System and method for monitoring diffusion range and filling degree of filling project in real time

Abstract

The invention relates to a filling engineering diffusion range and filling degree real-time monitoring system and method. The method comprises the steps that an elastic wave field acquisition device transmits acquired elastic wave data to a computer; the computer carries out storage and wave field analysis on the elastic wave data; time domain, frequency domain and time-frequency domain characteristic parameters of an elastic wave field are extracted; inputting the characteristic parameters into a pre-constructed filling state detection model, and outputting to obtain filling state data; inputting the characteristic parameter time sequence trend term into a pre-constructed filling degree detection model, and outputting to obtain filling state data; and further in combination with position information of a single-component velocity detector in the elastic wave field acquisition device, a filling state plane distribution diagram and a filling degree plane distribution diagram are output through a Kriging interpolation method. Compared with the prior art, the filling diffusion range and the filling degree can be accurately monitored in real time, and a user can conveniently, visually and accurately know the time evolution form and the space distribution characteristics of diffusion of the filling material.

Description

Technical Field

[0001] The present invention relates to the technical field of civil engineering construction monitoring, and in particular to a system and method for real-time monitoring of the diffusion range and filling degree of a filling project. Background Art

[0002] During civil engineering construction, high water pressure strata will be crossed, which may easily cause sudden water inrush and sand flow. At the same time, high head pressure places higher demands on the sealing and anti-seepage capabilities of civil engineering. Backfill construction is a key technology in civil engineering construction. Its main function is to reduce stratum loss, control surface settlement, improve waterproofing and anti-seepage capabilities, and improve project quality.

[0003] Since backfilling projects are mostly concealed construction projects, the current backfilling construction quality control is often determined manually based on experience and combined with the backfilling pressure. The actual backfilling construction effect and backfilling material distribution pattern cannot be intuitively and accurately determined. Especially in sandy soil layers with a large permeability coefficient, backfilling materials such as slurry will diffuse in the stratum, resulting in under-grouting. Summary of the invention

[0004] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and to provide a real-time monitoring system and method for the diffusion range and filling degree of filling projects, which can monitor the filling diffusion range and filling degree in real time and accurately, so that users can intuitively and accurately know the time evolution morphology and spatial distribution characteristics of the diffusion of filling materials.

[0005] The object of the present invention can be achieved by the following technical solutions: a real-time monitoring system for the diffusion range and filling degree of a filling project, comprising an elastic wave field acquisition device and a computer connected thereto, wherein the elastic wave field acquisition device is used to collect elastic wave data of the filling construction;

[0006] The computer is used to store elastic wave data, analyze and process the elastic wave data, output corresponding filling state data and filling state data, and output a filling state plane distribution diagram and a filling degree plane distribution diagram.

[0007] Furthermore, the elastic wave field acquisition device includes a plurality of triangular arrays of detectors, the triangular array of detectors is composed of three single-component velocity type detectors distributed in a triangle, the single-component velocity type detectors are closely connected to the filling construction surface through a coupling device, the single-component velocity type detectors are connected to an acquisition instrument, and the acquisition instrument is connected to a computer.

[0008] Furthermore, the plurality of triangular arrays of detectors are arranged with equal intervals along the circumferential direction with the filling hole as the center.

[0009] Furthermore, an automatic excitation hammer is connected to the center of the detector triangular array.

[0010] A method for real-time monitoring of the diffusion range and filling degree of a filling project comprises the following steps:

[0011] S1, the elastic wave field acquisition device transmits the elastic wave data collected in real time to the computer;

[0012] S2. The computer stores and performs wave field analysis on the received elastic wave data. The wave field analysis includes:

[0013] Extract characteristic parameters of elastic wave field in time domain, frequency domain and time-frequency domain;

[0014] Input the characteristic parameters into a pre-built filling state detection model, and output the corresponding filling state data;

[0015] Input the characteristic parameter time series trend item into the pre-built filling degree detection model, and output the corresponding filling state data;

[0016] Combining the filling state data, the filling state data and the position information of the single-component velocity detector in the elastic wave field acquisition device, the filling state plane distribution map and the filling degree plane distribution map are output through the Kriging interpolation method.

[0017] Furthermore, in step S2, the computer specifically saves the received elastic wave data according to the serial number and acquisition time sequence of the single-component velocity type geophones in the elastic wave acquisition device.

