Method for detecting geological abnormal body in lining removal operation and signal processing method

Abstract

The application discloses a kind of lining demolition operation in geological anomalous body detection method and signal processing method, first, by being arranged in the lining inside and the cutting route parallel two detection lines in multiple detectors, vibration signal between cutting disc and concrete lining in the lining cutting operation process is acquired in real time, and vibration signal obtained in real time is handled.Then, the vibration signal after processing is carried out two-dimensional fast Fourier transform, and the frequency-wave number spectrum corresponding to vibration signal is obtained.Afterwards, dispersion curve and reflected wave signal are extracted from the frequency-wave number spectrum.Finally, dispersion curve is carried out interference wave inversion, and the shear wave velocity spectrum inside the geological body behind lining is obtained, and reflected wave signal is inverted and imaged, and the reflected interface image inside the geological body behind lining is obtained.Combining reflected interface image and shear wave velocity spectrum can accurately locate the anomaly of the geological body behind lining, and effectively detect the geological body anomaly behind existing lining.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of signal processing, in particular to a method for detecting geological abnormal body in lining demolition operation and a signal processing method. BACKGROUND

[0002] The in-situ reconstruction and expansion of existing tunnel is to expand the size of tunnel section by demolishing the lining of existing tunnel and expanding the surrounding, so as to increase the number of lanes and relieve traffic pressure. In the construction process of in-situ reconstruction and expansion of existing tunnel, the existing lining structure of tunnel is demolished, and the lining structure is the main load-bearing part of tunnel structure. If the geological abnormal body behind the lining is not effectively detected during the demolition operation, the stability of the surrounding rock mass of the original tunnel will be easily destroyed, which will lead to safety accidents such as collapse and roof fall during the construction of in-situ reconstruction and expansion of existing tunnel, and seriously threaten the life and property safety of construction workers.

[0003] At present, there is no effective method for detecting the geological abnormal body behind the lining during the demolition construction of in-situ reconstruction and expansion of existing tunnel. The traditional electromagnetic detection method is difficult to effectively detect the geological abnormal body behind the existing lining due to the shielding effect of the lining steel layer and the initial support steel arch. The traditional detection method using vibration reflection wave signal is easily disturbed by multiple reflection waves from the side wall of the lining due to the arc cross-section form of the tunnel lining structure, resulting in poor detection effect. SUMMARY

[0004] In view of the deficiencies in the prior art, the present application provides a method for detecting geological abnormal body in lining demolition operation and a signal processing method, which can effectively detect the geological abnormal body behind the existing lining during the demolition construction. The specific technical solutions are as follows:

[0005] In the first aspect, a signal processing method is provided, comprising:

[0006] obtaining a vibration signal in the lining cutting operation and processing the vibration signal;

[0007] performing two-dimensional fast Fourier transform on the vibration signal to obtain a frequency-wavenumber spectrum of the vibration signal;

[0008] extracting a dispersion curve and a reflection wave signal from the frequency-wavenumber spectrum;

[0009] respectively inverting and imaging based on the dispersion curve and the reflection wave signal to respectively obtain a shear wave velocity spectrum inside the geological body behind the lining and a reflection interface image.

[0010] In a first implementation manner of the first aspect, the signal processing on the vibration signal comprises:

[0011] The vibration signal is corrected in a non-profile line direction.

[0012] In a second implementation manner of the first aspect, the vibration signal is corrected in a non-profile line direction, and the vibration signal is corrected in a non-profile line direction comprises:

[0013] According to the inter-channel distance of the acquisition system, the self-excitation and self-reception time and the apparent velocity of the vibration wave, the vibration wave propagation time corresponding to the mirror source is calculated;

[0014] A time difference is calculated through the vibration wave propagation time and the propagation time of the vibration wave in the vibration signal;

[0015] The vibration signal is corrected according to the time difference.

[0016] In a third implementation manner of the first aspect, the signal processing on the vibration signal further comprises:

[0017] The sound wave signal in the corrected vibration signal is removed based on the wave velocity difference.

[0018] In a fourth implementation manner of the first aspect, the signal processing on the vibration signal further comprises:

[0019] The vibration signal after the sound wave signal is removed is subjected to frequency spectrum analysis, and the vibration signal after the sound wave signal is removed is subjected to high-frequency filtering according to the frequency spectrum analysis result.

[0020] In a fifth implementation manner of the first aspect, based on the reflected wave signal, a wave impedance inversion method is used for inversion to obtain a reflected interface image of the geological body behind the lining.

[0021] In a sixth implementation manner of the first aspect, based on the dispersion curve, a dispersion curve inversion method is used for inversion to obtain a transverse wave velocity spectrum of the geological body behind the lining.

