Submarine sedimentary layer acoustic characteristic analysis method based on wavelet consistency calibration

Abstract

The invention discloses a seabed sedimentary layer acoustic characteristic analysis method based on wavelet consistency joint calibration, and belongs to the technical field of ocean engineering investigation and seabed detection. Comprising the following steps: denoising sound wave data collected in water and a seabed sedimentary layer to obtain an actual water sound field and an actual sedimentary layer sound field; establishing a reference sound field based on zero-phase bandwidth wavelets by using acoustic characteristics in water; solving a matched filter of the actual underwater sound field and the reference sound field; applying the matched filter to the actual sedimentary layer sound field, and picking up the peak travel time and amplitude of each channel of the filtered sedimentary layer sound field by using envelope fitting; and based on the obtained peak travel time and amplitude, inverting acoustic characteristic parameters of the sedimentary layer, the acoustic characteristic parameters including sound velocity and sound attenuation factors. According to the method, an accurate calculation result of the acoustic characteristics of the deposited layer can be obtained.

Description

Technical Field

[0001] The present invention belongs to the technical field of marine engineering survey and seabed detection, and in particular relates to a method for analyzing acoustic characteristics of seabed sediment layers based on joint calibration of underwater reference sound field and wavelet consistency. Background Art

[0002] Seafloor acoustic in-situ detection is an important means to obtain the acoustic characteristics of seafloor sediments. By picking up the travel time and amplitude of the sound source arriving at different channels, the speed and attenuation law of the wavelet in the sediment are calculated. In the prior art, many studies have been carried out on in-situ measurement devices for the acoustic characteristics of seafloor sediments (such as CN202211594471.0).

[0003] In the in-situ measurement of the acoustic characteristics of the seabed sediment layer, the accuracy of the first arrival and amplitude picking of the longitudinal wave directly determines the reliability of the calculated results. Traditional first arrival picking is mostly based on the real starting point of the wavelet (such as STA / LTA, AIC, PAI-S / K and other methods). Since the initial starting amplitude of the wavelet is low, the signal-to-noise ratio is relatively low, which has a great impact on the subsequent first arrival picking. 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 practical applications, due to the constraints of hardware and acquisition environment, the wavelet will show certain directional characteristics, which will interfere with the wavelet first arrival picking and amplitude statistics, affecting the accurate evaluation of the acoustic characteristics of the sediment layer and reducing the reliability of the calculated results. Summary of the invention

[0004] In order to solve the problems in the prior art, the present invention proposes a method for analyzing the acoustic characteristics of seabed sediments based on wavelet consistency calibration. By establishing an underwater reference sound field based on zero-phase bandwidth wavelets to solve the matched filters of each receiving channel, and applying it to the actual sediment sound field, the interference caused by the directional characteristics of the factor waves can be overcome, and accurate calculation results of the acoustic characteristics of the sediments can be obtained.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0006] A method for analyzing acoustic characteristics of seafloor sediments based on wavelet consistency joint calibration includes the following steps:

[0007] 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;

[0008] 2) Using the acoustic characteristics of water, a reference sound field is established based on zero-phase bandwidth wavelets;

[0009] 3) Solve the matching filter between the actual underwater sound field and the reference sound field;

[0010] 4) Applying the matched filter to the actual sediment layer sound field, and using envelope fitting to pick up the peak travel time and amplitude of each channel of the filtered sediment layer sound field;

[0011] 5) Based on the peak travel time and amplitude obtained in step 4), the acoustic characteristic parameters of the sediment layer are inverted, including the sound velocity and the sound attenuation factor.

[0012] As a preferred embodiment of the present invention, step 1) adopts bandpass filtering and statistical denoising methods.

