GPR Detection Imaging Method, Device and Processing Equipment for the Development of Frozen Wall

Abstract

The present application provides a GPR detection imaging method, device and processing equipment for the development of frozen walls. Based on the signals collected by GPR detection, the correlation between each channel of signals is additionally considered, and secondary imaging is realized through the cross-correlation backprojection algorithm, avoiding the interference brought by the complexity conditions of electromagnetic interference detection environments such as shield segments. In this way, the resolution and imaging accuracy can be effectively improved, which helps to more clearly complete the identification of the development of frozen walls and meet the high-quality data usage requirements of rock engineering involving AGF.

Description

Technical Field

[0001] The present application relates to the field of geology, and in particular to a GPR detection imaging method, device and processing equipment for frozen wall development. Background Art

[0002] Artificial Ground Freezing (AGF) involves using artificial refrigeration technology to convert natural rock and soil into frozen soil at low temperatures, forming a frozen wall to temporarily isolate groundwater. It is an important construction method for traversing complex strata. Due to its advantages such as good water-isolating effect, strong adaptability, and environmental friendliness, it has been widely used in various underground projects.

[0003] In actual geotechnical engineering, adverse geological conditions often arise, such as excessive groundwater velocity, water-rich cemented rock layers, gravel formations, localized underground cavities, and excessively high soil salinity. Under these conditions, frozen walls often fail to close on time, their overall strength falls short of standards, or they develop cavities within the wall. This not only causes significant economic losses but also poses a significant threat to construction safety. Therefore, the development of frozen walls directly determines the success or failure of freezing projects, making early prediction, process monitoring, and effectiveness evaluation of abnormal frozen wall development crucial.

[0004] In traditional methods, the development of frozen walls is usually judged by temperature measurement data, and the expansion and thickness of the frozen walls are roughly inferred through experience. However, due to the very limited location and number of temperature measurement points, it is impossible to accurately describe the overall development of the frozen area, which can easily lead to misjudgment and omission of some unfrozen areas.

[0005] Ground Penetrating Radar (GPR) uses the reflection and transmission of ultra-high frequency electromagnetic waves (1MHz to 5GHz) to determine the distribution within a medium. Dielectric constant and conductivity are the two most critical factors affecting GPR detection effectiveness. The greater the difference in electromagnetic parameters between the media, the more pronounced the electromagnetic wave reflection deflection, making the two media easier to detect and identify. GPR is playing an increasingly important role in near-surface exploration. The physical and electrical properties of natural frozen soil differ significantly from those of unfrozen soil. Therefore, by conducting GPR detection on frozen rock and soil at appropriate locations and analyzing and comparing the data, the distribution areas of frozen wall anomalies and their development can be determined.

[0006] However, the inventors of the present application have found that there are still problems in the process of using GPR detection to identify the development of the frozen wall in the existing solutions. Specifically, due to the complexity of the detection environment, such as the electromagnetic interference of the shield segments, the frozen wall is usually adjacent to the segment area, and the electromagnetic wave needs to pass through the segment layer to reach the target soil layer, which will affect the accurate determination of the detection image results, resulting in limitations in the recognition accuracy and efficiency of the development of the frozen wall. Summary of the Invention

[0007] The present application provides a GPR detection imaging method, device and processing equipment for the development of the frozen wall, which, on the basis of the signals collected by GPR detection, additionally considers the correlation between each signal and realizes secondary imaging through the cross-correlation back-projection algorithm, avoiding the interference brought by the complexity of the electromagnetic interference detection environment such as shield segments. In this way, the resolution and imaging accuracy can be effectively improved, which helps to more clearly complete the identification of the development of the frozen wall and meet the high-quality data usage requirements of rock engineering involving AGF.

[0008] In the first aspect, the present application provides a GPR detection imaging method for the development of the frozen wall, and the method includes:

[0009] Obtain a first signal obtained by performing GPR detection processing on the frozen rock and soil to be detected, wherein the frozen rock and soil to be detected forms a corresponding frozen wall through AGF processing;

[0010] Perform data preprocessing on the first signal to obtain a second signal to initially enhance the signal quality;

[0011] On the basis of the second signal, when performing imaging processing using the back-projection algorithm, consider the correlation between each signal, and realize secondary imaging through the cross-correlation back-projection algorithm to obtain a reconstructed image;

[0012] Perform secondary signal processing on the reconstructed image to obtain a third signal to continuously enhance the signal quality.

[0013] In the second aspect, the present application provides a GPR detection imaging device for the development of the frozen wall, and the device includes:

[0014] An acquisition unit for acquiring a first signal obtained by performing GPR detection processing on the frozen rock and soil to be detected, wherein the frozen rock and soil to be detected forms a corresponding frozen wall through AGF processing;

[0015] A preprocessing unit for performing data preprocessing on the first signal to obtain a second signal to initially enhance the signal quality;

[0016] An imaging unit, which, in the process of performing imaging processing using the back-projection algorithm based on the second signal, takes into account the correlation between each channel signal, and realizes secondary imaging through the cross-correlation back-projection algorithm to obtain a reconstructed image;

[0017] A secondary processing unit, which is used to perform secondary signal processing on the reconstructed image to obtain a third signal so as to continuously enhance the signal quality.

