Intelligent detection method for dynamic compaction quality of piled mass based on vibration energy and its application

Abstract

The present invention discloses an intelligent detection method for the dynamic compaction quality of a pile based on vibration energy. By monitoring the acceleration time curve of the rammer during the dynamic compaction process, based on the energy dissipation principle of mechanical kinetic energy and response signals, an intelligent detection index for the dynamic compaction quality is proposed, and a correlation between the intelligent detection index for the dynamic compaction quality and the tamping amount, dynamic probing value, etc. is established. An intelligent detection method for the dynamic compaction quality of a pile based on vibration energy is proposed, which can realize real-time and accurate detection of the dynamic compaction quality.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent detection of dynamic compaction quality of ultra-high and wide piles, and particularly relates to a method for detecting dynamic compaction quality during the dynamic compaction process. Background Art

[0002] Dynamic consolidation, also known as dynamic consolidation, involves repeatedly lifting a rammer to a certain height using lifting equipment. The rammer's kinetic energy then generates powerful shock waves and high stresses in the soil, reducing compressibility, improving resistance to vibrational liquefaction, and eliminating collapsibility. Since its invention by the French company Menard in 1969, this method has been increasingly used in various types of foundation treatment projects worldwide for various purposes, owing to its economical and practical advantages, including simple equipment, convenient construction, material savings, easy quality control, wide applicability, and short construction periods. Dynamic consolidation quality testing involves determining the quality and changing trends of dynamic consolidation foundation reinforcement by examining factors that influence its effectiveness. The goal is to ensure that dynamic consolidation construction achieves the desired treatment results.

[0003] The traditional means of detecting the quality and effectiveness of dynamic compaction are to use dynamic probing and static load test methods of point testing. These traditional methods of detecting the effect of foundation reinforcement can more intuitively grasp the effect of dynamic compaction foundation treatment, but the work efficiency is low and there are more requirements on the site environment. Even if in-situ testing can be carried out, the number of measuring points is relatively small, and it is only a point test, and it is not possible to conduct a comprehensive and uniform overall detection of the effect of the reinforced foundation on the plane.

[0004] Therefore, the present invention monitors the acceleration time curve of the rammer during the dynamic compaction process, proposes an intelligent detection index for dynamic compaction quality based on the principle of energy dissipation of mechanical kinetic energy and response signals, establishes a correlation between the intelligent detection index for dynamic compaction quality and the tamping amount, dynamic probing value, etc., and proposes an intelligent detection method for dynamic compaction quality of a pile based on vibration energy.

[0005] Tongji University's Li Wanli's article, "Application of Impact Acceleration Testing in Strong Compaction," first introduces several different methods for measuring compaction sinkage in real time, as well as methods for detecting the degree of compaction using the acceleration of the rammer or the force changes in the soil during compaction. Experiments revealed a close relationship between the peak acceleration and the duration of action and the amount of compaction sinkage. The peak value's variation pattern generally remains consistent with the cumulative compaction sinkage, while the duration of action is similar to that of a single compaction sinkage. Finally, a new method using MEMS accelerometers and wireless chips as an acceleration acquisition system is proposed. However, the article does not address a continuous monitoring method for compaction quality at the construction site, nor does it address the effectiveness of the detection. Summary of the Invention

[0006] The purpose of the present invention is to detect the quality index of dynamic compaction in real time by monitoring the acceleration time history curve of the rammer during the dynamic compaction process, and proposes an intelligent detection method for the dynamic compaction quality of a pile based on vibration energy.

[0007] The above-mentioned object of the present invention is achieved through the following technical solutions.

[0008] The present invention provides a compaction quality control method based on real-time detection of filler density during railway roadbed vibration rolling, which comprises the following steps:

[0009] Step 1: Place a Beidou positioning device on the main body of the tamping machine and an acceleration sensor on the tamping hammer. During the dynamic tamping process, monitor the tamping hammer acceleration time history curve f(x1) at different dynamic tamping times, where x1 is time.

