Unmanned construction machine group cooperative regulation and control method and system based on volume-mechanical detection

Abstract

The present application relates to a method and system for collaborative regulation of unmanned construction machine group based on volume-mechanics detection, the method comprising: establishing a qualified interval database of compaction degree-torsional shear strength; correcting the qualified interval database through a compaction degree correction model to obtain a corrected qualified interval database; before construction, calibrating the control parameters of the unmanned road roller and the unmanned paver at each compaction stage based on the corrected qualified interval database to obtain standard construction parameters; in the construction process, collecting multi-source sensing data of the construction layer in real time, matching and comparing the multi-source sensing data with the corrected qualified interval database to obtain compaction quality determination results; and adjusting the standard construction parameters according to the compaction quality determination results to adaptively control the unmanned road roller and the unmanned paver. The uniformity of construction quality and the stability of pavement structure are improved, and the collaborative operation and closed-loop regulation of the unmanned construction machine group are realized.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of asphalt pavement construction control, and particularly relates to an unmanned construction machine group collaborative regulation method and system based on volume-mechanical detection. BACKGROUND

[0002] Traditional asphalt pavement compaction construction usually relies on manually driven road rollers to roll on freshly paved high-temperature asphalt mixture, and the construction temperature is generally 150-180℃. Under such operating conditions, the operator not only needs to withstand the high-temperature operating environment for a long time, but also is exposed to harmful substances such as asphalt volatiles and dust, which poses significant occupational health risks. At the same time, the operating quality of the manually driven road roller is affected by subjective factors such as operating habits, mental state, and fatigue level, and problems such as uneven rolling quality and insufficient control accuracy are prone to occur. In addition, manual construction is greatly dependent on external conditions such as weather and light, and it is difficult to achieve all-weather high-efficiency operation. In contrast, unmanned road rollers and unmanned pavers can continuously operate in extreme environments such as high temperature, high humidity, and high altitude, which not only effectively reduces labor input and safety risks, but also enables 24-hour continuous uninterrupted construction, greatly improving construction efficiency. Therefore, the development of unmanned machine group collaborative operation and intelligent regulation technology for asphalt pavement construction has important engineering value and promotion significance.

[0003] However, the dynamic control strategy of existing unmanned road rollers mostly relies on construction experience or manually set initial process parameters, such as pre-fixed rolling speed, rolling passes, vibration frequency, and vibration amplitude, and is adjusted through simple threshold comparison during operation. This control mode ignores the real-time changes of material properties and structure state during construction, resulting in lagging regulation response and insufficient accuracy. In complex and variable construction site environments, such simplified control logic is prone to cause problems such as insufficient compaction, excessive compaction, or uneven compaction, which in turn affects the service performance and service life of the pavement structure.

[0004] For compaction quality regulation, some studies have attempted to introduce the compaction degree as a volume index in unmanned road roller construction, and adjust the rolling process parameters by comparing the measured compaction degree with the standard state compaction degree. However, due to the uneven spatial distribution of aggregates, asphalt, and mineral powder in the asphalt mixture during compaction, the mechanical properties under the same compaction degree differ significantly, and a single volume index cannot fully reflect the skeleton stability, shear resistance, and durability of the mixture. Therefore, the traditional regulation method based on compaction degree still has problems of insufficient scientificity and limited regulation effect in unmanned road roller construction.

[0005] Currently, the regulation methods of unmanned road rollers are mostly based on construction experience or preset threshold for parameter setting, lacking comprehensive analysis of dynamic changes of volume state and mechanical properties of asphalt mixture in the construction process, and difficult to realize scientific optimization and adaptive adjustment of operation parameters, which has deficiencies in precision and site adaptability. The compaction quality evaluation system generally takes single volume index such as compaction degree as the core, and cannot fully reflect the stability and shear resistance of the mixture skeleton structure, which is easy to cause quality defects such as insufficient compaction, excessive compaction or uneven compaction. In addition, the existing unmanned construction system still has limitations in real-time cooperation and linkage ability of machine group operation, and it is difficult to realize accurate determination and closed-loop regulation of compaction quality in the whole construction process. SUMMARY

[0006] In order to solve the above technical problems, the present application provides an unmanned construction machine group cooperative regulation method and system based on volume-mechanical detection.

[0007] The technical scheme adopted by the present application is:

[0008] In a first aspect, an unmanned construction machine group cooperative regulation method based on volume-mechanical detection is provided, comprising:

[0009] By testing the asphalt mixture test piece, a qualified interval database of compaction degree-torsional shear strength is established;

[0010] The compaction degree of the asphalt mixture test piece is detected, a compaction degree correction model is established, and the qualified interval database is corrected by the compaction degree correction model to obtain a corrected qualified interval database;

[0011] Before construction, the control parameters of the unmanned road rollers and the unmanned pavers in each compaction stage are calibrated based on the corrected qualified interval database to obtain standard construction parameters;

[0012] In the construction process, the multi-source perception data of the construction layer are collected in real time, and the multi-source perception data are matched and compared with the corrected qualified interval database to obtain a compaction quality determination result;

[0013] The standard construction parameters are adjusted according to the compaction quality determination result, so as to adaptively control the unmanned road rollers and the unmanned pavers.

