Site vulnerability assessment method based on background noise

Abstract

The present invention discloses a site vulnerability assessment method based on background noise, including: S1, collecting three-component background noise data of the site; S2, calculating the three-component background noise spectrum ratio curve; S3, extracting the dominant frequency; S4, extracting the site amplification factor; S5, calculating the Z-component background noise dispersion curve; S6, extracting the phase velocity corresponding to the dominant period; S7, phase velocity-apparent velocity conversion; S8, calculating the site vulnerability factor; S9, conducting site assessment. The method is suitable for small space areas and is not restricted by complex environments; it has strong anti-interference ability and reliable detection accuracy; and the working cost is low.

Description

Technical Field

[0001] The invention relates to the field of engineering geological survey, and in particular to a method for evaluating the vulnerability of an engineering site based on background noise. Background Art

[0002] Site vulnerability assessment is a key link in the design of railway, highway, civil engineering and other projects. Currently, it is mainly carried out through mapping, drilling, in-situ testing, wave velocity testing and other methods. However, mapping can only obtain qualitative information, thereby indirectly evaluating the vulnerability of the site; drilling and in-situ testing are similar, both of which have the characteristics of high cost and long cycle, and are difficult to implement in areas with complex terrain or small space, and the evaluation and judgment errors are large in areas with large lateral structural changes; wave velocity testing is difficult to implement in areas with thick overburden, and it is difficult to obtain accurate longitudinal wave velocity. Summary of the invention

[0003] In order to solve the problems existing in the prior art, the present invention provides a method for assessing the vulnerability of an engineering site which has strong spatial applicability, reliable detection accuracy and low cost.

[0004] To this end, the present invention adopts the following technical solutions:

[0005] A site vulnerability assessment method based on background noise includes the following steps:

[0006] S1, site three-component background noise data acquisition: use a three-component node seismograph to observe background noise data, start blindly collecting seismic background noise data for a certain period of time;

[0007] S2, calculate the three-component background noise spectrum ratio curve: pre-process the seismic background noise data obtained in S1, and perform Fourier transform on the pre-processed background noise data to obtain the spectrum of the three-component signal, and obtain the spectrum ratio curve A(f) according to the following formula:

[0008] A(f)=H(f) / V(f),

[0009] Among them, V(f) = Z(f) is the spectrum curve of the vertical component Z; H(f) is the spectrum of the horizontal component, which is expressed as follows,

[0010]

[0011] Where X(f) and Y(f) represent the frequency spectrum curves of horizontal components X and Y respectively;

[0012] S3, extract the superior frequency f ０ :Get the dominant frequency f corresponding to the maximum amplitude position from the spectral ratio curve obtained by S2 ０ ;

[0013] S4, extracting the site amplification factor: determining the maximum amplitude value corresponding to the dominant frequency, and obtaining the site amplification factor A h (f ０ );

[0014] S5, calculating the Z component background noise dispersion curve: calculating the surface wave dispersion curve at each acquisition point through the vertical component Z in the background noise signal; the calculation of the surface wave dispersion curve requires data from at least two seismographs and is calculated through a multi-channel comparison method:

[0015]

[0016] Where, E is the total dispersion curve spectrum, f and v represent the frequency and phase velocity respectively; n is the number of seismic traces, n≥2; is the dispersion spectrum of the jth track and the first track at different frequencies and phase velocities calculated by the signal comparison method, j>1;

[0017] S6, extracting the phase velocity corresponding to the dominant period: According to the dominant frequency f0 obtained in S3, the surface wave phase velocity v corresponding to the frequency f0 is picked up from the surface wave dispersion curve obtained in S5. R ;

[0018] S7, phase velocity-apparent velocity conversion: The surface wave phase velocity v is converted into R Converted to apparent velocity v s ,

[0019] v s =v R / sinθ,

[0020] Among them, θ is the propagation angle of the surface wave on the site surface, and the units of apparent velocity and phase velocity are m / s;

[0021] S8, calculate the site vulnerability factor G:

[0022]

[0023] S9, performing site evaluation according to the site vulnerability factor G obtained in S8.

[0024] The pre-processing described in step S2 comprises the following sub-steps:

[0025] S21, performing bandpass filtering on the background noise data;

[0026] S22, performing time normalization processing on the background noise data processed in S21 to balance the energy of signals with different frequencies.

[0027] Preferably, the effective frequency band range of the bandpass filtering in step S21 is 5-30 Hz.

[0028] The certain time mentioned in step S1 is at least 30 minutes. To ensure the signal-to-noise ratio, the acquisition time can be appropriately extended.

