CN111610565A - Sound wave signal processing method - Google Patents
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Abstract
The invention discloses a sound wave signal processing method, which comprises the following steps: collecting time domain sound wave signals through a sound wave transmitter and a sound wave receiver; performing channel destruction on the time domain acoustic signals, intercepting effective data length as effective signals, and performing cross-correlation operation on the effective signals and the emission wavelets to obtain seismic wave trains; transforming the seismic wave train from a time domain to a space domain by utilizing Fourier forward transformation, and filtering the transformed seismic wave train according to the difference of geological information, effective waves and interference waves on frequency spectrum; transforming the filtered seismic wave train from a space domain to a time domain by utilizing inverse Fourier transform to compensate the amplitude of the seismic wave train; according to the reflected wave principle, when traveling is calculated, the longitudinal wave speed and the reflected wave weak signal of the direct wave are extracted from the compensated sound wave signal; establishing a speed profile; and F-K offset imaging processing is carried out on the reflected wave weak signal according to the speed profile to obtain the position and the form of the acoustic impedance interface. The invention monitors the geology in front of the face in real time.
Description
Technical Field
The invention belongs to the technical field of tunnel geological detection, and particularly relates to a sound wave signal processing method.
Background
With the rapid development of tunnel traffic engineering in China, the safe and efficient construction is paid more attention by people. The method is characterized in that the advance forecasting work of the tunnel is carried out, the geological condition in front of the tunnel face of the tunnel is accurately mastered, the prevention work is made in advance, and the method is an important guarantee for the safety and the high-efficiency construction of tunnel engineering. The advance prediction in the soft soil tunnel based on the seismic wave reflection technology is to detect the distribution condition of the bad geologic bodies such as boulders in the soft soil layer by utilizing the propagation principle of seismic waves and carry out effective early warning on the distribution condition so as to realize the purposes of high tunneling speed and low risk.
Currently, many methods for processing acoustic signals of shield tunnel detection front geological structures exist, such as a true reflection tomography method, a negative visual velocity method, an ultrasonic phased array technology and the like. The True Reflection Tomography (TRT) realizes space observation in an observation mode by arranging detectors and excitation shots on two sides and a tunnel face of a tunnel, can expand transverse spread to the maximum extent to fully obtain space wave field information, and adopts seismic migration imaging; the observation by the negative apparent velocity method is to punch holes on the side wall of the tunnel and arrange detectors and shot points, wherein the detectors and the shot points are arranged on the same straight line, the wave velocity of the rock mass is estimated by using the direct wave, and the position of a front reflection interface is estimated by using the intersection point of the reflected wave travel time curve and the direct wave travel time curve; the ultrasonic phased array technology is characterized in that an ultrasonic phased array sound wave transmitting probe and a signal receiving device are installed on a shield machine, and a geologic body in front of a tunnel is detected through the phased array technology. Both the true reflection tomography method and the negative visual velocity method belong to the earth surface hole crossing method, have high resolution, but need to drill holes for many times, and have complicated operation. In the ultrasonic phased array technology, the ultrasonic frequency adopted by a sound detection source leads to fast sound wave attenuation and insufficient detection depth.
Chinese patent (patent No. CN201610811231X) discloses a method for detecting boulders in front of a subway shield tunnel, which utilizes the existing advanced drilling to emit sound waves in the tunnel rock mass and installs a receiving sensor at the end part of the existing anchor rod at the rear to collect reflected sound wave signals.