[0010] Step 2: Based on the coupling effect principle of the rammer and the parametric filler, a dynamics theory equation of the dynamic compaction process is proposed. The dynamic coupling theory equation is solved using MATLAB / SIMULINK and ABQUS numerical calculation software or Mathematics software to obtain the simulated acceleration time history curve f(x2) of the rammer at different dynamic compaction times, where x2 is time.

[0011] Step 3: Using the frequency domain integration method, integrate the measured rammer acceleration time history curve f(x1) and the simulated rammer acceleration time history curve f(x2) to obtain the measured and simulated rammer velocity time history curves g(x1) and g(x2), respectively.

[0012] Step 4: Based on the principle of conservation of kinetic energy, establish the kinetic energy conservation system during the dynamic compaction process, that is, the kinetic energy conservation state equation of the rammer and the parametric vibrating filler;

[0013] Step 5: For the rammer, the kinetic energy of the parametrically vibrating filler is called the rammer kinetic energy loss, which is recorded as W. As the mass of the ramming increases, the parametric mass of the filler increases, and the greater the kinetic energy of the filler, the greater the kinetic energy loss.

[0014] Step 6: Based on the rammer acceleration time history curve f(x1), use the EMD-Hilbert-Huang transformation to calculate the energy of the dynamic compaction vibration signal at different dynamic compaction times;

[0015] Step 7: Based on the energy conservation state equation, calculate the kinetic energy loss of the vibration signal at different dynamic compaction times through step 6;

[0016] Step 8: Use a level and a ruler to measure the elevation H1 of the roadbed surface before each dynamic compaction and the elevation H2 of the roadbed surface after dynamic compaction. The conventional detection indicator "tamping amount" H is equal to the elevation H1 of the roadbed surface before each dynamic compaction - the elevation H2 of the roadbed surface after dynamic compaction;

[0017] Step 9: Construct the correlation between kinetic energy loss, vibration energy and conventional index "ramming sinking amount", and propose the correlation coefficient between loss, vibration energy and conventional index;

[0018] Step 10: Verify through field tests that the correlation coefficients of kinetic energy loss, vibration energy and the conventional indicator "ramming settlement" are all greater than 0.8. In this case, there is a strong correlation between the intelligent detection indicators of dynamic compaction quality "kinetic energy loss" and "vibration energy" and the conventional indicator "ramming settlement", and the dual indicators of "kinetic energy loss" and "vibration energy" can be used to control the dynamic compaction quality.

[0019] Beneficial effects

[0020] (1) The present invention relates to a non-destructive real-time detection method for the quality of dynamic compaction of a piled material during dynamic compaction construction;

[0021] (2) The present invention proposes a control method for the dynamic compaction process of different types of fillers, which effectively avoids over-compaction and under-compaction during the dynamic compaction process;

[0022] (3) The present invention is not only applicable to railways, but can also be widely used in highway, water conservancy and airport construction.

[0023] The production method proposed in this invention is simple to operate, highly feasible, and a highly efficient intelligent method for dynamic compaction quality testing. This method completes compaction quality testing during the construction phase and adjusts construction conditions in areas with poor compaction, avoiding over- and under-compaction. This significantly improves the efficiency of quality inspection for high-speed railway subgrade construction, resulting in significant economic and social benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 This is a schematic diagram of the acceleration time history curve of the rammer at different positions during dynamic compaction;

[0025] Figure 2 This is a schematic diagram of the system dynamics theory of the dynamic compaction process;

[0026] Figure 3 is the normalized kinetic energy curve;

[0027] Figure 4 This is a schematic diagram of the measured acceleration time history curve of the kinetic energy loss of the parametric filler;

[0028] Figure 5 is the marginal spectrum of the acceleration time history curve of the rammer;

[0029] Figure 6 is the signal vibration energy of the tamper;

[0030] Figure 7 is the tamping amount of filler with different dynamic tamping times;

[0031] Figure 8 is the correlation diagram between the tamping amount and the kinetic energy of the tamping hammer;

[0032] Figure 9 is the correlation diagram between tamping amount and signal vibration energy;

[0033] Figure 10 Flow chart of the detection method of the present invention. DETAILED DESCRIPTION

[0034] The present invention will be further described in detail below in conjunction with specific embodiments. The examples given are only for illustrating the present invention, not for limiting the scope of the present invention.