[0018] In a third aspect, the present application provides a processing device, including a processor and a memory. A computer program is stored in the memory. When the processor calls the computer program in the memory, it executes the method provided in the first aspect of the present application or any possible implementation manner of the first aspect of the present application.

[0019] In a fourth aspect, the present application provides a computer-readable storage medium. The computer-readable storage medium stores multiple instructions, and the instructions are suitable for being loaded by a processor to execute the method provided in the first aspect of the present application or any possible implementation manner of the first aspect of the present application.

[0020] It can be concluded from the above content that the present application has the following beneficial effects:

[0021] Regarding the GPR detection imaging target of the freezing wall development situation, based on the signals collected by GPR detection, the present application additionally considers the correlation between each channel signal, and realizes secondary imaging through the cross-correlation back-projection algorithm, avoiding the interference brought by the complexity conditions of the electromagnetic interference detection environment such as shield segments. In this way, the resolution and imaging accuracy can be effectively improved, which helps to more clearly complete the identification of the freezing wall development situation and meet the high-quality data usage requirements of rock engineering involving AGF. Description of the Drawings

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present application. For those skilled in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0023] Figure 1 It is a schematic flowchart of a GPR detection imaging method for the freezing wall development situation of the present application;

[0024] Figure 2 It is a schematic diagram of a scenario for GPR detection when the present application moves from the frozen area to the unfrozen area;

[0025] Figure 3 It is a schematic structural diagram of a GPR detection imaging device for the freezing wall development situation of the present application;

[0026] Figure 4 This is a schematic structural diagram of the processing device of the present application. Detailed implementation manners

[0027] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative efforts shall fall within the protection scope of the present application.

[0028] Terms such as "first" and "second" in the specification, claims and the above-mentioned drawings of the present application are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that such used data can be interchanged under appropriate circumstances so that the embodiments described herein can be implemented in an order different from that shown or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or modules does not necessarily limit to those clearly listed steps or modules, but may include other steps or modules not clearly listed or inherent to these processes, methods, products or devices. The naming or numbering of steps that appear in the present application does not mean that the steps in the method flow must be executed in the time / logical sequence indicated by the naming or numbering. The named or numbered process steps can be changed in the execution order according to the technical purpose to be achieved, as long as the same or similar technical effects can be achieved.

[0029] The division of modules in the present application is a logical division. In actual implementation, there may be other division methods. For example, multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed couplings or direct couplings or communication connections between each other can be through some interfaces. The indirect couplings or communication connections between modules can be electrical or other similar forms, which are not limited in the present application. And the modules or sub-modules described as separate components may or may not be physically separated, may or may not be physical modules, or may be distributed to multiple circuit modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of the present application.

[0030] Before introducing the GPR detection imaging method for the development of the freezing wall provided by the present application, the background content involved in the present application will be introduced first.

[0031] The GPR detection and imaging method, device and computer-readable storage medium for the development of frozen walls provided in this application can be applied to processing equipment to additionally consider the correlation between each signal on the basis of the signals collected by GPR detection, and realize secondary imaging through the cross-correlation back projection algorithm, so as to avoid the interference caused by the complex conditions of electromagnetic interference detection environment such as shield segments. This can effectively improve the resolution and imaging accuracy, help to more clearly complete the identification of the development of frozen walls, and meet the high-quality data usage requirements of rock engineering involving AGF.

[0032] The GPR imaging method for detecting frozen wall development mentioned in this application can be implemented by a GPR imaging device for detecting frozen wall development, or by various types of processing devices, such as a server, physical host, or user equipment (UE) that integrates the GPR imaging device for detecting frozen wall development. The GPR imaging device for detecting frozen wall development can be implemented using hardware or software, and the UE can be a terminal device such as a smartphone, tablet computer, laptop computer, desktop computer, or personal digital assistant (PDA). The processing device can be configured as a device cluster.

[0033] It is understandable that, in actual situations, considering that the present application usually carries out data processing based on the existing data obtained by GPR detection and processing, the processing equipment that executes the GPR detection and imaging method for frozen wall development of the present application, or the processing equipment equipped with the corresponding application service of the GPR detection and imaging method for frozen wall development of the present application, usually only needs to meet the required data processing capabilities. If it involves GPR detection data acquisition and processing, or the output / display of image results, it is obvious that the specific equipment structure and equipment deployment form of the processing equipment can be further adaptively adjusted according to the actual situation.

[0034] As an example, the processing equipment of this application under the equipment cluster solution can specifically include GPR equipment responsible for data collection on site, central processing equipment responsible for data processing in the background, and display equipment responsible for image display on the user side, corresponding to the three major aspects that can be involved when applying the solution of this application, thus having a relatively complete solution deployment feature.

[0035] Next, the GPR detection and imaging method for frozen wall development provided by the present application will be introduced.

[0036] First, see Figure 1 , Figure 1Fig. 0 shows a schematic flow chart of a GPR detection imaging method for the development of a frozen wall according to the present application. The GPR detection imaging method for the development of a frozen wall provided by the present application may specifically include the following steps S101 to S104:

[0037] Step S101: Obtain a first signal obtained by performing GPR detection processing on the frozen rock and soil to be detected, where the frozen rock and soil to be detected forms a corresponding frozen wall through AGF processing;

[0038] It can be understood that in engineering work, the application of AGF (i.e., artificial ground freezing method) may be involved, so that natural rock and soil is transformed into frozen soil under the action of low temperature to form a frozen wall, so as to play a role in temporarily isolating groundwater. In this regard, there is a corresponding need for frozen wall monitoring to ensure that the project can be advanced under expected conditions.

