CN108152854B - Micro-motion power spectral density-based nondestructive detection method and application thereof - Google Patents
Micro-motion power spectral density-based nondestructive detection method and application thereof Download PDFInfo
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Abstract
The invention relates to a nondestructive detection method based on micro-motion power spectral density and application thereof, wherein the detection method comprises the following steps of ① data acquisition, ② preprocessing and processing analysis of originally acquired data, ③ drawing a result drawing, ④ analysis and interpretation, and application of the micro-motion power spectral density detection method, and is used for detecting longitudinal and transverse uneven geologic bodies in a depth range of 100m of a shallow surface in urban engineering construction.
Description
Technical Field
The invention relates to an engineering geophysical detection method, in particular to a micro-motion power spectral density-based nondestructive detection method for longitudinal and transverse uneven geologic body detection in a depth range of 100m on a shallow surface in urban engineering construction and application thereof.
Background
The earth's surface has a natural weak vibration, called pulsation or constant micromotion (Microtremor animal vibration), which originates from various activities in nature and human beings, anywhere and anytime. The micromovement is a complex vibration composed of body waves (P-waves and S-waves) and surface waves (rayleigh waves and love waves), and the energy of the surface waves in the vertical direction accounts for more than 70% of the total energy of the signal. Although the amplitude and the form of the micro-motion signal change along with the space-time change, the micro-motion signal has statistical stability in a certain space-time range and can be described by a stable random process in time and space. The existing micro-motion detection method is based on the theory of a stable random process, extracts a frequency dispersion curve of a surface wave (Rayleigh wave) from a micro-motion signal, and obtains a transverse wave velocity structure of an underground medium through inversion of the frequency dispersion curve.
The micromotion signal contains rich information of the geologic body below the station array measuring point. In addition to surface wave dispersion curves, the probabilistic power spectral density function of the micro-motion signal is a useful parameter that can be exploited for fine detection of laterally inhomogeneous bodies.
The seismic wave field is essentially the result of the interference and superposition of vibrations of different types and different polarization characteristics, and the propagating elastic seismic waves in the geotechnical layer are essentially the propagation process of energy, and it is the geophysical properties of the medium that influence the energy propagation. The micromotion probability power spectral density function (PSD) can be regarded as a representation of the vibration energy. Generally, the probability power spectrum function observed at the same measuring point for a certain time is very stable; for different measuring points and probability power spectrum functions observed at different time, abnormality caused by energy difference can be avoided through energy normalization processing, and continuity of a section is provided; through calculation of a micromotion probability power spectrum function, energy distribution characteristics of different frequencies can be seen, random micromotion signals which are similar to irregularities are only related to a stratum structure below a measuring point generally, and abnormal geologic bodies below the measuring point, including bed rock fluctuation, boulders in a granite weathering layer, cavities and the like, can be analyzed according to a micromotion power spectrum density profile.
Various underground obstacles are frequently encountered in urban engineering construction, for example, urban subway shield construction, spherical weathering nuclei are frequently developed in weathered soil layers of granite areas in the south, and the road blocking tigers are commonly called boulders in shield tunneling construction.
The boulders bring great risks to subway shield construction, and if unexplored boulders are encountered in the tunneling process of the shield machine, the shield machine can be frequently seriously damaged, and even the unexpected situations of gushing, collapse and the like can be caused. Passive processing of boulders also causes environmental damage, delays construction period, road traffic congestion, increased uncertainty in investment control, and the like, and the resulting losses are often enormous. Therefore, it is very necessary to find the boulder before the shield construction starts.
Boulder detection methods generally fall into two broad categories, drilling and geophysical exploration. The core drilling and sampling method is the most direct method and is often used as the most main geological exploration means in the subway design stage. However, core sampling is only 'one hole' and only can reflect the distribution of spherical boulders in a limited range of a drill hole and the periphery of the drill hole, and the boulders are not obviously regular in development and relatively random in burial and distribution, so that the information for disclosing the spherical boulders through core sampling is very limited, and the distribution situation of the spherical boulders is difficult to find through geological drilling. Although the probability of finding the boulder can be increased and the engineering risk can be reduced by the encrypted drilling, the drilling is often difficult to implement due to the limitation of cost, site conditions and the like. Meanwhile, barriers such as densely distributed underground complex pipelines of electric power, telecommunication, rainwater, sewage, fuel gas and street lamps often exist in urban roads, and drilling has considerable risks. Therefore, it is imperative to find a geophysical method adaptive to urban complex environments to detect solitary rocks.