[0013] As a preferred embodiment of the present invention, the method of using underwater acoustic characteristics to establish a reference sound field based on a zero-phase bandwidth wavelet includes:

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

[0015] Given the attenuation factor in water, the amplitudes of different receiving channels are calculated using the observation system;

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

[0017] As a preferred embodiment of the present invention, the process of solving the matched filter between the actual underwater sound field and the reference sound field is expressed as:

[0018]

[0019] Among them, O 水 represents the actual underwater sound field, M 水 represents the reference sound field in water, 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.

[0020] As a preferred embodiment of the present invention, the acoustic field of the sediment layer after filtering is expressed as:

[0021]

[0022] Among them, M 沉积层 represents the actual sediment layer acoustic field, F represents the filter group, FM 沉积层 Represents the acoustic field of the sediment layer after filtering.

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

[0024]

[0025] Where n is the total number of receiving channels, E v 、E α The square error functions corresponding to the sound velocity and the sound attenuation factor, v match, α match is the sound velocity and sound attenuation factor to be solved, Ts i 、T i As is the fitted travel time and measured travel time of the corresponding channel i, i , A i are the fitted amplitude and measured amplitude corresponding to channel i.

[0026] As a preferred embodiment of the present invention, the fitting travel time is obtained by match The input observation system is calculated, and the fitting amplitude is calculated by giving α match Calculated by input observation system.

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

[0028] (1) Since the speed of sound in water and the attenuation factor in water can be obtained through actual measurement, constructing a reference sound field using the acoustic characteristics of water can effectively eliminate the problem of sub-wave directionality and improve the reliability of the calculation results;

[0029] (2) After consistency calibration, the wavelet undergoes zero-phase processing, so the peak value is the starting point of the first arrival, which can effectively improve the signal-to-noise ratio of the first arrival point and make the first arrival of the wavelet more accurate.

[0030] (3) The envelope picking method is used to pick up the peak travel time and amplitude of each channel of the filtered sediment layer acoustic field. Combining it with the simulation and inversion method can effectively improve the stability of the calculation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 The figure is a flow chart of the method for analyzing the acoustic characteristics of seafloor sediments based on wavelet consistency calibration;

[0032] Figure 2 Comparison of the results of in-situ detection in water (left) with the reference sound field (middle) and after consistency calibration (right).

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

[0034] Figure 4 Comparison of acoustic data consistency before and after calibration in mud;

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

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

[0037] The present invention is further described and illustrated below in conjunction with specific embodiments. The embodiments are merely exemplary of the present disclosure and do not define the scope of limitation. The technical features of each embodiment of the present invention may be combined accordingly without conflicting with each other.

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

[0039]

[0040] Among them, S, R, E, G and N represent the system response of the transmitter, the system response of the receiver, the acoustic characteristics of the medium, the geometric diffusion of the observation system and the environmental noise respectively. v and α represent the speed of sound and the acoustic 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 based on the positional relationship between the sub-wave transmitter and the receiver, given the sound speed, and can simulate and calculate the amplitude information given the attenuation factor. The observation system itself is a well-known technology in the field and will not be described here.

[0042] Due to the influence of the equipment itself, S and R have a directional problem that changes with the incident angle, which manifests as waveform distortion, abnormal travel time and amplitude, etc. In order to eliminate this difference, the present invention uses the measured data M in water 水 The waveform system response directionality is calibrated, and a method for analyzing the acoustic characteristics of seafloor sediments based on the joint calibration of the underwater reference sound field and the wavelet consistency is proposed. Figure 1 As shown, the method includes:

[0043] S1, denoising of data collected in water and sediment layers; generally, a bandpass filter is used to set the bandpass filter frequency band 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 a statistical denoising method is used to identify and remove noise in the data, such as by averaging multiple signal data to reduce noise or using an autocorrelation function to eliminate noise; other types of signal denoising methods known in the art can also be used.

[0044] S2, using the speed of sound in water and the acoustic attenuation coefficient to establish an underwater reference sound field.