[0039] In this regard, as in the prior art, after AGF processing, GPR (ground penetrating radar) detection processing can be carried out on the frozen rock and soil to be detected on site to obtain the original signal for subsequent data processing. For the convenience of description, the data of the original signal obtained here is recorded as the first signal, and subsequent signals will also be distinguished by the second signal and the third signal.

[0040] It should be noted that the acquisition and processing of the first signal here can either be real-time signal acquisition and processing, that is, it involves real-time GPR detection processing, or it can be the extraction and processing of existing signals, that is, directly extract the detection results of the completed GPR detection processing, which can be adjusted according to actual needs.

[0041] As an exemplary embodiment here, the GPR detection processing involved in the present application may specifically include the following processing contents:

[0042] After radar selection, survey line layout, and detection environment optimization, enter the specific detection work. The GPR host is kept close to the surface of the segment and moves forward uniformly and linearly along the survey line direction at a speed not higher than 5 cm / s and always remains consistent. The distance advanced along the survey line during each operation is the same and the error does not exceed 5 cm. The detection time node starts before freezing, and during the active freezing period, ensure that detection is carried out every 6 hours, and each survey line is detected 3 times each time.

[0043] Among them, there is:

[0044] (1) For the radar selection process, specifically, the target detection depth can be determined according to the designed thickness and strength of the frozen wall in the frozen project, combined with the design dimensions of the segment, so as to clarify the center frequency of the GPR device (i.e., the ground penetrating radar). Usually, a range of 400 - 1200 MHz can be selected to balance the target detection depth and resolution.

[0045] (2) For the survey line layout process, specifically, the distribution and length of the survey lines can be reasonably planned and arranged in combination with the position and estimated thickness of the frozen wall to ensure that the subsequent detected data can comprehensively reflect the development of the frozen area.

[0046] (3) For the detection environment optimization process, specifically, in order to improve the imaging quality and prevent misjudgment and missed judgment of the detection results, on the one hand, due to the shielding effect of metal conductors on electromagnetic waves, it is necessary to minimize its electromagnetic interference. The construction environment at the freezing site can be cleaned up, such as temporarily removing unnecessary scaffolding and steel pipes near the survey line to ensure that there are no large loading equipment around during the detection work. On the other hand, in order to make the detection results as simple and clear as possible and avoid complex multi-layer media, during the detection work, under the condition that the overall freezing effect is not affected, the segment insulation layer can be temporarily removed and reinstalled after the detection work is completed.

[0047] (4) For the specific detection work, during the detection work, the GPR host (transmitting / receiving antenna) can be kept closely attached to the surface of the segment and move forward uniformly in a straight line along the survey line direction at a speed not higher than 5 cm / s and always remain consistent, and the distance advanced along the survey line during each operation is the same and the error does not exceed 5 cm; the detection time node starts before freezing, and during the active freezing period, it is ensured to detect once every 6 hours, and each survey line is detected 3 times each time to ensure the reliability and stability of the data.

[0048] Regarding the specific detection scheme here, it should be noted that in the conventional GPR detection and processing, when detecting the interface of different media, the interface of adjacent media is usually parallel to the layout direction of the survey line. In the freezing project, the target medium changes along the detection direction, which has an adverse impact on the detection resolution and accuracy. In contrast, the specific detection scheme given in this application can effectively avoid this problem and ensure high-level imaging accuracy and resolution in the follow-up, so it has better practical value.

[0049] Step S102, perform data preprocessing on the first signal to obtain a second signal to initially enhance the signal quality;

[0050] After obtaining the first signal, instead of directly performing the corresponding imaging process, this application also involves data preprocessing to enhance the signal quality, which helps improve the processing efficiency and accuracy of subsequent imaging processes.

[0051] It can be understood that data preprocessing is a common part of data analysis work. The specific preprocessing operations involved can usually adopt existing solutions, or can be further optimized and improved on the basis of existing solutions, or novel self-developed solutions can also be adopted, all of which are allowed in actual situations.

[0052] Thus, after completing data preprocessing and obtaining the second signal, the specific imaging process can be carried out.

[0053] As an exemplary embodiment here, the data preprocessing involved in this application can specifically include the removal of data points with abnormal noise, the removal of data points with missing content, time zero point correction processing, background noise removal processing, and gain processing.

[0054] Specifically, there are:

[0055] (1) For the removal of data points with abnormal noise, obviously, its purpose is to remove / filter out data points with abnormal noise, that is, abnormal noise points, which is one of the more traditional data preprocessing operations;

[0056] (2) For the removal of data points with missing content, obviously, its purpose is to remove / filter out data points with missing content, that is, missing content points, which is one of the more traditional data preprocessing operations;

[0057] (3) Time zero point correction processing, considering that due to the relative positions of the transmitting and receiving antennas, the echo signal may not be on the correct time axis, so the time zero point / time axis of the data can be corrected;

[0058] (4) Background noise removal processing, considering that there may be noise from the antenna system itself in the data, so background noise can be eliminated by methods such as background averaging or filtering;

[0059] (5) Gain processing, considering that since the signal will attenuate during the process of penetrating the medium, increasing the gain can improve the visibility of the later reflected signal. Specifically, time-varying gain or exponential gain and other gain methods can be used to strengthen the signal.

