A remote communication monitoring system for construction state of pavement material

Abstract

The present application relates to the technical field of computer-aided design, in particular to a road surface material construction state remote communication monitoring system, the system comprises: a construction environment sensing module collects voltage and pulse signals and converts them into road surface temperature and wind speed to construct a monitoring data set, a heat flux dynamic calculation module generates a convective heat transfer coefficient in combination with the wind speed and calculates the surface heat dissipation flux, an internal state deduction module constructs a virtual grid model and configures material parameters, calculates the heat energy exchange amount of the nodes according to the heat dissipation flux to generate a core temperature gradient sequence, and a construction window monitoring module extracts the central node temperature, and if it is less than a threshold value, a stop rolling pre-warning instruction is generated. In the present application, the internal heat energy exchange is deduced by constructing a virtual grid model, deep analysis from surface data to core temperature is realized, the problem that the internal state cannot be grasped only by surface monitoring is solved, the compaction operation timing is accurately controlled, and the road surface forming quality is significantly improved.

Description

Technical Field

[0001] This invention relates to the field of computer-aided design technology, and in particular to a remote communication monitoring system for the construction status of road materials. Background Technology

[0002] Computer-aided design technology generally refers to the use of computers and their graphics devices to assist designers in their work, encompassing a range of activities from design, drafting, analysis to documentation. One example is the traditional remote communication monitoring system for road material construction status, which involves deploying multiple sensors at the construction site, including temperature, humidity, and pressure sensors. These sensors are connected to a field data acquisition unit via wired or wireless means. The acquisition unit initially summarizes the data and then sends data packets to a remote server via a GSM or GPRS module. The monitoring software on the server receives the data and displays it in the form of tables or simple graphs.

[0003] Existing remote communication monitoring systems for road material construction status measure parameters such as temperature directly by deploying sensors at the construction site and then remotely displaying the collected data. This monitoring method is relatively direct and only reflects the real-time state of the road surface. This monitoring mode, relying on direct physical measurement, cannot reveal the heat transfer and distribution patterns within the material. Especially for materials like asphalt mixtures that require strict internal temperature control, it is difficult to accurately determine whether the internal temperature is still within the appropriate compaction temperature range based solely on surface data. Therefore, in complex construction environments, the guidance provided by the monitoring system is limited, potentially leading the construction team to prematurely or lately perform compaction work due to an inability to grasp the dynamic changes in the internal core temperature, thus affecting the final road surface quality and durability. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies by proposing a remote communication monitoring system for the construction status of road materials.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a remote communication monitoring system for the construction status of road materials includes:

[0006] The construction environment sensing module collects analog voltage signals, pulse signals, and atmospheric ambient temperature values, converts the analog voltage signals into road surface temperature values ​​and the pulse signals into ambient wind speed values, and constructs a real-time monitoring dataset.

[0007] The heat flux dynamic calculation module calculates the difference between the road surface temperature value and the atmospheric environment temperature value based on the real-time monitoring dataset, generates the surface convection heat transfer coefficient based on the ambient wind speed value, and calculates the product of the difference and the surface convection heat transfer coefficient to generate the surface heat dissipation flux value.

[0008] The internal state deduction module constructs a virtual mesh model including discrete computing nodes, configures the specific heat capacity and thermal conductivity of asphalt mixture, calculates the heat exchange of the discrete computing nodes in multiple layers based on the surface heat dissipation flux, the specific heat capacity and thermal conductivity of asphalt mixture, and generates a core temperature gradient sequence.

[0009] The construction window monitoring module extracts the temperature value of the center node of the core temperature gradient sequence. If the temperature value of the center node is less than the minimum temperature threshold for compaction, a stop compaction warning command is generated.

[0010] As a further aspect of the present invention, the construction environment sensing module includes:

[0011] The signal acquisition submodule acquires the analog voltage signal reflecting the road surface radiation intensity through an infrared temperature transmitter, acquires the pulse signal reflecting the air flow frequency through a three-cup anemometer, and simultaneously obtains the ambient atmospheric temperature value at the site.

[0012] The data conversion submodule converts the analog voltage signal into the road surface temperature value according to a preset voltage-temperature mapping table, and converts the pulse signal into the ambient wind speed value according to a pulse frequency conversion formula.