[0014] Further, by testing the asphalt mixture test piece, a qualified interval database of compaction degree-torsional shear strength is established, comprising:

[0015] Under laboratory conditions, asphalt mixture test pieces with different compaction states are prepared according to the designed mix proportion, a plurality of compaction degree gradients are set, and torsional shear strength tests are carried out under corresponding temperature conditions to establish the evolution relationship between compaction degree and torsional shear strength;

[0016] For each experimental compaction degree K i and its corresponding experimental temperature T i Determine the corresponding experimental torsional shear strength τ i The qualified range, the expression for the qualified range is:

[0017] ;

[0018] in, For τ i The average value, σ i For τ i The standard deviation, and τ i coefficient of variation C v Satisfy C v The requirement is ≤0.1;

[0019] Establish a database of acceptable intervals for compaction degree and torsional shear strength based on the acceptable interval expression.

[0020] Furthermore, compaction tests were conducted on asphalt mixture specimens, and a compaction correction model was established. The corrected acceptable interval database was obtained by correcting the database using the compaction correction model, including:

[0021] The compaction degree of asphalt mixture specimens under different compaction conditions was tested using a nucleus-free density meter to obtain the original compaction degree K. w ;

[0022] According to K w With K i The measurement error correction amount ΔK is calculated, and the formula for ΔK is:

[0023] ;

[0024] in, For K w The average value;

[0025] Based on ΔK and K w A compaction degree correction model is constructed, and its expression is as follows:

[0026] ;

[0027] Among them, K j For K w Corrected compaction degree;

[0028] The corrected qualified interval database is obtained by correcting the qualified interval database using the compaction correction model.

[0029] Further, before construction, the control parameters of the unmanned road roller and the unmanned paver in each compaction stage are calibrated based on the revised qualified interval database to obtain standard construction parameters, including:

[0030] Before construction, based on the revised qualified interval database, the unmanned paver and the unmanned road roller are controlled to complete the work of each compaction stage in turn according to the preset standard operating parameters under the ideal construction condition of the test road section, and the compaction stage includes the initial compaction stage, the recompaction stage and the final compaction stage;

[0031] In each compaction stage, the ideal compaction degree and the ideal torsional shear strength of the construction layer are synchronously collected through the nuclear density gauge and the shear characteristic detection device of the integrated temperature sensing module;

[0032] In the initial compaction stage, the standard rolling speed V s1 , the standard vibration frequency f s1 , the standard amplitude A s1 and the standard rolling number N s1 of the unmanned steel wheel road roller are calibrated in combination with the real-time evolution characteristics of the ideal compaction degree and the ideal torsional shear strength;

[0033] In the recompaction stage, the standard rolling speed V s2 and the standard rolling number N s2 of the unmanned rubber-tired road roller are determined according to the change trend of the ideal compaction degree and the ideal torsional shear strength;

[0034] In the final compaction stage, the standard rolling speed V s3 and the standard rolling number N s3 of the unmanned steel wheel road roller are determined according to the interval in which the ideal torsional shear strength tends to be stable;

[0035] Based on the standard rolling speed and the standard rolling number of the unmanned steel wheel road roller and the unmanned rubber-tired road roller in each compaction stage, the standard paving speed V p of the unmanned paver is determined by reverse deduction, and the standard construction parameters are obtained by comprehensively considering the parameters of the unmanned steel wheel road roller, the unmanned rubber-tired road roller and the unmanned paver.

[0036] Further, in the construction process, the multi-source sensing data of the construction layer are collected in real time, and the multi-source sensing data are matched and compared with the revised qualified interval database to obtain the compaction quality determination result, including:

[0037] After the unmanned steel wheel road roller and the unmanned rubber-tired road roller complete the rolling work in the construction process, the measured compaction degree is collected by the nuclear density gauge at the same detection position of the construction layer, the measured temperature and the measured torsional shear strength are collected by the torsional shear strength detection device, and the positioning information and the time information are collected by the positioning and timing device;

[0038] Based on the space-time registration algorithm, the measured compaction degree, the measured temperature and the measured torsional shear strength are time-series aligned and spatially matched according to the positioning information and the time information, and a unified format compaction state data package is formed by fusion;

[0039] According to the matching comparison between the compaction state data package and the corrected qualified interval database, the compaction quality determination result is obtained.

[0040] Further, according to the matching comparison between the compaction state data package and the corrected qualified interval database, the compaction quality determination result is obtained, including:

[0041] The positioning information R S and the time information t S of the compaction state data package are analyzed. S S ;

[0042] K S and τ S are matched and compared with the corrected qualified interval database.

[0043] If K S corresponding τ S ∈ , it is determined that the compaction quality determination result at R S at t S is qualified.

[0044] If K S corresponding τ S > , it is determined that the compaction quality determination result at R S at t S is over-compacted.

[0045] If K S corresponding τ S < , it is determined that the compaction quality determination result at R S at t S is under-compacted.