[0022] The second aspect provides a computer readable storage medium, which stores a computer program, and the computer program is executed to realize the signal processing method in any one of the first aspect and the first to seventh implementation manners of the first aspect.

[0023] The third aspect provides a geological body anomaly detection method, which comprises:

[0024] Two detection lines are arranged in parallel on both sides of the cutting route of the concrete lining, and each detection line comprises a plurality of geophones.

[0025] Collect vibration signals in the process of lining cutting operation through two detection lines;

[0026] The vibration signals are processed by the signal processing method of any one of the first aspect, the first to seventh possible implementation manners of the first aspect, to obtain the shear wave velocity spectrum and the reflection interface image of the geological body behind the lining;

[0027] According to the shear wave velocity spectrum and the reflection interface image, the geological anomaly body condition of the geological body behind the lining is determined.

[0028] In combination with the third aspect, in the first possible implementation manner of the third aspect, two detection lines are arranged in parallel along the two sides of the cutting route of the concrete lining, comprising:

[0029] A plurality of drill holes are arranged in parallel along the two sides of the cutting route on the concrete lining;

[0030] The plurality of geophones are inserted into the concrete lining along different drill holes, and gypsum is filled in each drill hole to fix the geophones.

[0031] Beneficial effects: The lining removal operation geological anomaly body detection method and signal processing method of the present application use the vibration of the cutting disc and the concrete structure in the process of lining cutting operation as the signal source, avoids the separate arrangement of the vibration excitation device, simplifies the vibration signal collection, and uses the interference wave inversion result to supplement the reflection wave inversion result, which makes up for the problems of being easily affected by multiple reflection waves of the lining wall in pure reflection wave detection and insufficient lateral resolution for water-rich geological anomaly bodies.

[0032] Moreover, for the in-situ reconstruction and expansion construction of the existing tunnel, the lining cutting operation process uses cutting vibration as the seismic source, which eliminates the need for artificial excitation of the seismic source in the traditional elastic wave exploration, has high operation efficiency, and ensures the safety of the lining cutting operation. The use of non-longitudinal side lines avoids the overlap of the side lines and the cutting blade forward route, also makes the side line arrangement more flexible, and improves the operability of the device arrangement.

[0033] The smoothL1 sparse wave impedance inversion method with regularization constraint is used to better realize reflection wave inversion imaging. The joint imaging of reflection wave and interference wave makes up for the problem of insufficient lateral resolution of reflection wave, and realizes high-precision positioning of the lining internal anomaly body. BRIEF DESCRIPTION OF DRAWINGS

[0034] In order to more clearly illustrate the specific embodiments of the present application, the drawings needed in the specific embodiments will be briefly introduced below. In all the drawings, the elements or parts are not necessarily drawn according to the actual scale.

[0035] Figure 1 A flowchart of a signal processing method provided in an embodiment of the present invention;

[0036] Figure 2 This is a schematic diagram of the layout and correction of a non-longitudinal lateral vibration signal acquisition system according to an embodiment of the present invention;

[0037] Figure 3 This is a flowchart of a geological anomaly detection method provided in an embodiment of the present invention;

[0038] Figure 4 This is a schematic diagram of the detector distribution provided in an embodiment of the present invention. Detailed Implementation

[0039] The embodiments of the technical solution of the present invention will now be described in detail with reference to the accompanying drawings. These embodiments are merely illustrative of the technical solution of the present invention and are therefore intended to limit the scope of protection of the present invention.

[0040] like Figure 1 The flowchart shown illustrates a signal processing method, which includes:

[0041] Step 1: Acquire vibration signals during the lining cutting process and perform signal processing on the vibration signals;

[0042] Step 2: Perform a two-dimensional fast Fourier transform on the vibration signal to obtain the frequency-wavenumber spectrum of the vibration signal;

[0043] Step 3: Extract the dispersion curve and reflected wave signal from the frequency-wavenumber spectrum;

[0044] Step 4: Perform inversion imaging based on the dispersion curve and the reflected wave signal respectively to obtain the shear wave velocity spectrum and reflection interface image of the geological body behind the lining.

[0045] Specifically, firstly, the vibration signals between the cutting disc and the concrete lining during the lining cutting operation can be acquired in real time and processed. Then, a two-dimensional fast Fourier transform (FFT) is performed on the processed vibration signals to obtain the corresponding frequency-wavenumber spectrum. Next, the dispersion curve and reflected wave signal can be extracted from the frequency-wavenumber spectrum. Finally, interferometric wave inversion can be performed on the dispersion curve to obtain the shear wave velocity spectrum inside the geological body behind the lining. The reflected wave signal is then inverted and imaged to obtain an image of the reflection interface inside the geological body behind the lining.