[0018] Furthermore, the specific process of extracting the characteristic parameters of the elastic wave field in the time domain, frequency domain and time-frequency domain in step S2 is as follows: first, the collected elastic wave signal is converted into the form of amplitude variation over time through interpretation, the average amplitude is calculated to obtain the characteristics of the elastic wave in the time domain, that is, the variation law of the elastic wave response energy over time, and then the characteristic parameters of the elastic wave in the frequency domain, the dominant frequency and the dominant frequency amplitude, are obtained through fast Fourier transform. Finally, the characteristic parameters of the elastic wave in the time-frequency domain, the variation law of the dominant frequency attenuation time, are obtained through continuous wavelet transform.

[0019] Furthermore, the characteristic parameter time series trend items in step S2 include time series trend items of response energy, dominant frequency, dominant frequency amplitude and dominant frequency decay time.

[0020] Furthermore, the filling state detection model is specifically a neural network model established using a machine learning method, which combines the characteristic parameters of historical elastic waves in the time domain, frequency domain and time-frequency domain with the corresponding filling state, and obtains the filling state detection model through learning and training.

[0021] Furthermore, the filling degree detection model specifically utilizes the time series trend items of the historical elastic wave field characteristic parameters and the corresponding filling degrees, and establishes a mapping relationship between the two to establish the filling degree detection model.

[0022] Compared with the prior art, the present invention has the following advantages:

[0023] 1. The present invention sets an elastic wave field acquisition device and a computer connected thereto, uses the elastic wave field acquisition device to collect elastic wave data of filling construction; uses a computer to store elastic wave data, and performs analysis and processing on the elastic wave data, outputs corresponding filling state data and filling state data, and outputs a plane distribution diagram showing the filling state and the plane distribution diagram of the filling degree. In this way, the filling diffusion range and the filling degree can be monitored in real time and accurately, and the time evolution morphology and spatial distribution characteristics of the filling material diffusion can be intuitively and accurately known.

[0024] Second, the elastic wave field acquisition device designed by the present invention includes a plurality of triangular arrays of detectors, which are arranged with equal spacing along the circumferential direction with the filling hole as the center, and each triangular array of detectors is composed of three single-component velocity type detectors distributed in a triangular pattern, and the single-component velocity type detectors are closely connected to the filling construction surface through a coupling device to prevent the detectors from moving during the monitoring process due to the unevenness of the monitoring surface. In addition, an automatic excitation hammer is connected to the center of the triangular array of detectors. Therefore, according to the shape of the projection of the filling range and the elastic wave field acquisition requirements, the detectors are combined into an array suitable for acquisition, which can fully guarantee the quality of elastic wave data acquisition and improve monitoring efficiency.

[0025] 3. In the present invention, after receiving the elastic wave data, the computer, on the one hand, saves the elastic wave data according to the detector number and time sequence, and on the other hand, performs wave field analysis on the elastic wave data: first, the characteristic parameters and time series trend items of the elastic wave data in the time domain, frequency domain and time-frequency domain are extracted, and then combined with the pre-constructed filling state detection model and filling degree detection model, the corresponding filling state data and filling state data can be obtained quickly and accurately, and further combined with the detector position information, the Kriging interpolation method is used to obtain the plane distribution map of the filling state and the plane distribution map of the filling degree, thereby realizing a spatiotemporal monitoring plan for filling construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a schematic diagram of the system structure of the present invention;

[0027] Figure 2a and Figure 2b It is a schematic diagram of the structure of the detector triangle array in the present invention;

[0028] Figure 3 It is a schematic diagram of the method flow of the present invention;

[0029] Figure 4 It is a schematic diagram of the application process of the embodiment;

[0030] Figure 5a and Figure 5b Schematic diagram of response energy extracted in the embodiment;

[0031] Figure 6a and Figure 6b Schematic diagram of the excellent frequency amplitude extracted in the embodiment;

[0032] Figure 7a and Figure 7b This is a schematic diagram of the main frequency attenuation time extracted in the embodiment;

[0033] Figure 8 A schematic diagram of a time series trend item of response energy in an embodiment;

[0034] Figure 9a , 9b and 9c are plan views of the filling diffusion range and the filling degree distribution diagram in the embodiment;

[0035] Explanation of the marks in the figure: 1. Single-component velocity detector, 2. Filling hole, 3. Automatic excitation hammer, 4. Coupling device, 5. Filling material, 6. Filling space, 7. Collection instrument, 8. Computer. DETAILED DESCRIPTION

[0036] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0037] Example

[0038] like Figure 1 As shown, a real-time monitoring system for the diffusion range and filling degree of a filling project includes an elastic wave field acquisition device and a computer 8 connected thereto, wherein the elastic wave field acquisition device is used to collect elastic wave data of the filling construction;

[0039] The computer 8 is used to store elastic wave data, analyze and process the elastic wave data, output corresponding filling state data, filling state data, and output a filling state plane distribution diagram and a filling degree plane distribution diagram.

