Urban Karst Water Conveying Channel Detection System and Method Based on Seismic Krauklis Wave

Abstract

This invention discloses a detection system and method for urban karst water-conducting channels based on seismic Krauklis waves, comprising a piezoelectric controllable source, an array-type seismic receiving system, and a multi-wave seismograph. The piezoelectric controllable source is used to generate seismic waves; the multi-wave seismograph is used to acquire seismic data collected by various seismic acceleration sensors in the array-type seismic receiving system. This structure ensures the accuracy of data acquisition for each seismic wave. The acquired seismic wave data is first separated and extracted using an energy-frequency dual-selection method. Then, based on the dispersion characteristics of Krauklis waves, a mapping model between crack aperture and wavefield response is established. Finally, according to the mapping model, the aperture of the urban karst water-conducting channel is determined, and the dynamic flow rate of the urban karst water-conducting channel is obtained through inversion. This method enables the monitoring of the aperture and dynamic flow rate of urban karst water-conducting channels, ultimately effectively improving the prevention and control of hidden geological hazards.

Description

Technical Field

[0001] This invention belongs to the field of geophysical exploration and urban geological disaster prevention technology, specifically relating to a detection system and method for urban karst water-conducting channels based on seismic Krauklis waves. Background Technology

[0002] Traditional methods for detecting karst water-conducting channels rely on seismic wave methods (such as P-wave / S-wave reflection signals) and electromagnetic methods. However, these methods are insufficient in identifying dynamic water flow characteristics and are severely affected by urban environmental noise, resulting in an error rate as high as 30% in assessing the connectivity of water-conducting channels. For example, conventional seismic wave methods have insufficient resolution for centimeter-level fractures (>10 meters), while electromagnetic methods struggle to distinguish between static water-retaining structures and dynamic water-conducting channels. Recent studies have found that the dispersion characteristics of Krauklis waves (a type of slow guided wave in fluid-filled fractures) are directly related to fracture aperture, fluid filling properties, and flow velocity, and can dynamically invert fracture size and its water conductivity. However, the signal extraction and fracture inversion techniques for Krauklis waves in complex urban environments are still immature.

[0003] Therefore, the research direction of this invention is to provide a new method to monitor the opening and dynamic flow of urban karst water diversion channels by exploring the hydrodynamic response characteristics of Krauklis waves, and ultimately to effectively improve the prevention and control of hidden geological disasters. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention provides a detection system and method for urban karst water-conducting channels based on seismic Krauklis waves. By exploring the hydrodynamic response characteristics of Krauklis waves, the system monitors the opening and dynamic flow of urban karst water-conducting channels, ultimately effectively improving the prevention and control of hidden geological disasters.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is: a detection system for urban karst water-conducting channels based on seismic Krauklis waves, comprising a piezoelectric controllable source, an array-type seismic receiving system, and a multi-wave seismograph;

[0006] The piezoelectric controllable source is used to generate seismic waves;

[0007] The array-type seismic receiving system includes multiple parallel and equally spaced survey lines. Each survey line includes multiple seismic acceleration sensors arranged in a straight line and connected in sequence. The number of seismic acceleration sensors on each survey line is the same, and the seismic acceleration sensors on each survey line are distributed at equal intervals.

[0008] The multi-wave seismograph is connected to an array-type seismic receiving system to acquire seismic data collected by various seismic acceleration sensors along each survey line. After subsequent analysis and processing, the opening and dynamic flow of urban karst water diversion channels are determined.

[0009] Furthermore, the frequency of the seismic waves excited by the piezoelectric controllable source is 0.1 to 100 Hz.

[0010] Furthermore, the sampling frequency of the multi-wave seismograph is 1kHz to 100kHz.

[0011] Furthermore, the spacing between two adjacent seismic acceleration sensors on different survey lines is the same.

[0012] Furthermore, it also includes a vehicle-mounted mobile detection platform for transporting piezoelectric controllable seismic sources, array-type seismic receiving systems, and multi-wave seismometers, and for deploying the piezoelectric controllable seismic sources and array-type seismic receiving systems to the required locations.