[0013] The dataset construction submodule aligns and associates the road surface temperature values, the atmospheric ambient temperature values, and the ambient wind speed values ​​according to a unified timestamp to generate the real-time monitoring dataset.

[0014] As a further aspect of the present invention, the heat flux dynamic calculation module includes:

[0015] The difference calculation submodule extracts the road surface temperature value and the atmospheric ambient temperature value from the real-time monitoring dataset, and performs a subtraction operation to generate the temperature difference value between the road surface and the environment.

[0016] The coefficient generation submodule calls a preset wind speed heat transfer correlation model, uses the ambient wind speed value as an input variable to perform a power law operation, and generates the surface convection heat transfer coefficient.

[0017] The flux calculation submodule obtains the temperature difference value and the surface convective heat transfer coefficient, performs a multiplication operation to quantify the heat loss rate per unit area, and generates the surface heat dissipation flux value.

[0018] As a further aspect of the present invention, the internal state deduction module includes:

[0019] The virtual modeling submodule sets the spatial step size according to the physical thickness of the road material, establishes the virtual mesh model including multiple discrete computing nodes along the vertical depth direction, and assigns the specific heat capacity value of the asphalt mixture and the thermal conductivity value to each discrete computing node.

[0020] The heat exchange calculation submodule uses the surface heat dissipation flux value as a boundary condition, and combines the temperature gradient between adjacent nodes and the thermal conductivity value to calculate the heat energy exchange of the multi-layer discrete computing nodes at the current time step.

[0021] The gradient output submodule updates the temperature status of all the discrete computing nodes based on the heat exchange amount, arranges the real-time temperature values ​​of multiple nodes in depth order, and generates the core temperature gradient sequence.

[0022] As a further aspect of the present invention, the construction window monitoring module includes:

[0023] The node extraction submodule parses the length of the core temperature gradient sequence, locates the temperature data at the middle index position of the sequence, and marks it as the temperature value of the central node.

[0024] The threshold comparison submodule obtains the preset minimum temperature threshold for compaction operation and compares the temperature value of the center node with the minimum temperature threshold for compaction operation.

[0025] The instruction generation submodule triggers alarm logic and generates the stop compaction warning instruction when the comparison result shows that the temperature value of the center node is lower than the minimum temperature threshold of the compaction operation.

[0026] As a further aspect of the present invention, the process of converting the analog voltage signal into the road surface temperature value in the data conversion submodule includes:

[0027] The amplitude of the analog voltage signal is obtained, and the corresponding equivalent radiation temperature value is found using a preset blackbody radiation calibration curve. The equivalent radiation temperature value is then subjected to background reflection compensation calculation in conjunction with the atmospheric ambient temperature value to obtain the road surface temperature value.

[0028] As a further aspect of the present invention, the process by which the coefficient generation submodule generates the surface convective heat transfer coefficient is specifically performed according to the following formula:

[0029] ;

[0030] in, This represents the generated surface convective heat transfer coefficient. This represents the collected environmental wind speed value. Represents the fundamental heat transfer constant under natural convection conditions. Represents the influence factor of wind speed convection. This represents the fluid dynamics correction index.

[0031] As a further aspect of the present invention, the process by which the heat energy exchange quantity is calculated by the exchange calculation submodule is specifically performed according to the following formula:

[0032] ;

[0033] in, Representing the The updated temperature values ​​of the discrete computing nodes described in the layer. Representing the The current temperature value of the layer node. and These represent the current temperature values ​​of the adjacent upper-level node and the adjacent lower-level node, respectively. The thermal conductivity value represents the configuration. Represents the time step. Represents the spatial grid step size. This represents the specific heat capacity of the asphalt mixture. This represents the density of the asphalt mixture;

[0034] The heat exchange calculation submodule calculates the amount of heat exchange based on the updated temperature value.

[0035] As a further aspect of the present invention, the generation process of the instruction generation submodule includes:

[0036] When it is determined that rolling needs to be stopped, the rate of decrease of the current temperature value of the center node is obtained, and the time window for the material to reach the hardening critical point is predicted based on the rate of decrease. A control message including the remaining working time and the requirement to stop operation immediately is constructed, and the stop rolling warning command is generated.

