A method for continuously detecting and evaluating compaction quality of fillers based on a degree of oscillation

Abstract

The application provides a kind of compaction quality continuous detection evaluation method based on the extent of hunting, comprising: carrying out compaction test: real-time collection of vertical vibration acceleration of vibrating wheel, vertical vibration acceleration of upper rack and eccentric block position data;Calculate the vibrating wheel-filler interaction force of each detection period per hour;Vibrating wheel-filler interaction force curve is analyzed, to determine whether hunting phenomenon occurs in the detection period, and the compaction hunting value CJV calculation model of different working conditions is used to calculate the compaction hunting value CJV corresponding to the detection period;Establish compaction quality detection evaluation model based on CJV. The compaction quality of rolling surface is continuously detected and evaluated by using CJV. The application realizes real-time, continuous and full coverage detection of compaction quality, which can effectively guarantee the compaction quality. The continuous detection and evaluation method provided by the application is suitable for continuous detection and evaluation of compaction quality of various fillers.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of earthwork filling construction, and particularly relates to a filling material compaction quality continuous detection and evaluation method based on a vibration jump degree. BACKGROUND

[0002] In earthwork filling projects such as dams, highways, railways and airports, a vibratory roller is generally used to compact and densify the filling material, and the compaction quality of the filling material is crucial for the safe and stable operation of the project.

[0003] At present, the compaction quality of the filling material is mainly detected by means of supervision and on-site sampling after compaction, which is time-lagged, greatly affected by human factors, time-consuming and inefficient, and cannot realize the whole-process control and comprehensive detection of the compaction quality of the filling material, which may cause potential quality problems of the project.

[0004] To solve the above problems, some scholars propose continuous compaction technology, which installs a continuous detection device on the vibratory roller, calculates the continuous detection index value of the compaction quality in real time during the compaction process, and realizes real-time and continuous detection of the compaction quality of the filling material. The commonly used continuous detection index is a harmonic index based on frequency domain analysis of acceleration, such as compaction meter value (CMV), total harmonic distortion (THD) and compaction control value (CCV). These indexes analyze the frequency domain of the acceleration signal by Fast Fourier Transform (FFT), and evaluate the compaction quality of the filling material according to the ratio of the amplitude of high-order harmonics to the amplitude of the fundamental wave in the Fourier spectrum. However, when performing FFT processing, frequency spectrum leakage may occur when the acceleration is intercepted, and when processing discrete signals of limited length, the periodicity assumption of FFT may introduce boundary effects, resulting in distortion of the frequency spectrum analysis result. At the same time, the index calculation result is greatly affected by the length of the intercepted signal and the signal sampling rate, resulting in large discreteness and low continuous detection accuracy. SUMMARY

[0005] In view of the defects of the prior art, the application provides a filling material compaction quality continuous detection and evaluation method based on a vibration jump degree, which can effectively solve the above problems.

[0006] The technical scheme adopted by the application is as follows:

[0007] The application provides a filling material compaction quality continuous detection and evaluation method based on a vibration jump degree, which comprises the following steps:

[0008] Step S1, carrying out a filling material compaction detection test: in the process of compaction of the filling material by the vibratory roller, the vertical vibration acceleration of the vibratory wheel, the vertical vibration acceleration of the upper rack and the eccentric block position data are collected in real time;

[0009] Step S2, according to the eccentric block position data, determine each detection period; in each detection period, according to the vertical vibration acceleration of the vibrating wheel, the vertical vibration acceleration of the upper rack and the eccentric block position data, using the vibrating wheel-filling material interaction force model, the vibrating wheel-filling material interaction force is calculated in each detection period per time;

[0010] Step S3, in each detection period, the time is taken as the horizontal coordinate, and the vibrating wheel-filling material interaction force is taken as the vertical coordinate, and the vibrating wheel-filling material interaction force curve is drawn; the vibrating wheel-filling material interaction force curve is analyzed to determine whether the vibration jump phenomenon occurs in the detection period; if not, the non-vibration jump working condition compaction jump value CJV calculation model is used to calculate the compaction jump value CJV corresponding to the detection period; if it occurs, the vibration jump working condition compaction jump value CJV calculation model is used to calculate the compaction jump value CJV corresponding to the detection period;

[0011] Step S4, in each detection period, the filling material compaction quality conventional detection index is detected, so that a plurality of test data of the filling material compaction quality conventional detection index and the compaction jump value CJV are obtained;

[0012] Step S5, a filling material compaction quality detection evaluation model based on CJV is established, and the model parameters of the filling material compaction quality detection evaluation model based on CJV are determined by using the plurality of test data obtained in step S4, so that the filling material compaction quality detection evaluation model based on CJV after the model parameters are determined is obtained;

[0013] Step S6, the actual rolling of the filling material is carried out by using the vibrating roller, the compaction jump value average value is calculated in each rolling unit, and then the filling material compaction quality conventional detection index corresponding to the rolling unit is obtained by using the filling material compaction quality detection evaluation model based on CJV after the model parameters are determined, and whether the filling material compaction quality conventional detection index meets the requirements is judged; if it meets the requirements, the rolling of the rolling unit is stopped; if it does not meet the requirements, the rolling of the rolling unit is continued until the filling material compaction quality conventional detection index meets the requirements.