[0060] Thus, through the above data preprocessing operations, in specific applications, the difference between frozen soil and unfrozen soil can be further highlighted, which helps improve the subsequent imaging quality.

[0061] In step S103, during the imaging process using the back-projection algorithm based on the second signal, considering the correlation between signals of each channel, the cross-correlation back-projection algorithm is used to achieve secondary imaging and obtain a reconstructed image.

[0062] During the imaging process, back-projection processing is involved. It can be understood that the back-projection processing itself is also a processing link involved in the prior art. However, the inventors of the present application found that the back-projection processing or the back-projection algorithm adopted in the existing solution only considers the combination (accumulation result) of the response amplitudes (in vector form) of each channel as the final imaging result, but does not consider the inherent correlation in the vector, thus having limitations in imaging accuracy and resolution.

[0063] In this case, during the imaging process involved in the present application, when performing imaging processing through the back-projection algorithm, the correlation between signals of each channel is additionally considered / attended to, and the cross-correlation back-projection algorithm specifically designed is used to calculate the combined result of the response amplitudes, which is output as a new imaging result to obtain improved imaging accuracy and resolution.

[0064] The output data of the imaging process here is itself also a kind of signal, which can be denoted as a reconstructed image.

[0065] Next, the imaging process here can be more deeply understood in combination with GPR detection processing.

[0066] Reference Figure 2 shows a schematic diagram of a scenario where the present application moves from the frozen area to the unfrozen area for GPR detection. During the detection process, the following contents may be involved:

[0067] The specified detection area is divided into m×n pixels, each pixel having a width of dx and a height of dz, thus forming a planar model. The left side is the frozen area, and the right side is the unfrozen area. Starting from x = 0, the radar moves forward, continuously emitting and receiving electromagnetic waves.

[0068] Corresponding to the limited working range of the GPR main lobe, the detection scanning process can be divided into four different stages:

[0069] 1) Stage I: Detect the frozen area below, characterized by a single medium, with a stable response amplitude (ResponseAmplitude, RA) and no deflection.

[0070] 2) Stage II: At the boundary where the main lobe range intersects with the unfrozen area, the response amplitude shows stratification, resulting in deflection.

[0071] 3) Phase III: The main lobe signal contains both frozen and unfrozen areas, indicating that the scan coverage gradually transitions to the unfrozen area;

[0072] 4) Phase IV: Detect the unfrozen area below and complete the full scanning process.

[0073] GPR has three scanning modes, corresponding to which three types of data can be obtained: A-scan data (single-channel waveform data), B-scan data (two-dimensional profile data) and C-scan data (three-dimensional data).

[0074] As an exemplary embodiment, the back projection algorithm mentioned above may specifically include the following contents:

[0075] Assume that the designated detection area is divided into m×n pixels, and the two-way travel time (TWT) τ of pixel A in the p-th channel signal of the A-scan data is A,P It can be expressed as follows:

[0076]

[0077] Among them, ε1 is the relative dielectric constant of the frozen soil area, dimensionless, dx is the pixel width, dz is the pixel height, c is the speed of light in vacuum, i A is the horizontal coordinate of pixel A, j A is the ordinate of pixel A,

[0078] In this case, the response amplitude RA corresponding to each pixel is A,P It can be expressed as follows:

[0079] RA A，p =s p (t=τ A，p ),

[0080] Among them, S p The reflected electromagnetic wave recorded by the GPR moving to the p-th channel signal is:

[0081] Then, considering that the transmitted radar signal has a main lobe characteristic, if a pixel (for example, pixel B) is outside the main lobe of the A-scan, the response amplitude value may appear to be zero. Generally, the response amplitude of a pixel in Phase I can be expressed as follows:

[0082]

[0083] Where θ is the maximum coverage distance of the radar main lobe signal,

[0084] When the GPR enters phases II and III, due to the change of the medium along the measurement line, the signal is refracted. For example, for pixel D, the two-way propagation time of pixel D in the A-scan α can be expressed as follows:

[0085]

[0086] where ε2 is the relative permittivity of the unfrozen soil area, dimensionless,

[0087] The electromagnetic wave is emitted from the α-th synthetic aperture position and passes through the refraction point R(i R , j R ) to reach point D(i D , j D ) according to Snell's law of refraction, and then reaches the GPR antenna for reception. The coordinates of the refraction point R(i R , j R ) can be determined by the iterative method. When the electromagnetic wave enters the unfrozen area, the response amplitude of the pixel can be described as follows:

[0088]

[0089] The GPR measurement generates n sets of A-scan data, as Figure 2 shown. The response distribution of each imaging point in the signal is in these n sets of A-scan data generated by the GPR measurement. For example, for a given point A, corresponding to pixel A, at least n two-way propagation times must be calculated. These TWT data are used to index and retrieve the information corresponding to point A in the corresponding A-scan data, so as to generate an n×1 vector representing point A, that is, [RA A,1 , RA A,2 , … RA A,n ,

[0090] In this case, for the standard back-projection algorithm, corresponding to pixel A, there are n sets of response amplitudes (here n corresponds to the n in the previous m×n pixels, that is, it is the same specific numerical value). The vector combination is an imaging output result, as shown in the following formula:

[0091]

[0092] However, the inventors of the present application found that the existing back-projection algorithm (Back projection method, BP) only combines these n vectors to obtain the final imaging result, but does not consider the correlation between each A-scan signal, which brings limitations to the imaging accuracy and resolution in imaging.

