Method for analyzing acoustic properties of seabed sediment layers based on wavelet consistency calibration

Abstract

The application discloses a seabed sediment layer acoustic characteristic analysis method based on wavelet consistency joint calibration and belongs to the technical field of marine engineering investigation and seabed detection. The method comprises the following steps: denoising the collected sound wave data in water and the seabed sediment layer to obtain an actual water sound field and an actual sediment layer sound field; establishing a reference sound field based on a zero-phase bandwidth wavelet by using the water acoustic characteristics; solving a matched filter of the actual water sound field and the reference sound field; applying the matched filter to the actual sediment layer sound field, picking up the peak time and amplitude of each channel of the filtered sediment layer sound field by using envelope fitting; and inverting the acoustic characteristic parameters of the sediment layer based on the obtained peak time and amplitude, wherein the acoustic characteristic parameters include the sound velocity and the sound attenuation factor. The application can obtain accurate calculation results of the sediment layer acoustic characteristics.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of marine engineering survey and seabed detection, and particularly relates to a seabed sediment layer acoustic characteristic analysis method based on water reference sound field and wavelet consistency joint calibration. BACKGROUND

[0002] Seabed acoustic in-situ detection is an important means to obtain the acoustic characteristics of seabed sediment layers, and the velocity and attenuation of the wavelet in the sediment layer are calculated by picking up the travel time and amplitude of the sound source at different channels. In the prior art, more researches have been carried out on the in-situ measurement device for the acoustic characteristics of seabed sediment layers (such as CN202211594471.0).

[0003] In the in-situ measurement of the acoustic characteristics of seabed sediment layers, the accuracy of the first arrival and amplitude picking up of the longitudinal wave directly determines the reliability of the calculated results. The traditional first arrival picking up is mostly based on the true take-off point of the wavelet (such as STA / LTA, AIC, PAI-S / K and other methods), and due to the low initial take-off amplitude of the wavelet, the signal-to-noise ratio is relatively low, which greatly affects the subsequent first arrival picking up. At the same time, the existing in-situ detection is generally based on the wavelet consistency assumption, that is, the wavelet is consistent along different incident angles. In actual application, the wavelet shows a certain directional characteristic due to the restriction of hardware and collection environment, which interferes with the wavelet first arrival picking up and amplitude statistics, and affects the accurate evaluation of the acoustic characteristics of the sediment layer and the reliability of the calculated results. SUMMARY

[0004] To solve the problems in the prior art, the application provides a seabed sediment layer acoustic characteristic analysis method based on wavelet consistency calibration, which establishes a reference sound field based on a zero-phase bandwidth wavelet to solve the matched filter of each receiving channel, and applies it to the actual sediment layer sound field, thereby overcoming the interference caused by the directional characteristic of the wavelet and obtaining accurate calculation results of the acoustic characteristics of the sediment layer.

[0005] To achieve the above purpose, the technical scheme adopted by the application is as follows:

[0006] A seabed sediment layer acoustic characteristic analysis method based on wavelet consistency joint calibration, comprising the following steps:

[0007] 1) Denoising the collected acoustic data in water and the seabed sediment layer to obtain the actual water sound field and the actual sediment layer sound field;

[0008] 2) Establishing a reference sound field based on a zero-phase bandwidth wavelet using the acoustic characteristics in water;

[0009] 3) Solving the matched filter of the actual water sound field and the reference sound field;

[0010] 4) Apply the matched filter to the actual sedimentary layer acoustic field, pick up the peak travel time and amplitude of each channel of the filtered sedimentary layer acoustic field by envelope fitting;

[0011] 5) Invert the acoustic parameters of the sedimentary layer, including the sound velocity and the sound attenuation factor, based on the peak travel time and amplitude obtained in step 4).

[0012] As a preferred embodiment of the present application, step 1) adopts band-pass filtering and statistical denoising method.

[0013] As a preferred embodiment of the present application, the reference acoustic field is established based on zero-phase bandwidth wavelet using the acoustic characteristics in water, which includes:

[0014] The zero-phase bandwidth wavelet is emitted into water, and the travel time of different receiving channels is calculated by the observation system through the sound velocity in water;

[0015] The amplitude of different receiving channels is calculated by the observation system given the attenuation factor in water;

[0016] The expected waveform of each receiving channel is determined according to the travel time and amplitude of different channels, and the reference acoustic field is constructed.