[0014] Preferably, step S1 is specifically:

[0015] The satellite positioning system, the signal acquisition system and the data processing system are installed on the vibrating roller;

[0016] The satellite positioning system acquires the three-dimensional position information of the vibrating roller in real time;

[0017] The signal acquisition system includes a vibratory wheel acceleration acquisition device, an upper frame acceleration acquisition device, and an eccentric block position detection device. The vibratory wheel acceleration acquisition device and the upper frame acceleration acquisition device are respectively installed on the vibratory wheel and the upper frame, and are used to acquire the vertical vibration acceleration of the vibratory wheel and the vertical vibration acceleration of the upper frame in real time during the rolling process. The eccentric block position detection device is used to acquire the eccentric block position data in real time during the rolling process.

[0018] The data processing system is used to process and store the vertical vibration acceleration of the vibrating wheel, the vertical vibration acceleration of the upper frame, and the position data of the eccentric block acquired by the signal acquisition system.

[0019] Preferably, the satellite positioning system has centimeter-level positioning capability;

[0020] The acceleration acquisition device of the vibrating wheel and the acceleration acquisition device of the upper frame have an acceleration sensor range of not less than ±15g and an acquisition frequency of not less than 1000Hz.

[0021] The eccentric block position detection device uses electromagnetic effects to determine the position of the eccentric block.

[0022] Preferably, before inputting the vertical vibration acceleration of the vibrating wheel and the vertical vibration acceleration of the upper frame into the vibrating wheel-packing interaction force model, the method further includes:

[0023] The vertical vibration acceleration of the vibrating wheel and the vertical vibration acceleration of the upper frame are low-pass filtered to remove high-frequency acceleration signals higher than 3 times the fundamental frequency.

[0024] Preferably, each detection cycle is determined based on the eccentric block position data, specifically as follows:

[0025] The time interval between two consecutive times when the eccentric block is at the bottom is one detection cycle; the time length of each detection cycle may be the same or different.

[0026] Preferably, in step S2, the interaction force model between the vibrating wheel and the packing is:

[0027]

[0028] Wherein: F s,k (t) represents the interaction force between the vibrating wheel and the packing at time t within the k-th detection cycle; m0 is the mass of the eccentric block; e0 is the distance from the center of gravity of the eccentric block to the eccentric axis; t k,eb，1 t represents the start time of the k-th detection cycle, and also the time when the eccentric block is detected to be at its lowest position for the first time within the k-th detection cycle; k,eb，2t represents the end time of the k-th detection cycle, and also the time when the eccentric block is detected to be at its lowest position for the second time within the k-th detection cycle; k,eb，1 ≤t≤t k,eb，2 ;m d The mass of the vibrating wheel is m. f g is the mass of the upper frame; g is the acceleration due to gravity. The vertical vibration acceleration of the vibrating wheel detected at time t within the k-th detection period is the filtered value. Let be the filtered vertical vibration acceleration of the upper frame detected at time t within the k-th detection period.

[0029] Preferably, the interaction force curve between the vibrating wheel and the packing is analyzed to determine whether a jumping vibration phenomenon occurs during the detection cycle. Specifically:

[0030] In the vibration wheel-packing interaction force curve, the time when the first peak of two adjacent peaks appears is T. k,1 The second peak appears at time T. k,2 Then, in the interaction force curve of the vibrating wheel and the packing, at time T k,1 At time T k,2 The curve between them is the interaction force curve of the vibrating wheel and the packing corresponding to the kth detection cycle;

[0031] Determine the minimum value F of the vibration wheel-packing interaction force from the vibration wheel-packing interaction force curve corresponding to the kth detection cycle. min,k ;

[0032] Pre-set the minimum control value σ for the interaction force between the vibrating wheel and the packing;

[0033] If F min,k If F ≤ σ, then it is determined that oscillation occurred in the kth detection cycle; if F min,k If the value is greater than σ, then it is determined that no oscillation occurred in the k-th detection cycle.

