Intelligent cooperative construction management method for paving road roller cluster

Abstract

The invention relates to the technical field of road construction, in particular to an intelligent cooperative construction management method for a paving road roller cluster, which comprises the following steps of: acquiring an asphalt layer total thickness design value, paving road section basic parameters and paving resource parameters; generating division distances according to the total thickness design value of the asphalt layer, the basic parameters of the paving and pressing road section and the paving and pressing resource parameters; dividing the paving road section into a plurality of to-be-compacted areas along the paving direction according to the division distance; each to-be-compacted area is divided into a plurality of to-be-compacted subareas in the width direction of the paving surface, and each to-be-compacted subarea is provided with a road roller; according to the road roller parameters and the basic parameters of the to-be-compacted subarea, the to-be-compacted subarea is divided into a plurality of rolling belts; and each road roller is controlled to move along the rolling belt in the corresponding to-be-compacted subarea. By the adoption of the scheme, the to-be-compacted area can be partitioned according to the actual construction condition, so that the construction quality is improved, conflicts are prevented when multiple machines are parallel, and the balance between the construction efficiency and the quality is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of road construction, and particularly to an intelligent collaborative construction management method for a paving roller cluster. Background Art

[0002] As an important part of modern transportation infrastructure, the construction quality of asphalt pavement directly affects the service life of the road and driving safety. Asphalt concrete, as the core paving material, is a mixture with viscoelastic properties formed by accurately graded aggregates, asphalt binder and functional additives through high-temperature mixing. In the construction process, the mixture needs to go through three key stages: paving and forming, dynamic compaction and later curing. Among them, the compaction process is a key link in forming a high-density pavement structure by applying mechanical loads to the loose mixture by rollers to promote the reconstruction of the aggregate skeleton and expel internal voids. However, traditional compaction operations rely on manually driving rollers to repeatedly roll, which has significant defects such as harsh working conditions, limited efficiency and quality fluctuations.

[0003] In a high-temperature paving environment, the temperature of the asphalt mixture usually remains at 140-160°C. Roller operators need to work in an environment of continuous thermal radiation, asphalt fumes and mechanical vibration, which poses occupational health risks. Especially in night construction or long-span continuous operation scenarios, manual fatigue is likely to cause phenomena such as deviation of rolling tracks, missed compaction or over-compaction, resulting in quality defects such as insufficient local density or aggregate crushing. Therefore, the technology of driverless rollers has gradually become a research hotspot in the industry. By integrating environment perception, path planning and autonomous control modules, it can achieve all-weather precise compaction operations and effectively avoid safety hazards of manual operations. However, existing driverless compaction systems still face multi-dimensional technical bottlenecks in engineering practice.

[0004] Currently, the control of unmanned roller clusters mostly adopts a static construction area division strategy, that is, the paving section is evenly divided based on a preset fixed length, and a unified wheel track overlap rate parameter is used. Such methods do not fully consider the dynamic effects of the thickness fluctuations of the paving layer and the geometric characteristics of the roadbed (such as curve radius, longitudinal slope) in actual construction, which affects the actual construction quality. In addition, the existing systems lack intelligent optimization of the collaborative operation of the roller group. When multiple machines operate in parallel, trajectory conflicts or resource allocation imbalances are likely to occur, and it is difficult to achieve the optimal balance between construction efficiency and quality. Therefore, there is an urgent need to provide an intelligent collaborative construction management method for a paving roller cluster, which can divide the area to be compacted according to the actual construction situation to improve construction quality and prevent conflicts when multiple machines operate in parallel, so as to achieve the balance between construction efficiency and quality. Summary of the Invention

[0005] The present invention provides an intelligent collaborative construction management method for a paving roller cluster, which can divide the area to be compacted according to the actual construction situation, so as to improve the construction quality, prevent conflicts when multiple machines are operating in parallel, and achieve a balance between construction efficiency and quality.

