

[0158] The dynamic compactability window calculation unit is designed to dynamically calculate the effective temperature operating range (i.e., the dynamic compactability window) of a material state vector in the next process stage (especially the compaction stage) based on the static material properties of the material state vector instance and its past process history.

[0159] In one specific implementation, the dynamic compactability window calculation unit is configured to receive a set of tasks to be performed from the task path and status prediction unit. Instance of matter state vector in .

[0160] The dynamic compressibility window calculation unit first accesses Process resume collection And query the number of structured compaction events (e.g., event type "nth compaction") generated by the process history update unit, denoted as . .

[0161] Next according to The value is mapped according to the preset process stage rules. Determine the instance of the matter state vector. The next compaction phase to be executed :

[0162] ;

[0163] in, express The next compaction stage to be performed (e.g., "initial compaction", "secondary compaction" or "final compaction"). This represents a predefined function that maps the number of completed iterations to the next process stage. Represents an instance of a matter state vector The number of structured compaction events that have been completed.

[0164] Meanwhile, access to the dynamic compressibility window computing unit static property set To obtain its material gradation type .

[0165] The dynamic compactability window calculation unit maintains a preset compaction parameter library. This compaction parameter library It stores different material gradation types. Different compaction stages The corresponding upper and lower temperature thresholds.

[0166] The dynamic compactability window calculation unit then queries , to calculate Dynamic compressibility window This dynamic compactability window is determined by the lowest temperature. and highest temperature Definition:

[0167] ; ;

[0168] in, Represents an instance of a matter state vector exist The minimum effective compaction temperature of the stage; Represents an instance of a matter state vector exist The highest effective compaction temperature of the stage; Indicates from the compaction parameter library A function to retrieve the lowest temperature threshold; Indicates from the compaction parameter library A function to retrieve the highest temperature threshold; Example of a matter state vector Material gradation type.

[0169] The dynamic compactability window calculation unit will calculate the... Dynamic compressibility window Together with the predicted temperature from the job path and status prediction unit and interception time The commands are then output to the feedforward control command generation unit.

[0170] The feedforward control command generation unit is responsible for receiving the future predicted state of the material state vector provided by the operation path and state prediction unit, and the effective operating temperature range of the material state vector provided by the dynamic compactability window calculation unit. It compares and judges the two in real time and generates optimized and forward-looking construction process control commands accordingly.

[0171] In one specific implementation, the feedforward control command generation unit is configured to receive, in real time, specific material state vector instances. (Located at the road roller) The following three sets of data (on the predicted trajectory):

[0172] Interception time calculated by the job path and status prediction unit ;

[0173] Calculated by the job path and status prediction unit: exist Predicted temperature at any time ;

[0174] Calculated by the dynamic compactability window calculation unit: Dynamic compressibility window .

[0175] The feedforward control command generation unit includes a state discrimination subunit. This state discrimination subunit is located at time... Regarding the upcoming Conformity check of work conditions at any given time This state compliance check is defined as a Boolean logic judgment:

[0176] ;

[0177] in, express The result of the conformity check of the predicted state is a Boolean value (true or false). Represents a predicted instance of a matter state vector. At the moment of interception Temperature; express The minimum effective compaction temperature; express The highest effective compaction temperature; Represents the logical AND operator.

[0178] The feedforward control command generation unit further includes a command decision subunit. This command decision subunit, based on... The boolean value generates two independent outputs: instruction type. and instruction parameter set .

[0179] Scenario 1: If A value of True indicates that the road roller is moving according to its current state of motion (as determined by...). (Decision) to drive, will arrive within the optimal temperature window. At this point, the instruction decision subunit is generated:

[0180] Instruction type Set as standard work.

[0181] Instruction parameter set This instruction parameter set contains parameters from the compaction parameter library. Found in, and of Standard process parameters corresponding to each stage, for example .