The detection of the boulders in the shield construction of the urban subway is a well-known technical problem, for example, in the Guangzhou subway construction, more than ten geophysical prospecting methods are adopted, because the urban comprehensive environment in which the subway construction is located is complex, the electromagnetic wave method is seriously interfered by the urban complex electromagnetic background, the conventional earthquake method and the direct current method are greatly influenced by the narrow ground space, the complex ground surface condition and the like of the city, various cross-hole CT methods have certain effects, the advantages are obvious compared with the conventional ground geophysical prospecting method, but the effects of different methods among holes are different, and the influences of the hole spacing are also received, so that the cost is high, and the construction period is long. Generally, a plurality of geophysical prospecting methods cannot achieve the expected effect, and are difficult to popularize and use.
Disclosure of Invention
The invention aims to provide a nondestructive detection method based on the micro power spectrum density and application thereof, which has the advantages of convenient field acquisition, high detection precision and strong resolution capability.
The purpose of the invention is realized by the following technical scheme: a micromotion power spectral density detection method comprises the following steps:
①, data acquisition, namely, in the determined detection construction area, arranging a two-dimensional array along a survey line and acquiring earth surface micro-vibration signal data by adopting a high-resolution three-component digital seismograph;
② preprocessing and processing analysis of the raw collected data, which comprises the following steps:
a process ⑴, preprocessing the original collected data, selecting a proper critical value to remove an extreme sample value, selecting a proper STA/LTA ratio interval to remove an interference signal caused by a short-time transient source, and forming a stable micro-motion data file;
a process ⑵, setting a proper time window length, and windowing the preprocessed stable data;
a process ⑶, obtaining windowed power spectral density data by using fast fourier transform;
a process ⑷, obtaining power spectral density data of each measurement point component by using a geometric mean method in statistics on the power spectral density data subjected to windowing;
a flow ⑸, energy normalization processing, namely, energy normalization processing is carried out on the data of the three components, and a file is formed;
step ③, drawing a result chart, namely selecting a target area from the file of the flow 5 through an MATLAB program to carry out normalization processing on each measuring point, drawing a single-component and three-component frequency-power spectral density profile, and highlighting the abnormity of the target area;
and ④, analyzing and explaining, namely analyzing and explaining based on the seismic wave propagation theory, relating to Rayleigh wave propagation, particle motion and elliptical polarization, and analyzing and explaining by synthesizing a three-component power spectrum density profile according to drilling data near the site and surrounding geological conditions.
The application of the micromotion power spectral density detection method is used for detecting longitudinal and transverse uneven geologic bodies in the depth range of 100m of the shallow earth surface in urban engineering construction.
Compared with the prior art, the invention has the advantages that: the nondestructive detection method can be provided for the geological body longitudinally and transversely uneven on the shallow surface of the urban engineering construction, and has the advantages of convenience in field acquisition, high detection precision, strong resolution capability, shortening of the exploration period, reduction of engineering cost, reduction of exploration risks and the like.
Drawings
FIG. 1 is a schematic diagram of a micro-motion prospecting method array layout. Wherein, a is a circular array, b is an embedded triangular array, c is a T-shaped array, d is an L-shaped array, e is a cross-shaped array, and f is a U-shaped array.
FIG. 2 is a schematic view of the micro-motion circular array observing system of embodiment 1.
Figure 3 is a normalized power spectral density contour plot.
FIG. 4 is a schematic view of the micro-motion circular array observing system of embodiment 2.
Figure 5 is a normalized power spectral density contour plot.
Detailed Description
The invention is described in detail below with reference to the drawings and examples of the specification:
a nondestructive detection method based on micromotion power spectral density comprises the following steps:
and ①, acquiring data, namely arranging a two-dimensional array along a survey line in the determined detection construction area, acquiring earth surface micro-vibration signal data by adopting a high-resolution three-component digital seismograph, reasonably adopting one or a mixture of a circular array, an embedded triangular array, a T-shaped array, an L-shaped array, a cross-shaped array and a U-shaped array according to actual site conditions of the two-dimensional array (as shown in figure 1), and acquiring for 10-15 min.