[0035] See also Figure 10 The present invention provides an intelligent detection method for the quality of dynamic compaction of a pile, which comprises the following steps:

[0036] Step 1: Place a Beidou positioning device on the main body of the tamping machine and an acceleration sensor on the tamping hammer. During the dynamic tamping process, monitor the tamping hammer acceleration time history curve f(x1) at different dynamic tamping times.

[0037] (2) Based on the principle of rammer-filler coupling, a theoretical model of system dynamics of the dynamic compaction process is proposed. Figure 2 , construct the theoretical equation of dynamics of the dynamic compaction process system:

[0038]

[0039] Where: m h is the mass of the rammer, kg; m s is the filler vibration mass ;λ ——Indicates displacement; ——Indicates speed; —— represents acceleration; Ce is filler damping; Ke is filler stiffness; Fs is the rammer-filler interaction force.

[0040] (3) The frequency domain integration method is used to integrate the acceleration time history curve f(x) of the rammer once to obtain the rammer speed time history curve. The planned rammer speed time history curve g(x) under different dynamic tamping times is obtained by normalization method. Figure 3 ;

[0041] The conversion between time domain and frequency domain uses Fast Fourier Transformation. The integral theorem of Fourier transform is:

[0042]

[0043] As can be seen from the above formula, when ω<1, that is, f<1 / 2π, the signal will be amplified; after the FFT transformation, the DC component is moved to the middle of the spectrum, so that the real and imaginary data obtained by FFT correspond to the frequency, and the common spectrum diagram order is obtained.

[0044] The speed integral calculation formula is:

[0045] f(x)=Ae jωt

[0046]

[0047] A——Constant term.

[0048] (4) According to the theoretical calculation formula of the kinetic energy of the vibration system, the kinetic energy of the dynamic compaction system is proportional to the square of the velocity of the entire system. According to the principle of conservation of kinetic energy, the entire system (tamper and vibrating filler) is in a state of kinetic energy conservation.

[0049]

[0050] Where: m h is the mass of the rammer, m s is the mass of the filler, g(x) represents the maximum value of the tamper speed time history curve; i represents the speed of the i-th time;

[0051] (5) Since the kinetic energy of the parametric filler described in step (4) cannot be obtained through the measured acceleration time curve, the kinetic energy of the parametric filler is called the normalized kinetic energy loss of the rammer and is recorded as W. As the mass of the ramming increases, the parametric mass of the filler increases, and the kinetic energy of the filler increases. The larger the normalized kinetic energy loss is, the larger the normalized kinetic energy loss is, see Figure 4 .

[0052] (6) According to the acceleration time history curve of the dynamic compaction process, the EMD-Hilbert-Huang transformation is used to calculate the dynamic compaction vibration signal energy. The calculation process is as follows:

[0053] 1) Decompose the EMD (empirical mode decomposition) of the acceleration time history curve of the dynamic compaction process to obtain multiple IMFs (intrinsic mode functions):

[0054]

[0055] Where f(t) is the acceleration time history curve of the dynamic compaction process, IMF i (t) are K intrinsic mode functions. K(t) is the remainder after subtracting the IMF from the signal.

[0056] 2) Define the Hilbert transformation of the acceleration time history curve of the dynamic compaction process as the time-frequency-energy spectrum H[f(t) 1 / L ],See Figure 5 .

[0057]

[0058] Where t is time, unit is s.

[0059] 3) The integral formula for time integration of the time-frequency-energy curve is: Figure 6 :

[0060]

[0061] Where H(ω,t) is the Hilbert spectrum function; e(ω,t) is the Hilbert marginal spectrum function, and ω is the frequency of the ramming hammer time history curve during the dynamic compaction process;

[0062] 4) Integrating the above 3) in the frequency domain can obtain the single compaction energy.