Disclosure of Invention
The invention provides a sound wave signal processing method aiming at the problems of complex operation, fast sound wave attenuation and insufficient detection depth of the existing tunnel geological detection method, and solves the problems that the existing detection method needs drilling and the detection depth is insufficient.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
an acoustic signal processing method, comprising the steps of:
s1, collecting time domain sound wave signals from the front of the tunnel face through a sound wave transmitter and a sound wave receiver;
s2, performing channel cutting on the time domain acoustic signals, intercepting effective data length from the time domain acoustic signals to serve as effective signals, and performing cross-correlation operation on the effective signals and the emission wavelets respectively to obtain seismic wave trains reflecting geological states;
s3, transforming the seismic wave train obtained in the step S2 from a time domain to a space domain by utilizing Fourier forward transform, and filtering the transformed seismic wave train according to the difference of geological information, effective waves and interference waves on frequency spectrum;
s4, transforming the filtered seismic wave train obtained in step S3 from the spatial domain to the time domain by inverse fourier transform, and performing amplitude compensation on the seismic wave train;
s5, calculating travel time according to the reflected wave principle, and then extracting the longitudinal wave velocity of the direct wave from the compensated sound wave signal obtained in the step S4 by adopting a waveform coherent superposition method;
s6, extracting a reflected wave weak signal from the compensated sound wave signal obtained in the step S4 by suppressing a direct wave by using an F-K filtering technology;
s7, setting the sound wave propagation speed of the geology in front of the tunnel face to be uniform, defining a space range based on the geological region detected in front of the tunnel face, and establishing a speed profile by taking the defined space range as a reference and according to the longitudinal wave speed of the direct wave obtained in the step S5;
and S8, performing F-K offset imaging processing on the reflected wave weak signal extracted in the step S6 according to the speed profile established in the step S7, and showing the position and the form of an acoustic impedance interface.
In step S1, the operation formula of the time domain acoustic wave signal is:
a(t)＝(D(t)+r(t))·ω(t)+n(t)；
in the formula, t represents a time sequence, a (t) represents a time-domain acoustic wave signal, D (t) represents a direct wave coefficient, r (t) represents a reflection wave coefficient, omega (t) represents a seismic wavelet, and n (t) represents a noise signal.
In step S2, the operation formula of the cross-correlation operation is:
in the formula: tau represents the time difference between two signals of the time domain acoustic wave signal a (t) and the seismic wavelet omega (t), and y (tau) represents a seismic time domain waveform, namely a seismic wave train after cross-correlation operation.
In step S3, the formula for transforming the seismic wave train from the time domain to the space domain is:
in the formula, f represents a frequency sequence, Y (f) represents a frequency spectrum of the acoustic wave signal after conversion, i represents an imaginary number, tau represents a time difference between two signals of the acoustic wave signal a (t) in the time domain and a seismic wavelet omega (t), and y (tau) represents a seismic wave train.
In step S4, the formula for transforming the filtered seismic wave train from the spatial domain to the time domain is:
where Y (t) represents a seismic wave train transformed to the time domain, and Y' (f) represents an acoustic wave signal obtained by filtering the seismic wave train Y (f) transformed to the space domain with a band-pass filter.
In step S4, the operational formula for amplitude compensation of the seismic wave train is:
G(T)＝aTb；
wherein G (T) represents an amplitude compensation factor, T represents the travel from the excitation point to the reception point, and a and b represent coefficients.
In step S5, the operational formula of the travel time T is:
in the formula I1Denotes the offset,/2The distance from the face to the reflector is shown, and v is the formation longitudinal wave velocity.
In step S5, the longitudinal wave velocity v of the direct wave is the reciprocal of the slow speed S, and the operational formula of the slow speed S is:
wherein s represents slowness, TwRepresents a time window, ymThe signals collected by the mth acoustic receiver in the N receiving arrays are represented, d represents the distance between two acoustic receivers with waveform coherence superposition, and rho (s, T) represents a coherence coefficient.
The operation formula for extracting the reflected wave weak signal is as follows:
in the formula, G (t, z) represents a time-space domain waveform, F (F, k) represents a frequency-wavenumber domain waveform, k represents a wavenumber, z represents a radial position, i represents an imaginary number, F represents a frequency series, and t represents a time series.