Generally, the two-dimensional array employs a circular array. The circular array can take vibration signals in all directions into consideration. When the site conditions are limited, embedded triangular arrays, T-shaped arrays, L-shaped arrays, cross-shaped arrays, U-shaped arrays and the like are flexibly adopted, and the arrays are prevented from being symmetrically arranged as much as possible. Generally speaking, the more detectors are arranged, the more side length is, and the more accurate the extracted dispersion curve is; a circular array (with one circle center and 5 evenly distributed circles) formed by 6 detectors is the most economical and reasonable mode.
② preprocessing and processing analysis of the raw collected data, which comprises the following steps:
a process ⑴, preprocessing the original collected data, selecting a proper critical value to remove the extreme sample value, selecting a proper STA/LTA ratio interval to remove the interference signal caused by the short-time transient source, and forming a stable micro-motion data file, wherein the specific processing method is as follows:
i. setting a critical value to remove the extreme sampling point signal with larger amplitude;
removing the interference signal of the short-time transient source by using STA/LTA, wherein the STA is the absolute amplitude average value of the short-time window, and the LTA is the absolute amplitude average value of the long-time window;
in the formula, ai，ajAnd setting a proper STA/LTA ratio interval for the amplitude values of the signals of the sampling points i and j respectively to remove the short-time transient source interference signals.
⑵, performing time windowing analysis on the preprocessed stable data, namely setting a proper time window length and windowing the data;
a process ⑶, obtaining windowed power spectral density data by using fast fourier transform;
flow ⑷, flow ⑵, set up the appropriate time window length, divide the window to the steady data after preconditioning;
a process ⑶, obtaining windowed power spectral density data by using fast fourier transform;
a flow ⑷, obtaining the power spectral density data of each measuring point component by using a geometric mean mode in statistics on the power spectral density data processed by the windowing, wherein the geometric mean can stably process extreme values in the samples and is a statistical mode close to normal distribution samples;
the process ⑸ includes energy normalization, which is to normalize the energy of the data of the three components and form a file, improve the continuity of the profile by energy normalization, and process the power spectral density data of the three components to avoid the abnormal condition caused by different sampling energies at different times, the specific processing method is as follows:
i. integrating the respective frequencies of the three-component power spectral densities to obtain respective energy spectra;
summing to obtain a three-component energy spectrum sum;
and iii, performing energy normalization processing on all the measuring points according to the respective energy spectrum sum.
Step ③, drawing a result chart, namely selecting a target area from the file of the flow 5 through an MATLAB program to carry out normalization processing on each measuring point, drawing a frequency-power spectral density profile of a single component (Z component) and a three component (X, Y, Z component), and highlighting the abnormality of the target area;
and ④, analyzing and explaining, namely analyzing and explaining based on the seismic wave propagation theory, relating to Rayleigh wave propagation, particle motion and elliptical polarization, and analyzing and explaining by synthesizing a three-component (X, Y, Z component) power spectrum density profile according to drilling data near the site and surrounding geological conditions.
The method is mainly applied to the detection of the longitudinal and transverse uneven geologic body in the depth range of 100m on the shallow ground surface in the urban engineering construction. The detection content comprises granite spherical weathering nuclei (boulders) in subway shield construction, bad geologic bodies in station continuous wall construction, bedrock surface buried depth and fluctuation forms, underground barriers, karsts, soil caves and cavities.
The present invention will now be described with reference to examples
Example 1: micro-motion detection of poor geologic body in construction of station underground continuous wall of subway in certain place
Overview of the engineering: the sites where certain stations of the subway are located are roads, auxiliary roads, sidewalks, green belts and the like, the terrain is flat, a large number of high-rise buildings are distributed on the north side of the lines, and the surrounding environmental conditions along the lines are complex. The original landform of the field belongs to the coastal and marine area. Influenced by city development and construction, the road is manually dug, filled and leveled along the road, the terrain is flat, and the ground elevation is generally 2-3 m. The ground layers of the field mainly comprise filling soil (filled stones), silt (muddy soil), silty clay, medium sand, residual sandy clay and granite weathered rock (local diabase) from top to bottom. According to the exploration data, the site granite has particularly obvious differential weathering, and weathering nuclei (boulders) are commonly existed in residual layers and all-strong weathering zones.