[0037] As a further aspect of the present invention, the process by which the virtual modeling submodule establishes the virtual mesh model includes:

[0038] Obtain the total design thickness of the road paving layer, set a spatial distance that meets the numerical stability requirements, and divide the total design thickness into... There are three equally spaced mesh layers, with the first layer defined as the surface boundary node, the second layer as the third layer, and the fourth layer as the fourth layer. The layer consists of the bottom boundary nodes and the second to third layers. The layers are internal nodes, and the virtual mesh model used for heat conduction calculations is established.

[0039] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0040] In this invention, a real-time monitoring dataset is constructed by collecting environmental parameters such as road surface temperature and wind speed. Combined with the material's own physical properties such as specific heat capacity and thermal conductivity, a virtual grid model is built that can reflect the internal heat transfer process of the material. This allows for the deduction of the dynamic gradient change of the core temperature inside the asphalt mixture. This approach is no longer limited to the direct observation of surface phenomena but delves into the dynamic evolution of the material's internal state. By calculating the surface heat dissipation flux and simulating internal heat exchange, the critical core temperature that determines the construction window can be accurately predicted. This generates an early warning instruction before the core temperature drops to the compaction threshold, providing a more scientific and forward-looking basis for construction decisions. This ensures that the compaction operation is completed within the optimal temperature window, effectively improving construction quality. Attached Figure Description

[0041] Figure 1 This is a schematic diagram of the overall structure of the remote communication monitoring system for road material construction status of the present invention;

[0042] Figure 2 This is a flowchart of the construction environment sensing module of the present invention;

[0043] Figure 3 This is a flowchart of the dynamic heat flux calculation module of the present invention;

[0044] Figure 4 This is a flowchart of the internal state deduction module of the present invention;

[0045] Figure 5 This is a flowchart of the construction window monitoring module of the present invention. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of this invention clearer, the software-based technical solution is described in detail below with reference to system architecture diagrams and embodiments. It should be understood that the specific embodiments described herein are only for explaining the technical solutions of this invention and do not constitute a limitation on the scope of protection.

[0047] In the description of this invention, the system architecture relationships or data processing flows indicated by terms such as "layer," "module," "interface," "data flow," "client," and "server" are all defined based on the architecture diagram or flowchart corresponding to the embodiments. This way of describing is only used to clearly illustrate the logical relationships between the elements in the technical solution, and not to limit the physical deployment form. The term "multiple" includes two or more technical units, including but not limited to multiple data nodes, processing threads, service instances, or functional components and other scalable elements. The specific number is determined according to the actual business scenario and needs to be specifically specified.

[0048] Please see Figure 1 and Figure 2This invention provides a technical solution: a remote communication monitoring system for the construction status of road materials, comprising:

[0049] The construction environment sensing module collects analog voltage signals, pulse signals, and atmospheric temperature values, converts the analog voltage signals into road surface temperature values ​​and the pulse signals into ambient wind speed values, and constructs a real-time monitoring dataset.

[0050] The construction environment perception module includes:

[0051] The signal acquisition submodule acquires analog voltage signals reflecting the road surface radiation intensity through an infrared temperature transmitter, acquires pulse signals reflecting the air flow frequency through a three-cup anemometer, and simultaneously obtains the ambient atmospheric temperature value at the site.

[0052] The data conversion submodule converts the analog voltage signal into a road surface temperature value according to the preset voltage-temperature mapping table, and converts the pulse signal into an ambient wind speed value according to the pulse frequency conversion formula.

[0053] The dataset construction submodule aligns and correlates road surface temperature values, atmospheric ambient temperature values, and ambient wind speed values ​​according to a unified timestamp to generate a real-time monitoring dataset.

[0054] The process of converting analog voltage signals into road surface temperature values ​​in the data conversion submodule includes:

[0055] The amplitude of the analog voltage signal is obtained, and the corresponding equivalent radiation temperature value is found using the preset blackbody radiation calibration curve. The equivalent radiation temperature value is then calculated by combining the atmospheric ambient temperature value with background reflection compensation to obtain the road surface temperature value.

[0056] During the execution of the construction environment perception module, the system first activates the power supply circuits of the configured infrared temperature transmitter and three-cup anemometer, and completes the sensor initialization self-test. The signal acquisition submodule controls the infrared temperature transmitter to be aimed at the asphalt pavement paving area. The photodetector inside the sensor receives the infrared radiation energy emitted by the pavement, and the photoelectric conversion circuit linearly maps the radiation energy into an amplitude value within... to The analog voltage signal is within the range. Simultaneously, the rotating component of the three-cup anemometer rotates with the airflow, and its internal photoelectric encoder disk cuts the light beam, generating a pulse signal whose frequency varies with the rotational speed. The signal acquisition submodule captures this pulse signal through a high-speed counter interface and simultaneously reads the ambient atmospheric temperature value output by the temperature sensor located at the on-site weather station.