[0017] As a preferred embodiment of the present application, the solving process of the matched filter of the actual water acoustic field and the reference acoustic field is represented as:

[0018]

[0019] Wherein, O 水 represents the actual water acoustic field, M 水 represents the reference acoustic field in water, and F represents the filter group. Each channel in the acoustic field corresponds to a filter, and the filter parameters of different channels do not affect each other.

[0020] As a preferred embodiment of the present application, the filtered sedimentary layer acoustic field is represented as:

[0021]

[0022] Wherein, M 沉积层 represents the actual sedimentary layer acoustic field, and F represents the filter group. FM 沉积层 represents the filtered sedimentary layer acoustic field.

[0023] As a preferred embodiment of the present application, the calculation formula for inverting the acoustic parameters of the sedimentary layer is:

[0024]

[0025] Wherein, n is the total number of receiving channels, E v , E α correspond to the square error function of the sound velocity and the sound attenuation factor respectively, v match, a match is the sound speed and sound attenuation factor to be solved, Ts i , T i is the fitted travel time and measured travel time corresponding to channel i, As i , A i is the fitted amplitude and measured amplitude corresponding to channel i.

[0026] As a preferred embodiment of the present application, the fitted travel time is calculated by inputting a given v match into the observation system, and the fitted amplitude is calculated by inputting a given a match into the observation system.

[0027] Compared with the prior art, the present application has the following beneficial effects:

[0028] (1) Since the sound speed in water and the sound attenuation factor in water can be obtained by measurement, the reference sound field can be constructed using the acoustic characteristics in water, which can effectively eliminate the wavelet directivity problem and improve the reliability of the calculation results;

[0029] (2) After consistency calibration, the wavelet is subjected to zero phase processing, and at this time the peak value is the take-off point of the first arrival, which can effectively improve the signal-to-noise ratio of the first arrival point and make the wavelet first arrival picking more accurate;

[0030] (3) The envelope picking method is used to pick the peak travel time and amplitude of each channel of the filtered sediment sound field, and the method of fitting and inversion can effectively improve the stability of the calculation results. BRIEF DESCRIPTION OF DRAWINGS

[0031] Figure 1 is a flowchart of the seabed sediment acoustic characteristic analysis method based on wavelet consistency calibration;

[0032] Figure 2 is a comparison of the results of in-situ detection in water (left), reference sound field (middle), and consistency calibration (right).

[0033] Figure 3 is a matching filter obtained based on the detection and reference sound field;

[0034] Figure 4 is a comparison of the results before and after consistency calibration of the acoustic data in mud;

[0035] Figure 5 is the error curve of the sound speed and sound attenuation in water obtained based on least squares fitting;

[0036] Figure 6 is the error curve of the sound speed and sound attenuation in mud obtained based on least squares fitting; DETAILED DESCRIPTION

[0037] The present application will be further described and illustrated with reference to the specific embodiments. The embodiments are only exemplary and do not limit the scope of the disclosure. The technical features of various embodiments of the present application can be combined without conflict, as long as they are not mutually exclusive.

[0038] The in-situ acoustic detection result M is determined by multiple factors such as the observation system, the acoustic field properties and the environmental noise, and its mathematical expression is as follows:

[0039]

[0040] Wherein, S, R, E, G and N represent the transmitting end system response, the receiving end system response, the medium acoustic characteristics, the observation system geometric diffusion and the environmental noise respectively. v and a represent the sound speed and the sound attenuation constant, which determine the travel time and amplitude attenuation of the waveform.

[0041] The observation system can simulate and calculate the travel time information by giving the sound speed and the amplitude information by giving the attenuation factor according to the positional relationship between the wavelet transmitting end and the receiving end. The observation system itself is a known technology in the art, which will not be described here.