[0040] The elastic wave field acquisition device includes a plurality of triangular arrays of geophones, each of which is composed of three single-component velocity geophones 1 distributed in a triangle (e.g. Figure 2a , Figure 2b As shown), the single-component velocity type detector 1 is closely connected to the filling construction surface through a coupling device 4, the single-component velocity type detector 1 is connected to a collection instrument 7, and the collection instrument 7 is connected to a computer 8.

[0041] A plurality of geophone triangular arrays are arranged with equal intervals along the circumferential direction with the filling hole 2 as the center, and an automatic excitation hammer 3 is connected to the center position of the geophone triangular array.

[0042] In practical applications, firstly, the detector 1 and the coupling device 4 are connected to the acquisition instrument 7 and the computer 8 through the connecting cable, and the coupling device 4 ensures that the detector 1 is closely combined with the surface of the filling area; multiple detector triangular arrays are arranged according to the acquisition requirements starting from the filling hole 2 according to a certain track spacing to fully cover the monitoring area, and the automatic excitation hammer 3 is used to vertically strike near the detector 1 to excite elastic waves. In the actual operation process, try to keep the same force each time to strike the surface at the same distance from the detector 1, that is, when the hammer is used to excite the elastic wave signal, the force of each hammer and the distance from the detector 1 are kept consistent as much as possible to prevent human factors from interfering with the elastic wave field. In addition, the influence of environmental noise can be removed by filtering operation to reduce the accuracy of other factors interfering with the elastic wave field data. The acquisition instrument 7 collects elastic wave data according to the set acquisition time, and transmits it to the computer 8 in real time for data storage and analysis.

[0043] In this embodiment, a spring buffer device is added to the coupling device, which can ensure that the detector is tightly fitted to the monitoring surface under different conditions, and prevent the detector from moving during the monitoring process and causing a position change; in this embodiment, the number of single-component velocity detectors is proportional to the size of the monitoring range, and each detector is connected to the connecting cable through a separate interface, and elastic wave collection work is carried out at intervals from the start of filling construction.

[0044] Based on the above monitoring system, a real-time monitoring method for the diffusion range and filling degree of the filling project is realized, such as Figure 3 As shown, the following steps are included:

[0045] S1, the elastic wave field acquisition device transmits the elastic wave data collected in real time to the computer;

[0046] S2. The computer saves the received elastic wave data and performs wave field analysis. The wave field analysis includes:

[0047] Extract characteristic parameters of elastic wave field in time domain, frequency domain and time-frequency domain;

[0048] Input the characteristic parameters into a pre-built filling state detection model, and output the corresponding filling state data;

[0049] Input the characteristic parameter time series trend item into the pre-built filling degree detection model, and output the corresponding filling state data;

[0050] Combining the filling state data, the filling state data and the position information of the single-component velocity detector in the elastic wave field acquisition device, the filling state plane distribution map and the filling degree plane distribution map are output through the Kriging interpolation method.

[0051] This embodiment applies the above technical solution, such as Figure 4 As shown, the main contents are:

[0052] Step 1: Elastic wave field acquisition: a triangular array of detectors consisting of single-component velocity detectors is arranged at a certain distance from the starting position of the filling construction, and the detector is closely attached to the filling construction surface using a coupling device to prevent the detector from moving. The detector, the acquisition instrument, and the computer are connected using a connecting cable, the acquisition instrument is started, and the acquisition time is set. The elastic wave signal is excited by an automatic excitation hammer, and the elastic wave field data during the filling construction process is collected in real time using the detector and the acquisition instrument.

[0053] Step 2, wave field analysis, the elastic wave data during the filling construction process is stored in the computer in real time and dynamically through data transmission, and the elastic wave data is saved in the computer according to the detector number and time sequence. According to the position and number of each detector, the detector data at different positions are extracted and arranged in time sequence from the beginning to the end of filling, and then wave field analysis is performed.