[0057] After receiving the above signals, the data conversion submodule first processes the analog voltage signal. The system retrieves nonlinear calibration data from memory, which describes the correspondence between voltage amplitude and blackbody radiation temperature. The amplitude of the analog voltage signal is then obtained. The value is then substituted into a pre-defined fourth-order polynomial fitting equation to find the uncompensated equivalent radiation temperature. Then, the current atmospheric ambient temperature value is read. Background reflection compensation calculations are performed. The calculation process is based on the inverse derivation of the Stefan-Boltzmann law, eliminating environmental reflected radiation components. Specifically, the emissivity of the road surface material is set. (Value) ), using formula The calculated surface temperature value of the road surface For pulse signals, the submodule calculates the unit time window (set to...). Number of pulses within ) According to the pulse frequency conversion formula Calculations were performed to obtain the ambient wind speed value. The dataset construction submodule establishes a circular buffer indexed by millisecond-level UNIX timestamps. The submodule updates the buffer every [time period]. Read the converted road surface temperature value once. Atmospheric ambient temperature values and ambient wind speed values Write these three sets of data into the same line of the buffer and tag it with the current system clock timestamp. When the number of records in the buffer reaches the preset batch size ( When processing a batch of data, the submodule packages the data to generate a real-time monitoring dataset containing time-series information, which is then transmitted to the subsequent processing unit.

[0058] Taking an asphalt paving site on a highway as an example, the amplitude of the analog voltage signal acquired by the signal acquisition submodule is... The frequency of the pulse signal is The atmospheric ambient temperature value is (Right now The data conversion submodule first determines the voltage-temperature mapping relationship. The equivalent radiation temperature value was calculated. (Right now Next, background reflection compensation calculation is performed, and the emissivity is set. Substitute into the compensation formula to calculate: Converted to degrees Celsius, the road surface temperature is... For wind speed calculation, set the sensor calibration parameters. , The collected pulse frequency Substitute into the formula to calculate: Finally, the dataset construction submodule generates a monitoring record: {timestamp: 1715678400, road surface temperature: 141.13, ambient temperature: 25.0, ambient wind speed: 4.7}.

[0059] Please see Figure 1 and Figure 3 The heat flux dynamic calculation module calculates the difference between the road surface temperature and the ambient temperature based on the real-time monitoring dataset, generates the surface convection heat transfer coefficient based on the ambient wind speed, and calculates the product of the difference and the surface convection heat transfer coefficient to generate the surface heat dissipation flux value.

[0060] The heat flux dynamic calculation module includes:

[0061] The difference calculation submodule extracts the road surface temperature value and the atmospheric environment temperature value from the real-time monitoring dataset, and performs a subtraction operation to generate the temperature difference value between the road surface and the environment.

[0062] The coefficient generation submodule calls the preset wind speed heat transfer correlation model, uses the ambient wind speed value as the input variable to perform power law calculation, and generates the surface convection heat transfer coefficient.

[0063] The flux calculation submodule obtains the temperature difference value and the surface convection heat transfer coefficient, performs multiplication operations to quantify the heat loss rate per unit area, and generates the surface heat dissipation flux value.

[0064] The coefficient generation submodule generates the surface convection heat transfer coefficient according to the following formula:

[0065] ;

[0066] in, Represents the surface convective heat transfer coefficient. This represents the collected ambient wind speed value. Represents the fundamental heat transfer constant under natural convection conditions. Represents the influence factor of wind speed convection. This represents the fluid dynamics correction index.