[0046] Further, when the compaction quality determination result is over-compacted,

[0047] According to the compaction quality determination result, the standard construction parameters are adjusted, including:

[0048] According to the compaction quality determination result being over-compacted, the Boolean determination value Q is determined, and the expression of Q is:

[0049] ;

[0050] In the initial compaction stage, the standard rolling speed V s1 ​adjusting to , the standard vibration frequency f s1 adjusting to , the standard amplitude A s1 adjusting to , the standard rolling number N s1 adjusting to , k V1 , k f1 , k A1 and k N1 are preset control coefficients;

[0051] In the complex pressure stage, the standard rolling speed V s2 of the unmanned rubber-tired roller is adjusted to , the standard rolling number N s2 is adjusted to , k V2 and k N2 are preset control coefficients;

[0052] In the final pressure stage, the standard rolling speed V s3 of the unmanned steel-tired roller is adjusted to , the standard rolling number N s3 is adjusted to , k V3 and k N3 are preset control coefficients;

[0053] The standard paving speed V p of the unmanned paver is adjusted to , k p1 is a preset control coefficient.

[0054] Further, when the compaction quality determination result is under-compaction,

[0055] According to the compaction quality determination result, the standard construction parameters are adjusted, including:

[0056] According to the compaction quality determination result, the Boolean determination value Q is determined for over-compaction, and the expression of Q is:

[0057] ;

[0058] In the initial pressure stage, the standard rolling speed V s1 of the unmanned steel-tired roller is adjusted to , the standard vibration frequency f s1 is adjusted to , the standard amplitude A s1 is adjusted to , the standard rolling number N s1 is adjusted to , , , and is a preset control coefficient;

[0059] In the secondary compression stage, the standard rolling speed V s2 is adjusted to , and the standard rolling number N s2 is adjusted to , and is a preset control coefficient;

[0060] In the final compression stage, the standard rolling speed V s3 of the unmanned steel wheel roller is adjusted to , and the standard rolling number N s3 is adjusted to , and is a preset control coefficient;

[0061] The standard paving speed V p of the unmanned paver is adjusted to , is a preset control coefficient.

[0062] In the second aspect, an unmanned construction machine group cooperative control system based on volume-mechanical detection is provided, comprising:

[0063] A qualified interval database establishment module is configured to establish a qualified interval database of compaction degree-torsional shear strength by testing asphalt mixture test pieces.

[0064] A compaction degree correction module is configured to detect the compaction degree of the asphalt mixture test pieces, establish a compaction degree correction model, and correct the qualified interval database through the compaction degree correction model to obtain a corrected qualified interval database.

[0065] A control parameter calibration module is configured to calibrate the control parameters of the unmanned road rollers and the unmanned pavers in each compaction stage based on the corrected qualified interval database before construction to obtain standard construction parameters.

[0066] A compaction quality determination module is configured to collect multi-source sensing data of the construction layer in real time during construction, match and compare the multi-source sensing data with the corrected qualified interval database, and obtain a compaction quality determination result.

[0067] An unmanned construction machine group cooperative control module is configured to adjust the standard construction parameters according to the compaction quality determination result to perform self-adaptive control on the unmanned road rollers and the unmanned pavers.

[0068] The present application has the following beneficial effects:

[0069] The qualified interval database of compaction degree-torsional shear strength is established by testing the asphalt mixture test piece; the compaction degree correction model is established by testing the compaction degree of the asphalt mixture test piece, and the qualified interval database is corrected by the compaction degree correction model to obtain the corrected qualified interval database; before construction, the control parameters of the unmanned road roller and the unmanned paver in each compaction stage are calibrated based on the corrected qualified interval database to obtain the standard construction parameters; in the construction process, the multi-source sensing data of the construction layer are collected in real time, and the multi-source sensing data are matched and compared with the corrected qualified interval database to obtain the compaction quality determination result; the standard construction parameters are adjusted according to the compaction quality determination result, so that the unmanned road roller and the unmanned paver are adaptively controlled; the double-index collaborative qualified interval database integrating the compaction degree and the torsional shear strength is constructed, and the correction model of the non-nuclear density meter and the standardized parameter calibration of the test section are combined to realize the accurate operation control of the unmanned road roller and the unmanned paver in the whole construction process; the volume-mechanical comprehensive determination result of the compaction quality can be dynamically obtained on the construction site, and the optimization control instructions for the rolling speed, the vibration frequency, the amplitude, the rolling times, the paving speed and the driving path are automatically generated and issued according to the determination logic of the corrected qualified interval database, so that the adaptive matching of the equipment operation parameters and the site working conditions in each construction stage is ensured; not only the quality problems such as insufficient compaction, overcompaction and unevenness are effectively avoided, but also the uniformity of the construction quality and the stability of the pavement structure are significantly improved, and the collaborative operation and closed-loop control of the unmanned construction machine group are realized, so that the construction efficiency and the long-term service performance of the pavement are greatly improved. BRIEF DESCRIPTION OF DRAWINGS

[0070] Figure 1 The flow chart of the unmanned construction machine group collaborative control method based on volume-mechanical detection of the present application;

[0071] Figure 2 The structural diagram of the unmanned construction machine group collaborative control system based on volume-mechanical detection of the present application. DETAILED DESCRIPTION

[0072] The present application will be further described below in conjunction with the drawings. The following examples are only used to more clearly illustrate the technical solutions of the present application, and cannot be used to limit the protection scope of the present application.