The invention has the beneficial effects that:
the method has the advantages of simple steps, reasonable design, convenient realization and good use effect, and can realize the purpose of monitoring the geologic body in front of the tunnel face in real time in the tunneling process by utilizing the sound wave transmitter and the sound wave receiver which are arranged on the cutter head of the shield machine to collect sound wave signals and through signal channel set pretreatment, noise suppression, energy compensation, reflected wave extraction, speed estimation and depth offset; F-K filtering can effectively suppress direct waves and effectively extract weak signals of reflected waves; the longitudinal wave velocity of the direct wave is extracted by a waveform coherent superposition method, so that the velocity estimation is more accurate and reliable, and the precise abnormal body impedance interface position and form, namely the specific position and distribution condition of the unfavorable geologic body in front of the tunnel face, can be more favorably obtained in the depth migration step.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic arrangement of an acoustic transmitter and an acoustic receiver.
Fig. 2 is a waveform of an acoustic signal transmitted by an acoustic transmitter.
Fig. 3 is a frequency spectrum of an acoustic signal emitted by an acoustic emitter.
Fig. 4 is an autocorrelation waveform of an acoustic signal transmitted by an acoustic transmitter.
Fig. 5 is a waveform of a signal received by the sonic receiver.
FIG. 6 is a schematic diagram of geological detection according to the present invention.
FIG. 7 is a schematic view of the geologic survey imaging of FIG. 6.
FIG. 8 is a schematic flow chart of the present invention.
In the figure, 1 is a cutter head, 1-1 is a first concentric circle, 1-2 is a second concentric circle, 2 is an acoustic wave transmitter, and 3 is an acoustic wave receiver.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without inventive effort based on the embodiments of the present invention, are within the scope of the present invention.
Example 1: an acoustic wave signal processing method, as shown in fig. 8, includes the steps of:
s1, collecting sound wave signals: collecting time domain sound wave signals from the front of a tunnel through a sound wave transmitter 2 and a sound wave receiver 3 on a cutter head 1;
as shown in fig. 1, a cutter head 1 is arranged at the front part of the shield tunneling machine, the collection of the sound wave signals is realized by S sound wave transmitters 2 and M sound wave receivers 3 which are arranged on the cutter head 1, and the value ranges of S and M are both more than or equal to one; a plurality of concentric circles are arranged on the cutter head 1, and the centers of the concentric circles are coincident with the center of the cutter head 1; the concentric circles comprise a first concentric circle 1-1 and a second concentric circle 1-2, and the first concentric circle 1-1 is arranged on the inner side of the second concentric circle 1-2;
in the present embodiment, S ═ 3, M ═ 12; the three sound wave emitters 2 are respectively T1, T2 and T3, and the three sound wave emitters 2 are respectively fixedly arranged at trisection points of a second concentric circle 1-2 of the cutter head 1; the number of the sound wave receivers 3 is twelve, every four sound wave receivers 3 are in one group, three groups of sound wave receivers are formed, the first group is R11, R12, R13 and R14, the second group is R21, R22, R23 and R24, the third group is R31, R32, R33 and R34, and the included angle between every two adjacent groups of sound wave receivers 3 is 120 degrees; each group of sound wave receivers 3 are fixedly arranged on the diameter of the cutter head 1 from inside to outside in sequence, the distance between two adjacent sound wave receivers 3 in each group of sound wave receivers 3 is equal, the first two sound wave receivers 3 in the three groups of sound wave receivers 3 are arranged on a first concentric circle 1-1 to facilitate signal processing, and a second concentric circle 1-2 is arranged between R13 and R14; the acoustic receiver and the acoustic transmitter are arranged in such a way, so that signals can be effectively acquired, and the subsequent three-dimensional inversion imaging of the geologic body is facilitated.