[0067] During the execution of the heat flux dynamic calculation module, the difference calculation submodule first parses the real-time monitoring dataset and extracts the road surface temperature values ​​at the same time point. With atmospheric ambient temperature values The submodule executes the subtraction instruction. The temperature difference between the road surface and the environment was obtained. The coefficient generation submodule then calls the wind speed heat transfer correlation model, which has already incorporated the empirical formulas mentioned earlier. The submodule will then use the ambient wind speed values... As an independent variable input, combined with a preset fluid dynamics correction index Perform an exponentiation operation, then multiply by the wind speed convection influence factor. Finally, add the basic heat transfer constant. Thus, the surface convective heat transfer coefficient can be calculated. The coefficient generation submodule generates the surface convection heat transfer coefficient according to the following formula: ;

[0068] in, Represents the surface convective heat transfer coefficient, in units of It represents the amount of heat transferred per unit time per unit area for every 1 degree Celsius change in temperature under the combined effects of a specific wind speed and natural convection. Represents the fundamental heat transfer constant under natural convection conditions, with units of . This indicates the heat exchange capacity generated solely by changes in air density caused by temperature differences when the wind speed is zero. Represents the wind speed convection influence factor, in units of This is used to quantify the linear or nonlinear enhancement of the heat transfer coefficient by wind speed increase; This represents the collected ambient wind speed value, in units of... ; Represents the fluid dynamics correction exponent, which is dimensionless. The superscript symbol indicates exponentiation. It is used to correct the nonlinear relationship between wind speed and heat transfer coefficient, and reflects the turbulent characteristics of airflow over rough surfaces.

[0069] Regarding the formula , and The parameter settings were calibrated through wind tunnel simulation experiments. The experiment, conducted under the condition of a constant temperature difference, adjusted the wind speed from... to The actual convective heat transfer coefficients at different wind speeds were measured using a heat flux meter. The experimental data are shown in Table 1.

[0070] Table 1. Measured data of convective heat transfer coefficient at different wind speeds.

[0071] ;

[0072] As shown in Table 1, based on the measured data, the least squares method was used to perform nonlinear regression fitting on the formula. First, determine... Take the wind speed as The measured value at that time, i.e. The remaining data was then fitted to determine... and The optimal solution is: , Based on the environmental wind speed values ​​obtained in the aforementioned embodiments... Substitute it into the formula to calculate: The calculation process is as follows: , , This result indicates that, in the current... Under wind conditions, the temperature difference per square meter and per degree Celsius on the road surface will generate Heat loss.

[0073] The flux calculation submodule receives temperature difference values. With surface convection heat transfer coefficient Perform multiplication operations Given the surface temperature value of the road surface. Atmospheric ambient temperature values ,but Calculate the surface heat flux. : The calculation result characterizes the rate at which asphalt pavement loses heat to the atmosphere through convection under the current wind speed and temperature difference conditions, i.e., the surface heat dissipation flux value. This value will be used as a boundary condition to be passed to the internal state inference module.

[0074] Please see Figure 1 and Figure 4 The internal state deduction module constructs a virtual mesh model including discrete computing nodes, configures the specific heat capacity and thermal conductivity of asphalt mixture, calculates the heat exchange of multi-layer discrete computing nodes based on the surface heat dissipation flux, specific heat capacity and thermal conductivity of asphalt mixture, and generates a core temperature gradient sequence.

[0075] The internal state simulation module includes:

[0076] The virtual modeling submodule sets the spatial step size based on the physical thickness of the road material, establishes a virtual mesh model including multiple discrete calculation nodes along the vertical depth direction, and assigns the specific heat capacity and thermal conductivity of the asphalt mixture to each discrete calculation node.

[0077] The exchange calculation submodule uses the surface heat dissipation flux value as a boundary condition, and combines the temperature gradient and thermal conductivity values ​​between adjacent nodes to calculate the heat energy exchange of the multi-layer discrete computing nodes at the current time step.

[0078] The gradient output submodule updates the temperature status of all discrete computing nodes based on the amount of heat exchange, arranges the real-time temperature values ​​of multiple nodes in depth order, and generates a core temperature gradient sequence.

[0079] The process of establishing a virtual mesh model in the virtual modeling submodule includes:

[0080] Obtain the total design thickness of the pavement layer, set the spatial distance that meets the numerical stability requirements, and divide the total design thickness into... There are three equally spaced mesh layers, with the first layer defined as the surface boundary node, the second layer as the third layer, and the fourth layer as the fourth layer. The layer consists of the bottom boundary nodes and the second to third layers. The layers are internal nodes, and a virtual mesh model is established for heat conduction calculations.