[0063] (7) Based on the energy conservation state equation, the kinetic energy loss of the vibration signal at different dynamic compaction times is calculated through step (6), see Figure 6 .

[0064] (8) Use a level and a ruler to measure the elevation H1 of the roadbed surface before each strong compaction and the elevation H2 of the roadbed surface after each strong compaction. The conventional detection indicator "compaction amount" H is equal to the elevation H1 of the roadbed surface before each strong compaction - the elevation H2 of the roadbed surface after each strong compaction, see Figure 7 .

[0065] (9) Based on the least squares method, the correlation between the kinetic energy loss of the rammer, the vibration energy and the conventional index "ramming sinking amount" was constructed, and the correlation coefficients between the kinetic energy loss of the rammer, the vibration energy and the conventional index were 0.96 and 0.8, respectively. Figure 8-9 .

[0066] y=a+bx

[0067]

[0068] Where: x is the kinetic energy loss and vibration energy of the rammer, y is the ramming amount; n is the number of detection point data; a and b are regression coefficients, R is the correlation coefficient, x i represents the kinetic energy and vibration energy of the i-th rammer, y i Represents the i-th tamping amount data.

[0069] The test results show that the correlation coefficients between the vibration energy of the rammer signal, the kinetic energy of the rammer and the tamping amount are all greater than 0.8.

[0070] (10) Field tests have verified that the correlation coefficients of kinetic energy loss, vibration energy and the conventional indicator "ramming sinking amount" are all greater than 0.8. Therefore, there is a strong correlation between the intelligent detection indicators of dynamic compaction quality "kinetic energy loss" and "vibration energy" and the conventional indicator "ramming sinking amount". The dual indicators of "kinetic energy loss" and "vibration energy" can be used to control the dynamic compaction quality.

[0071] According to step (9) of the above embodiment, the correlation coefficients between the ramming hammer signal vibration energy, the ramming hammer kinetic energy, and the ramming hammer sinking amount are all greater than 0.8. Therefore, the ramming hammer signal vibration energy and the ramming hammer kinetic energy can both represent the conventional indicator ramming hammer sinking amount during the dynamic compaction process, that is, they can intelligently detect the dynamic compaction quality in real time.

[0072] The present invention monitors the acceleration time history curve of the rammer during the dynamic compaction process, proposes an intelligent detection index for dynamic compaction quality based on the principle of energy dissipation of mechanical kinetic energy and response signal, establishes a correlation between the intelligent detection index for dynamic compaction quality and the tamping amount, dynamic probing value, etc., and realizes intelligent detection of dynamic compaction quality of the accumulation body based on vibration energy.