[0046] Thus, by combining reflected waves and interferometric waves for imaging, we can overcome the problems of simple reflected wave detection being susceptible to multiple reflections from the lining wall and the insufficient lateral resolution of reflected waves, thereby achieving high-precision positioning of anomalies inside the lining.

[0047] In this embodiment, as Figure 3 As shown, before the in-situ expansion and lining demolition of the tunnel lining, a cutting route for the concrete lining cutting discs can be planned, and two detection lines can be laid parallel to both sides of the cutting route, i.e., along the longitudinal direction of the tunnel. Multiple detectors are installed on each detection line. The detectors are three-component detectors. The detectors can be inserted upwards into the lining through drilled holes, which are then filled with plaster to secure them. All detectors can be connected to the data acquisition host.

[0048] The lining removal operation begins. When the front end of the lining cutting disc reaches the position of the first geophone, the first geophone can start signal acquisition and send the acquired vibration signal to the data acquisition host. The data acquisition host processes, decomposes, and inverts the vibration signal to obtain the changes in the geological body behind the lining.

[0049] The cutting disc continues forward after cutting the initial section of the lining, reaching the next geophone position for another vibration signal acquisition and detection. This process repeats until the entire lining is cut or an anomaly occurs. Utilizing the vibration of the lining cutting disc against the concrete structure as a signal source, this method allows for single deployment, multiple acquisitions, and continuous detection. It eliminates the need for additional excitation devices, reducing detection costs. Furthermore, it enables continuous, limited detection of the geological conditions behind the lining during lining removal operations, ensuring the safety of in-situ reconstruction and expansion of existing tunnels during lining removal.

[0050] The signal processing procedure for vibration signals will be explained in detail below.

[0051] In this embodiment, signal processing of the vibration signal includes:

[0052] First, the vibration signal is corrected for non-longitudinal vibration signals. Non-longitudinal correction can correct the irregularities and nonlinearities in the propagation time difference of the vibration signal waveform, which is the basis for subsequent inversion imaging of reflected wave signals and interferometric wave signals. In addition, during the in-situ resection of tunnels for reconstruction and expansion, the vibration sources generated by the lining cutting blades and the concrete structure are mostly high-frequency signals. The non-longitudinal vibration signal contains a large amount of noise signals due to mutual interference. Non-longitudinal vibration signal correction can also convert the above-mentioned noise signals from nonlinear to linear, which is beneficial for noise removal.

[0053] In this embodiment, optionally, the vibration signal is subjected to non-longitudinal vibration signal correction, including:

[0054] Based on the channel spacing, self-excitation and self-reception time, and apparent velocity of the vibration wave in the acquisition system, the vibration wave propagation time corresponding to the mirror source is calculated.

[0055] The time difference is calculated by the vibration wave propagation time in the vibration signal and the vibration wave propagation time;

[0056] The vibration signal is corrected according to the time difference.

[0057] Specifically, the distance between the non-measurement line source point and each geophone is nonlinearly changed, and therefore the source S is taken as a center line to obtain a mirror source S' by mirror symmetry, and the mirror source point and the geophone are on the same measurement line, wherein L is a non-parallel distance.

[0058] For the mirror source S', the vibration wave propagation time t' can be expressed as:

[0059]

[0060] Wherein t0 is the self-excitation and self-reception time, v is the apparent velocity of the vibration wave, and Δd is the inter-channel distance of the acquisition system.

[0061] In order to eliminate the nonlinearity of the non-parallel measurement line vibration signal propagation time difference, the vibration wave propagation time t in the vibration signal can be subtracted by a time difference Δt, and Δt can be expressed as:

[0062]

[0063] The corrected vibration signal waveform diagram can be obtained by subtracting the corresponding correction time difference Δt from each vibration signal propagation time.

[0064] Then, the acoustic signal in the corrected vibration signal is removed based on the wave velocity difference. As shown in the figure, Figure 2 During the in-situ cutting process of the tunnel reconstruction and expansion, the lining cutting blade and the concrete structure produce not only vibration signals but also a large amount of acoustic waves. The acoustic wave is a fixed propagation speed interference wave, and its propagation speed in the air is 340 m / s. The fixed propagation speed in the vibration signal waveform diagram is expressed as the slope (i.e. the wave velocity) of the wave shape phase axis, which is 340. Therefore, the interference of the vibration signal can be eliminated by fixed slope cutting.