[0182] Scenario 2: If It is false, and This indicates the current real-time operation speed. During operation, the matter state vector will become supercooled (i.e., the temperature will fall below the operating limit). At this point, the command decision subunit determines the current real-time operating speed. Too slow, must be accelerated. The instruction decision subunit calculates the target speed for correction. (in Greater than (current rate), The determination of this is to allow for a new interception moment determined by the target's velocity. The corresponding predicted temperature satisfy This condition. The new interception time. The calculation is as follows:

[0183] ;

[0184] in, Indicates the revised new interception time; Represents an instance of a matter state vector Anchor coordinates; : Indicates the time when the road roller is High-precision three-dimensional spatial coordinates; This indicates the corrected target velocity; This represents the Euclidean norm (used to calculate distance or speed).

[0185] The instruction decision subunit is then generated:

[0186] Instruction type Set as a priority job.

[0187] Instruction parameter set This instruction parameter set contains the corrected target velocity, for example... .

[0188] Scenario 3: If It is false, and This indicates the current real-time operation speed. During operation, the matter state vector will overheat (i.e., not sufficiently cooled below the operational limit). At this point, the command decision subunit determines the current real-time operational speed. Too fast. The instruction decision subunit calculates the necessary waiting time. Or the target speed to be corrected (in Less than (Current rate). The goal of this decision is to make the new interception time... The corresponding predicted temperature satisfy .

[0189] The instruction decision subunit is then generated:

[0190] Instruction type Set to wait for job (WAIT).

[0191] Instruction parameter set This instruction parameter set includes the corrected target speed or waiting time, for example... .

[0192] The feedforward control command generation unit will generate and Output to the construction machinery control interface or operator display terminal.

[0193] The human-machine interaction and command issuance module serves as the final interface between the feedforward control decision generation module and the construction machinery execution end (i.e., the operator or vehicle automatic controller). This module is responsible for converting abstract control commands into intuitive visual guidance information and managing the issuance of commands and feedback on their execution status.

[0194] In one specific implementation, the human-computer interaction and command issuance module includes a visualization display unit and a command issuance and feedback unit.

[0195] The instruction issuance and feedback unit is configured to receive instruction types generated by the feedforward control instruction generation unit in real time. (e.g., “STANDARD”, “PRIORITY”, or “WAIT”) and instruction parameter sets. (For example, containing) and The instruction issuance and feedback unit is further configured to obtain the measured speed of the road roller from the equipment status sensing unit in real time. One of the core functions of this instruction issuance and feedback unit is to perform feedback calculations, processing the received instruction parameters (especially...) ) and real-time current speed Compare and calculate the speed deviation. :

[0196] ;

[0197] in, express Speed ​​deviation at any moment; express The actual measured speed of the road roller at all times; Indicates by Provided target speed required for the current work area.

[0198] The instruction issuance and feedback unit then receives the instruction. , And the calculated They were sent together to the visualization unit.

[0199] In another embodiment, the instruction issuing and feedback unit also performs an instruction issuing function. The instruction issuing and feedback unit is configured to issue instruction parameter sets... (in particular and The signal is converted into a control electrical signal that conforms to the vehicle control network (e.g., CAN bus) protocol and sent directly to the roller's traveling controller (TCU) or vibration controller to achieve closed-loop automatic control of the roller's speed and vibration frequency.

[0200] The visualization unit is configured to be installed on the road roller. A graphical user interface is generated on the display terminal inside the driver's cab.

[0201] The visualization unit receives data from the instruction issuance and feedback unit and generates two core components on the graphical user interface: a highlight layer for the work area. and target speed indicator .

[0202] Highlight layer of the work area according to Update its visual presentation:

[0203] like For "STANDARD", The area where the work is to be done exist The color is rendered as a standard color (e.g., green).

[0204] like For "PRIORITY", Rendered in an emergency color (e.g., red) and accompanied by an expedited visual cue.

[0205] like For "WAIT", Render it as a waiting color (e.g., blue) and add a slowdown visual cue.

[0206] Target speed indicator Receive speed deviation And display the speed deviation in real time graphically (e.g., with color bars or pointers). When When approaching zero, the target speed indicator turns green; when... When the speed deviates from zero, the target speed indicator turns red to prompt the operator to adjust the vehicle speed. Approaching .

[0207] Please refer to the appendix. Figure 3 The data storage and quality backtracking module stores all material state vector instance data generated by the system during construction and provides a spatially based, refined interface for quality backtracking and causal analysis.

[0208] In one specific implementation, the data storage and quality backtracking module includes: a material state vector database unit and a quality backtracking analysis unit.