[0034] Preferably, the calculation model for the compaction vibration value CJV under non-vibration conditions is as follows:

[0035]

[0036] Among them: CJV k T represents the compaction vibration value calculated for the kth detection cycle. k,c T represents the time length of the k-th detection period. vj,k T represents the virtual vibration wheel disengagement time during the k-th detection cycle. k,3 2F min,k -σ line is the moment of the first intersection point of the vibration wheel-packing interaction force curve corresponding to the kth detection cycle; where 2Fmin,k The -σ line represents the vertical axis of the vibrating wheel-packing interaction force curve coordinate system, with 2F as the ordinate. min,k -σ horizontal line; T k,4 2F min,k -The moment when the σ line intersects the second intersection point of the vibration wheel-packing interaction force curve corresponding to the kth detection cycle;

[0037] The calculation model for the compaction vibration value CJV under the vibration condition is as follows:

[0038]

[0039] Wherein: T j,k T is the time for the vibrating wheel to detach during the kth detection cycle; k,5 For F s = The moment when the σ line intersects the first point of the interaction force curve between the vibrating wheel and the packing corresponding to the kth detection cycle; where F s =σ line is a horizontal line with ordinate σ in the coordinate system of the interaction force curve of the vibrating wheel and the packing; T k,6 For F s = The moment when the σ line intersects the second point of the interaction force curve between the vibrating wheel and the packing corresponding to the kth detection cycle.

[0040] Preferably, the CJV-based packing compaction quality testing and evaluation model is established using a univariate linear regression method, and its expression is as follows:

[0041] K = a + bCJV

[0042] or

[0043] The CJV-based packing compaction quality detection and evaluation model is established using a multiple regression method or a deep learning algorithm, and its expression is as follows:

[0044] K = f(CJV, v, f, P, ω, ...)

[0045] Where: K is the conventional test index of the compaction quality of the fill material, including compaction degree, dynamic deformation modulus, and subgrade coefficient; a and b are fitting parameters; v is the speed of the roller; f is the vibration frequency; P is the fill material gradation parameter; and ω is the moisture content.

[0046] Preferably, in each compaction unit, the average compaction vibration value is calculated, specifically as follows:

[0047] The compaction surface is divided into multiple compaction units with a length of L and a width of B;

[0048] Based on the satellite positioning system and the geometry of the roller's vibratory drum, determine the time interval [t] for the roller to pass through a specific compaction unit. m ,t n], determine the time period [t m ,t n Each detection cycle within ]; for time period [t] m ,t n For each testing cycle within the specified period, the vibration wheel-packing interaction force model is used to obtain the vibration wheel-packing interaction force at each moment within that testing cycle, thus obtaining the vibration wheel-packing interaction force curve corresponding to that testing cycle. The vibration wheel-packing interaction force curve is analyzed to determine whether vibration jumping occurs within that testing cycle. If it does not occur, the CJV calculation model for compaction vibration value under non-vibration jumping conditions is used to obtain the compaction vibration value for that testing cycle. If it occurs, the CJV calculation model for compaction vibration value under vibration jumping conditions is used to obtain the compaction vibration value for that testing cycle.

[0049] Therefore, for the time period [t] m ,t n The average compaction vibration value of the compaction unit is obtained by averaging the compaction vibration values ​​of each detection cycle within the unit.

[0050] The method for continuous detection and evaluation of filler compaction quality based on vibration intensity provided by this invention has the following advantages:

[0051] This invention enables real-time, continuous, and comprehensive monitoring of packing compaction quality, effectively ensuring its quality. The continuous monitoring and evaluation method proposed in this invention is applicable to the continuous monitoring and evaluation of compaction quality for various types of packing materials. Attached Figure Description

[0052] Figure 1 A flowchart of a continuous detection and evaluation method for filler compaction quality based on vibration intensity provided by the present invention;

[0053] Figure 2 This is a schematic diagram of CJV calculation under non-vibration conditions provided by the present invention;

[0054] Figure 3 This is a schematic diagram of CJV calculation under the vibration jumping condition provided by the present invention;

[0055] Figure 4 The graph shows the relationship between CJV and the conventional test index K for compaction quality provided by this invention. Detailed Implementation

[0056] To make the technical problems solved, the technical solutions, and the beneficial effects of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and are not intended to limit the invention.