[0081] The heat energy exchange calculation submodule calculates the heat energy exchange amount according to the following formula:

[0082] ;

[0083] in, Representing the The updated temperature values ​​of the discrete nodes in the layer are calculated. Representing the The current temperature value of the layer node. and These represent the current temperature values ​​of the adjacent upper-level node and the adjacent lower-level node, respectively. The value representing the thermal conductivity of the configuration. Represents the time step. Represents the spatial grid step size. This represents the specific heat capacity of asphalt mixtures. This represents the density of the asphalt mixture;

[0084] The heat exchange calculation submodule calculates the amount of heat exchange based on the updated temperature value.

[0085] During the execution of the internal state simulation module, the virtual modeling submodule first reads the pavement design parameters from the construction plan to obtain the total design thickness of the paving layer. The submodule sets the spatial step size based on the stability requirements of numerical computation. Total thickness Divide by Rounded down, the number of grid layers is obtained. Allocate memory for a size of Floating-point arrays, index Corresponding route table, index The corresponding subgrade contact surface. This submodule consults the material property database and extracts the specific heat capacity value of the current asphalt mixture. Thermal conductivity value and density These physical constants are then assigned to each discrete computation node in the array. The exchange computation submodule employs an explicit finite difference method, with time steps... This is a cyclical increment. Within each time step, the submodule first processes the boundary conditions: setting the input heat flux of the first-layer nodes to a negative surface heat dissipation flux value. For the second layer to the... For nodes within a layer, the submodule iterates through the array, using the discrete form of Fourier's law of heat conduction to calculate the net heat flow into and out of the node, and then updates the node's temperature state. The heat exchange calculation submodule calculates the heat exchange amount according to the following formula: ;

[0086] in, Representing the The updated temperature values ​​for the layer discrete computing nodes, in units of or ; Representing the The current temperature value of the layer node, in units of or ; and These represent the current temperature values ​​of the adjacent upper-level node and the adjacent lower-level node, respectively, in units of... or ; This represents the thermal conductivity value of the configuration, in units of... ; Represents the time step, in units of ; Represents the spatial grid step size, in units of ; This represents the specific heat capacity of asphalt mixtures, in units of... ; This represents the density of the asphalt mixture, in units of... ; in the formula The second derivative of temperature in space is represented by the Laplace operator, which reflects the nodal... Net heat flux density at the location.

[0087] In the specific calculation example, the total design thickness of the road paving layer is set. Space is far from where you can walk Calculate the number of grid layers To query asphalt mixture parameters: specific heat capacity value. ,density thermal conductivity value Set the time step. Calculate the grid Fourier number. Assume that in the current core temperature gradient sequence, the th... Layer node temperature , No. Layer node temperature , No. Layer node temperature Calculate the first... Temperature of layer nodes at the next time step Substituting into the formula yields The calculation result within the parentheses is... The change is ,but The result indicates that within this one-second time step, due to the lower temperature of adjacent nodes, the... A small amount of heat conduction occurs between layer nodes and the layers above and below. After each full-field temperature update, the gradient output submodule arranges the temperature values ​​in the array according to their depth index, generating a sequence containing... A sequence of core temperature gradients at various temperature points.

[0088] Please see Figure 1 and Figure 5 The construction window monitoring module extracts the temperature value of the center node of the core temperature gradient sequence. If the temperature value of the center node is less than the minimum temperature threshold for compaction, a stop compaction warning command is generated.

[0089] The construction window monitoring module includes:

[0090] The node extraction submodule parses the length of the core temperature gradient sequence, locates the temperature data at the middle index position of the sequence, and marks it as the temperature value of the center node.

[0091] The threshold comparison submodule obtains the preset minimum temperature threshold for compaction operations and compares the temperature value of the center node with the minimum temperature threshold for compaction operations.

[0092] The instruction generation submodule triggers alarm logic and generates a stop compaction warning instruction when the comparison result shows that the temperature value of the center node is lower than the minimum temperature threshold for compaction.

[0093] The generation process of the instruction generation submodule includes:

[0094] When it is determined that rolling needs to be stopped, the rate of decrease of the current central node temperature value is obtained, and the time window for the material to reach the hardening critical point is predicted based on the rate of decrease. A control message including the remaining working time and the requirement to stop operation immediately is constructed, and a stop rolling warning command is generated.