As shown in fig. 2-4, the acoustic transmitter 2 transmits an acoustic signal, the acoustic signal is reflected by the geology in front of the tunnel face and then received by the acoustic receiver 3, the acoustic transmitter 2 and the acoustic receiver 3 are both connected with the control system, and finally the control system is responsible for processing the received acoustic signal;
as shown in fig. 5, the time-domain acoustic wave signal is composed of a direct wave, a reflected wave and noise, and the operation formula of the time-domain acoustic wave signal is as follows:
a(t)＝(D(t)+r(t))·ω(t)+n(t)；
in the formula, t represents a time sequence, a (t) represents a time-domain acoustic wave signal, D (t) represents a direct wave coefficient, r (t) represents a reflection wave coefficient, omega (t) represents a seismic wavelet, and n (t) represents a noise signal.
S2, signal preprocessing: performing channel destruction on the time domain acoustic wave signals obtained in the step S1, intercepting effective data length as effective signals, and performing cross-correlation operation on the effective signals and the emission wavelets respectively to obtain seismic wave trains reflecting geological states;
the effective data length refers to signal sampling at specific intervals on the time domain sound wave signals after the bad channels are cut off;
the operation formula of the cross-correlation operation is as follows:
in the formula: tau represents the time difference between two signals of the time domain acoustic wave signal a (t) and the seismic wavelet omega (t), and y (tau) represents a seismic time domain waveform, namely a seismic wave train after cross-correlation operation.
S3, spectral analysis and noise suppression: transforming the seismic wave train obtained in the step S2 from a time domain to a space domain by utilizing Fourier forward transform, and filtering the transformed seismic wave train according to the difference of geological information, effective waves and interference waves on frequency spectrums;
the operation formula for transforming the seismic wave train from the time domain to the space domain is as follows:
where f denotes a frequency series, y (f) denotes a spectrum of a seismic wave train transformed to a spatial domain, and i denotes an imaginary number.
The seismic wave train is transformed from a time domain to a space domain so as to conveniently filter seismic time domain waveforms, the frequency of a transmitting wave is generally between 1 and 3kHz, and high-frequency and low-frequency signals can be directly deleted by filtering the transformed seismic wave train by a band-pass filter.
S4, energy compensation: transforming the filtered seismic wave train obtained in step S3 from the spatial domain to the time domain using inverse fourier transform, and performing amplitude compensation on the seismic wave train;
the operational formula for transforming the filtered seismic wave train from the spatial domain to the time domain is as follows:
wherein Y (t) represents a seismic wave train transformed to a time domain, and Y' (f) represents a sound wave signal obtained by filtering the seismic wave train Y (f) transformed to a space domain by using a band-pass filter;
the operation formula for amplitude compensation of the seismic wave train is as follows:
G(T)＝aTb；
wherein G (T) represents an amplitude compensation factor, T represents the travel from the excitation point to the receiving point, and a and b represent coefficients;
because the amplitude of the sound wave signal is lost due to geometric diffusion in the process of propagation, the sound wave signal is geometrically compensated in a time domain, so that the sound wave signal can keep a relatively true amplitude.
S5, longitudinal wave velocity extraction: calculating the traveling time according to the reflected wave principle, and then extracting the longitudinal wave velocity of the direct wave from the compensated sound wave signal obtained in the step S4 by adopting a waveform coherent superposition method;
the operational formula for calculating the travel time T is as follows:
in the formula I1Denotes the offset,/2The distance from the face to the reflector is shown, and v represents the longitudinal wave velocity of the stratum;
the reflector can be a boulder or other abnormal geologic body;
the operation formula for extracting the longitudinal wave velocity v of the direct wave is as follows:
in the formula, s represents the slowness, i.e. the reciprocal of the longitudinal wave velocity v of the direct wave, TwRepresents a time window, ymRepresenting the signal collected by the mth sonic receiver in the N receiving arrays, d representing the distance between two sonic receivers 3 with the waveform coherently superposed, and ρ (s, T) representing the coherence coefficient;
and solving the slowness s according to an operational formula for extracting the longitudinal wave velocity v of the direct wave, and then solving the longitudinal wave velocity v of the direct wave.