[0006] To achieve the above object, the present application provides the following technical solutions:

[0007] An intelligent collaborative construction management method for a paving roller cluster, comprising the following steps:

[0008] Obtain the designed total thickness value of the asphalt layer, the basic parameters of the paving section, and the compaction resource parameters. The basic parameters of the paving section include the road curvature radius, road slope, and road width. The compaction resource parameters include the working years of technicians and the maximum compaction width of the roller;

[0009] Generate a division distance according to the designed total thickness value of the asphalt layer, the basic parameters of the paving section, and the compaction resource parameters;

[0010] Divide the paving section into a number of areas to be compacted along the paving direction according to the division distance;

[0011] Divide each area to be compacted into a number of sub-areas to be compacted along the width direction of the paving surface; One roller is provided for each sub-area to be compacted to perform the compaction operation of the corresponding sub-area to be compacted;

[0012] Divide the sub-area to be compacted into a number of compaction zones according to the roller parameters and the basic parameters of the sub-area to be compacted;

[0013] Control each roller to move along the compaction zones in the corresponding sub-area to be compacted until the compaction operation of all compaction zones in the sub-area to be compacted is completed.

[0014] Furthermore, the calculation formula of the division distance is as follows:

[0015]

[0016] In the formula, L is the division distance, L base is the reference division distance, α1 is the curvature radius influence coefficient, R norm is the road curvature radius, α2 is the road slope influence coefficient, S norm is the road slope, α3 is the road width influence coefficient, W norm is the road width, α4 is the thickness influence coefficient, X t is the designed total thickness value of the asphalt layer, β1 is the experience influence coefficient, E norm is the working years of technicians, β2 is the equipment influence parameter, M norm is the maximum compaction width of the roller.

[0017] Further, according to the roller parameters and the basic parameters of the area to be compacted, the area to be compacted is divided into several rolling zones, including:

[0018] Obtain the roller parameters and the basic parameters of the area to be compacted; the roller parameters include the wheel width and wheelbase of the roller; the basic parameters of the area to be compacted include the radius of curvature of the area to be compacted, the actual thickness of the asphalt layer in the area to be compacted, and the boundary information of the area to be compacted;

[0019] Generate the rolling zone overlap distance according to the wheel width of the roller, the wheelbase of the roller, the radius of curvature of the area to be compacted, and the actual thickness of the asphalt layer;

[0020] Divide the area to be compacted into several rolling zones according to the wheel width of the roller, the boundary information of the area to be compacted, and the rolling zone overlap distance.

[0021] Further, the calculation formula for the rolling zone overlap distance is as follows:

[0022]

[0023] In the formula, L overlap is the rolling zone overlap distance, k is the overlap coefficient, W is the wheel width of the roller, L is the wheelbase of the roller, R is the radius of curvature of the area to be compacted, γ is the layer thickness correction value, X a is the actual thickness of the asphalt layer.

[0024] Further, divide the area to be compacted into several rolling zones according to the wheel width of the roller, the boundary information of the area to be compacted, and the rolling zone overlap distance, including:

[0025] By means of artificial intelligence, analyze the rolling zone width and the number of rolling zones according to the wheel width of the roller, the boundary information of the area to be compacted, and the rolling zone overlap distance, and use the wheel width of the roller, the boundary information of the area to be compacted, and the rolling zone overlap distance as the input of the input layer, and the rolling zone width and the number of rolling zones as the output of the output layer;

[0026] Divide the area to be compacted into several rolling zones according to the analyzed rolling zone width, the number of rolling zones, and the rolling zone overlap distance.

[0027] Further, control each roller to move along the rolling zones in its respective area to be compacted until the compaction operation of all the rolling zones in the area to be compacted is completed, including:

[0028] Control each roller to move along the rolling zones in its respective area to be compacted, and collect the pavement compaction degree of the corresponding rolling zone in real time;

[0029] Analyze whether the pavement compactness is greater than a preset compactness threshold. If so, control the roller to change lanes laterally to an adjacent rolling zone in the to-be-compacted zone until the compaction operation of all rolling zones in the to-be-compacted zone is completed.

[0030] Furthermore, control each roller to move along the rolling zone in the to-be-compacted zone respectively until the compaction operation of all rolling zones in the to-be-compacted zone is completed, including:

[0031] Set one roller as the leading roller and the rest of the rollers as following rollers;

[0032] Control the leading roller to move along the rolling zone in the to-be-compacted zone and collect the pavement compactness of the corresponding rolling zone in real time;

[0033] Analyze whether the pavement compactness is greater than a preset compactness threshold. If so, control the leading roller to change lanes laterally to an adjacent rolling zone in the to-be-compacted zone until the compaction operation of all rolling zones in the to-be-compacted zone is completed;

[0034] Each following roller obtains the operation parameters of the leading roller and performs compaction actions synchronously with the leading roller according to the obtained operation parameters.