The observation system for micro-motion detection mainly adopts regular pentagonal circular arrays (namely circular table arrays), as shown in fig. 2, each circular array is composed of 6 detectors placed at the vertex and the central point of a regular pentagon, and the distance from the vertex to the central point of the regular pentagon is called as an observation radius R. According to different site conditions, 2.5 m-radius arrays are respectively adopted for observation, and the observation is carried out point by point according to the distance between 5m measuring points so as to form two-dimensional profile observation.
1. Instrumentation and equipment
The micro-motion detection adopts an SWS-6 engineering seismometer and a three-component detector to complete micro-motion data acquisition. The geophone is buried on the ground, converts ground vibration caused by seismic waves into an electric signal and sends the electric signal to the seismograph through a cable; the digital seismograph amplifies the received electric signals, converts the electric signals into binary data through an analog-to-digital converter, organizes the data and stores the data.
2. Preprocessing and processing analysis of raw collected data.
3. The two-dimensional cross section is shown in figure 3.
4. Interpretation of exploration results
As shown in fig. 3: in the graph, the abscissa is a mileage stake mark, the ordinate is frequency (Hz), different gray levels represent the energy of the power spectrum, low values indicate that the corresponding frequency wave impedance is small, and high values indicate that the corresponding frequency wave impedance is large. The 4-7Hz relatively continuous energy in the figure represents the undulation of the basal face, 4 anomalies are obvious above the basal face, the black box positions in the figure are respectively named as anomalies A, B, C, D, and the transverse widths of the 4 anomalies are respectively 25m, 20m and 50 m. And estimating the abnormal buried depth according to the half wavelength of the corresponding frequency according to the frequency dispersion curve extracted by the circular array.
Example 2: air-raid shelter detection for certain building site
Overview of the engineering: during the geotechnical investigation of a project, the air-raid shelters are exposed in places where boreholes BK8 and BK10 are constructed on the south side of the field, and are distributed in the weathered granite, the exposed top depth is 11.30-11.40 m, the exposed top elevation is 3.46-3.94 m, and the height of the air-raid shelters is about 1.30-1.50 m. The air-raid shelter is a abandoned air-raid shelter, and the position of the opening is not found. The ground rock-soil layer structure of place is comparatively simple, divide into from last to extremely down: miscellaneous fill, filled stone, fully-weathered granite and stroke granite, and the thickness of the covering layer is relatively thin. The hole drilled by BK8 is below 3m for stroke-induced granite, and the hole drilled by BK10 is below 1.3m for stroke-induced granite.
The observation system for micro-motion detection mainly adopts regular pentagonal circular arrays (namely circular table arrays), as shown in fig. 4, each circular array is composed of 6 detectors placed at the vertex and the central point of a regular pentagon, and the distance from the vertex to the central point of the regular pentagon is called as an observation radius R. According to different field conditions, 2 m-radius arrays are respectively adopted for observation, and the observation is carried out point by point according to the measuring point interval of 4m so as to form two-dimensional profile observation.
1. Instrumentation and equipment
Data acquisition is completed through EPS series integrated micro-power consumption digital seismographs (6 seismographs with 2Hz synchronously and independently acquire data respectively).
2. Preprocessing and processing analysis of raw collected data.
3. The two-dimensional cross section is shown in figure 5.
4. And (5) explaining detection results.
As shown in fig. 5: in the graph, the abscissa is a milepost number, the ordinate is frequency (Hz), and different gray scales represent the energy of the power spectrum. In the figure, BK8, M4, BK10 and M23 have obvious high-energy abnormity at the position of 30-40Hz, and are inferred to be the reflection of the air defense. BK8 revealed a cavity at 11.4-12.7m, with a thickness of 1.3 m; BK10 revealed voids at 11.3-12.8m, 1.5m thick. The abnormal center frequency is estimated at about 38Hz, and the buried depth D-V of the cavity is calculated according to the formation speed above the cavity of 900m/sS/(2*f)＝11.8m，VSThe average shear wave velocity of the formation above the cavity is generally more consistent with the actual formation velocity.