[0093] In this regard, in order to emphasize the inherent correlation between the acquired vectors, the present application improves the back-projection algorithm and realizes it through the constructed correlation matrix V.

[0094] Specifically, as an exemplary embodiment herein, the correlation between each channel signal (A-scan signal) can be specifically represented by the correlation matrix V constructed by the following formula:

[0095]

[0096] In this way, through the cross-correlation operation, the computational amount is increased from n to n×(n - 1) / 2, and the correlation superposition process can be expressed as follows:

[0097]

[0098] where E A CBP is the total response amplitude calculated by the cross-correlation back-projection algorithm, and i and j are respectively the row number and column number of the current element in the correlation matrix v.

[0099] It can be seen that the present application performs cross-correlation back-projection based on the designed correlation matrix V and obtains E that takes into account the correlation between each signal A CBP , and for pixel A, the calculation of the response amplitude with higher accuracy and more in line with the deep situation is realized. Thus, overall, it can promote the consideration of both imaging accuracy and resolution.

[0100] Specifically, the imaging processing involved in the present application, or the improved back-projection algorithm involved, can clearly image, suppress most of the clutter interference, avoid the interference brought by the complexity conditions of the electromagnetic interference detection environment such as shield segments, effectively improve the imaging accuracy and resolution. Secondly, for the unconventional stratified medium model of the vertical freezing front, it can also better image the position of the frozen-unfrozen boundary and the development form of the frozen wall, improve the readability of the detection results, and more intuitively highlight the stratified area and the abnormal area.

[0101] Step S104, perform secondary signal processing on the reconstructed image to obtain a third signal to further enhance the signal quality.

[0102] It can be understood that after the imaging process of the second signal is completed, further data enhancement can be performed on the obtained reconstructed image. It can be understood that the data enhancement process here is denoted as secondary processing. The specific strategies / rules involved in its specific data enhancement operations are different from the previous data preprocessing. It is necessary to consider not only the data characteristics of the reconstructed image obtained after the previous imaging process as the input data, but also the input requirements involved in subsequent data analysis work, rather than staying at the level of generally improving data quality as conventionally understood.

[0103] Further, as an exemplary embodiment here, the secondary signal processing involved in the present application may specifically include filtering processing and data enhancement processing;

[0104] The filtering processing includes high-pass filtering, low-pass filtering, band-pass filtering, and removing direct waves;

[0105] The data enhancement processing includes frequency domain conversion, eliminating random noise through convolution operation, and comparing data at different time points.

[0106] In the filtering processing, specifically, there are:

[0107] (1) For high-pass filtering and low-pass filtering, a suitable cut-off frequency is preselected according to the data characteristics to remove high-frequency noise and low-frequency drift in the data;

[0108] (2) For band-pass filtering, it is to retain the effective signals within a specific frequency band and further reduce noise;

[0109] (3) For removing direct waves, considering that direct waves may mask important reflection signals, especially in near-surface detection, differential filtering and other methods can be used to remove them.

[0110] It can be understood that the above filtering processing means are relatively common filtering methods in signal filtering processing. They are combined with data enhancement means to effectively and preferably achieve the effect of signal secondary enhancement.

[0111] In the data enhancement processing, specifically, there are:

[0112] (1) For frequency domain conversion, it is for frequency analysis. Through methods such as Fourier transform, the signal is converted to the frequency domain to enhance signal characteristics and make signal analysis more convenient;

[0113] (2) For eliminating random noise through convolution operation, it is to further eliminate random noise in the signal through convolution operation;

[0114] (3) For comparing data at different time points, it can also be referred to as differential processing. For freeze effect evaluation, the time difference method can be used to compare data at different time points, thus more conveniently and intuitively highlighting the changes in the frozen area.

[0115] Generally speaking, from the above solution content, for the GPR detection imaging target of the frozen wall development situation, based on the signals collected by GPR detection, this application additionally considers the correlation between each channel signal and realizes secondary imaging through the cross-correlation back-projection algorithm, avoiding the interference brought by the complexity conditions of electromagnetic interference detection environments such as shield segments. In this way, the resolution and imaging accuracy can be effectively improved, which helps to more clearly complete the identification of the frozen wall development situation and meet the high-quality data usage requirements of rock engineering involving AGF.

[0116] After the imaging processing and signal secondary processing are completed, it can be understood that it can be put into the specific data application link, and the most important one is obviously the identification and analysis processing of the frozen wall development situation.

[0117] In this regard, as an exemplary embodiment, after step S104 performs signal secondary processing on the reconstructed image to obtain a third signal to further enhance the signal quality, the method of this application may further include:

[0118] Based on the third signal, further data analysis processing is carried out;

[0119] Among them, the data analysis processing includes reflected signal analysis, frozen wall development situation identification, and differential imaging. Specifically, there are:

[0120] (1) The reflected signal analysis specifically analyzes the changes in the medium before and after freezing according to the signal characteristics including intensity and phase change. The strong reflection area corresponds to the frozen area or abnormal structure;

[0121] (2) The frozen wall development situation identification specifically estimates the frozen wall thickness and the abnormal development area of the frozen wall based on the relationship between the reflection time and the velocity, and verifies the detection imaging results by combining the temperature measurement inversion temperature field method;

[0122] (3) The differential imaging specifically performs background subtraction processing on the radar data before and after freezing to eliminate the unchanged background signal.