[0013] The detection method of the above-mentioned urban karst water-conducting channel detection system based on seismic Krauklis waves includes the following specific steps:

[0014] Step 1: Deploy the detection system: First, determine the detection area, then deploy multiple survey lines along the vehicle-mounted mobile detection platform within the detection area to form an array-type seismic receiving system. Next, deploy a piezoelectric controllable seismic source on one side of the array-type seismic receiving system and connect the array-type seismic receiving system to a multi-wave seismograph.

[0015] Step 2: Data Acquisition: Activate the multi-wave seismograph and piezoelectric controllable source. The piezoelectric controllable source generates seismic waves for a specific duration in a single excitation. The array-type seismic receiver continuously feeds back the seismic wave data received during this excitation time to the multi-wave seismograph and performs cross-correlation processing to remove noise, obtaining the seismic wave data generated in this excitation. Repeat this step to generate multiple seismic waves at the same location and obtain the corresponding seismic data from each excitation. Vertically superimpose the multiple seismic data to finally obtain the effective seismic data for that location.

[0016] Step 3: Extract Krauklis wave: Remove the direct wave from the effective seismic data in Step 2, and use the energy-frequency dual selection method to separate and extract the Krauklis wave from the remaining signal;

[0017] Step 4: Model Establishment: Based on the dispersion characteristics of Krauklis waves (i.e., the relationship between phase velocity and frequency), establish a mapping model between crack aperture and wave field response.

[0018] Step 5: Determine the opening and dynamic flow of urban karst water diversion channels: Based on the mapping model in Step 4, determine the opening of urban karst water diversion channels and inversely obtain the dynamic flow of urban karst water diversion channels.

[0019] Furthermore, step three employs an energy-frequency dual-selection method to separate and extract the Krauklis wave, specifically as follows:

[0020] ① Short-time energy detection:

[0021] Define the signal energy within the time window: Where N is the number of sampling points, t is the point number at the end of the time window, and n is the point number within the time window, when E(t) > γ·E avg The time is determined to be the effective segment of the Krauklis wave, where γ is the threshold factor, usually taken as 0.5; E avg The average energy of the background noise is used to initially separate the effective segment of the Krauklis wave;

[0022] ② Frequency feature screening:

[0023] Calculation step ①: Obtain the power spectral density (PSD) of the effective band of the Krauklis wave. The specific formula is as follows: Where N is the number of sampling points, f s f is the sampling rate. n The target frequency is determined; then the main frequency band in the power spectral density between 10 and 200 Hz is extracted, and finally the Krauklis wave is separated and extracted.

[0024] Furthermore, step four specifically includes:

[0025] The dispersion curve of the u(t) signal of the Krauklis wave was calculated using high-precision linear Radon transform to obtain the relationship between wave velocity and frequency, and a mapping model between crack aperture and wave field response was established. The specific steps are as follows:

[0026] 1. Fracture parameterization integration path

[0027] Let the principal direction of the fracture be θ. Then, the coordinates (x, y) of the seismic accelerometer satisfy:

[0028] x=dcosθ-ssinθ, y=dsinθ+scosθ

[0029] Where d is the projection distance and s is the parameter for extension along the crack;

[0030] Radon integral of Krauklis wave amplitude along the principal direction θ of the fracture:

[0031]

[0032] Where u(x,y) is the Krauklis wave displacement field, and the integration path corresponds to the normal projection of the fracture surface;

[0033] 2. Dispersion Feature Extraction

[0034] Krauklis wave phase velocity versus frequency dispersion relation:

[0035] In the formula v p Let ν be the phase velocity, h be the crack aperture, υ be Poisson's ratio, and v be the phase velocity. s Let be the transverse wave velocity; and thus establish a mapping model between crack aperture and wave field response.

[0036] Furthermore, in step five, the dynamic flow rate of the urban karst water-conducting channel is obtained by inversion, specifically by first extracting the Krauklis group velocity v using time-frequency analysis. g (f,t), and then based on the group velocity information, the dynamic flow rate of the urban karst water-conducting channel is obtained by inversion calculation. The specific formula is:

[0037] Transient flow In the formula, f is the frequency variable, used to characterize the Krauklis wave in different frequency bands, and v g (f,t) represents the group velocity, K(f) is a dimensionless frequency-related weighting coefficient, and C(t) is a correction term used to compensate for background flow or steady-state / low-frequency components not covered by the model.