[0029] The criteria for site evaluation in step S9 are as follows:

[0030] When the vulnerability factor G < 0, the site strength is greater than that of the bedrock, and it is not easy to rupture, but attention should be paid to the situation of soft interlayers below the site;

[0031] When the vulnerability factor 0 < G < 1.0×10 -4 , the site vulnerability is poor and it is not easy to rupture;

[0032] When the vulnerability factor 1.0×10 -4 < G, the site vulnerability is strong and it is easy to rupture.

[0033] The above-mentioned site vulnerability evaluation method further includes the following steps:

[0034] S10. Calculate and evaluate the vulnerability factors at all measurement point positions within the site according to S1 - S9;

[0035] S11. Output a site evaluation report.

[0036] The present invention comprehensively considers the advantages and disadvantages of various methods, extracts the dominant frequency of the formation and the velocity of the overlying formation from the background noise, and calculates the site vulnerability factor, so as to conduct site evaluation. Compared with the prior art, the present invention has the following beneficial effects:

[0037] 1. This method is mainly used for the vulnerability evaluation of railway bridges, tunnel entrances and exits, and large civil engineering construction sites, providing a reference basis for geology and design professionals in engineering construction, so as to optimize geological interpretation and ensure the safety of design and construction.

[0038] 2. This method is suitable for narrow space areas, is not restricted by complex environments, and has strong spatial applicability.

[0039] 3. This method has strong anti-interference ability, reliable detection accuracy, and has great popularization and application value.

[0040] 4. Compared with methods such as drilling, in-situ testing, and wave velocity testing, the working cost of this method is reduced by at least 50% to 60%.

[0041] 5. This method has a short working cycle. To complete the field work of vulnerability evaluation for a single measurement point, only 30 - 60 minutes of background noise data needs to be collected. Compared with methods such as drilling, in-situ testing, and wave velocity testing that require several days of field work, the working cycle and efficiency are greatly improved. Description of the Drawings

[0042] Figure 1 is a flow chart of the evaluation method of the present invention;

[0043] Figure 2 is a spectral ratio curve calculated from the three-component background noise signal data in the present invention;

[0044] Figure 3 It is the dispersion curve calculated from the Z component background noise signal data in the present invention. DETAILED DESCRIPTION

[0045] The evaluation method of the present invention is described in detail below with reference to the accompanying drawings.

[0046] See also Figure 1 The site vulnerability assessment method based on background noise of the present invention comprises the following steps:

[0047] S1, site three-component background noise data collection:

[0048] According to the pre-designed observation system, three-component node-type seismographs are arranged at the site to observe the background noise data, and the seismic background noise data is blindly collected for a certain length of time. Generally, at least 30 minutes of noise recording is required. In order to ensure the signal-to-noise ratio, the acquisition time can be appropriately extended.

[0049] S2, calculate the three-component background noise spectrum ratio curve:

[0050] The original three-component background noise data is preprocessed, mainly including two items: (1) bandpass filtering, which is determined according to the engineering detection depth and the background noise frequency band range, generally 5-30 Hz is the effective frequency band range; (2) One-bit normalization, that is, time normalization of the signal to balance the energy of signals of different frequencies.

[0051] After preprocessing, the background noise signal is Fourier transformed to obtain the spectrum of the three-component signal, and the spectrum ratio is further calculated. The spectrum ratio curve is obtained by the following formula:

[0052] A(f)=H(f) / V(f),

[0053] Among them, A(f) is the spectral ratio curve, V(f)=Z(f) is the spectrum curve of the vertical component Z; H(f) is the spectrum of the horizontal component, which can be expressed as:

[0054]

[0055] Wherein, X(f) and Y(f) represent the frequency spectrum curves of horizontal components X and Y respectively.

[0056] S3, extract the superior frequency f ０ :

[0057] Extract the frequency corresponding to the maximum amplitude position in the spectrum ratio curve, that is, the dominant frequency f0, where the unit of f0 is Hertz (Hz). Figure 2 Shown is the spectral ratio curve for a certain site location, with the corresponding dominant frequency f0 being approximately 12 Hz.

[0058] S4, extract the site magnification factor:

[0059] The maximum amplitude corresponding to the superior frequency is the site amplification factor A h (f0); the site magnification factor is a dimensionless parameter; Figure 2 The site magnification factor A is shown h (f0) is approximately 0.62.

[0060] S5, calculate the Z component background noise dispersion curve:

[0061] The vertical component (i.e., Z component) of the three-component background noise is used to calculate the surface wave dispersion curve at each acquisition point. The calculation of the dispersion curve requires data from at least two seismographs and is calculated using the multi-channel comparison method:

[0062]

[0063] Where E is the total dispersion curve spectrum, f and v represent frequency and phase velocity respectively, n is the number of seismic traces (n≥2), The dispersion spectra of the jth (j>1) track and the first track at different frequencies and phase velocities calculated using the signal comparison method.

[0064] S6, extract the phase velocity corresponding to the dominant period: According to the dominant frequency f0 obtained in S3, pick up the surface wave phase velocity v corresponding to the frequency f0 in the surface wave dispersion curve in S5 R ,like Figure 3 shown.