[0057] The inventors discovered that during the compaction of packing material, as the density of the packing increases, the interaction force between the vibrating wheel and the packing also increases. When the interaction force between the vibrating wheel and the packing exceeds twice the mass distributed by the front wheel of the vibrating wheel, the vibrating wheel will periodically detach from the packed packing, i.e., vibration jumping occurs. Vibration jumping is the main reason for the appearance of second and higher harmonics in the acceleration spectrum of the vibrating wheel. As the density of the packing gradually increases, the degree of vibration jumping also increases, and there is a corresponding relationship between the two. Therefore, this invention provides a method for continuous detection and evaluation of packing compaction quality based on the degree of vibration jumping.

[0058] See Figure 1 This invention provides a method for continuous detection and evaluation of filler compaction quality based on vibration intensity, comprising the following steps:

[0059] Step S1, conduct a fill compaction test: during the compaction of the fill by the vibratory roller, collect data on the vertical vibration acceleration of the vibratory wheel, the vertical vibration acceleration of the upper frame, and the position of the eccentric block in real time.

[0060] Step S1 is as follows:

[0061] Install satellite positioning system, signal acquisition system and data processing system on vibratory rollers;

[0062] The satellite positioning system collects the three-dimensional position information of the vibratory roller in real time;

[0063] The signal acquisition system includes a vibratory wheel acceleration acquisition device, an upper frame acceleration acquisition device, and an eccentric block position detection device. The vibratory wheel acceleration acquisition device and the upper frame acceleration acquisition device are respectively installed on the vibratory wheel and the upper frame, and are used to acquire the vertical vibration acceleration of the vibratory wheel and the vertical vibration acceleration of the upper frame in real time during the rolling process. The eccentric block position detection device is used to acquire the eccentric block position data in real time during the rolling process.

[0064] The data processing system is used to process and store the vertical vibration acceleration of the vibrating wheel, the vertical vibration acceleration of the upper frame, and the position data of the eccentric block acquired by the signal acquisition system.

[0065] In practical applications, the satellite positioning system has centimeter-level positioning capabilities; the acceleration acquisition device of the vibrating wheel and the acceleration acquisition device of the upper frame have acceleration sensors with a range of not less than ±15g and an acquisition frequency of not less than 1000Hz; the eccentric block position detection device uses electromagnetic effects to determine the position of the eccentric block.

[0066] Before inputting the vertical vibration acceleration of the vibrating wheel and the vertical vibration acceleration of the upper frame into the vibrating wheel-packing interaction force model, the method further includes: performing low-pass filtering on the vertical vibration acceleration of the vibrating wheel and the vertical vibration acceleration of the upper frame to filter out high-frequency acceleration signals higher than 3 times the fundamental frequency.

[0067] Step S2: Determine each detection cycle based on the eccentric block position data; in each detection cycle, calculate the vibration wheel-packing interaction force at each moment in each detection cycle based on the vertical vibration acceleration of the vibrating wheel, the vertical vibration acceleration of the upper frame, and the eccentric block position data, using the vibrating wheel-packing interaction force model.

[0068] In this step, each detection cycle is determined based on the position data of the eccentric block. Specifically, the time interval between two consecutive times when the eccentric block is at the bottom is one detection cycle; the time length of each detection cycle may be the same or different.

[0069] In this step, the interaction force model between the vibrating wheel and the packing is as follows:

[0070]

[0071] Wherein: F s,k (t) represents the interaction force between the vibrating wheel and the packing at time t within the k-th detection cycle; m0 is the mass of the eccentric block; e0 is the distance from the center of gravity of the eccentric block to the eccentric axis; t k,eb，1 t represents the start time of the k-th detection cycle, and also the time when the eccentric block is detected to be at its lowest position for the first time within the k-th detection cycle; k,eb，2 t represents the end time of the k-th detection cycle, and also the time when the eccentric block is detected to be at its lowest position for the second time within the k-th detection cycle; k,eb，1 ≤t≤t k,eb，2 ;m d The mass of the vibrating wheel is m. f g is the mass of the upper frame; g is the acceleration due to gravity. The vertical vibration acceleration of the vibrating wheel detected at time t within the k-th detection period is the filtered value. Let be the filtered vertical vibration acceleration of the upper frame detected at time t within the k-th detection period.

[0072] Step S3: In each detection cycle, a vibration wheel-packing interaction force curve is plotted with time as the abscissa and the vibration wheel-packing interaction force as the ordinate. The vibration wheel-packing interaction force curve is analyzed to determine whether vibration jumping occurs in that detection cycle. If it does not occur, the compaction vibration jumping value CJV corresponding to the detection cycle is calculated using the non-vibration jumping condition compaction vibration jumping value CJV calculation model. If it occurs, the compaction vibration jumping value CJV corresponding to the detection cycle is calculated using the vibration jumping condition compaction vibration jumping value CJV calculation model.