Claims (5)
1. A nondestructive detection method based on micromotion power spectral density is characterized in that: it comprises the following steps:
①, data acquisition, namely, in the determined detection construction area, arranging a two-dimensional array along a survey line and acquiring earth surface micro-vibration signal data by adopting a high-resolution three-component digital seismograph;
② preprocessing and processing analysis of the raw collected data, which comprises the following steps:
a process ⑴, preprocessing the original collected data, selecting a proper critical value to remove an extreme sample value, selecting a proper STA/LTA ratio interval to remove an interference signal caused by a short-time transient source, and forming a stable micro-motion data file;
the specific processing manner for preprocessing the raw collected data in the process ⑴ is as follows:
i. setting a critical value to remove the extreme sampling point signal with larger amplitude;
removing the interference signal of the short-time transient source by using STA/LTA, wherein the STA is the absolute amplitude average value of the short-time window, and the LTA is the absolute amplitude average value of the long-time window;
in the formula, ai，ajSetting a proper STA/LTA ratio interval for the amplitude values of the signals of the sampling points i and j to remove the short-time transient source interference signals;
a process ⑵, setting a proper time window length, and windowing the preprocessed stable data;
a process ⑶, obtaining windowed power spectral density data by using fast fourier transform;
a process ⑷, obtaining power spectral density data of each measurement point component by using a geometric mean method in statistics on the power spectral density data subjected to windowing;
a flow ⑸, energy normalization processing, namely, energy normalization processing is carried out on the data of the three components, and a file is formed;
the specific processing of the flow ⑸ is as follows:
i. integrating the respective frequencies of the three-component power spectral densities to obtain respective energy spectra;
summing to obtain a three-component energy spectrum sum;
performing energy normalization processing on all measuring points according to respective energy spectrum sums;
step ③, drawing a result chart, namely selecting a target area from the file of the flow 5 through an MATLAB program to carry out normalization processing on each measuring point, drawing a single-component and three-component frequency-power spectral density profile, and highlighting the abnormity of the target area;
and ④, analyzing and explaining, namely analyzing and explaining based on the seismic wave propagation theory, relating to Rayleigh wave propagation, particle motion and elliptical polarization, and analyzing and explaining by synthesizing a three-component power spectrum density profile according to drilling data near the site and surrounding geological conditions.
2. The lossless detection method based on the micromotion power spectral density according to claim 1, wherein in step ①, the two-dimensional array adopts one or a mixture of several of a circular array, an embedded triangular array, a T-shaped array, an L-shaped array, a cross-shaped array and a U-shaped array, and the acquisition time is 10-15 min.
3. The method of claim 2, wherein the two-dimensional array is a circular array in step ①.
4. Use of the detection method according to any one of claims 1-3, characterized in that: the method is used for detecting the longitudinal and transverse uneven geologic body in the depth range of 100m on the shallow earth surface in the urban engineering construction.
5. Use of the detection method according to claim 4, characterized in that: the detection content comprises a bad geologic body in subway shield construction and station continuous wall construction, and the detection content comprises granite spherical weathering nuclei, bedrock surface burial depth and fluctuation forms, underground barriers, karst, soil caves and cavities.
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| CN109472245A (en) * | 2018-11-15 | 2019-03-15 | 长安大学 | The method for calculating the corresponding place natural frequency of vibration theoretical depth of earth pulsation excellent frequency |
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| CN110031893A (en) * | 2019-04-19 | 2019-07-19 | 中国电建集团铁路建设有限公司 | Drilling surveys new method with combining the subway engineering of fine motion detection |
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| CN110488349B (en) * | 2019-08-20 | 2021-11-02 | 福建省建筑设计研究院有限公司 | Micro-motion three-component spectral ratio VHSR-based nondestructive detection method and application |
| CN111458749B (en) * | 2020-04-13 | 2020-11-27 | 中国地质大学（北京） | Surface wave and body wave separation method and system applied to passive source seismic exploration |
| CN111812724B (en) * | 2020-06-29 | 2021-08-27 | 山东大学 | Hidden karst pipeline detection method and system |
| CN111812707A (en) * | 2020-07-07 | 2020-10-23 | 中交二公局第三工程有限公司 | Method for detecting boulders in subway line site based on micro-motion and surface wave exploration |
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