[0095] During the execution of the construction window monitoring module, the node extraction submodule receives the core temperature gradient sequence and reads the total number of elements in the sequence. The submodule calculates the intermediate index position. Using this index, the corresponding floating-point temperature value is located and read from the sequence, and marked as the temperature value of the central node. The threshold comparison submodule reads the minimum temperature threshold for compaction operations from the system's configuration register. This threshold is preset based on the viscosity-temperature characteristic curve of asphalt mixtures, representing the minimum allowable temperature at which the material can achieve a specified degree of compaction. The submodule executes the comparison logic: [Judging / Determining...] Is the condition met? The instruction generation submodule acts based on the comparison result. If the condition is met, it indicates that the core temperature has fallen below the critical value, and the compaction operation must be stopped. At this time, the submodule calls the most recent data from the historical database. The current rate of temperature decrease is calculated by performing a first-order linear regression on the central node temperature values ​​at each time point. Using formulas Predict the remaining time, construct a control message including the remaining workable time and the requirement to stop operation immediately, and generate a stop compaction warning command.

[0096] Regarding the minimum temperature threshold for compaction operations in the threshold comparison submodule The settings are based on the Brookfield rotational viscosity test data of the asphalt binder. According to construction specifications, the viscosity range of the asphalt during the compaction stage should be within... Viscosity-temperature curves of a specific type of modified asphalt were measured, and the experimental data are shown in Table 2.

[0097] Table 2 Experimental Data on Viscosity-Temperature Characteristics of Asphalt

[0098] ;

[0099] As shown in Table 2, the target viscosity The corresponding temperature is located at and Between. The viscosity was determined by interpolation. The temperature at that time was approximately Considering the heat generated by the roller's work and the safety margin, a minimum temperature threshold is set for the end of final compaction. In actual calculations, assume the sequence length is... Calculate intermediate index Extract the first Temperature value of the center node of the layer node Perform a comparison: If the result is true, the warning logic is triggered. The submodule calculates the average descent rate. Then calculate the theoretical deviation time. The generated stop-rolling warning command includes the current core temperature. Threshold And a recommendation to immediately stop the compaction operation.

[0100] The above embodiments illustrate preferred embodiments of the present invention. Any equivalent adjustments to the technical solution based on software engineering methods are within the scope of protection, including but not limited to: implementing algorithm logic using different programming languages, refactoring functional modules into services, adjusting data interaction protocols, and optimizing resource scheduling strategies. Any implementation scheme derived from reasonable modifications to the data processing flow, service call chain, or system architecture layer without departing from the core technology of the present invention should be considered within the protection scope defined by the technical solution of the present invention.

Claims

1. A remote communication monitoring system for the construction status of road materials, characterized in that, The system includes: The construction environment sensing module collects analog voltage signals, pulse signals, and atmospheric ambient temperature values, converts the analog voltage signals into road surface temperature values ​​and the pulse signals into ambient wind speed values, and constructs a real-time monitoring dataset. The heat flux dynamic calculation module calculates the difference between the road surface temperature value and the atmospheric environment temperature value based on the real-time monitoring dataset, generates the surface convection heat transfer coefficient based on the ambient wind speed value, and calculates the product of the difference and the surface convection heat transfer coefficient to generate the surface heat dissipation flux value. The internal state deduction module constructs a virtual mesh model including discrete computing nodes, configures the specific heat capacity and thermal conductivity of asphalt mixture, calculates the heat exchange of the discrete computing nodes in multiple layers based on the surface heat dissipation flux, the specific heat capacity and thermal conductivity of asphalt mixture, and generates a core temperature gradient sequence. The construction window monitoring module extracts the temperature value of the center node of the core temperature gradient sequence. If the temperature value of the center node is less than the minimum temperature threshold for compaction, a stop compaction warning command is generated. The internal state deduction module includes: The virtual modeling submodule sets the spatial step size according to the physical thickness of the road material, establishes the virtual mesh model including multiple discrete computing nodes along the vertical depth direction, and assigns the specific heat capacity value of the asphalt mixture and the thermal conductivity value to each discrete computing node. The heat exchange calculation submodule uses the surface heat dissipation flux value as a boundary condition, and combines the temperature gradient between adjacent nodes and the thermal conductivity value to calculate the heat energy exchange of the multi-layer discrete computing nodes at the current time step. The gradient output submodule updates the temperature status of all the discrete computing nodes according to the heat exchange amount, arranges the real-time temperature values ​​of multiple nodes in depth order, and generates the core temperature gradient sequence. The process by which the heat energy exchange submodule calculates the heat energy exchange amount is specifically performed according to the following formula: ； in, Representing the The updated temperature values ​​of the discrete computing nodes described in the layer. Representing the The current temperature value of the layer node. and These represent the current temperature values ​​of the adjacent upper-level node and the adjacent lower-level node, respectively. The thermal conductivity value represents the configuration. Represents the time step. Represents the spatial grid step size. This represents the specific heat capacity of the asphalt mixture. This represents the density of the asphalt mixture; The heat exchange calculation submodule calculates the amount of heat energy exchanged based on the updated temperature value; The process by which the virtual modeling submodule establishes the virtual mesh model includes: Obtain the total design thickness of the road paving layer, set a spatial distance that meets the numerical stability requirements, and divide the total design thickness into... There are three equally spaced mesh layers, with the first layer defined as the surface boundary node, the second layer as the third layer, and the fourth layer as the fourth layer. The layer consists of the bottom boundary nodes and the second to third boundaries. The layers are internal nodes, and the virtual mesh model used for heat conduction calculations is established.