[0073] The construction collaborative control platform applying the unmanned construction machine group collaborative control method based on volume-mechanical detection in the present application establishes a high-speed wireless data transmission path with the unmanned construction machine group, the non-nuclear density meter and the torsional shear strength detection device integrated with the temperature sensing module, so as to realize data interaction;

[0074] The unmanned construction machine group includes an unmanned steel wheel road roller, an unmanned rubber tire road roller and an unmanned paver.

[0075] AsFigure 1 As shown, the embodiment of the present application provides a method for collaborative regulation of unmanned construction machine groups based on volume-mechanical detection, comprising:

[0076] 101. A reasonable interval database of compaction degree-torsional shear strength is established by testing asphalt mixture specimens;

[0077] In this embodiment, under laboratory conditions, asphalt mixture specimens in different compaction states are prepared according to the designed mix proportion, a plurality of compaction degree gradients are set, for example, 90%, 92%, 94%, 96%, and 98%, and torsional shear strength tests are carried out under corresponding temperature conditions to establish the evolution relationship between compaction degree and torsional shear strength.

[0078] For each experimental compaction degree K i and its corresponding experimental temperature T i , the qualified interval of the corresponding experimental torsional shear strength τ i is determined, and the qualified interval expression is:

[0079] ;

[0080] wherein, is the average value of τ i , σ i is the standard deviation of τ i , and the coefficient of variation C i of τ v satisfies the requirement of C v ≤0.1;

[0081] The qualified interval database of compaction degree-torsional shear strength is established according to the qualified interval expression.

[0082] 102. The compaction degree of the asphalt mixture specimen is detected, a compaction degree correction model is established, and the qualified interval database is corrected by the compaction degree correction model to obtain a corrected qualified interval database;

[0083] In this embodiment, the compaction degree of the asphalt mixture specimen in different compaction states in the above laboratory conditions is detected by using a nuclear density gauge to obtain the original compaction degree K w ;

[0084] The measurement error correction amount ΔK is calculated according to K w and K i , and the calculation formula of ΔK is:

[0085] ;

[0086] wherein, is the average value of K w ;

[0087] According to ΔK and K w The compaction correction model is constructed, and the expression of the compaction correction model is:

[0088] ;

[0089] Wherein, K j is K w The corrected compaction degree;

[0090] The qualified interval database is corrected through the compaction correction model to obtain a corrected qualified interval database;

[0091] The construction of the corrected qualified interval database can correct the qualified interval database of the compaction degree-torsional shear strength established under the laboratory conditions and the compaction degree error under the actual scene.

[0092] 103, before construction, based on the corrected qualified interval database, the control parameters of the unmanned road roller and the unmanned paver in each compaction stage are calibrated to obtain standard construction parameters;

[0093] In this embodiment, before formal construction, based on the corrected qualified interval database, the ideal construction conditions of the test road section are simulated, and the unmanned paver and the unmanned road roller are controlled to complete the work of each compaction stage in turn according to the preset standard operation parameters, and the compaction stages include the initial compaction stage, the recompaction stage and the final compaction stage;

[0094] In each compaction stage, the ideal compaction degree and the ideal torsional shear strength of the construction layer are synchronously collected through the nuclear density gauge and the shear characteristic detection device integrated with the temperature sensing module;

[0095] In the initial compaction stage, the standard rolling speed V s1 , the standard vibration frequency f s1 , the standard amplitude A s1 and the standard rolling number N s1 of the unmanned steel wheel road roller are calibrated in combination with the real-time evolution characteristics of the ideal compaction degree and the ideal torsional shear strength;

[0096] In the recompaction stage, the standard rolling speed V s2 and the standard rolling number N s2 of the unmanned rubber-tired road roller are determined according to the change trend of the ideal compaction degree and the ideal torsional shear strength;

[0097] In the final compaction stage, the standard rolling speed V s3 and the standard rolling number N s3 of the unmanned steel wheel road roller are determined according to the interval in which the ideal torsional shear strength tends to be stable;

[0098] Based on the standard rolling speed and the standard rolling times of the unmanned steel wheel roller and the unmanned rubber tire roller in each compaction stage, the standard paving speed of the unmanned paver is determined V p The process of backstepping is as follows:

[0099] Firstly, taking the operation requirements of the unmanned steel wheel roller and the unmanned rubber tire roller as constraints, the standard parameters of the unmanned steel wheel roller and the unmanned rubber tire roller in the initial compaction, the secondary compaction and the final compaction are known respectively as (V1, T1), (V2, T2) and (V3, T3) V s1 , N s1 ), (V2, T2) and (V3, T3) V s2 , N s2 ), (V2, T2) and (V3, T3) V s3 , N s3 ) ; the theoretical processing time per unit length is calculated as:

[0100] ;

[0101] wherein, is the parallel / overlapping operation reduction coefficient, when multiple same devices are in parallel or in strip overlapping, reflects the efficiency gain, and the default value is 1, and accordingly the upper limit speed of the unmanned machine group can be obtained, and the expression of the upper limit speed is:

[0102] ;