[0073] In this step, the interaction force curve between the vibrating wheel and the packing is analyzed to determine whether vibration jumping occurs during the detection cycle. Specifically:

[0074] In the vibration wheel-packing interaction force curve, the time when the first peak of two adjacent peaks appears is T. k,1 The second peak appears at time T. k,2 Then, in the interaction force curve of the vibrating wheel and the packing, at time T k,1 At time T k,2 The curve between them is the interaction force curve of the vibrating wheel and the packing corresponding to the kth detection cycle;

[0075] Determine the minimum value F of the vibration wheel-packing interaction force from the vibration wheel-packing interaction force curve corresponding to the kth detection cycle. min,k ;

[0076] Pre-set the minimum control value σ for the interaction force between the vibrating wheel and the packing;

[0077] If F min,k If F ≤ σ, then it is determined that oscillation occurred in the kth detection cycle; if F min,k If the value is greater than σ, then it is determined that no oscillation occurred in the k-th detection cycle.

[0078] Specifically, due to errors in data acquisition and processing, when the vibrating wheel detaches from the packing, the calculated interaction force between the vibrating wheel and the packing is not equal to 0, but rather a small value. A minimum control value σ for the interaction force between the vibrating wheel and the packing can be set based on actual measurements. When the minimum interaction force F... min,k When the vibration is less than or equal to σ, it is judged as vibration jumping; when the minimum value of the interaction force between the vibrating wheel and the packing is F... min,k If the value is greater than σ, it is determined that no oscillation has occurred.

[0079] In this step, such as Figure 2 As shown, when no vibration occurs, the smaller the packing density, the lower the minimum value of the interaction force F between the vibrating wheel and the packing. min,k With 2F min,kThe further away the -σ line is, the more accurate the calculation of the CJV under non-vibration conditions. To reflect the degree of vibration under non-vibration conditions, the following CJV calculation model for compaction vibration under non-vibration conditions is used to calculate the CJV under non-vibration conditions:

[0080]

[0081] Among them: CJV k T represents the compaction vibration value calculated for the kth detection cycle. k,c T represents the time length of the k-th detection period. vj,k T represents the virtual vibration wheel disengagement time during the k-th detection cycle. k,3 2F min,k -σ line is the moment of the first intersection point of the vibration wheel-packing interaction force curve corresponding to the kth detection cycle; where 2F min,k The -σ line represents the vertical axis of the vibrating wheel-packing interaction force curve coordinate system, with 2F as the ordinate. min,k -σ horizontal line; T k,4 2F min,k -The moment when the σ line intersects the second intersection point of the vibration wheel-packing interaction force curve corresponding to the kth detection cycle;

[0082] As can be seen from the above formula, CJV is negative under non-vibration conditions. The smaller CJV is, the farther the roller is from the vibration phenomenon and the weaker the vibration degree.

[0083] like Figure 3 As shown, when vibration occurs, the greater the packing density, the more the interaction force curve between the vibrating wheel and the packing is at F. s The greater the portion below the σ line, the more accurate the calculation of the CJV under the vibration condition using the following vibration condition compaction vibration value CJV calculation model:

[0084]

[0085] Wherein: T j,k T is the time for the vibrating wheel to detach during the kth detection cycle; k,5 For F s = The moment when the σ line intersects the first point of the interaction force curve between the vibrating wheel and the packing corresponding to the kth detection cycle; where F s =σ line is a horizontal line with ordinate σ in the coordinate system of the interaction force curve of the vibrating wheel and the packing; T k,6 For F s = The moment when the σ line intersects the second point of the interaction force curve between the vibrating wheel and the packing corresponding to the kth detection cycle.

[0086] As can be seen from the above formula, CJV is a positive value under the vibration jumping condition. The larger the CJV, the stronger the vibration jumping.

[0087] Step S4: In each detection cycle, the conventional test index of the packing compaction quality is detected, thereby obtaining multiple sets of test data of the conventional test index of the packing compaction quality and the compaction vibration value CJV.

[0088] Step S5: Establish a CJV-based packing compaction quality detection and evaluation model, and use multiple sets of test data obtained in step S4 to determine the model parameters of the CJV-based packing compaction quality detection and evaluation model, and obtain the CJV-based packing compaction quality detection and evaluation model after the model parameters are determined.

[0089] In this step, the CJV-based packing compaction quality detection and evaluation model is as follows: Figure 4 As shown, it can be established using the univariate linear regression method, with the following expression:

[0090] K = a + bCJV

[0091] or

[0092] The CJV-based packing compaction quality detection and evaluation model simultaneously collects data such as CJV, vehicle speed, vibration frequency, packing gradation, and packing moisture content. It is established using a multiple regression method or deep learning algorithm, and the expression is as follows:

[0093] K = f(CJV, v, f, P, ω, ...)