2. The remote communication monitoring system for road material construction status according to claim 1, characterized in that, The construction environment sensing module includes: The signal acquisition submodule acquires the analog voltage signal reflecting the road surface radiation intensity through an infrared temperature transmitter, acquires the pulse signal reflecting the air flow frequency through a three-cup anemometer, and simultaneously obtains the ambient atmospheric temperature value at the site. The data conversion submodule converts the analog voltage signal into the road surface temperature value according to a preset voltage-temperature mapping table, and converts the pulse signal into the ambient wind speed value according to a pulse frequency conversion formula. The dataset construction submodule aligns and correlates the road surface temperature values, the atmospheric ambient temperature values, and the ambient wind speed values ​​according to a unified timestamp to generate the real-time monitoring dataset.

3. The remote communication monitoring system for road material construction status according to claim 1, characterized in that, The heat flux dynamic calculation module includes: The difference calculation submodule extracts the road surface temperature value and the atmospheric ambient temperature value from the real-time monitoring dataset, and performs a subtraction operation to generate the temperature difference value between the road surface and the environment. The coefficient generation submodule calls a preset wind speed heat transfer correlation model, uses the ambient wind speed value as an input variable to perform a power law operation, and generates the surface convection heat transfer coefficient. The flux calculation submodule obtains the temperature difference value and the surface convective heat transfer coefficient, performs a multiplication operation to quantify the heat loss rate per unit area, and generates the surface heat dissipation flux value.

4. The remote communication monitoring system for road material construction status according to claim 1, characterized in that, The construction window monitoring module includes: The node extraction submodule parses the length of the core temperature gradient sequence, locates the temperature data at the middle index position of the sequence, and marks it as the temperature value of the central node. The threshold comparison submodule obtains the preset minimum temperature threshold for the compaction operation and compares the temperature value of the center node with the minimum temperature threshold for the compaction operation. The instruction generation submodule triggers alarm logic and generates the stop compaction warning instruction when the comparison result shows that the temperature value of the center node is lower than the minimum temperature threshold of the compaction operation.

5. The remote communication monitoring system for road material construction status according to claim 2, characterized in that, The process of converting the analog voltage signal into the road surface temperature value in the data conversion submodule includes: The amplitude of the analog voltage signal is obtained, and the corresponding equivalent radiation temperature value is found using a preset blackbody radiation calibration curve. The equivalent radiation temperature value is then subjected to background reflection compensation calculation in conjunction with the atmospheric ambient temperature value to obtain the road surface temperature value.

6. The remote communication monitoring system for road material construction status according to claim 3, characterized in that, The process by which the coefficient generation submodule generates the surface convective heat transfer coefficient is specifically executed according to the following formula: ； in, This represents the generated surface convective heat transfer coefficient. This represents the collected environmental wind speed value. Represents the fundamental heat transfer constant under natural convection conditions. Represents the influence factor of wind speed convection. This represents the fluid dynamics correction index.

7. The remote communication monitoring system for road material construction status according to claim 4, characterized in that, The generation process of the instruction generation submodule includes: When it is determined that rolling needs to be stopped, the rate of decrease of the current temperature value of the center node is obtained, and the time window for the material to reach the hardening critical point is predicted based on the rate of decrease. A control message including the remaining working time and the requirement to stop operation immediately is constructed, and the stop rolling warning command is generated.

Images