[0123] It can be understood that in the embodiments herein, in addition to identifying the development of the frozen wall related to the high-precision third signal obtained previously, it may also involve the identification of the frozen area / anomaly structure, and the background removal based on the frozen area, thereby providing specific practical solutions for the data applications that the present application may involve from three aspects, and can provide high-quality data support for different types of underground engineering projects such as deep mines, disaster relief, or municipal subways, which helps to promote the underground engineering projects more safely, stably, and efficiently, and thus has better practical value.

[0124] Among them, it should be understood that for the data analysis operations in these three aspects, in actual applications, either the existing solutions can be adopted, or further optimization and improvement can be made on the basis of the existing solutions, or novel self-developed solutions can be adopted, all of which are acceptable and can be configured according to the actual user requirements.

[0125] The above is an introduction to the GPR detection imaging method for the development of the frozen wall provided by the present application. To facilitate the better implementation of the GPR detection imaging method for the development of the frozen wall provided by the present application, the present application also provides a GPR detection imaging device for the development of the frozen wall from the perspective of functional modules.

[0126] Refer to Figure 3 , Figure 3 FIG. is a schematic structural diagram of a GPR detection imaging device for the development of the frozen wall according to the present application. In the present application, the GPR detection imaging device 300 for the development of the frozen wall may specifically include the following structures:

[0127] An acquisition unit 301, configured to acquire a first signal obtained by performing GPR detection processing on a frozen rock and soil body to be detected, wherein the frozen rock and soil body to be detected forms a corresponding frozen wall through AGF processing;

[0128] A preprocessing unit 302, configured to perform data preprocessing on the first signal to obtain a second signal to initially enhance the signal quality;

[0129] An imaging unit 303, configured to, on the basis of the second signal, during the imaging process using the backprojection algorithm, consider the correlation between each channel signal, and implement secondary imaging through the cross-correlation backprojection algorithm to obtain a reconstructed image;

[0130] A secondary processing unit 304, configured to perform secondary signal processing on the reconstructed image to obtain a third signal to continuously enhance the signal quality.

[0131] As an exemplary embodiment, the backprojection algorithm includes the following content:

[0132] Suppose the specified detection area is divided into m×n pixels, and the two-way propagation time τ of pixel A in the p-th signal of the A-scan data A,P is expressed as follows:

[0133]

[0134] where ε1 is the relative dielectric constant of the frozen soil area, dx is the pixel width, dz is the pixel height, c is the propagation speed of light in a vacuum, i A is the abscissa of pixel A, j A is the ordinate of pixel A,

[0135] The response amplitude RA corresponding to each pixel point A,P is expressed as follows:

[0136] RA A，p = s p (t = τ A，p ),

[0137] where S p is the reflected electromagnetic wave recorded when the GPR moves to the p-th signal,

[0138] The response distribution of each imaging point in the signal is in the n sets of A-scan data generated by the GPR measurement. For the corresponding pixel A, there are n sets of response amplitudes, and the vector combination is an imaging output result, which is expressed as follows:

[0139]

[0140] As another exemplary embodiment, the correlation between each signal is represented by a correlation matrix V constructed by the following formula:

[0141]

[0142] The correlation superposition process is expressed as follows:

[0143]

[0144] where E A CBP is the total response amplitude calculated by the cross-correlation backprojection algorithm, and i and j are the row number and column number of the current element in the correlation matrix v, respectively.

[0145] As another exemplary embodiment, the GPR detection process includes the following processing contents:

[0146] After the radar is selected, the survey line is arranged, and the detection environment is optimized, the specific detection work is carried out. The GPR host is kept close to the segment surface and moves forward uniformly in a straight line along the survey line direction. The speed is not higher than 5 cm / s and remains consistent all the time. The distance advanced along the survey line during each operation is the same and the error does not exceed 5 cm. The detection time node starts before freezing, and during the active freezing period, detection is guaranteed every 6 hours. Each survey line is detected 3 times each time.

[0147] As another exemplary embodiment, the data preprocessing includes the removal processing of data points with abnormal noise points, the removal processing of data points with content loss, the time zero point correction processing, the background noise removal processing, and the gain processing.

[0148] As another exemplary embodiment, the signal secondary processing includes the filtering processing and the data enhancement processing;

[0149] The filtering processing includes high-pass filtering, low-pass filtering, band-pass filtering, and the removal of direct waves;

[0150] The data enhancement processing includes frequency domain conversion, the elimination of random noise through convolution operation, and the comparison of data at different time points.

[0151] As another exemplary embodiment, the device further includes an application unit 305, which is used for:

[0152] Based on the third signal, further data analysis and processing are carried out;

[0153] Among them, the data analysis and processing include reflection signal analysis, frozen wall development situation identification, and differential imaging;

[0154] The reflection signal analysis specifically analyzes the changes in the medium before and after freezing according to the signal characteristics including intensity and phase changes. The strong reflection area corresponds to the frozen area or abnormal structure;

[0155] The identification of the frozen wall development situation specifically calculates the frozen wall thickness and the abnormal area of the frozen wall development based on the relationship between the reflection time and the speed, and verifies the detection imaging result by combining the temperature measurement inversion temperature field method;

[0156] The differential imaging specifically performs background subtraction processing on the radar data before and after freezing to eliminate the unchanged background signal.