[0209] The function of the material state vector database unit is to receive in real time the complete dataset of material state vector instances generated by the material state vector lifecycle management unit and the spatiotemporal evolution analysis and state update module, and to store it in a structured manner in a permanent, queryable database.

[0210] In one implementation, a matter state vector database unit is configured for each matter state vector instance. Store its complete data record. This data record includes:

[0211] Globally unique identifier for the matter state vector ;

[0212] Static attribute set of matter state vector (Include , , , , );

[0213] Dynamic state set of matter state vector (Including its final anchor coordinates) and temperature evolution over time (complete sequence);

[0214] The structured process history set of the matter state vector after processing by the process history update unit ;

[0215] and the associated environment slices of the matter state vector .

[0216] The matter state vector database unit records the above data with the matter state vector instance. and anchor coordinates Create an index to facilitate rapid spatial queries by the quality backtracking analysis unit.

[0217] The quality backtracking analysis unit is designed to respond to location-based query requests at any time after construction is completed, retrieve the complete lifecycle data of the material state vector instance at a specific location from the material state vector database unit, and perform comparative analysis.

[0218] In one specific implementation, the quality backtracking analysis unit is configured to receive three-dimensional target query coordinates from an operator or quality analyst. The coordinates of the three-dimensional target query correspond to the location of the detected road surface anomaly or defect.

[0219] The quality backtracking analysis unit will then Forwarded to the matter state vector database unit to perform a spatial proximity search, thereby identifying the... The instance of the target matter state vector that is physically closest is denoted as... The search operation is defined as follows:

[0220] ;

[0221] in, This represents the state vector instance of the target substance located by the query. This represents the set of all material state vector instances stored in the material state vector database cell; This represents a search function used in a set. Find the one that minimizes the expression within the parentheses. Example; Represents an instance of a matter state vector stored in Concentrated anchor coordinates; Represents the coordinates of a 3D target input by the user; This represents the Euclidean norm (used to calculate distance or speed).

[0222] In determining Subsequently, the mass backtracking analysis unit retrieves data from the material state vector database unit. All related data, especially its detailed process history set and dynamic state set .

[0223] The quality backtracking analysis unit is further configured to, Process Resume Collection The actual process parameters recorded in the data (e.g., (and the theoretical temperature window required at this stage by the dynamic compactability window calculation unit) By comparing the results, the system can automatically determine whether there are any process violations at the location of the defect and perform a cause analysis of the construction quality defects.

Claims

1. A highway asphalt pavement construction data analysis processing system, characterized by, Comprise: a data acquisition and preprocessing module configured to obtain equipment state data from construction equipment, obtain environmental data from environmental sensors, and perform data cleaning and spatio-temporal alignment operations; a material state vector instantiation and management module configured to create a material state vector instance based on a preset unit mass, the material state vector instance having a static attribute set, a dynamic state set, a process history set, and an associated environment slice; a spatio-temporal evolution analysis and state update module configured to anchor the material state vector instance to a road surface three-dimensional coordinate, and iteratively update the average temperature of the material state vector instance in the dynamic state set based on a physical model and the environmental data; a feedforward control decision generation module configured to predict a future trajectory of the road roller, predict a predicted temperature of a target material state vector instance at an interception time on the future trajectory, calculate a dynamic compactability window of the target material state vector instance by querying a preset compaction parameter library, and generate a feedforward control instruction based on a comparison of the predicted temperature and the dynamic compactability window; a human-machine interaction and instruction issuing module configured to receive the feedforward control instruction and convert the feedforward control instruction into a control signal or visual guidance information to issue to a road roller on-board terminal; a data storage and quality backtracking module configured to store complete life cycle data of the material state vector instance and provide a reverse query interface based on geographic spatial coordinates; the material state vector instance created by the material state vector instantiation and management module is composed of a globally unique identifier, a static attribute set, a dynamic state set, a process history set, and an associated environment slice; the static attribute set includes the density, specific heat capacity, and thermal conductivity of the mixture; the dynamic state set includes a three-dimensional spatial position vector and an average temperature; the process history set is an ordered event list recording key process events; the associated environment slice records data snapshots of environmental air temperature, underlying surface temperature, and wind speed; the spatio-temporal evolution analysis and state update module includes a state evolution model unit, which uses a heat transfer model to calculate the updated temperature of the material state vector instance after the next discrete time step based on the current average temperature, mass, specific heat capacity, discrete time step of the material state vector instance, and the sum of conductive heat with adjacent material state vector instances, conductive heat flux with the underlying layer, convective heat flux with the environment air, and radiative heat flux with the environment; the feedforward control decision generation module includes a work path and state prediction unit, which is configured to: calculate the interception time of the road roller reaching the target material state vector instance based on the distance between the current position of the road roller and the anchor coordinate of the target material state vector instance, and the current speed of the road roller; and call the heat transfer model in the spatio-temporal evolution analysis and state update module to forward simulate the temperature evolution of the target material state vector instance from the current time to the interception time to obtain the predicted temperature; The predicted temperature takes the average temperature recorded in the dynamic state set as an initial value, and the heat transfer model is used to continuously calculate the updated temperature for multiple times according to the discrete time step until the cumulative time reaches the interception time, thereby obtaining the predicted temperature.