[0094] Where: K is the conventional test index of the compaction quality of the fill material, including compaction degree, dynamic deformation modulus, and subgrade coefficient; a and b are fitting parameters; v is the speed of the roller; f is the vibration frequency; P is the fill material gradation parameter; and ω is the moisture content.

[0095] Step S6: The fill material is actually compacted using a vibratory roller. The compaction quality of different areas of the compacted surface is evaluated based on the three-dimensional position coordinates of the roller and the continuous detection results of CJV.

[0096] Specifically, in each compaction unit, the average compaction vibration value is calculated. Then, using the CJV-based filler compaction quality detection and evaluation model determined by the model parameters, the conventional detection index of filler compaction quality corresponding to the compaction unit is obtained. It is then determined whether the conventional detection index of filler compaction quality meets the requirements. If it does, the compaction of the compaction unit is stopped. If it does not meet the requirements, the compaction of the compaction unit continues until the conventional detection index of filler compaction quality meets the requirements.

[0097] In this step, the average compaction vibration value is calculated for each compaction unit, specifically as follows:

[0098] The compaction surface is divided into multiple compaction units with a length of L and a width of B;

[0099] Based on the satellite positioning system and the geometry of the roller's vibratory drum, determine the time interval [t] for the roller to pass through a specific compaction unit. m ,t n ], determine the time period [t m ,t n Each detection cycle within ]; for time period [t] m ,t n For each testing cycle within the specified period, the vibration wheel-packing interaction force model is used to obtain the vibration wheel-packing interaction force at each moment within that testing cycle, thus obtaining the vibration wheel-packing interaction force curve corresponding to that testing cycle. The vibration wheel-packing interaction force curve is analyzed to determine whether vibration jumping occurs within that testing cycle. If it does not occur, the CJV calculation model for compaction vibration value under non-vibration jumping conditions is used to obtain the compaction vibration value for that testing cycle. If it occurs, the CJV calculation model for compaction vibration value under vibration jumping conditions is used to obtain the compaction vibration value for that testing cycle.

[0100] Therefore, for the time period [t] m ,t n The average compaction vibration value of the compaction unit is obtained by averaging the compaction vibration values ​​of each detection cycle within the unit.

[0101] This invention proposes a novel continuous compaction quality monitoring index (CJV) and its calculation method. Specifically, based on the phenomenon that the compaction quality of the fill material affects the vibration level of the vibratory roller, a novel compaction vibration value (CJV) and its calculation method are proposed. The methods include: (a) calculating the interaction force between the vibratory roller and the fill material; (b) setting a minimum control value σ for the interaction force between the vibratory roller and the fill material to determine whether vibration occurs; (c) for non-vibration conditions, calculating CJV using a non-vibration condition compaction vibration value CJV calculation model; for vibration conditions, calculating CJV using a vibration condition compaction vibration value CJV calculation model; and (d) using CJV for continuous monitoring and evaluation of fill material compaction quality. Regression analysis or deep learning can be used to establish the relationship between CJV and conventional compaction quality indices. This invention is applicable to the continuous monitoring and evaluation of fill material compaction quality in earthwork filling projects such as dams, railways, highways, and airports.

[0102] In summary, the inventors discovered that the vibration level of a vibratory roller is directly related to the compaction density of the fill material. By analyzing the relationship between CJV and conventional test indicators of fill material compaction quality, a continuous testing and evaluation method for fill material compaction quality was established. Compared with traditional fill material compaction quality testing methods, this invention can achieve real-time, continuous, accurate, and comprehensive testing of fill material compaction quality. Compared with existing continuous testing methods for fill material compaction quality, CJV directly characterizes the vibration level, reflects the fill material compaction density, and avoids the problem of large dispersion of harmonic indicators such as CMV, THD, and CCV, resulting in higher testing accuracy.

[0103] The continuous detection and evaluation method for packing compaction quality based on vibration intensity provided by this invention has the following characteristics:

[0104] This invention proposes a direct and quantitative index reflecting the degree of vibration—the compaction vibration value (CJV)—as a continuous detection index for the compaction quality of packing. Calculation methods for CJV under both vibration and non-vibration conditions are proposed, and a continuous detection and evaluation method for the compaction quality of packing based on CJV is established, which has higher detection accuracy for continuous detection of compaction quality of various types of packing.