S6, reflected wave extraction: extracting reflected wave weak signals from the compensated sound wave signals obtained in the step S4 by suppressing direct waves by using an F-K filtering technology;
the operation formula for extracting the reflected wave weak signal is as follows:
where G (t, z) represents a time-space domain waveform, F (F, k) represents a frequency-wavenumber domain waveform, k represents a wavenumber, and z represents a radial position, i.e., a distance between the acoustic transmitter 2 and the acoustic receiver 3;
the position corresponding to the reflected wave weak signal after time-depth conversion is the position of the target body in front of the tunnel face, so that the intensity of the reflected wave signal has an important influence on the inversion imaging.
S7, speed estimation: assuming that the sound wave propagation speed of the geology in front of the tunnel face is uniform, defining a space range based on the geological region detected in front of the tunnel face, and establishing a speed profile by taking the defined space range as a reference and according to the longitudinal wave speed of the direct wave obtained in the step S5;
generally, the longitudinal section of the space tunneled by the shield tunneling machine is circular or rectangular, so the space range of the detected region in front of the tunnel face is usually defined as a cylinder or a cube, and the longitudinal wave speeds of the direct waves in the cylinder or the cube are all consistent.
S8, depth offset: as shown in fig. 6 and 7, according to the velocity profile established in step S7, F-K offset imaging processing is performed on the reflected wave weak signal extracted in step S6 to obtain the position and shape of the abnormal geology in front of the acoustic impedance interface, i.e., the tunnel face;
the principle of the F-K offset imaging is to image x on the face of a palm0Wavefield received at a location
Deriving a wave field when t is equal to 0 at the x position of the abnormal geologic body in front of the tunnel face
The imaging effect of the abnormal geologic body can be better obtained by carrying out offset imaging processing on the reflected wave weak signals.
In this embodiment, the signal transmitted by the acoustic transmitter 2 is a direct wave, and the direct wave is a frequency sweep signal.
Example 2: a sound wave signal processing method, the difference between this embodiment and embodiment 1 is that the signal emitted by the sound wave emitter 2 is a single frequency signal, so in this embodiment, the cross-correlation operation in step S2 is eliminated, that is, the effective signal obtained after intercepting the effective data length is the seismic wave train reflecting the geological state, and steps S3-S8 are the same as those in embodiment 1.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (9)
1. An acoustic signal processing method, comprising the steps of:
s1, collecting time domain sound wave signals from the front of the tunnel face through the sound wave transmitter (2) and the sound wave receiver (3);
s2, performing channel cutting on the time domain acoustic signals, intercepting effective data length from the time domain acoustic signals to serve as effective signals, and performing cross-correlation operation on the effective signals and the emission wavelets respectively to obtain seismic wave trains reflecting geological states;
s3, transforming the seismic wave train obtained in the step S2 from a time domain to a space domain by utilizing Fourier forward transform, and filtering the transformed seismic wave train according to the difference of geological information, effective waves and interference waves on frequency spectrum;
s4, transforming the filtered seismic wave train obtained in step S3 from the spatial domain to the time domain by inverse fourier transform, and performing amplitude compensation on the seismic wave train;
s5, calculating travel time according to the reflected wave principle, and then extracting the longitudinal wave velocity of the direct wave from the compensated sound wave signal obtained in the step S4 by adopting a waveform coherent superposition method;
s6, extracting a reflected wave weak signal from the compensated sound wave signal obtained in the step S4 by suppressing a direct wave by using an F-K filtering technology;
s7, setting the sound wave propagation speed of the geology in front of the tunnel face to be uniform, defining a space range based on the geological region detected in front of the tunnel face, and establishing a speed profile by taking the defined space range as a reference and according to the longitudinal wave speed of the direct wave obtained in the step S5;
and S8, performing F-K offset imaging processing on the reflected wave weak signal extracted in the step S6 according to the speed profile established in the step S7, and showing the position and the form of an acoustic impedance interface.