[0065] S7, phase velocity-apparent velocity conversion:

[0066] Surface wave phase velocity v R - Apparent speed v s The conversion makes the velocity value closer to the actual shear wave velocity of the site:

[0067] v s =v R / sinθ,

[0068] Among them, θ is the propagation angle of the surface wave on the site surface, and the units of apparent velocity and phase velocity are m / s;

[0069] S8, calculate site vulnerability factor: comprehensive site amplification factor A h (f0), dominant frequency f0, apparent velocity v sCalculate the site vulnerability factor G:

[0070]

[0071] S9, evaluate the site according to the vulnerability factor;

[0072] When the vulnerability factor G < 0, the site strength is greater than the bedrock, and it is not easy to rupture, but attention should be paid to the situation of weak interlayers below the site;

[0073] When the vulnerability factor 0 < G < 1.0×10 -4 , the site vulnerability is poor, the strength is large, and it is not easy to rupture;

[0074] When the vulnerability factor 1.0×10 -4 < G, the site vulnerability is strong, the strength is small, and it is easy to rupture.

[0075] S10, repeat steps S1 - S9 to complete the calculation and evaluation of the vulnerability factors at all measuring point positions within the site.

[0076] S11, output the site evaluation report.

Claims

1. A site vulnerability assessment method based on background noise, characterized in that: The following steps are involved: S1, site three-component background noise data acquisition: use a three-component node seismograph to observe background noise data, start blindly collecting seismic background noise data for a certain period of time; S2, calculate the three-component background noise spectrum ratio curve: pre-process the seismic background noise data obtained in S1, and perform Fourier transform on the pre-processed background noise data to obtain the spectrum of the three-component signal, and obtain the spectrum ratio curve A(f) according to the following formula: A(f)=H(f) / V(f), Among them, V(f) = Z(f) is the spectrum curve of the vertical component Z; H(f) is the spectrum of the horizontal component, which is expressed as follows, Where X(f) and Y(f) represent the frequency spectrum curves of horizontal components X and Y respectively; S3, extracting the dominant frequency f0: obtaining the dominant frequency f0 corresponding to the maximum amplitude position from the spectrum ratio curve obtained in S2; S4, extracting the site amplification factor: determining the maximum amplitude value corresponding to the dominant frequency, and obtaining the site amplification factor A h (f0); S5, calculating the Z component background noise dispersion curve: calculating the surface wave dispersion curve at each acquisition point through the vertical component Z in the background noise signal; the calculation of the surface wave dispersion curve requires data from at least two seismographs and is calculated through a multi-channel comparison method: Where, E is the total dispersion curve spectrum, f and v represent the frequency and phase velocity respectively; n is the number of seismic traces, n≥2; is the dispersion spectrum of the jth track and the first track at different frequencies and phase velocities calculated by the signal comparison method, j>1; S6, extracting the phase velocity corresponding to the dominant period: according to the dominant frequency f0 obtained in S3, picking up the frequency f in the surface wave dispersion curve obtained in S5 ０ The corresponding surface wave phase velocity v R ; S7, phase velocity-apparent velocity conversion: The surface wave phase velocity v is converted into R Converted to apparent velocity v s , v s =v R / sinθ, Among them, θ is the propagation angle of the surface wave on the site surface, and the units of apparent velocity and phase velocity are m / s; S8, calculate the site vulnerability factor G: S9, performing site evaluation according to the site vulnerability factor G obtained in S8.

2. The site vulnerability assessment method based on background noise according to claim 1, characterized in that: The preprocessing described in S2 includes: S21, performing bandpass filtering on the background noise data; S22, performing time normalization processing on the background noise data processed in S21 to balance the energy of signals with different frequencies.

3. The site vulnerability assessment method based on background noise according to claim 2, characterized in that: The effective frequency band of the bandpass filter in S21 is 5-30Hz.

4. The site vulnerability assessment method based on background noise according to claim 1, characterized in that: The certain time mentioned in S1 is at least 30 minutes.

5. The site vulnerability assessment method based on background noise according to claim 1, characterized in that: The criteria for site evaluation in S9 are: When the fragility factor G<0, the site strength is greater than the bedrock and is not prone to rupture, but attention should be paid to the presence of weak interlayers beneath the site; When the fragility factor is 0 <G<1.0*10 -4 When the site is fragile, it is not easy to break; When the vulnerability factor is 1.0 * 10 -4 <G, the site vulnerability is strong and rupture is likely to occur.

6. The site vulnerability assessment method based on background noise according to claim 1, characterized in that: The following steps are also included: S10, complete the calculation and evaluation of vulnerability factors of all measuring points in the site according to S1-S9; S11, output site evaluation report.

Images