[0103] The upper limit speed gives the maximum allowable forward speed of the unmanned paver under the premise that no downstream rolling bottleneck is caused; the maximum allowable forward speed of the unmanned paver under the premise that no downstream rolling bottleneck is caused; secondly, in order to meet the thermal-time window and operation safety constraints, the minimum safety longitudinal distance between the unmanned paver and the first roller D min and the allowed earliest rolling waiting time t min are introduced, so as to ensure that the paving can be started within t min after paving and to avoid the unmanned roller from rear-ending, the paving speed of the unmanned paver should not be lower than the safety speed, and the calculation formula of the safety speed is:

[0104] ;

[0105] In addition, the followable constraint of the first roller also needs to be considered, in order to ensure the coordination between the unmanned paver and the initial compaction operation, the paving speed should not exceed the running capacity of the roller in the initial compaction stage, and the paving speed is taken asV L = V s1 ;

[0106] In summary, the standard paving speed for unmanned pavers is determined as follows:

[0107] V p =max( V safe ,min( V H , V L ));

[0108] Ultimately, will { V p , V s1 , N s1 , V s2 , N s2 , V s3 , N s3 The parameters, including vibration frequency and amplitude, are compiled together to form a standard construction parameter set for the fleet, providing a standard basis for the full-process coordinated control of the unmanned construction fleet.

[0109] Standard construction parameters are obtained by combining the parameters of unmanned steel wheel rollers, unmanned rubber-tired rollers, and unmanned pavers.

[0110] 104. During the construction process, multi-source sensing data of the construction layer is collected in real time, and the multi-source sensing data is matched and compared with the corrected qualified interval database to obtain the compaction quality judgment result.

[0111] In this embodiment, after the unmanned steel wheel roller and the unmanned rubber-tired roller complete the compaction operation during the construction process, the measured compaction degree is collected at the same detection position of the construction layer by a non-nuclear density meter, the measured temperature and measured torsional shear strength are collected by a torsional shear strength detection device, and the positioning information and time information are collected by a positioning and timing device.

[0112] Based on the spatiotemporal registration algorithm, the measured compaction degree, measured temperature, and measured torsional shear strength are time-series aligned and spatially matched according to the location and time information, and fused to form a unified compaction status data package. The unified compaction status data package provides basic data support for subsequent compaction quality evaluation and intelligent control of construction parameters.

[0113] Location information R is obtained by parsing the compaction status data packet. STime information t S Measured compaction degree K at time S and measured torsional shear strength τ S ;

[0114] K S and τ S Match and compare with the corrected qualified interval database;

[0115] If K S The corresponding τ S ∈ Then determine R S t S The compaction quality assessment result at that time was qualified;

[0116] If K S The corresponding τ S > Then determine R S t S The compaction quality assessment result at that time was over-compaction;

[0117] If K S The corresponding τ S < Then determine R S t S The compaction quality assessment result at that time was under-compaction.

[0118] 105. Adjust standard construction parameters based on the compaction quality assessment results to enable adaptive control of unmanned road rollers and unmanned pavers.

[0119] In this embodiment, when the compaction quality judgment result is qualified, no adjustment is required to the standard construction parameters;

[0120] When the compaction quality assessment result is over-compaction,

[0121] Based on the compaction quality judgment result, a Boolean judgment value Q is determined for over-compression. The expression for Q is:

[0122] ;

[0123] In the initial compaction stage, the standard compaction speed V of the unmanned steel wheel roller is set. s1 Adjusted to Standard vibration frequency f s1 Adjusted to Standard amplitude A s1 Adjusted to Standard number of compaction passes N s1 Adjusted to k V1 k f1 k A1 and kN1 The preset control coefficient;

[0124] During the secondary compaction stage, the standard compaction speed V of the unmanned rubber-tired roller is increased. s2 Adjusted to Standard number of compaction passes N s2 Adjusted to k V2 and k N2 The preset control coefficient;

[0125] In the final compaction stage, the standard compaction speed V of the unmanned steel wheel roller is increased. s3 Adjusted to Standard number of compaction passes N s3 Adjusted to k V3 and k N3 The preset control coefficient;

[0126] Because the increased operating speed of unmanned steel-wheel rollers and unmanned rubber-tired rollers after adjustment has led to an improvement in the overall compaction efficiency, in order to maintain the continuity and matching of construction procedures, it is necessary to adjust the standard paving speed V of the unmanned paver. p Adjusted to k p1 A preset control coefficient is used to ensure the rhythm of paving and compaction is coordinated.

[0127] When the compaction quality assessment result is under-compaction.

[0128] In the initial compaction stage, the standard compaction speed V of the unmanned steel wheel roller is set. s1 Adjusted to Standard vibration frequency f s1 Adjusted to Standard amplitude A s1 Adjusted to Standard number of compaction passes N s1 Adjusted to , , , and The preset control coefficient;

[0129] During the secondary compaction stage, the standard compaction speed V of the unmanned rubber-tired roller is increased. s2 Adjusted to Standard number of compaction passes N s2 Adjusted to , and The preset control coefficient;

[0130] In the final compaction stage, the standard compaction speed V of the unmanned steel wheel roller is increased. s3 Adjusted to Standard number of compaction passes N s3 Adjusted to , and The preset control coefficient;

[0131] When the compaction quality is determined to be insufficient and parameter adjustments are triggered, the operating speeds of the unmanned steel wheel roller and the unmanned rubber-tired roller will be reduced accordingly, resulting in a decrease in the overall compaction efficiency. To maintain the continuity and matching of construction procedures and avoid rhythm imbalance between paving and compaction, the standard paving speed V of the unmanned paver will be adjusted. p Adjusted to , This is the preset control coefficient.