2. The acoustic signal processing method according to claim 1, wherein in step S1, the operation formula of the time-domain acoustic signal is:
a(t)＝(D(t)+r(t))·ω(t)+n(t)；
in the formula, t represents a time sequence, a (t) represents a time-domain acoustic wave signal, D (t) represents a direct wave coefficient, r (t) represents a reflection wave coefficient, omega (t) represents a seismic wavelet, and n (t) represents a noise signal.
3. The acoustic signal processing method according to claim 2, wherein in step S2, the formula of the cross-correlation operation is:
in the formula: tau represents the time difference between two signals of the time domain acoustic wave signal a (t) and the seismic wavelet omega (t), and y (tau) represents a seismic time domain waveform, namely a seismic wave train after cross-correlation operation.
4. A sonic signal processing method according to claim 1 or 3 characterized in that in step S3 the formula of the operation of transforming the seismic wave train from the time domain to the space domain is:
where f denotes the frequency series, Y (f) denotes the spectrum of the seismic wave train transformed into the spatial domain, i denotes an imaginary number, τ denotes the time difference between the two signals of the time-domain acoustic signal a (t) and the seismic wavelet ω (t), and y (τ) denotes the seismic wave train.
5. A method for acoustic signal processing according to claim 4 wherein, in step S4, the filtered seismic waveform train is transformed from the spatial domain to the time domain by the equation:
where Y (t) represents a seismic wave train transformed to the time domain, and Y' (f) represents an acoustic wave signal obtained by filtering the seismic wave train Y (f) transformed to the space domain with a band-pass filter.
6. A sonic signal processing method as claimed in claim 5 in which in step S4 the formula of the amplitude compensation for the seismic waveform is:
G(T)＝aTb；
wherein G (T) represents an amplitude compensation factor, T represents the travel from the excitation point to the reception point, and a and b represent coefficients.
7. The acoustic signal processing method according to claim 1 or 6, wherein in step S5, the travel time T is calculated by the formula:
in the formula I1Denotes the offset,/2The distance from the face to the reflector is shown, and v is the formation longitudinal wave velocity.
8. The acoustic wave signal processing method according to claim 7, wherein in step S5, the longitudinal wave velocity v of the direct wave is the reciprocal of the slow speed S, and the operational formula of the slow speed S is:
wherein s represents slowness, TwRepresents a time window, ymRepresents the signal collected by the m sound wave receiver (3) in the N receiving arrays, d represents the waveform coherenceThe distance, ρ (s, T), between the two superposed acoustic receivers (3) represents the coherence coefficient.
9. The acoustic signal processing method according to claim 1 or 8, wherein the operation formula of extracting the reflected wave weak signal is:
in the formula, G (t, z) represents a time-space domain waveform, F (F, k) represents a frequency-wavenumber domain waveform, k represents a wavenumber, z represents a radial position, i represents an imaginary number, F represents a frequency series, and t represents a time series.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5148407A (en) * | 1987-06-02 | 1992-09-15 | Schlumberger Technology Corporation | Method for vertical seismic profiling |