[0054] Step 2.1, using the elastic wave field analysis module of the computer to analyze the collected elastic wave field data, including the analysis of the elastic wave field in the time domain, frequency domain and time-frequency domain: extracting the elastic wave characteristic parameter response energy in the time domain (such as Figure 5a , 5b As shown), specifically, the collected elastic wave signal is converted into the form of amplitude variation over time through interpretation, and the average amplitude is calculated to obtain the characteristics of the elastic wave in the time domain, that is, the law of variation of the elastic wave response energy over time;

[0055] The characteristic parameters of elastic waves in the frequency domain, namely, the dominant frequency and the dominant frequency amplitude (such as Figure 6a , 6b Specifically, the characteristic parameters of elastic waves in the frequency domain, namely, the dominant frequency and the dominant frequency amplitude, are obtained by fast Fourier transform.

[0056] The time-frequency domain characteristic parameters are extracted by continuous wavelet transform, such as the main frequency decay time (such as Figure 7a , 7b Specifically, the characteristic parameter of elastic waves in the time-frequency domain, the change law of the main frequency decay time over time, is obtained by continuous wavelet transform;

[0057] In addition, the time series trend item analysis module of the computer is used to extract the time series trend items of the response energy, the dominant frequency, the dominant frequency amplitude and the main frequency decay time. In this embodiment, the time series trend item of the response energy is as follows: Figure 8 shown.

[0058] Step 2.2: Use machine learning methods to establish a filling state detection model, and use the changes in elastic wave characteristic parameters to determine the filling state.

[0059] Step 2.3: Use the time series trend term analysis to summarize the changing rules of elastic wave characteristic parameters with filling time, establish a trend term model of filling state changing with filling time (i.e., filling degree detection model), and use the time series trend term model to determine the filling degree of the filling project.

[0060] Step 3: Determine the filling status of the location through the changes in the characteristic parameters of the elastic wave field collected by the geophones at different locations, and then realize the filling construction diffusion range (such as Figure 9a ), the time evolution law of filling state and the spatial distribution diagram (as shown in Figure 9b , 9c shown).

[0061] The diffusion range in the filling project can be monitored by the position information of the detector; the filling degree refers to the ratio of the filling area to the total monitoring area. The filling result is divided into two situations: full and underfilled by the filling degree. In this embodiment, the diffusion range that meets the filling requirements and the filling degree is greater than 85% is evaluated as qualified; the diffusion range that meets the design requirements and the filling degree between 65-85% is defined as basically qualified; other situations are unqualified. In this way, the diffusion range and filling degree indicators are used to quickly and accurately evaluate the quality of the filling project.

[0062] In summary, this plan proposes a spatiotemporal monitoring plan for civil engineering filling construction. Through the elastic wave field acquisition device, wave field analysis method, filling status assessment model construction, time series trend item extraction method, and filling engineering spatiotemporal evaluation model construction, the diffusion range and filling degree of the filling construction can be monitored quickly and in real time, and the filling distribution form and filling quality can be detected and evaluated.

[0063] This solution combines the detectors into an array suitable for acquisition according to the shape of the filling range projection and the elastic wave field acquisition requirements, thereby ensuring the acquisition quality and improving the monitoring efficiency.

[0064] This scheme uses wave field analysis methods and time series trend term extraction methods to extract characteristic parameters of elastic waves in time domain, frequency domain and time-frequency domain, and analyzes the changes of characteristic parameters in time domain, frequency domain and time-frequency domain with filling construction time.

[0065] This scheme uses machine learning methods to establish a neural network model, establish the relationship between the characteristic parameters of elastic waves in the time domain, frequency domain and time-frequency domain and the filling state, and use the model to quickly and accurately detect the filling state.

[0066] This scheme uses time series trend analysis to analyze the change pattern of elastic wave characteristic parameters with filling time, and establishes a mapping relationship between the time series trend items of elastic wave field characteristic parameters and the filling degree of the filling project to quickly and accurately detect the filling degree.

[0067] This scheme uses the filling state assessment model and the filling degree assessment model, combined with the Kriging interpolation method and the coordinate information of the detector, to analyze the filling state and the filling degree spatial distribution form. By using the filling engineering diffusion range and filling degree as evaluation parameters, the quality of the filling engineering can be quickly and accurately evaluated. It provides data support for the monitoring of the filling diffusion range and filling degree during the filling process, and escorts the actual engineering application of grouting in the later stage.

[0068] This scheme defines the diffusion range meeting the requirements and the filling degree greater than 85% as qualified, the diffusion range meeting the requirements and the filling degree between 65-85% as basically qualified, and the other cases as unqualified. That is, the diffusion range and filling degree indicators can be used to quickly and effectively evaluate the quality of the filling project.