[0073] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions merely illustrate the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent detection method for the quality of dynamic compaction of a pile based on vibration energy, comprising the following steps: Step 1: Place a Beidou positioning device on the main body of the tamping machine and an acceleration sensor on the tamping hammer. During the dynamic tamping process, monitor the tamping hammer acceleration time history curve f(x1) at different dynamic tamping times, where X1 is time. Step 2: Based on the coupling principle of the rammer and the parametric filler, a theoretical dynamics equation of the dynamic compaction process system is proposed. The MATLAB / SIMULINK and ABQUS numerical calculation software or Mathematics software is used to solve the above dynamic coupling dynamics theoretical equation to obtain the simulated acceleration time history curve f(x2) of the rammer at different dynamic compaction times, where X2 is time; Step 3: Using the frequency domain integration method, integrate the measured rammer acceleration time history curve f(x1) and the simulated rammer acceleration time history curve f(x2) to obtain the measured and simulated rammer velocity time history curves g(x1) and g(x2), respectively. Step 4: Based on the principle of conservation of kinetic energy, establish the kinetic energy conservation system during the dynamic compaction process, that is, the kinetic energy conservation state equation of the rammer and the parametric vibrating filler; Step 5: For the rammer, the kinetic energy of the parametrically vibrating filler is called the rammer kinetic energy loss, which is recorded as W. As the mass of the ramming increases, the parametric mass of the filler increases, and the greater the kinetic energy of the filler, the greater the kinetic energy loss. Step 6: Based on the measured rammer acceleration time history curve f(x1), the EMD-Hilbert-Huang transformation is used to calculate the energy of the dynamic compaction vibration signal at different dynamic compaction times; Step 7: Based on the energy conservation state equation, calculate the kinetic energy loss of the vibration signal at different dynamic compaction times through step 6; Step 8: The amount of strong compaction settlement is the difference between the elevations of the roadbed measuring points before and after a single strong compaction. Use a level and a ruler to measure the elevation H1 of the roadbed surface before each strong compaction and the elevation H2 of the roadbed surface after each strong compaction. The conventional detection indicator "settlement" H is equal to the elevation H1 of the roadbed surface before each strong compaction - the elevation H2 of the roadbed surface after the strong compaction. Step 9: Construct the correlation between kinetic energy loss, vibration energy and the conventional indicator "ramming sinking amount", and propose the correlation coefficient between kinetic energy loss, vibration energy and the conventional indicator "ramming sinking amount"; Step 10: Verify through field tests that the correlation coefficients between kinetic energy loss, vibration energy and the conventional indicator "ramming settlement" are all greater than 0.

8. In this case, there is a strong correlation between the intelligent detection indicators of dynamic compaction quality "kinetic energy loss" and "vibration energy" and the conventional indicator "ramming settlement". Therefore, the dual indicators of "kinetic energy loss" and "vibration energy" can be used to detect dynamic compaction quality.

2. The intelligent detection method for the quality of dynamic compaction of a pile based on vibration energy according to claim 1 is characterized by: The step 3 includes the following contents: the conversion between the time domain and the frequency domain in the frequency domain integration method adopts Fast Fourier Transformation; the integration theorem of Fourier transform is: ； a(t) is the time history curve of the rammer acceleration; t is time; ω is the frequency of the time history curve of the rammer acceleration; jw is the complex function e -jwt Index of From the above formula, we can see that when ω<1, that is, f<1 / 2π, the signal is amplified; after the FFT transformation, the DC component is moved to the middle of the spectrum, so that the real and imaginary data obtained by FFT correspond to the frequency, and the common spectrum diagram order is obtained; The speed integral calculation formula is: ； ； ——Rammer acceleration time history curve; A——constant; ——Complex variable function; ω is the frequency.

3. The intelligent detection method for the quality of dynamic compaction of a pile based on vibration energy according to claim 1 is characterized by: The step 6 includes the following: 1) The empirical mode decomposition of the rammer acceleration time history curve is used to obtain multiple intrinsic mode functions (IMFs): ； Where f(t) is the acceleration time history curve of the dynamic compaction process, IMF i (t) are K intrinsic mode functions; where r K (t) is the remainder after subtracting IMF from the signal; i is the number of IMF signals; 2) Define the Hilbert transform of the acceleration time history curve of the dynamic compaction process as the time-frequency-energy spectrum H[f(t)] ； Where t is time, unit is s; τ is the integrand and has no practical meaning; 3) The integral formula for time integration of the time-frequency-energy curve is: ； Where H(ω,t) is the Hilbert spectrum function; e(ω,t) is the Hilbert marginal spectrum function, and ω is the frequency; 4) Integrating step 3) in the frequency domain can obtain the single compaction energy.

4. A non-volatile storage medium, characterized in that: The non-volatile storage medium includes a stored program, wherein when the program is executed, the device where the non-volatile storage medium is located is controlled to execute the method according to any one of claims 1 to 3.

5. An electronic device, characterized in that: The method comprises a processor and a memory; the memory stores computer-readable instructions, and the processor is used to execute the computer-readable instructions, wherein the computer-readable instructions execute the method according to any one of claims 1 to 3 when executed.

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