[0132] The beneficial effects achieved by the embodiments of the present invention are as follows:

[0133] This invention constructs a database of synergistic acceptable intervals for compaction degree and torsional shear strength under laboratory conditions, avoiding the limitations of relying solely on volumetric indicators such as compaction degree. It enables simultaneous evaluation of the compactness and mechanical properties of asphalt mixtures, effectively identifying problems such as insufficient compaction, excessive compaction, and uneven compaction. This improves the accuracy and scientific nature of compaction quality judgment from the source, providing a reliable basis for precise control during construction.

[0134] By introducing a two-level correction mechanism—indoor and on-site—and using a nucleus-free density meter to test specimens with different compaction degrees in the laboratory, a correction model was established, followed by a secondary correction based on test section data. This significantly improved the measurement accuracy and adaptability of the nucleus-free density meter in actual construction environments. This correction method effectively overcomes measurement deviations caused by the equipment under different construction conditions, ensuring the comparability and consistency of compaction degree data under different working conditions.

[0135] Under ideal working conditions in the test section, this invention calibrated the parameters of unmanned road rollers and unmanned pavers at each compaction stage, and established a standard construction parameter system covering rolling speed, vibration frequency, amplitude, number of rolling passes and paving speed. This system can be directly transferred to large-scale construction, enabling rapid deployment and precise adaptation of construction equipment parameter configuration, and improving the organization efficiency and quality stability of on-site construction.

[0136] When underpressure or overpressure is detected, the operating parameters of the unmanned roller and the speed of the unmanned paver can be optimized simultaneously to ensure that the rhythm of each process is matched in space and time, and realize the collaborative optimization of the unmanned construction machine group and the closed-loop control of the entire process of construction quality.

[0137] Through dynamic control, the compaction process can automatically optimize the construction rhythm according to changes in material properties and site conditions. This avoids energy consumption and construction time waste caused by repeated rolling, and also prevents skeleton damage and shear performance degradation caused by over-compaction. While ensuring the uniformity of construction quality, this method can effectively extend the service life of the pavement and significantly improve construction economy and durability.

[0138] Based on the above embodiments, the collaborative control method for unmanned construction machine swarms based on volume-mechanical detection is described below through embodiments.

[0139] like Figure 2 As shown, this embodiment of the invention provides a collaborative control system for unmanned construction machinery fleets based on volumetric-mechanical detection, comprising:

[0140] The qualified interval database establishment module 201 is used to establish a qualified interval database of compaction degree-torsional shear strength by testing asphalt mixture specimens.

[0141] The compaction correction module 202 is used to test the compaction of asphalt mixture specimens, establish a compaction correction model, and obtain a corrected qualified interval database by correcting the qualified interval database through the compaction correction model.

[0142] The control parameter calibration module 203 is used to calibrate the control parameters of the unmanned road roller and unmanned paver at each compaction stage based on the corrected qualified interval database before construction, so as to obtain standard construction parameters.

[0143] The compaction quality judgment module 204 is used to collect multi-source sensing data of the construction layer in real time during the construction process, match and compare the multi-source sensing data with the corrected qualified interval database, and obtain the compaction quality judgment result.

[0144] The unmanned construction machine group collaborative control module 205 is used to adjust the standard construction parameters based on the compaction quality judgment results, thereby enabling adaptive control of the unmanned road roller and unmanned paver.

[0145] The beneficial effects achieved by this invention are as follows:

[0146] The qualified interval database establishment module 201 establishes a qualified interval database of compaction degree and torsional shear strength by testing asphalt mixture specimens; the compaction degree correction module 202 conducts compaction degree tests on asphalt mixture specimens, establishes a compaction degree correction model, and corrects the qualified interval database through the compaction degree correction model to obtain a corrected qualified interval database; the control parameter calibration module 203 calibrates the control parameters of unmanned rollers and unmanned pavers at each compaction stage based on the corrected qualified interval database before construction to obtain standard construction parameters; the compaction quality judgment module 204 collects multi-source sensing data of the construction layer in real time during construction, matches and compares the multi-source sensing data with the corrected qualified interval database to obtain the compaction quality judgment result; the unmanned construction machine group collaborative control module 205 adjusts the standard construction parameters according to the compaction quality judgment result, thereby performing adaptive control of unmanned rollers and unmanned pavers. By constructing a dual-index collaborative qualified interval database integrating compaction degree and torsional shear strength, and combining a corrected model without a core density meter with standardized parameter calibration of test sections, this invention achieves precise operational control of unmanned rollers and pavers throughout the entire construction process. The invention can dynamically acquire the volumetric-mechanical comprehensive evaluation results of compacted material at the construction site, and automatically generate and issue optimized control commands for rolling speed, vibration frequency, amplitude, number of rolling passes, paving speed, and travel path based on the judgment logic of the corrected qualified interval database. This ensures adaptive matching of equipment operating parameters with site conditions at each construction stage. It not only effectively avoids quality problems such as insufficient compaction, over-compaction, and unevenness, significantly improving the uniformity of construction quality and the stability of the pavement structure, but also realizes collaborative operation and closed-loop control of unmanned construction machine fleets, greatly improving construction efficiency and the long-term service performance of the pavement.