[0105] In this invention, the CJV index is directly calculated through the interaction force curve of the vibrating wheel and the packing, which avoids the shortcomings of the current harmonic index using FFT for spectrum analysis, such as spectrum leakage, boundary effects, and large influence from signal length and sampling frequency. It can more accurately reflect the compaction quality of the packing.

[0106] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for continuously detecting and evaluating the compaction quality of fillers based on the degree of vibration, characterized in that, The method comprises the following steps: Step S1, carrying out a filler compaction detection test: collecting the vertical vibration acceleration of the vibration wheel, the vertical vibration acceleration of the upper frame and the eccentric block position data in real time during the compaction of the filler by the vibration roller; Step S2, determining each detection period according to the eccentric block position data; in each detection period, calculating the vibration wheel-filler interaction force at each time point in the detection period by using a vibration wheel-filler interaction force model according to the vertical vibration acceleration of the vibration wheel, the vertical vibration acceleration of the upper frame and the eccentric block position data; Step S3, in each detection period, drawing a vibration wheel-filler interaction force curve with time as the horizontal coordinate and the vibration wheel-filler interaction force as the vertical coordinate; analyzing the vibration wheel-filler interaction force curve to determine whether the vibration jump phenomenon occurs in the detection period; If not, calculating the compaction vibration jump value CJV corresponding to the detection period by using a non-vibration jump working condition compaction vibration jump value CJV calculation model; if so, calculating the compaction vibration jump value CJV corresponding to the detection period by using a vibration jump working condition compaction vibration jump value CJV calculation model; Step S4, in each detection period, detecting the filler compaction quality conventional detection index to obtain a plurality of sets of test data of the filler compaction quality conventional detection index and the compaction vibration jump value CJV; Step S5, establishing a filler compaction quality detection evaluation model based on CJV, and determining the model parameters of the filler compaction quality detection evaluation model based on CJV by using the plurality of sets of test data obtained in step S4 to obtain the filler compaction quality detection evaluation model based on CJV after the model parameters are determined; Step S6, using the vibration roller to actually roll the filler, calculating the average value of the compaction vibration jump value in each rolling unit, and then obtaining the filler compaction quality conventional detection index corresponding to the rolling unit by using the filler compaction quality detection evaluation model based on CJV after the model parameters are determined to determine whether the filler compaction quality conventional detection index meets the requirements; if so, stopping the rolling of the rolling unit; if not, continuing to roll the rolling unit until the filler compaction quality conventional detection index meets the requirements; analyzing the vibration wheel-filler interaction force curve to determine whether the vibration jump phenomenon occurs in the detection period, specifically: In the vibration wheel-filler interaction force curve, the time when the first wave crest in the two adjacent wave crests appears is , and the time when the second wave crest appears is , then in the vibration wheel-filler interaction force curve, the curve between the time and the time is the vibration wheel-filler interaction force curve corresponding to the first detection period . In the Determine the minimum value of the vibration wheel-packing interaction force from the vibration wheel-packing interaction force curves corresponding to each testing cycle. ; Pre-setting the minimum control value of the vibration wheel-filler interaction force ; If , it is judged that the oscillation occurs in the first detection cycle; if , it is judged that the oscillation does not occur in the first detection cycle; the non-vibration jump working condition compaction vibration jump value CJV calculation model is: ； in: For the calculated first The compaction vibration value for each testing cycle; For the first The duration of each detection cycle; For the first The virtual vibration wheel disengagement time for each detection cycle; for Line and the The moment of the first intersection of the vibration wheel-packing interaction force curves corresponding to each detection cycle; where... The line is in the coordinate system of the interaction force curve between the vibrating wheel and the packing, with the ordinate being... Horizontal line; for Line and the The moment of the second intersection of the vibration wheel-packing interaction force curves corresponding to each detection cycle; the vibration jump working condition compaction vibration jump value CJV calculation model is: ； in: For the first The vibration wheel disengagement time for each detection cycle; for Line and the The moment of the first intersection of the vibration wheel-packing interaction force curves corresponding to each detection cycle; where... The line is in the coordinate system of the interaction force curve between the vibrating wheel and the packing, with the ordinate being... Horizontal line; for Line and the The moment of the second intersection of the vibration wheel-packing interaction force curves corresponding to each detection cycle.