[0069] This plan is of great significance to the establishment of civil engineering survey, hidden engineering monitoring method research and engineering quality assessment. It is also of great significance to further effectively reduce civil engineering risks and improve civil engineering quality capabilities through related research in the future.

Claims

1. A real-time monitoring system for the diffusion range and filling degree of a filling project, characterized in that: It comprises an elastic wave field acquisition device and a computer (8) connected thereto, wherein the elastic wave field acquisition device is used to acquire elastic wave data of filling construction; The computer (8) is used to store elastic wave data, analyze and process the elastic wave data, output corresponding filling state data and filling state data, and output a filling state plane distribution diagram and a filling degree plane distribution diagram.

2. A real-time monitoring system for the diffusion range and filling degree of a filling project according to claim 1, characterized in that: The elastic wave field acquisition device comprises a plurality of geophone triangular arrays, wherein the geophone triangular array is composed of three single-component velocity geophones (1) distributed in a triangular arrangement, wherein the single-component velocity geophones (1) are closely connected to the filling construction surface via a coupling device (4), wherein the single-component velocity geophones (1) are connected to an acquisition instrument (7), and wherein the acquisition instrument (7) is connected to a computer (8).

3. A real-time monitoring system for the diffusion range and filling degree of a filling project according to claim 2, characterized in that: The plurality of triangular arrays of detectors are arranged with equal spacing along the circumferential direction with the filling hole (2) as the center.

4. A real-time monitoring system for the diffusion range and filling degree of a filling project according to claim 2, characterized in that: An automatic excitation hammer (3) is connected to the center of the detector triangle array.

5. A method for real-time monitoring of the diffusion range and filling degree of a filling project using the real-time monitoring system for the diffusion range and filling degree of a filling project as claimed in claim 2, characterized in that: The following steps are involved: S1, the elastic wave field acquisition device transmits the elastic wave data collected in real time to the computer; S2. The computer stores and performs wave field analysis on the received elastic wave data. The wave field analysis includes: Extract characteristic parameters of elastic wave field in time domain, frequency domain and time-frequency domain; Input the characteristic parameters into a pre-built filling state detection model, and output the corresponding filling state data; Input the characteristic parameter time series trend item into the pre-built filling degree detection model, and output the corresponding filling state data; Combining the filling state data, the filling state data and the position information of the single-component velocity detector in the elastic wave field acquisition device, the filling state plane distribution map and the filling degree plane distribution map are output through the Kriging interpolation method.

6. A method for real-time monitoring of the diffusion range and filling degree of a filling project according to claim 5, characterized in that: In step S2, the computer specifically saves the received elastic wave data according to the serial number and acquisition time sequence of the single-component velocity type geophones in the elastic wave acquisition device.

7. A method for real-time monitoring of diffusion range and filling degree of filling engineering according to claim 6, characterized in that: The specific process of extracting the characteristic parameters of the elastic wave field in the time domain, frequency domain and time-frequency domain in the step S2 is as follows: first, the collected elastic wave signal is converted into the form of amplitude variation over time through interpretation, the average amplitude is calculated to obtain the characteristics of the elastic wave in the time domain, that is, the variation law of the elastic wave response energy over time, and then the characteristic parameters of the elastic wave in the frequency domain, the dominant frequency and the dominant frequency amplitude, are obtained by fast Fourier transform. Finally, the characteristic parameters of the elastic wave in the time-frequency domain, the variation law of the dominant frequency attenuation time, are obtained by continuous wavelet transform.

8. A method for real-time monitoring of the diffusion range and filling degree of a filling project according to claim 7, characterized in that: The characteristic parameter time series trend items in step S2 include time series trend items of response energy, dominant frequency, dominant frequency amplitude and dominant frequency decay time.

9. A method for real-time monitoring of the diffusion range and filling degree of a filling project according to claim 5, characterized in that: The filling state detection model is specifically a neural network model established using a machine learning method, which combines the characteristic parameters of historical elastic waves in the time domain, frequency domain and time-frequency domain with the corresponding filling state, and obtains the filling state detection model through learning and training.

10. A method for real-time monitoring of diffusion range and filling degree of filling engineering according to claim 5, characterized in that: The filling degree detection model specifically utilizes the time series trend items of the historical elastic wave field characteristic parameters and the corresponding filling degrees, and establishes a mapping relationship between the two to establish the filling degree detection model.

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