[0035] The principle and advantages of the present invention are as follows:

[0036] 1. By establishing a division distance mathematical model that integrates multi-dimensional parameters such as road curvature radius, slope, width, and asphalt layer thickness, the dynamic optimization of the paving section is realized. Compared with the traditional static zoning method, this solution fully considers the coupling influence of road geometric features, material properties, and construction resource parameters, enables the zoning length to adaptively extend as the curvature radius increases and dynamically adjust with the steepness of the slope, effectively avoiding the quality risks of insufficient compaction in the bend area or offset of the rolling track in the ramp section.

[0037] 2. Dynamically adjust the overlapping distance of the rolling zones based on the roller width, wheelbase, and zoning curvature radius, breaking through the limitations of the traditional fixed overlapping rate. By introducing a curvature radius compensation term, the wheel track overlapping amount is automatically increased in the bend area to compensate for the lateral offset caused by centrifugal force, ensuring the integrity of the rolling coverage in complex alignment sections. Combining with the layer thickness correction mechanism of the actual thickness of the asphalt layer, the overlapping distance is dynamically adjusted to match the density requirements of different thickness layers. Further, through the artificial intelligence model, the collaborative optimization of the rolling zone width and quantity is realized, controlling the width error of the joints between the zones within ±2 cm, effectively eliminating the non-compacted zones and reducing the aggregate crushing rate.

[0038] 3. Adopt a lane-changing control strategy based on the compaction degree threshold. When it is detected that the compaction degree of the current rolling belt exceeds the set threshold, the system automatically triggers a lateral lane-changing instruction, forming a closed-loop control loop of "detection - determination - execution", which can reduce the number of ineffective rolling times and significantly improve the construction efficiency.

[0039] 4. Adopt a leader-follower collaborative control architecture to effectively solve problems such as trajectory intersection and resource competition existing in traditional systems. Field tests show that this solution can increase the cluster operation efficiency by 35%, and at the same time reduce the equipment idling rate to less than 8%, achieving the optimal balance between construction efficiency and quality. Description of the Drawings

[0040] Figure 1 It is a flowchart of an embodiment of an intelligent collaborative construction management method for a paving roller cluster of the present invention.

[0041] Figure 2 It is a schematic diagram of the method for dividing the area to be compacted in an embodiment of an intelligent collaborative construction management method for a paving roller cluster of the present invention. Detailed Embodiments

[0042] The following is a further detailed description through specific embodiments:

[0043] Embodiment 1:

[0044] An intelligent collaborative construction management method for a paving roller cluster. In this embodiment, a leading paver performs paving work on the paving section, and several rollers are arranged behind to compact the pavement paved by the leading paver. During the compaction process, in order to achieve the balance between compaction quality and efficiency, the paving section to be compacted is divided, and the compaction paths of each compactor are planned. As Figure 1 shown, it specifically includes the following steps:

[0045] S100. Divide the paving section into several areas to be compacted along the paving direction, including:

[0046] S101. Obtain the designed total thickness value of the asphalt layer, the basic parameters of the rolling section, and the rolling resource parameters. The basic parameters of the rolling section include the road curvature radius, road slope, and road width. The rolling resource parameters include the working years of technicians and the maximum rolling width of the roller. In this embodiment, taking the compaction starting point as the division starting point and 200 meters as the distance for parameter acquisition, obtain the basic parameters of the rolling section of the corresponding section. Among them, take the maximum curvature radius of this section as the road curvature radius, take the overall slope of this section as the road slope, and take the maximum width of this section as the road width. After completing the division of the previous area to be compacted, take the end point of the previous area to be compacted as the division starting point of the next area to be compacted, take 200 meters as the distance for parameter acquisition, obtain the basic parameters of the rolling section of the corresponding section, and generate the division distance corresponding to the next area to be compacted accordingly, thereby completing the division of the areas to be compacted in the entire paving section.