[0042] Due to the influence of the device itself, S and R have the problem of directivity changing with the incident angle, which is manifested as waveform distortion, travel time and amplitude anomaly and other phenomena. In order to eliminate this difference, the present application uses the measured data M 水 in water to calibrate the directivity of the waveform system response, and proposes a seabed sediment layer acoustic characteristic analysis method based on the consistency joint calibration of the reference acoustic field in water and the wavelet, as shown in Figure 1 The method comprises:

[0043] S1, denoising of data collected in water and sediment layer; generally, a band-pass filter is used to set the band-pass filter frequency range of the target acoustic data, allowing acoustic signals within a specific frequency range to pass through, while suppressing signals below and above the frequency range; or statistical denoising method is used to identify and remove noise in the data, such as reducing noise by averaging multiple signal data or using autocorrelation function to eliminate noise; other types of signal denoising methods known in the art can also be used.

[0044] S2, establishing a reference acoustic field in water using the sound speed and the sound attenuation coefficient in water.

[0045] In this step, the sound speed and the sound attenuation coefficient in water are used in combination with the observation system of the in-situ acoustic detection device to construct the expected waveform corresponding to different channel positions, and then the reference acoustic field is obtained.

[0046] The present application establishes a reference sound field based on zero-phase bandwidth wavelet, calculates the travel time of different receiving channels by emitting zero-phase bandwidth wavelet into water and using an observation system through water sound velocity; given water attenuation factor, calculates the amplitude of different receiving channels by using the observation system; determines the expected waveform of each receiving channel according to the travel time and amplitude of different channels, and constitutes the reference sound field. Here, the water sound velocity and water attenuation factor can be obtained by actual measurement.

[0047] S3, solve the matching filter between the actual water sound field and the reference sound field, which is used for realizing zero-phase of the water sound field and wavelet shaping.

[0048] In this step, the process of solving the matching filter is represented by the following formula:

[0049]

[0050] Wherein, O 水 is the water reference sound field, which is constructed based on zero-phase bandwidth wavelet, combined with water observation system (geometric diffusion) and water attenuation factor; F is the matching filter operator, which is used for converting the water measured data into the reference sound field.

[0051] As shown in Figure 3 , since the total number of receiving channels can be several, the matching filter obtained based on the measured and reference sound fields can be found by analysis that due to the different characteristics of wavelet inconsistency existing in different channel data, the corresponding zero-phase and wavelet shaping matching filter will also change accordingly, each channel corresponds to a matching filter, and the filter parameters of different channels do not affect each other.

[0052] As shown in Figure 2 , the comparison of the results of in-situ detection in water (left), reference sound field (middle) and consistency calibration (right). Data description: 32KHz main frequency transducer sound source, 8-channel acquisition (from bottom to top, corresponding to the 1st-8th channel), spherical geometric diffusion (amplitude decays according to 1 / R, wherein R is the propagation distance). It can be seen from this that there are abnormal phenomena of waveform amplitude and travel time in the detection results, which presents obvious wavelet directionality characteristics. Since the reference sound field is constructed according to the wavelet consistency, spherical diffusion and absorption attenuation law, it shows stable amplitude and travel time law, and the results after consistency calibration of the wavelet are basically consistent with the reference sound field.

[0053] S4, apply the matching filter to the sediment layer sound field data.

[0054] In this step, on the basis of formula (2), the matching filter is applied to the in-situ detection data M 沉积层 of the sediment layer, so as to obtain the consistency calibrated in-situ detection results FM 沉积层 of the sediment layer.

[0055]

[0056] In S5, the envelope fitting method is used to extract the peak travel time and amplitude of the filtered sediment layer acoustic data in S4, and the least squares fitting method is used to invert the acoustic properties of the sediment layer, including the sound velocity and acoustic attenuation factor.

[0057] In this step, based on formula (3), FM 沉积层 Perform envelope picking and extract the travel time T and amplitude A corresponding to the peak, as shown in Figure 4 Shown is a comparison of the results before and after consistency calibration of acoustic data in the sediment layer. The red line corresponds to the envelope fitting curve.