2. The expressway asphalt pavement construction data analysis processing system according to claim 1, characterized in that, The material state vector instantiation and management module is configured to perform a paving anchoring operation, which specifically comprises: Real-time receiving high-precision three-dimensional spatial position coordinates of the paver at a certain time; Based on the high-precision three-dimensional spatial position coordinates of the paver and the preset paver geometric offset vector, the anchoring coordinates of the material state vector instance are calculated; And the three-dimensional spatial position vector in the dynamic state set of the material state vector instance is updated to the anchoring coordinates.

3. The expressway asphalt pavement construction data analysis processing system according to claim 1, characterized in that, The space-time evolution analysis and state update module further comprises a process history update unit, which is configured to: Receive the original compaction event list in the process history set; By analyzing whether the time interval between the original compaction events is greater than the preset interval interval threshold, different rolling intervals are identified; And all original compaction events belonging to the same interval are aggregated to generate a structured compaction event, which contains an average compaction temperature.

4. The highway asphalt pavement construction data analysis processing system according to claim 1, characterized in that, The feedforward control decision generation module includes a dynamic compactability window calculation unit, which is configured to: Access the process history set of the target material state vector instance to determine the number of completed structured compaction events; Determine the next compaction phase according to the number of completed structured compaction events; Access the static attribute set of the target material state vector instance to obtain the material gradation type; And query the compaction parameter library to calculate the dynamic compactability window of the target material state vector instance, which is bounded by the minimum temperature and the maximum temperature.

5. The highway asphalt pavement construction data analysis processing system according to claim 4, characterized in that, The feedforward control decision generation module includes a feedforward control instruction generation unit, which is configured to: Perform a state compliance check, which is defined as determining whether the predicted temperature is not lower than the minimum temperature and not higher than the maximum temperature of the dynamic compactability window; When the state compliance check result is yes, a standard operation instruction type is generated; When the state compliance check result is no and the predicted temperature is lower than the minimum temperature, a priority operation instruction type is generated; When the state compliance check result is no and the predicted temperature is higher than the maximum temperature, a waiting operation instruction type is generated.

6. The highway asphalt pavement construction data analysis processing system according to claim 5, characterized in that, The human-computer interaction and instruction issuing module includes an instruction issuing and feedback unit and a visualization display unit, wherein: The instruction issuing and feedback unit is configured to calculate the speed deviation between the measured speed of the road roller and the target speed in the feedforward control instruction; The visualization display unit is configured to generate a work area highlight layer and a target speed indicator on the road roller on-board terminal; The work area highlight layer is rendered in different colors according to the instruction type; The target speed indicator graphically displays the speed deviation.

7. The highway asphalt pavement construction data analysis processing system according to claim 1, characterized in that, The data store and quality backtracking module includes a quality backtracking analysis unit configured to: receive a three-dimensional target query coordinate; perform a spatial proximity search in the store to identify a target material state vector instance having a minimum spatial distance between the anchor coordinate and the three-dimensional target query coordinate; and retrieve the process history set for the target material state vector instance for causal root cause analysis of quality defects.

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