[0047] S102. Generate a division distance according to the designed total thickness value of the asphalt layer, the basic parameters of the rolling section, and the rolling resource parameters. The calculation formula for the division distance is as follows:

[0048]

[0049] In the formula, L is the division distance, L base is the reference division distance, α1 is the curvature radius influence coefficient, R norm is the road curvature radius, α2 is the road slope influence coefficient, S norm is the road slope, α3 is the road width influence coefficient, W norm is the road width, α4 is the thickness influence coefficient, X t is the designed total thickness value of the asphalt layer, β1 is the experience influence coefficient, E norm is the working years of technicians, β2 is the equipment influence parameter, M norm is the maximum rolling width of the roller. In this embodiment, the reference division distance is 200 meters.

[0050] S103. Divide the paving section into several areas to be compacted along the paving direction according to the division distance.

[0051] S200, as Figure 2 shown, divide each area to be compacted into several sub-areas to be compacted along the width direction of the paving surface; one roller is provided for each sub-area to be compacted to perform the compaction operation of the corresponding sub-area to be compacted.

[0052] S300. Divide the sub-areas to be compacted into several rolling belts according to the roller parameters and the basic parameters of the sub-areas to be compacted, including:

[0053] S301. Obtain the roller parameters and the basic parameters of the area to be compacted. The roller parameters include the wheel width and wheelbase of the roller. The basic parameters of the area to be compacted include the radius of curvature of the area to be compacted, the actual thickness of the asphalt layer in the area to be compacted, and the boundary information of the area to be compacted. In this embodiment, the maximum radius of curvature of the corresponding road section of the area to be compacted is used as the radius of curvature of the corresponding area to be compacted, and the average thickness of the asphalt layer in the area to be compacted is used as the actual thickness of the area to be compacted.

[0054] S302. Generate the overlapping distance of the rolling belts according to the wheel width of the roller, the wheelbase of the roller, the radius of curvature of the area to be compacted, and the actual thickness of the asphalt layer. The calculation formula for the overlapping distance of the rolling belts is as follows:

[0055]

[0056] In the formula, L overlap is the overlapping distance of the rolling belts, k is the overlapping coefficient, W is the wheel width of the roller, L is the wheelbase of the roller, R is the radius of curvature of the area to be compacted, γ is the layer thickness correction value, and X a is the actual thickness of the asphalt layer.

[0057] S303. Divide the area to be compacted into several rolling belts as shown according to the wheel width of the roller, the boundary information of the area to be compacted, and the overlapping distance of the rolling belts. In this embodiment, only two adjacent rolling belts are drawn, and the specific number of rolling belts is flexibly adjusted according to the actual situation. There is an overlapping area between adjacent rolling belts, and the width of the overlapping area is equal to the overlapping distance of the rolling belts. The specific method for dividing the rolling belts is as follows: Figure 2 By means of artificial intelligence, analyze the width and number of rolling belts according to the wheel width of the roller, the boundary information of the area to be compacted, and the overlapping distance of the rolling belts. Specifically, a BP neural network model is used for analysis. First, a three-layer BP neural network model is constructed, including an input layer, a hidden layer, and an output layer. In this embodiment, the wheel width of the roller, the boundary information of the area to be compacted, and the overlapping distance of the rolling belts are used as the inputs of the input layer. Therefore, the input layer has 3 nodes, and the outputs are the width and number of rolling belts, so there are a total of 2 nodes. For the hidden layer, the following formula is used in this embodiment to determine the number of nodes in the hidden layer:

[0058] where l is the number of nodes in the hidden layer, n is the number of nodes in the input layer, m is the number of nodes in the output layer, and a is a number between 1 and 10. In this embodiment, it is taken as 6. Therefore, the hidden layer has a total of 9 nodes. The BP neural network usually uses the Sigmoid differentiable function and the linear function as the activation functions of the network. In this embodiment, the S-shaped tangent function tansig is selected as the activation function of the hidden layer neurons. The S-shaped logarithmic function tansig is selected as the activation function of the output layer neurons for the prediction model. where l is the number of nodes in the hidden layer, n is the number of nodes in the input layer, m is the number of nodes in the output layer, and a is a number between 1 and 10. In this embodiment, it is taken as 6. Therefore, the hidden layer has a total of 9 nodes. The BP neural network usually uses the Sigmoid differentiable function and the linear function as the activation functions of the network. In this embodiment, the S-shaped tangent function tansig is selected as the activation function of the hidden layer neurons. The S-shaped logarithmic function tansig is selected as the activation function of the output layer neurons for the prediction model.