[0147] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0148] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0149] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0150] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0151] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of the claims of the present invention pending approval.

Claims

1. A method for collaborative regulation of a group of unmanned construction machines based on volume-mechanical detection, characterized in that, The application relates to a method for self-adaptive control of unmanned road rollers and unmanned pavers. The method comprises the following steps: a qualified interval database of compaction degree-torsional shear strength is established by testing asphalt mixture test pieces; compaction degree detection is performed on the asphalt mixture test pieces, a compaction degree correction model is established, and a corrected qualified interval database is obtained by correcting the qualified interval database through the compaction degree correction model; before construction, control parameters of the unmanned road rollers and the unmanned pavers in each compaction stage are calibrated based on the corrected qualified interval database, and standard construction parameters are obtained; in the construction process, multi-source sensing data of a construction layer are collected in real time, the multi-source sensing data are matched and compared with the corrected qualified interval database, and a compaction quality determination result is obtained; the standard construction parameters are adjusted according to the compaction quality determination result, so that self-adaptive control is performed on the unmanned road rollers and the unmanned pavers; before construction, control parameters of the unmanned road rollers and the unmanned pavers in each compaction stage are calibrated based on the corrected qualified interval database, and standard construction parameters are obtained; before construction, the ideal construction conditions of a test road section are simulated based on the corrected qualified interval database, the unmanned pavers and the unmanned road rollers are controlled to sequentially complete the work of each compaction stage according to preset standard operation parameters; in each compaction stage, the ideal compaction degree and the ideal torsional shear strength of the construction layer are synchronously collected through a non-nuclear density gauge and a shear characteristic detection device integrated with a temperature sensing module; the standard rolling speed and the standard rolling number of the unmanned road rollers are obtained according to the ideal compaction degree and the ideal torsional shear strength; 2. The method of claim 1, wherein, the standard paving speed of the unmanned pavers is inversely determined based on the standard rolling speed and the standard rolling number, and the standard construction parameters are obtained by comprehensively considering the parameters of the unmanned road rollers and the unmanned pavers. The unmanned road rollers comprise unmanned steel wheel road rollers and unmanned rubber wheel road rollers, and the compaction stages comprise an initial compaction stage, a recompaction stage and a final compaction stage. In the initial pressure stage, the standard rolling speed V of the unmanned steel wheel roller is calibrated in combination with the real-time evolution characteristics of the ideal compaction degree and the ideal torsional shear strength s1 , the standard vibration frequency f s1 , the standard vibration amplitude A s1 , and the standard rolling number N s1 . In the re-pressing phase, according to the variation trend of the ideal compactness and the ideal torsional shear strength, the standard rolling speed V of the unmanned rubber-tired roller is determined s2 and the standard rolling number N of the unmanned rubber-tired roller is determined s2 ; In the final pressure stage, according to the interval in which the ideal torsional shear strength tends to be stable, the standard rolling speed V of the unmanned steel wheel roller is determined s3 and the standard rolling number N s3 .

3. The method of claim 2, wherein, The standard rolling speed and the standard rolling number of the unmanned road rollers are obtained according to the ideal compaction degree and the ideal torsional shear strength. The qualified interval database of compaction degree-torsional shear strength is established by testing the asphalt mixture test pieces. For each experimental compaction degree K i and its corresponding experimental temperature T i , a qualified interval of the corresponding experimental torsional shear strength τ i is determined, and the qualified interval is expressed as: ； Wherein, the is the average value of the i , the i is the standard deviation of the i , and the coefficient of variation C i of the v satisfies the requirement that C v ≤0.

1. Under laboratory conditions, asphalt mixture test pieces in different compaction states are prepared according to a designed mixing ratio, a plurality of compaction degree gradients are set, and torsional shear strength tests are performed under corresponding temperature conditions, so that an evolution relationship between the compaction degree and the torsional shear strength is established.

4. The method of claim 3, wherein, The qualified interval database of compaction degree-torsional shear strength is established according to the qualified interval expression. The coreless density instrument is used to detect the compaction degree of the asphalt mixture test piece in different compaction states, and the original compaction degree K is obtained w ; According to the K w With the K i The measurement error correction amount ΔK is calculated, and the calculation formula of the ΔK is: ； wherein the K w the average value of According to the ΔK and the K w A compaction correction model is constructed, and an expression of the compaction correction model is: ； Wherein, the K j is the K w corrected compaction degree; The compaction degree correction model is used to correct the qualified interval database to obtain the corrected qualified interval database.