[0038] Compared with the prior art, the present invention has the following advantages:

[0039] 1. The detection system of the present invention adopts an array-type seismic receiving system with a specific deployment method, and uses a piezoelectric controllable source to excite multiple seismic wave data at the same location. Each excited seismic wave is transmitted through the strata and fissure water-conducting channels by the array-type seismic receiving system. This structure can ensure the accuracy of acquiring each seismic wave data, and by superimposing the seismic wave data from multiple excitations at the same location, the accuracy of seismic wave data acquired at the same location is further improved, which facilitates the subsequent extraction of seismic wave data.

[0040] 2. This invention first uses an energy-frequency dual-selection method to separate and extract Krauklis waves from the acquired seismic wave data; then, based on the dispersion characteristics of Krauklis waves (i.e., the relationship between phase velocity and frequency), a mapping model between fracture aperture and wavefield response is established; finally, according to the mapping model, the aperture of urban karst water-conducting channels is determined, and a formula is established for inversion to obtain the dynamic flow rate of urban karst water-conducting channels. This processing method enables the monitoring of the aperture and dynamic flow rate of urban karst water-conducting channels, ultimately effectively improving the prevention and control of hidden geological disasters. Attached Figure Description

[0041] Figure 1 This is a schematic diagram of the layout of the detection system of the present invention;

[0042] Figure 2The relationship between Krauklis wave parameters and crack aperture and dynamic flow rate after processing using the present invention is shown.

[0043] (a) shows the relationship between Krauklis wave parameters and crack aperture; (b) shows the relationship between Krauklis wave parameters and dynamic flow rate. Detailed Implementation

[0044] The present invention will be further described below.

[0045] like Figure 1 As shown, a detection system for urban karst water-conducting channels based on seismic Krauklis waves includes a piezoelectric controllable source, an array-type seismic receiving system, and a multi-wave seismograph.

[0046] The piezoelectric controllable source is used to generate seismic waves; the frequency of the seismic waves generated by the piezoelectric controllable source is 0.1 to 100 Hz.

[0047] The array-type seismic receiving system includes multiple parallel and equally spaced survey lines. Each survey line consists of multiple seismic acceleration sensors arranged in a straight line and connected in sequence. The number of seismic acceleration sensors on each survey line is the same, and the seismic acceleration sensors on each survey line are distributed at equal intervals. The distance between two adjacent seismic acceleration sensors on different survey lines is the same, which is 1m.

[0048] The multi-wave seismograph is connected to an array-type seismic receiving system. The sampling frequency of the multi-wave seismograph is 1kHz to 100kHz. It is used to acquire seismic data collected by each seismic acceleration sensor in each survey line, and to determine the opening and dynamic flow of urban karst water diversion channels after subsequent analysis and processing.

[0049] As an improvement of the present invention, it also includes a vehicle-mounted mobile detection platform for transporting the piezoelectric controllable seismic source, the array-type seismic receiving system and the multi-wave seismograph, and deploying the piezoelectric controllable seismic source and the array-type seismic receiving system to the required locations.

[0050] The detection method of the above-mentioned urban karst water-conducting channel detection system based on seismic Krauklis waves includes the following specific steps:

[0051] Step 1: Deploy the detection system: First, determine the detection area, then establish a two-dimensional coordinate system within the detection area. Define the x-direction as the direction of the vehicle-mounted mobile detection platform, and the y-direction as perpendicular to x in the horizontal plane. Lay out survey lines along the x-direction, each consisting of 5 equally spaced seismic acceleration sensors, forming a 4m long survey line. Arrange 3 parallel survey lines along the y-direction, with a 1m spacing between them, ultimately forming a 5×3 array-type seismic receiving system. Then, deploy a piezoelectric controllable seismic source on one side of the array-type seismic receiving system and connect the array-type seismic receiving system to a multi-wave seismograph.