[0065] Finally, the vibration signal after removing the acoustic signal is subjected to frequency spectrum analysis, and the vibration signal after removing the acoustic signal is subjected to high frequency filtering according to the frequency spectrum analysis result.

[0066] Specifically, after removing the acoustic signal in the vibration signal, the vibration signal can be subjected to frequency spectrum analysis, and the bandwidth of the high frequency filtering can be determined according to the frequency spectrum analysis result. The vibration signal after removing the acoustic signal is subjected to high frequency filtering through the determined high frequency filtering bandwidth, so as to remove the high frequency noise in the vibration signal, to avoid the interference of other signals to the detection, and to improve the detection accuracy.

[0067] ​In the embodiment, the reflected wave signal can be obtained by removing the interference wave from the frequency-wave spectrum through F-K filtering, i.e., frequency-wave number filtering, of the vibration signal spectrum.

[0068] In the embodiment, optionally, based on the reflected wave signal, wave impedance inversion is performed to obtain the reflected interface image of the geological body behind the lining.

[0069] Specifically, the sparse wave impedance inversion method based on 2-norm constraint can be used to perform inversion on the reflected wave signal to determine the reflected interface image of the geological body behind the lining. Specifically,

[0070] The SmoothL1 inversion model with regularization established by sparse constraint is used, and the conjugate gradient method is used to solve the inversion model with regularization to image the layered structure of the soil body inside the lining and obtain the layered structure of the soil body inside the lining. The implementation steps of the wave impedance inversion based on the SmoothL1 regularization constraint are as follows:

[0071] First, the convolution matrix w(t) is constructed using the seismic wavelet data r(t). Then, the SmoothL1 with regularization constraint is used to construct the inversion objective function J(R), and the conjugate gradient method is used for iterative solution to calculate the reflection coefficient R'(t) of each layer. Finally, the final wave impedance inversion value is obtained by the reflection coefficient summation method.

[0072] The SmoothL1 with regularization constraint is used to construct the inversion objective function, which is represented as:

[0073]

[0074] where R(t) is the reflection coefficient, w(t) is the convolution matrix, d(t) is the seismic record, and λ||R||1 is the regularization constraint term.

[0075] It should be understood that the present embodiment is only exemplified by the sparse wave impedance inversion method, but the present application is not limited thereto, and other existing inversion methods can also be used to obtain the reflected interface image of the geological body behind the lining, such as the AVO inversion method, the reflected wave tomographic inversion, and the reflected wave full waveform inversion.

[0076] In the embodiment, optionally, based on the dispersion curve, the dispersion curve inversion method is used to perform inversion to obtain the shear wave velocity spectrum of the geological body behind the lining. Specifically, after the dispersion curve is extracted, the nonlinear genetic algorithm can be used to perform interference wave inversion on the dispersion curve to obtain the shear wave velocity spectrum inside the geological body behind the lining.

[0077] It should be understood that using nonlinear genetic algorithms for interferometric wave inversion is a conventional technique in this field, and its specific steps will not be elaborated here. It should also be understood that this embodiment only uses a nonlinear genetic algorithm as an example, but the present invention is not limited to this; other existing algorithms can also be used for interferometric wave inversion, such as the least squares method, simulated annealing, and neural network methods.

[0078] Reflected wave imaging offers good longitudinal resolution, effectively revealing the stratification of the soil within the lining. This stratification allows for the determination of the anomaly's burial depth. When vibration signals propagate through the layered structure, they generate high signal-to-noise ratio interferometric signals, which are particularly sensitive to water-rich, weak geological anomalies, thus facilitating the characterization of anomaly dimensions. The transverse wave velocity spectrum obtained from interferometric wave inversion can determine the anomaly's transverse width, compensating for the insufficient transverse resolution of reflected wave imaging and the resolution limitations of water-rich geological anomalies, thereby achieving high-precision location of anomalies within the lining.

[0079] A storage medium storing a computer program, which, when executed, implements the aforementioned method for detecting geological anomalies.

[0080] like Figure 2 The flowchart shown is a method for detecting geological anomalies. This method includes:

[0081] Step S1: Two detection lines are laid out in parallel on both sides of the cutting route of the concrete lining. Each detection line includes multiple detectors.

[0082] Step S2: Collect vibration signals during the lining cutting process using two detection lines;

[0083] Step S3: Process the vibration signal using the signal processing method described in any one of claims 1-7 to obtain the shear wave velocity spectrum and reflection interface image of the geological body behind the lining;

[0084] Step S4: Determine the geological anomaly behind the lining based on the shear wave velocity spectrum and reflection interface image.