2. The method for continuously detecting and evaluating the compaction quality of fillers based on the degree of oscillation according to claim 1, characterized in that, Step S1 specifically comprises: installing a satellite positioning system, a signal acquisition system and a data processing system on the vibration roller; the satellite positioning system collects the three-dimensional position information of the vibration roller in real time; The signal acquisition system comprises a vibrating wheel acceleration acquisition device, an upper rack acceleration acquisition device and an eccentric block position detection device; the vibrating wheel acceleration acquisition device and the upper rack acceleration acquisition device are respectively installed on the vibrating wheel and the upper rack, and are used for acquiring the vertical vibration acceleration of the vibrating wheel and the vertical vibration acceleration of the upper rack in real time during the rolling process; the eccentric block position detection device is used for acquiring the eccentric block position data in real time during the rolling process; The data processing system is used for processing and storing the vertical vibration acceleration of the vibrating wheel, the vertical vibration acceleration of the upper rack and the eccentric block position data acquired by the signal acquisition system.

3. The method according to claim 2, wherein, The satellite positioning system has a centimeter-level positioning function; The acceleration sensor of the vibrating wheel acceleration acquisition device and the upper rack acceleration acquisition device has a range of not less than ±15g and a collection frequency of not less than 1000Hz; The eccentric block position detection device determines the eccentric block position by using electromagnetic effect.

4. The method for continuously detecting and evaluating the compaction quality of fillers based on the degree of oscillation according to claim 1, characterized in that, Before the vertical vibration acceleration of the vibrating wheel and the vertical vibration acceleration of the upper rack are input into the vibrating wheel-filler interaction force model, the following steps are further included: The vertical vibration acceleration of the vibrating wheel and the vertical vibration acceleration of the upper rack are subjected to low-pass filtering to filter out high-frequency acceleration signals higher than 3 times the fundamental frequency.

5. The method for continuously detecting and evaluating the compaction quality of fillers based on the degree of oscillation according to claim 1, characterized in that, According to the eccentric block position data, each detection cycle is determined, specifically: The time interval when the eccentric block is at the lowest position for two times in succession is a detection cycle; the lengths of the detection cycles are the same or different.

6. The method for continuously detecting and evaluating the compaction quality of fillers based on the degree of oscillation according to claim 1, characterized in that, In step S2, the vibrating wheel-filler interaction force model is: in: For the first Within each detection cycle The interaction force between the vibrating wheel and the packing material at that time; For the mass of the eccentric block; This is the distance from the center of gravity of the eccentric block to the eccentric axis; For the first The start time of the first detection cycle, which is also the first detection cycle. The moment when the eccentric block is detected to be at its lowest point for the first time within a detection cycle; For the first The end time of the detection cycle, which is also the time when the first detection cycle ends. The moment when the eccentric block is detected at its lowest point for the second time within a detection cycle; ; The mass of the vibrating wheel; For the quality of the mounting rack; It is the acceleration due to gravity; For the first Within each detection cycle The vertical vibration acceleration of the vibrating wheel detected in real time after filtering; For the first Within each detection cycle The vertical vibration acceleration of the upper frame was detected after filtering.

7. The method for continuous detection and evaluation of the compaction quality of fillers based on the degree of bounce according to claim 1, characterized in that, The filler compaction quality detection and evaluation model based on CJV is established by using a linear regression method, and the expression is as follows: ； Or The filler compaction quality detection and evaluation model based on CJV is established by using a multiple regression method or a deep learning algorithm, and the expression is as follows: ； wherein: are conventional detection indexes of compaction quality of fillers, including compaction degree, dynamic deformation modulus, and foundation coefficient; , are fitting parameters; is the driving speed of the road roller; is the vibration frequency; is the filler grading parameter; is the water content.

8. The method for continuously detecting and evaluating the compaction quality of fillers based on the degree of oscillation according to claim 1, characterized in that, In each rolling unit, the average value of the compaction bounce value is calculated, specifically: The rolling surface is divided into a plurality of rolling units with a length of L and a width of B; According to the geometric dimensions of the satellite positioning system and the vibratory roller, a time period [t m ,t n ] of the vibratory roller passing through a certain rolling unit is determined, each detection period within the time period [t m ,t n ] is determined; for each detection period within the time period [t m ,t n ], the vibratory roller-filling material interaction force at each moment within the detection period is obtained through the vibratory roller-filling material interaction force model, so as to obtain the vibratory roller-filling material interaction force curve corresponding to the detection period; the vibratory roller-filling material interaction force curve is analyzed to determine whether the jump phenomenon occurs in the detection period; If not, the non-bounce working condition compaction bounce value CJV calculation model is used to obtain the compaction bounce value of the detection cycle; if so, the bounce working condition compaction bounce value CJV calculation model is used to obtain the compaction bounce value of the detection cycle; Therefore, the compaction jump value of each detection period within the time period [t m ,t n ] is averaged to obtain the average compaction jump value of the compaction unit .

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