[0052] Step 2: Data Acquisition: Turn on the multi-wave seismograph and piezoelectric controllable source. The piezoelectric controllable source generates seismic waves for 10 seconds at a time. The array-type seismic receiver continuously feeds back the seismic wave data received during this generation time to the multi-wave seismograph and performs cross-correlation processing to remove noise, obtaining the seismic wave data generated in this generation. Repeat this step to generate seismic waves at the same location 3 more times, obtaining a total of 4 seismic data. Vertically superimpose the 4 seismic data to finally obtain the effective seismic data for this location.

[0053] Step 3: Extracting Krauklis Waves: Direct waves from the valid seismic data in Step 2 are removed, and Krauklis waves are extracted from the remaining signal using an energy-frequency dual-selection method. Specifically:

[0054] ① Short-time energy detection:

[0055] Define the signal energy within the time window: Where N is the number of sampling points, t is the point number at the end of the time window, and n is the point number within the time window, when E(t) > γ·E avg The time is determined to be the effective segment of the Krauklis wave, where γ is the threshold factor, usually taken as 0.5; E avg The average energy of the background noise is used to initially separate the effective segment of the Krauklis wave;

[0056] ② Frequency feature screening:

[0057] Calculation step ①: Obtain the power spectral density (PSD) of the effective band of the Krauklis wave. The specific formula is as follows: Where N is the number of sampling points, f s f is the sampling rate. n The target frequency is determined; then the main frequency band in the power spectral density between 10 and 200 Hz is extracted, and finally the Krauklis wave is separated and extracted.

[0058] Step 4: Model Establishment: Based on the dispersion characteristics of Krauklis waves (i.e., the relationship between phase velocity and frequency), a mapping model between crack aperture and wave field response is established, specifically as follows:

[0059] The dispersion curve of the u(t) signal of the Krauklis wave was calculated using high-precision linear Radon transform to obtain the relationship between wave velocity and frequency, and a mapping model between crack aperture and wave field response was established. The specific steps are as follows:

[0060] 1. Fracture parameterization integration path

[0061] Let the principal direction of the fracture be θ. Then, the coordinates (x, y) of the seismic accelerometer satisfy:

[0062] x=dcosθ-ssinθ, y=dsinθ+scosθ

[0063] Where d is the projection distance and s is the parameter for extension along the crack;

[0064] Radon integral of Krauklis wave amplitude along the principal direction θ of the fracture:

[0065]

[0066] Where u(x,y) is the Krauklis wave displacement field, and the integration path corresponds to the normal projection of the fracture surface;

[0067] 2. Dispersion Feature Extraction

[0068] Krauklis wave phase velocity versus frequency dispersion relation:

[0069] In the formula v p Let ν be the phase velocity, h be the crack aperture, υ be Poisson's ratio, and v be the phase velocity. s Let be the transverse wave velocity; and thus establish a mapping model between crack aperture and wave field response.

[0070] Step 5: Determine the opening and dynamic flow rate of the urban karst water diversion channel: Based on the mapping model in Step 4, determine the opening of the urban karst water diversion channel and inversely obtain the dynamic flow rate of the urban karst water diversion channel, such as... Figure 2 As shown, specifically: first, time-frequency analysis is used to extract the Krauklis group velocity v. g (f,t), and then based on the group velocity information, the dynamic flow rate of the urban karst water-conducting channel is obtained by inversion calculation. The specific formula is:

[0071] Transient flow In the formula, f is the frequency variable, used to characterize the Krauklis wave in different frequency bands, and v g (f,t) represents the group velocity, K(f) is a dimensionless frequency-related weighting coefficient, and C(t) is a correction term used to compensate for background flow or steady-state / low-frequency components not covered by the model.