[0085] Specifically, such as Figure 3 As shown, before the in-situ expansion and lining demolition of the tunnel, the cutting route of the concrete lining cutting disc can be planned, and two detection lines can be laid out parallel to both sides of the cutting route, i.e., along the longitudinal direction of the tunnel. Each detection line is equipped with multiple detectors, of which three-component detectors are used.

[0086] When the front end of the lining cutting disc reaches the first geophone position, the first geophone can start signal collection and send the collected vibration signal to the data acquisition host. The data acquisition host can process, extract, and invert the vibration signal using the above method, and finally obtain the change of the geological body behind the lining.

[0087] If there is no abnormality, the cutting can continue along the cutting route. The front end of the lining cutting disc continues to move forward to the next geophone position for the next vibration signal collection and detection. This process is repeated until the entire lining is cut or an abnormality occurs.

[0088] The vibration of the lining cutting disc and the concrete structure serves as the signal source, which can realize one-time layout, multiple collection, and continuous detection without the need for additional excitation devices, thereby reducing the detection cost and ensuring the safety of the in-situ reconstruction and expansion of the existing tunnel.

[0089] In this embodiment, in step S1, two detection lines are arranged in parallel on both sides of the cutting route of the concrete lining, including:

[0090] A plurality of drill holes are arranged in parallel on both sides of the cutting route on the concrete lining.

[0091] The plurality of geophones are inserted into the concrete lining along different drill holes, and gypsum is filled in the drill holes to fix the geophones.

[0092] Specifically, the geophones can be inserted into the lining through the drill holes, and the gypsum is filled in the drill holes to fix the geophones. After the detection lines are arranged, all the geophones can be connected to the data acquisition host. The data acquisition host can process the abnormal signals collected by the geophones to obtain the change of the geological body behind the lining during the construction process.

[0093] The above embodiments are only used to illustrate the technical solutions of the present application, but not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can modify the technical solutions described in the foregoing embodiments, or make equivalent replacement for part or all of the technical features; and these modifications or replacements do not change the essence of the corresponding technical solutions, which should be covered in the scope of the claims and the description of the present application.

Claims

1. A signal processing method, characterized by, The method comprises the following steps: acquiring vibration signals during a lining cutting operation and performing signal processing on the vibration signals; performing two-dimensional fast Fourier transform on the vibration signals to obtain a frequency-wavenumber spectrum of the vibration signals; extracting a dispersion curve and a reflected wave signal from the frequency-wavenumber spectrum; performing inversion imaging based on the dispersion curve and the reflected wave signal respectively to obtain a shear wave velocity spectrum and a reflected interface image of a geological body behind the lining respectively; the signal processing on the vibration signals comprises: performing non-profile vibration signal correction on the vibration signals, specifically comprising: calculating vibration wave propagation time corresponding to a mirror source according to a channel spacing of a collection system, a self-excitation and self-reception time, and a vibration wave apparent velocity; calculating a time difference through the vibration wave propagation time and a propagation time of vibration waves in the vibration signals; correcting the vibration signals according to the time difference; the signal processing on the vibration signals further comprises: removing acoustic wave signals in the corrected vibration signals based on a wave velocity difference; performing frequency spectrum analysis on the vibration signals after the acoustic wave signals are removed, and performing high-frequency filtering on the vibration signals after the acoustic wave signals are removed according to a frequency spectrum analysis result.

2. The signal processing method of claim 1, wherein, Based on the reflected wave signal, a wave impedance inversion method is used for inversion to obtain a reflected interface image of the geological body behind the lining.

3. The signal processing method of claim 1, wherein, Based on the dispersion curve, a dispersion curve inversion method is used for inversion to obtain a shear wave velocity spectrum of the geological body behind the lining.

4. A computer readable storage medium storing a computer program, characterized in that, The computer program is executed to implement the signal processing method according to any one of claims 1-3.

5. A method of detecting anomalies in a geological body, characterized in that, The method comprises the following steps: parallelly arranging two detection lines on both sides of a cutting route of a concrete lining, each detection line comprising a plurality of geophones; acquiring vibration signals during a lining cutting operation through the two detection lines; performing signal processing on the vibration signals by using the signal processing method according to any one of claims 1-3 to obtain a shear wave velocity spectrum and a reflected interface image of a geological body behind the lining; determining a geological abnormal body condition of the geological body behind the lining according to the shear wave velocity spectrum and the reflected interface image.

6. The geologic body anomaly detection method of claim 5, wherein, Parallelly arranging two detection lines on both sides of a cutting route of a concrete lining comprises the following steps: parallelly arranging a plurality of drill holes on both sides of the cutting route on the concrete lining; inserting a plurality of geophones into the concrete lining along different drill holes and filling gypsum in the drill holes to fix the geophones.

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