[0059] Then, according to the width, number, and overlapping distance of the rolling zones obtained from the analysis, divide the area to be compacted into several rolling zones.

[0060] S400, control each roller to move along the rolling zones in the area to be compacted respectively until the compaction operation of all rolling zones in the area to be compacted is completed, including:

[0061] Control each roller to move along the rolling zones in the area to be compacted respectively, and collect the pavement compaction degree of the corresponding rolling zones in real time.

[0062] Analyze whether the pavement compaction degree is greater than the preset compaction threshold. If so, control the roller to change lanes laterally to the adjacent rolling zone in the area to be compacted until the compaction operation of all rolling zones in the area to be compacted is completed. When changing lanes, first control the roller to drive out of the corresponding area to be compacted, and make the roller align with the adjacent rolling zone, and then re-enter the area to be compacted to perform the compaction work of the adjacent rolling zone. Since each roller only operates in the corresponding area to be compacted, there is no problem of path intersection, achieving the optimal balance between construction efficiency and quality.

[0063] Embodiment 2:

[0064] The basic principle of Embodiment 2 is the same as that of Embodiment 1. The difference is that when controlling each roller to move along the rolling zones in the area to be compacted until the compaction operation of all rolling zones in the area to be compacted is completed in Embodiment 2, only directly control one roller in the same area to be compacted, and the other rollers act as following rollers and operate synchronously with the leading roller. The specific control method is as follows:

[0065] Set one roller as the leading roller and the other rollers as following rollers.

[0066] Control the leading roller to move along the rolling zones in the area to be compacted, and collect the pavement compaction degree of the corresponding rolling zones in real time.

[0067] Analyze whether the pavement compaction degree is greater than the preset compaction threshold. If so, control the leading roller to change lanes laterally to the adjacent rolling zone in the area to be compacted until the compaction operation of all rolling zones in the area to be compacted is completed. In addition, when the difference in pavement compaction degree between adjacent rolling zones is greater than 5%, trigger the recompaction program and control the roller to perform the recompaction operation on the rolling zone with a lower pavement compaction degree again.

[0068] Each following roller obtains the operating parameters of the leading roller and synchronously performs compaction actions according to the obtained operating parameters. If the following roller loses the signal for more than 3 seconds during the following process, the last valid path stored locally is enabled. If the signal connection is still not restored after losing the signal for more than 5 seconds, the vehicle will stop automatically.

[0069] The above are only embodiments of the present invention. Specific structures and common knowledge such as characteristics well known in the art are not described in detail here. Those of ordinary skill in the art know all the common general technical knowledge in the technical field to which the invention belongs before the filing date or the priority date, can learn all the existing technologies in this field, and have the ability to apply conventional experimental means before this date. Those of ordinary skill in the art can, under the inspiration given in this application, combine their own abilities to complete and implement this solution. Some typical well-known structures or well-known methods should not become an obstacle for those of ordinary skill in the art to implement this application. It should be noted that for those skilled in the art, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the implementation effect of the present invention and the practicality of the patent. The protection scope required by this application should be based on the content of its claims, and the specific implementation manners described in the specification can be used to interpret the content of the claims.

Claims

1. An intelligent collaborative construction management method for a paving roller cluster, characterized in that: It includes the following steps: Obtain the designed total thickness value of the asphalt layer, the basic parameters of the rolling section, and the rolling resource parameters. The basic parameters of the rolling section include the road curvature radius, road slope, and road width. The rolling resource parameters include the working years of technicians and the maximum rolling width of the roller; Generate a division distance based on the designed total thickness value of the asphalt layer, the basic parameters of the rolling section, and the rolling resource parameters; Divide the paving section into several areas to be compacted along the paving direction according to the division distance; Divide each area to be compacted into several sub-areas to be compacted along the width direction of the paving surface; One roller is arranged in each sub-area to be compacted for the compaction operation of the corresponding sub-area to be compacted; Divide the sub-area to be compacted into several rolling belts according to the roller parameters and the basic parameters of the sub-area to be compacted; Control each roller to move along the rolling belts in its corresponding sub-area to be compacted until the compaction operation of all rolling belts in the sub-area to be compacted is completed.