[0157] This application also provides a processing device from the perspective of the hardware structure. Refer to Figure 4 , Figure 4 shows a schematic structural diagram of the processing device of this application. Specifically, the processing device of this application may include a processor 401, a memory 402, and an input / output device 403. The processor 401 is used to implement the following when executing the computer program stored in the memory 402, as Figure 1The steps of the GPR detection imaging method for the development of the frozen wall in the corresponding embodiment; or, when the processor 401 is used to execute the computer program stored in the memory 402, it realizes as Figure 3 the functions of each unit in the corresponding embodiment. The memory 402 is used to store the above Figure 1 computer program required for the GPR detection imaging method for the development of the frozen wall in the corresponding embodiment.

[0158] Exemplarily, the computer program can be divided into one or more modules / units. One or more modules / units are stored in the memory 402 and executed by the processor 401 to complete this application. One or more modules / units can be a series of computer program instruction segments capable of performing specific functions, and these instruction segments are used to describe the execution process of the computer program in the computer device.

[0159] The processing device may include, but is not limited to, the processor 401, the memory 402, and the input / output device 403. Those skilled in the art can understand that the schematic diagram is only an example of the processing device and does not constitute a limitation on the processing device. It may include more or fewer components than shown, or combine certain components, or different components. For example, the processing device may also include a network access device, a bus, etc. The processor 401, the memory 402, the input / output device 403, etc. are connected through a bus.

[0160] The processor 401 may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The processor is the control center of the processing device and connects all parts of the entire device through various interfaces and lines.

[0161] The memory 402 can be used to store computer programs and / or modules. By running or executing the computer programs and / or modules stored in the memory 402 and calling the data stored in the memory 402, the processor 401 realizes various functions of the computer device. The memory 402 mainly includes a program storage area and a data storage area. Among them, the program storage area can store an operating system, application programs required for at least one function, etc.; the data storage area can store data created according to the use of the processing device, etc. In addition, the memory can include high-speed random access memory and can also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card, at least one magnetic disk storage device, flash device, or other volatile solid-state storage devices.

[0162] When the processor 401 is used to execute the computer program stored in the memory 402, the following functions can be specifically realized:

[0163] Obtain a first signal obtained by performing GPR detection processing on the frozen rock and soil to be detected, where the frozen rock and soil to be detected forms a corresponding frozen wall through AGF processing;

[0164] Perform data preprocessing on the first signal to obtain a second signal to initially enhance the signal quality;

[0165] On the basis of the second signal, during the process of performing imaging processing using the back-projection algorithm, considering the correlation between each channel signal, perform secondary imaging through the cross-correlation back-projection algorithm to obtain a reconstructed image;

[0166] Perform secondary signal processing on the reconstructed image to obtain a third signal to continue to enhance the signal quality.

[0167] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described GPR detection imaging device, processing device, and their corresponding units for the development of the frozen wall can refer to, for example, Figure 1 The description of the GPR detection imaging method for the development of the frozen wall in the corresponding embodiment is not specifically elaborated here.

[0168] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructions or by controlling relevant hardware through instructions. The instructions can be stored in a computer-readable storage medium and loaded and executed by a processor.

[0169] To this end, the present application provides a computer-readable storage medium storing multiple instructions that can be loaded by a processor to execute the steps of the GPR detection imaging method for the development of a frozen wall in the corresponding embodiment of the present application. For specific operations, reference can be made to the description of the GPR detection imaging method for the development of a frozen wall in the corresponding embodiment as shown in Figure 1 and will not be elaborated herein. Figure 1 For the description of the GPR detection imaging method for the development of a frozen wall in the corresponding embodiment, please refer to the description in the corresponding embodiment, and it will not be elaborated herein.

[0170] Among them, the computer-readable storage medium may include: Read Only Memory (ROM), Random Access Memory (RAM), magnetic disk or optical disc, etc.

[0171] Since the instructions stored in the computer-readable storage medium can execute the steps of the GPR detection imaging method for the development of a frozen wall in the corresponding embodiment of the present application, the beneficial effects achievable by the GPR detection imaging method for the development of a frozen wall in the corresponding embodiment of the present application can be realized. For details, please refer to the previous description and will not be elaborated herein. Figure 1 To this end, the present application provides a computer-readable storage medium storing multiple instructions that can be loaded by a processor to execute the steps of the GPR detection imaging method for the development of a frozen wall in the corresponding embodiment of the present application. For specific operations, reference can be made to the description of the GPR detection imaging method for the development of a frozen wall in the corresponding embodiment as shown in Figure 1 For the description of the GPR detection imaging method for the development of a frozen wall in the corresponding embodiment, please refer to the description in the corresponding embodiment, and it will not be elaborated herein.

[0172] The GPR detection imaging method, device, processing equipment, and computer-readable storage medium for the development of a frozen wall provided in the present application have been introduced in detail above. Specific examples are used in this article to elaborate on the principle and implementation manner of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the present application. At the same time, for those skilled in the art, based on the idea of the present application, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present application.