[0072] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A detection method of a city karst water passage detection system based on seismic Krauklis waves, characterized in that, The specific steps are: Step one, laying out the detection system: first determine the detection area, then lay out multiple measuring lines along the moving detection platform in the detection area to form an array seismic receiving system, then lay out a piezoelectric controlled source on one side of the array seismic receiving system, and connect the array seismic receiving system with a multi-wave seismic instrument; Step two, collecting data: turn on the multi-wave seismic instrument and the piezoelectric controlled source, the piezoelectric controlled source excites seismic waves for a certain time, the array seismic receiving system continuously feeds back the received seismic wave data in this excitation time to the multi-wave seismic instrument, and performs mutual correlation processing on the seismic wave data to remove noise, thereby obtaining the seismic wave data of this excitation; Repeat this step to continue exciting seismic waves multiple times at this location, and correspondingly obtain multiple excitation seismic data, vertically stack the multiple seismic data to obtain effective seismic data of this location; Step three, extracting Krauklis wave: cut off the direct wave in the effective seismic data of step two, and separate and extract the Krauklis wave from the remaining signal by using the energy-frequency double selection method; Step four, establishing a model: calculate the u(t) signal dispersion curve of the Krauklis wave by using high-precision linear Radon transformation, obtain the relationship between wave velocity and frequency, and establish a mapping model of crack opening and wave field response, the specific steps are: (1) Fracture parameterized integral path Let the main direction of the fracture be θ, at this time the seismic acceleration sensor coordinates (x, y) satisfy: Where d is the projection distance, and s is the extension parameter along the fracture; Along the main direction θ of the fracture, perform Radon integration on the Krauklis wave amplitude: Where u(x, y) is the Krauklis wave displacement field, and the integral path corresponds to the normal projection of the fracture surface; (2) Dispersion characteristic extraction The relationship between the phase velocity of the Krauklis wave and the frequency is: where is the phase velocity, h1is the fracture opening, is the Poisson's ratio, v s is the shear wave velocity; thereby establishing a mapping model of fracture opening and wavefield response; Step five, determining the opening and dynamic flow of the urban karst water channel: according to the mapping model of step four, determine the opening of the urban karst water channel, and inversely obtain the dynamic flow of the urban karst water channel.

2. The detection method according to claim 1, characterized in that, In step three, the Krauklis wave is separated and extracted by using the energy-frequency double selection method, specifically: Short-time energy detection: Definition of signal energy in time window: Where N is the number of sampling points, t is the point number of the end of time window, n is the point number in time window, and when it is determined as the effective segment of Krauklis wave, where is the threshold factor; is the average energy of background noise, so as to preliminarily separate the effective segment of Krauklis wave; Frequency feature screening: The power spectrum density of the effective segment of Krauklis wave is obtained by the calculation step, and the specific formula is: Wherein, N is the number of sampling points, f s is the sampling rate, f n is the target frequency; then the main frequency band in the power spectrum density is extracted, and finally the Krauklis wave is separated and extracted.

3. The method of claim 1, wherein The step five is to obtain the dynamic flow of the urban karst water channel by inversion, specifically: first, the Krauklis group velocity v g (f, t) is extracted by time-frequency analysis, and then the dynamic flow of the urban karst water channel is obtained by inversion calculation based on the group velocity information, and the specific formula is: transient flow rate where f is the frequency variable, is the group velocity, is the dimensionless frequency-dependent weighting coefficient, is the correction term.

4. The method of claim 1, wherein The urban karst water channel detection system adopted includes a piezoelectric controlled source, an array seismic receiving system and a multi-wave seismic instrument; The piezoelectric controlled source is used to excite seismic waves; The array seismic receiving system includes multiple parallel and equally spaced measuring lines, each measuring line includes multiple seismic acceleration sensors arranged in a straight line and connected in sequence, the number of seismic acceleration sensors on each measuring line is the same, and the seismic acceleration sensors on each measuring line are equally spaced; The multi-wave seismic instrument is connected with the array seismic receiving system, used to obtain seismic data collected by each seismic acceleration sensor in each measuring line, and determine the opening and dynamic flow of the urban karst water channel after subsequent analysis and processing.

5. The detection method according to claim 4, characterized in that, The frequency of the seismic wave excited by the piezoelectric controlled source is 0.1-100 Hz.

6. The detection method according to claim 4, characterized in that, The sampling frequency of the multi-wave seismic instrument is 1 kHz-100 kHz.

7. The detection method according to claim 4, characterized in that, The interval between two adjacent seismic acceleration sensors on different survey lines is the same.

8. The detection method of claim 4, wherein, The vehicle-mounted mobile detection platform is used for transporting the piezoelectric controlled source, the array seismic receiving system and the multi-wave seismic instrument, and deploying the piezoelectric controlled source and the array seismic receiving system to the required position.

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