5. The method of claim 4, wherein, In the construction process, multi-source sensing data of a construction layer are collected in real time, the multi-source sensing data are matched and compared with the corrected qualified interval database, and a compaction quality determination result is obtained. In the construction process, after the unmanned steel wheel roller and the unmanned rubber wheel roller complete the rolling work, the actual compaction degree is collected by the nuclear-free density gauge at the same detection position of the construction layer, the actual temperature and the actual torsional shear strength are collected by the torsional shear strength detection device, and the positioning information and the time information are collected by the positioning and timing device; Based on the space-time registration algorithm, the actual compaction degree, the actual temperature and the actual torsional shear strength are time-series aligned and spatially matched according to the positioning information and the time information, and a unified format compaction state data packet is formed by fusion; According to the compaction state data packet and the modified qualified interval database, a compaction quality judgment result is obtained.

6. The method of claim 5, wherein, According to the compaction state data packet and the modified qualified interval database, a compaction quality judgment result is obtained. resolving the compaction state data packet to obtain the positioning information R S at the time information t S the measured compaction degree K at the time instant S and the measured torsional shear strength τ S ; The K S and the τ S are matched and compared with the revised qualified interval database; If the K S Corresponding τ S ∈ Then the R S At the t S The compaction quality determination result is qualified. If the K S Corresponding τ S > If the R S At the t S time, the compaction quality determination result is over-compaction. If the K S Corresponding τ S < If the R S At the t S The compaction quality determination result at the t 7. The method of claim 6, wherein, When the compaction quality judgment result is over-compaction, According to the compaction quality judgment result, a Boolean judgment value Q is determined, and the expression of Q is: When the compaction quality judgment result is under-compaction, ； In the initial compaction stage, the standard compaction speed V of the unmanned steel wheel roller is... s1 Adjusted to The standard vibration frequency f s1 Adjusted to The standard amplitude A s1 Adjusted to The standard number of compaction passes N s1 Adjusted to The k V1 The k f1 The k A1 and the k N1 The preset control coefficient; During the secondary compaction stage, the standard compaction speed V of the unmanned rubber-tired roller is increased. s2 Adjusted to The standard number of compaction passes N s2 Adjusted to The k V2 and the k N2 The preset control coefficient; In the final pressure stage, the standard rolling speed V of the unmanned steel wheel roller is adjusted to V s3 Adjusting to , the standard rolling number N of the unmanned steel wheel roller is adjusted to N s3 Adjusting to , the k V3 and the k N3 are preset control coefficients. adjusting the standard paving speed V of the unmanned paving machine p adjusting to , the k p1 is a preset control coefficient.

8. The method of claim 6, wherein, According to the compaction quality judgment result, a Boolean judgment value Q is determined, and the expression of Q is: Including: The qualified interval database establishment module is used to establish a qualified interval database of compaction degree-torsional shear strength by testing the asphalt mixture test piece; ； In the initial pressure stage, the standard rolling speed V s1 is adjusted to , the standard vibration frequency f s1 is adjusted to , the standard amplitude A s1 is adjusted to , the standard rolling number N s1 is adjusted to , the , the , the and the are preset control coefficients. In the said re-pressing stage, the standard rolling speed V of the unmanned rubber-tired road roller is adjusted to V s2 , the standard rolling number N is adjusted to N , the standard rolling speed V is adjusted to V s2 , the standard rolling number N is adjusted to N , the standard rolling speed V is adjusted to V , the standard rolling number N is adjusted to N , and the said and the said are preset control coefficients. In the final pressure stage, the standard rolling speed V of the unmanned steel wheel roller is adjusted to V s3 , the standard rolling number N is adjusted to N , the standard rolling speed V is adjusted to V s3 , the standard rolling number N is adjusted to N , the standard rolling speed V is adjusted to V , the standard rolling number N is adjusted to N , and the preset control coefficient is adjusted to said standard paving speed V of said unmanned paver p is adjusted to , said is a preset control coefficient.

9. An unmanned construction machine group cooperative control system based on volume-mechanical detection, characterized in that, The compaction degree correction module is used to detect the compaction degree of the asphalt mixture test piece, establish a compaction degree correction model, and correct the qualified interval database to obtain a modified qualified interval database; The control parameter calibration module is used to simulate the ideal construction conditions of the test road section based on the modified qualified interval database before construction, and the unmanned paver and the unmanned roller complete the work of each compaction stage according to the preset standard operation parameters; the ideal compaction degree and the ideal torsional shear strength of the construction layer are synchronously collected by the nuclear-free density gauge and the shear characteristic detection device of the integrated temperature sensing module in each compaction stage; the standard rolling speed and the standard rolling number of the unmanned roller are obtained according to the ideal compaction degree and the ideal torsional shear strength; the standard paving speed of the unmanned paver is determined by reverse calculation based on the standard rolling speed and the standard rolling number, and the standard construction parameters are obtained by comprehensively considering the parameters of the unmanned roller and the unmanned paver; The compaction quality judgment module is used to collect multi-source sensing data of the construction layer in real time during the construction process, match and compare the multi-source sensing data with the modified qualified interval database, and obtain a compaction quality judgment result; The unmanned construction machine group cooperative control module is used to adjust the standard construction parameters according to the compaction quality judgment result, so as to adaptively control the unmanned roller and the unmanned paver. ​ ​

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