Claims

1. A GPR detection imaging method for the development of frozen walls, characterized in that, The method includes: Obtaining a first signal obtained by performing GPR detection processing on the frozen rock and soil to be detected, wherein the frozen rock and soil to be detected forms a corresponding frozen wall through AGF processing; Performing data preprocessing on the first signal to obtain a second signal to preliminarily enhance the signal quality; On the basis of the second signal, during the process of performing imaging processing using the backprojection algorithm, considering the correlation between each channel signal, secondary imaging is realized through the cross-correlation backprojection algorithm to obtain a reconstructed image; Performing secondary signal processing on the reconstructed image to obtain a third signal to continuously enhance the signal quality; The backprojection algorithm includes the following: Suppose the specified detection area is divided into m×n pixels, and the round-trip propagation time τ of pixel A in the p-th signal of the A-scan data is as follows: A,P is expressed as follows: Among them, ε1 is the relative permittivity of the frozen soil area, dx is the pixel width, dz is the pixel height, c is the propagation speed of light in a vacuum, i A is the abscissa of the pixel A, j A is the ordinate of the pixel A, The response amplitude RA corresponding to each pixel A,P is expressed as follows: RA A，p = s p (t = τ A，p ) Among them, S p is the reflected electromagnetic wave recorded by the GPR moving to the p-th trace signal, The response of each imaging point in the signal is distributed in n groups of A-scan data generated by GPR measurement. Corresponding to the pixel A, there are n groups of response amplitudes, and the vector combination is a kind of imaging output result, which is expressed as follows:

2. The method according to claim 1, wherein The correlation between each channel signal is represented by a correlation matrix V constructed by the following formula: The correlation superposition process is expressed as follows: where E A CBP is the sum of the response amplitudes calculated by the cross-correlation backprojection algorithm, and i and j are the row number and column number of the current element in the correlation matrix v, respectively.

3. The method according to claim 1, wherein The GPR detection processing includes the following processing contents: After radar selection, survey line layout, and detection environment optimization, specific detection work is entered. The GPR host keeps close to the segment surface and moves forward uniformly and linearly along the survey line direction at a speed not higher than 5 cm / s and always remains consistent. The distance advanced along the survey line during each operation is the same and the error does not exceed 5 cm. The detection time node starts before freezing, and during the active freezing period, detection is guaranteed every 6 hours, and each survey line is detected 3 times each time.

4. The method according to claim 1, characterized in that The data preprocessing includes the removal processing of data points with abnormal noise points, the removal processing of data points with missing content, time zero point correction processing, background noise removal processing, and gain processing.

5. The method according to claim 1, wherein The secondary signal processing includes filtering processing and data enhancement processing; The filtering processing includes high-pass filtering, low-pass filtering, band-pass filtering, and direct wave removal; The data enhancement processing includes frequency domain conversion, eliminating random noise through convolution operation, and comparing data at different time points.

6. The method according to claim 1, characterized in that, After performing secondary signal processing on the reconstructed image to obtain a third signal to continuously enhance the signal quality, the method further includes: Based on the third signal, further data analysis processing is carried out; Among them, the data analysis processing includes reflection signal analysis, frozen wall development situation identification, and differential imaging; The reflection signal analysis specifically analyzes the changes in the medium before and after freezing according to the signal characteristics including intensity and phase changes. The strong reflection area corresponds to the frozen area or abnormal structure; The identification of the frozen wall development situation specifically estimates the frozen wall thickness and the abnormal area of frozen wall development based on the relationship between reflection time and speed, and combines the temperature measurement inversion temperature field method to verify the detection imaging result; The differential imaging specifically performs background subtraction processing on the radar data before and after freezing to eliminate the unchanged background signal.

7. A GPR detection and imaging device for the development of frozen walls, characterized in that, The device includes: An acquisition unit for acquiring a first signal obtained by performing GPR detection processing on the frozen rock and soil to be detected, wherein the frozen rock and soil to be detected forms a corresponding frozen wall through AGF processing; A preprocessing unit for preprocessing the data of the first signal to obtain a second signal, so as to preliminarily enhance the signal quality; An imaging unit for considering the correlation between each channel signal and implementing secondary imaging through a cross-correlation backprojection algorithm to obtain a reconstructed image during the imaging process using the backprojection algorithm based on the second signal; A secondary processing unit for performing secondary signal processing on the reconstructed image to obtain a third signal, so as to continuously enhance the signal quality; The backprojection algorithm includes the following: Suppose the specified detection area is divided into m×n pixels, and the round-trip propagation time τ of pixel A in the p-th signal of the A-scan data is as follows: A,P is expressed as follows: where ε1 is the relative permittivity of the frozen soil area, dx is the pixel width, dz is the pixel height, c is the speed of light in vacuum, i A is the abscissa of the pixel A, j A is the ordinate of the pixel A The response amplitude RA corresponding to each pixel A,P is expressed as follows: RA A，p = s p (t = τ A，p ) Among them, S p is the reflected electromagnetic wave recorded by the GPR moving to the p-th trace signal The response of each imaging point in the signal is distributed in n groups of A-scan data generated by GPR measurement. For the corresponding pixel A, there are n groups of response amplitudes, and the vector combination is a kind of imaging output result, which is expressed as follows:

8. A processing device, characterized in that, It includes a processor and a memory. A computer program is stored in the memory, and when the processor calls the computer program in the memory, it executes the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores multiple instructions, and the instructions are suitable for being loaded by a processor to execute the method according to any one of claims 1 to 6.

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