| CN102478671A (en) * | 2010-11-23 | 2012-05-30 | 中国石油天然气集团公司 | Method for suppressing controllable seismic-source harmonic-wave interference |
| CN102928875A (en) * | 2012-11-07 | 2013-02-13 | 中国石油集团川庆钻探工程有限公司地球物理勘探公司 | Wavelet extraction method based on fractional Fourier transform (FRFT) domain |
| WO2014024818A1 (en) * | 2012-08-06 | 2014-02-13 | Ishikawa Yohei | Power generation system and power generation method |
| CN103790594A (en) * | 2014-02-26 | 2014-05-14 | 中铁一局集团有限公司 | Method for exploring and processing interior of boulder hole in front for shield method construction |
| CN104678428A (en) * | 2015-03-11 | 2015-06-03 | 山东大学 | Tunnel boring machine rock breaking seismic source and active source three-dimensional seismic combined advanced detection system |
| CN204496014U (en) * | 2015-03-11 | 2015-07-22 | 山东大学 | Rock tunnel(ling) machine breaks rock focus and active source 3-D seismics associating forward probe system |
| KR101547508B1 (en) * | 2014-09-04 | 2015-08-26 | (주)희송지오텍 | Apparatus for predicting front geological features and the method thereof |
| CN106324683A (en) * | 2016-09-08 | 2017-01-11 | 山东大学 | Acoustic wave device and method for metro shield tunnel front boulder detection |
-
2020
- 2020-06-05 CN CN202010504442.5A patent/CN111610565B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5148407A (en) * | 1987-06-02 | 1992-09-15 | Schlumberger Technology Corporation | Method for vertical seismic profiling |
| CN102478671A (en) * | 2010-11-23 | 2012-05-30 | 中国石油天然气集团公司 | Method for suppressing controllable seismic-source harmonic-wave interference |
| WO2014024818A1 (en) * | 2012-08-06 | 2014-02-13 | Ishikawa Yohei | Power generation system and power generation method |
| CN102928875A (en) * | 2012-11-07 | 2013-02-13 | 中国石油集团川庆钻探工程有限公司地球物理勘探公司 | Wavelet extraction method based on fractional Fourier transform (FRFT) domain |
| CN103790594A (en) * | 2014-02-26 | 2014-05-14 | 中铁一局集团有限公司 | Method for exploring and processing interior of boulder hole in front for shield method construction |
| KR101547508B1 (en) * | 2014-09-04 | 2015-08-26 | (주)희송지오텍 | Apparatus for predicting front geological features and the method thereof |
| CN104678428A (en) * | 2015-03-11 | 2015-06-03 | 山东大学 | Tunnel boring machine rock breaking seismic source and active source three-dimensional seismic combined advanced detection system |
| CN204496014U (en) * | 2015-03-11 | 2015-07-22 | 山东大学 | Rock tunnel(ling) machine breaks rock focus and active source 3-D seismics associating forward probe system |
| CN106324683A (en) * | 2016-09-08 | 2017-01-11 | 山东大学 | Acoustic wave device and method for metro shield tunnel front boulder detection |
Non-Patent Citations (9)
| Title |
|---|
| 冯波: "《数据域波动方程层析速度反演方法研究》", 31 August 2017, 同济大学出版社, pages: 40 * |
| 刘浩杰，王延光，魏国华等: "刘浩杰，王延光，魏国华等", 《物探化探计算技术》 * |
| 刘浩杰，王延光，魏国华等: "刘浩杰，王延光，魏国华等", 《物探化探计算技术》, 31 March 2019 (2019-03-31), pages 158 * |
| 张军华编著: "《地震资料去噪方法》", 28 February 2011, 石油大学出版社, pages: 47 * |
| 张承森，张璋，吴兴能等: "数字声波幅度比值方法在评价碳酸盐岩水平井储层中的应用", 《长江大学学报(自科版)》 * |
| 张承森，张璋，吴兴能等: "数字声波幅度比值方法在评价碳酸盐岩水平井储层中的应用", 《长江大学学报(自科版)》, 30 September 2015 (2015-09-30), pages 22 - 28 * |
| 曹国侯，刘浩著: "《隧道地质三维探测技术》", 30 January 2019, 上海科学技术出版, pages: 63 - 65 * |
| 王俊茹编著: "《物探数字信号分析与处理技术》", 30 September 2009, pages: 102 - 103 * |
| 长春地质学院编: "《地震勘探原理和方法》", 31 December 1980, pages: 379 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115951408A (en) * | 2023-01-03 | 2023-04-11 | 上海勘测设计研究院有限公司 | Slowness extraction method, device, medium and equipment for sound wave detection of underground stratum |
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