[0058] The positional relationship between each transmission and reception obtained by the observation system is used to simulate and analyze the sound velocity and sound attenuation factor, and then fit them with the measured results. The sound velocity and sound attenuation factor corresponding to the minimum square error between the fitted and measured results are considered to be the best inversion results. The mathematical process is shown in formulas (4) and (5):

[0059]

[0060] Where n is the total number of receiving channels, E v 、E α Corresponding to the square error function of sound speed and sound attenuation, v match , α match For the fitted sound velocity and sound attenuation factor, the range and step size can be adjusted according to the actual situation. i 、T i are the fitted travel time and measured travel time of the corresponding channel i, As i 、A i are the fitted amplitude and measured amplitude corresponding to channel i.

[0061] like Figure 5 Figure 2 shows the error curves for underwater sound velocity and attenuation obtained using least squares fitting based on the peak time and amplitude extracted from the data after consistency calibration. The lowest error shows a sound velocity of 1490 m / s and an underwater attenuation of 0 dB / m, which is consistent with the actual measurement results and proves the effectiveness of the method. The peak time and amplitude are extracted based on the envelope fitting curve (shown in red). Envelope fitting can more accurately reflect the overall trend of the waveform, making the picking result more reliable. Figure 6 This is the least squares fitting result in the sediment layer. From the figure, we can effectively extract that the sound velocity in the mud is 1550m / s and the sound attenuation in the mud is 5dB / m.

[0062] The above described embodiments only express one implementation of the present application, which is described more specifically and in detail, but cannot be understood as a limitation to the scope of the present application. For those skilled in the art, several modifications and improvements can be made without departing from the concept of the present application, which are all within the scope of protection of the present application.

Claims

1. A method for analyzing the acoustic characteristics of seabed sediments based on wavelet consistency joint calibration, characterized in that: The steps include: 1) De-noising the acoustic wave data collected in the water and the seabed sediment layer to obtain the actual underwater sound field and the actual sediment layer sound field; 2) Using underwater acoustic characteristics, a reference sound field is established based on zero-phase bandwidth wavelets, including: The zero-phase bandwidth wavelet is transmitted into the water, and the travel time of different receiving channels is calculated by the observation system based on the sound speed in the water; Given the attenuation factor in water, the amplitude of different receiving channels is calculated using the observation system; Determine the expected waveform of each receiving channel based on the travel time and amplitude of different channels to form a reference sound field; 3) Solve the matched filter between the actual underwater sound field and the reference sound field. The solution process is expressed as: Among them, O 水 Represents the actual underwater sound field, M 水 Represents the reference sound field, F represents the filter group, each channel in the sound field corresponds to a filter, and the filter parameters of different channels do not affect each other; 4) Applying the matched filter to the actual sediment layer acoustic field, and using envelope fitting to pick up the peak travel time and amplitude of each channel of the filtered sediment layer acoustic field; 5) Based on the peak travel time and amplitude obtained in step 4), invert the acoustic characteristic parameters of the sediment layer, wherein the acoustic characteristic parameters include sound velocity and sound attenuation factor.

2. The method for analyzing the acoustic characteristics of seabed sediments based on wavelet consistency joint calibration according to claim 1 is characterized in that: Step 1) Bandpass filtering and statistical denoising methods are used.

3. The method for analyzing the acoustic characteristics of seabed sediments based on wavelet consistency joint calibration according to claim 1 is characterized in that: The acoustic field of the sediment layer after filtering is expressed as: Among them, M 沉积层 represents the actual sediment layer sound field, F represents the filter group, FM 沉积层 represents the acoustic field of the sediment layer after filtering.

4. The method for analyzing the acoustic characteristics of seabed sediments based on wavelet consistency joint calibration according to claim 1 is characterized in that: The calculation formula for inverting the acoustic characteristic parameters of the sediment layer is: Where n is the total number of receiving channels, E v 、E α The square error functions corresponding to the sound velocity and sound attenuation factor, v match , α match are the sound velocity and sound attenuation factor to be solved, Ts i 、T i are the fitted travel time and measured travel time of channel i, respectively, As i 、A i are the fitted amplitude and measured amplitude of channel i, respectively.

5. The method for analyzing the acoustic characteristics of seabed sediments based on wavelet consistency joint calibration according to claim 4 is characterized in that: The fitting travel time is given by v match The input observation system is calculated, and the fitting amplitude is calculated by giving α match Calculated by input observation system.

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