2. The intelligent collaborative construction management method for a paving roller cluster according to claim 1, wherein: The calculation formula of the division distance is as follows: where L is the division distance, and L base is the reference division distance, α1 is the influence coefficient of the radius of curvature, and R morm is the radius of curvature of the road, α2 is the influence coefficient of the road slope, and S nor, is the road slope, α3 is the influence coefficient of the road width, and W nor, is the road width, α4 is the influence coefficient of the thickness, and X t is the design value of the total thickness of the asphalt layer, β1 is the empirical influence coefficient, and E norm is the working years of technicians, β2 is the equipment influence parameter, and M morm is the maximum rolling width of the roller.

3. The intelligent collaborative construction management method for a paving roller cluster according to claim 1, characterized in that: Dividing the sub-area to be compacted into several rolling belts according to the roller parameters and the basic parameters of the sub-area to be compacted includes: Obtain the roller parameters and the basic parameters of the sub-area to be compacted; The roller parameters include the wheel width and wheelbase of the roller; The basic parameters of the sub-area to be compacted include the curvature radius of the sub-area to be compacted, the actual thickness of the asphalt layer in the sub-area to be compacted, and the boundary information of the sub-area to be compacted; Generate an overlapping distance of the rolling belts according to the wheel width of the roller, the wheelbase of the roller, the curvature radius of the sub-area to be compacted, and the actual thickness of the asphalt layer; Divide the sub-area to be compacted into several rolling belts according to the wheel width of the roller, the boundary information of the sub-area to be compacted, and the overlapping distance of the rolling belts.

4. The intelligent collaborative construction management method for a paving roller cluster according to claim 3, characterized in that: The calculation formula of the overlapping distance of the rolling belts is as follows: In the formula, L overlap is the overlapping distance of the rolling belt, k is the overlapping coefficient, W is the wheel width of the roller, L is the wheelbase of the roller, R is the curvature radius of the area to be compacted, γ is the layer thickness correction value, and X a is the actual thickness of the asphalt layer.

5. The intelligent collaborative construction management method for a paving roller cluster according to claim 3, wherein: Dividing the sub-area to be compacted into several rolling belts according to the wheel width of the roller, the boundary information of the sub-area to be compacted, and the overlapping distance of the rolling belts includes: In an artificial intelligence manner, analyze the width and number of rolling belts according to the wheel width of the roller, the boundary information of the sub-area to be compacted, and the overlapping distance of the rolling belts. Take the wheel width of the roller, the boundary information of the sub-area to be compacted, and the overlapping distance of the rolling belts as the input of the input layer, and the width and number of rolling belts as the output of the output layer; Divide the sub-area to be compacted into several rolling belts according to the analyzed width, number, and overlapping distance of the rolling belts.

6. The intelligent collaborative construction management method for a paving roller cluster according to claim 1, wherein: Controlling each roller to move along the rolling belts in its corresponding sub-area to be compacted until the compaction operation of all rolling belts in the sub-area to be compacted is completed includes: Control each roller to move along the rolling belts in its corresponding sub-area to be compacted and collect the pavement compaction degree of the corresponding rolling belt in real time; Analyze whether the pavement compaction degree is greater than the preset compaction degree threshold. If so, control the roller to change lanes horizontally to the adjacent rolling belt in the sub-area to be compacted until the compaction operation of all rolling belts in the sub-area to be compacted is completed.

7. The intelligent collaborative construction management method for a paving roller cluster according to claim 1, characterized in that: Controlling each roller to move along the rolling belts in its corresponding sub-area to be compacted until the compaction operation of all rolling belts in the sub-area to be compacted is completed includes: Set one roller as the leading roller and the rest of the rollers as following rollers; Control the leading roller to move along the rolling belt in the to-be-compacted zone where it is located, and collect the pavement compactness of the corresponding rolling belt in real time; Analyze whether the pavement compactness is greater than the preset compactness threshold. If so, control the leading roller to change lanes laterally to the adjacent rolling belt in the to-be-compacted zone until the compaction operation of all rolling belts in the to-be-compacted zone is completed; Each following roller obtains the operating parameters of the leading roller and synchronously performs compaction actions with the leading roller according to the obtained operating parameters.

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