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

[0046] The present invention establishes a reference sound field based on a zero-phase bandwidth wavelet, transmits a zero-phase bandwidth wavelet into water, and calculates the travel time of different receiving channels using the speed of sound in water using an observation system; given an attenuation factor in water, the amplitude of different receiving channels is calculated using an observation system; the expected waveform of each receiving channel is determined according to the travel time and amplitude of different channels to form a reference sound field. Here, the speed of sound in water and the attenuation factor in water can both be obtained by actual measurement.

[0047] S3, solving the matching filter between the actual underwater sound field and the reference sound field, where the matching filter is used to achieve zero-phase and wavelet shaping of the underwater sound field.

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

[0049]

[0050] Among them, O 水 is the underwater reference sound field, which is constructed based on the zero-phase bandwidth wavelet, combined with the underwater observation system (geometric diffusion) and the underwater attenuation factor; F is the matched filter operator, which is used to convert the measured data in the water into the reference sound field.

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

[0052] like Figure 2 As shown, the results of in-situ detection in water (left) are compared with those of the reference sound field (middle) and after consistency calibration (right). Data description: 32KHz main frequency transducer sound source, 8-channel acquisition (corresponding to channels 1-8 from bottom to top), spherical geometric diffusion (amplitude decays according to 1 / R, where R is the propagation distance). It can be seen from this that there are abnormal waveform amplitude and travel time in the detection results, showing obvious sub-wave directional characteristics. The reference sound field is constructed strictly in accordance with the sub-wave consistency, spherical diffusion, and absorption attenuation laws, so it exhibits stable amplitude and travel time laws. The results after sub-wave consistency calibration are basically consistent with the reference sound field.

[0053] S4, applying the matched filter to the sediment layer acoustic field data.

[0054] In this step, based on formula (2), the matched filter is applied to the in-situ detection data M corresponding to the sedimentary layer. 沉积层 In order to obtain the in-situ detection results of the sedimentary layer after consistency calibration, FM 沉积层 :

[0055]

[0056] S5, the envelope fitting method is used to extract the peak travel time and amplitude of the acoustic data of the sediment layer after filtering in S4, and the least squares fitting method is used to invert the acoustic characteristics of the sediment layer, including the sound velocity and the 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 value, such as Figure 4 Shown is the comparison of the results before and after the consistency calibration of acoustic data in the sediment layer. The red line corresponds to the envelope fitting curve.

[0058] The position 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 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 The square error functions corresponding to the sound velocity 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 As is the fitted travel time and measured travel time of the corresponding channel i, i , A i are the fitted amplitude and measured amplitude corresponding to channel i.

[0061] like Figure 5 As shown in the figure, based on the peak time and amplitude extracted from the data after consistency calibration, the error curve of sound velocity and sound attenuation in water is obtained by least square fitting. The lowest error shows that the sound velocity in water is 1490m / s and the sound attenuation in water is 0dB / m, which is consistent with the actual measurement results, proving the effectiveness of the method. The extraction of peak time and amplitude is based on the envelope fitting curve (shown in the red curve). Envelope fitting can more accurately reflect the overall change trend of the waveform, so the picking result is more reliable. Figure 6 This is the least square 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-mentioned embodiment only expresses one implementation mode of the present invention, and its description is relatively specific and detailed, but it cannot be understood as limiting the scope of the present invention. For ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention.

Claims

1. A method for analyzing the acoustic characteristics of seafloor 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 the acoustic characteristics of water, a reference sound field is established based on zero-phase bandwidth wavelets; 3) Solve the matching filter between the actual underwater sound field and the reference sound field; 4) Applying the matched filter to the actual sediment layer sound field, and using envelope fitting to pick up the peak travel time and amplitude of each channel of the filtered sediment layer sound 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 seafloor sediments based on wavelet consistency joint calibration according to claim 1 is characterized in that: Step 1) uses bandpass filtering and statistical denoising methods.

3. The method for analyzing the acoustic characteristics of seafloor sediments based on wavelet consistency joint calibration according to claim 1 is characterized in that: The method of using underwater acoustic characteristics to establish a reference sound field based on a zero-phase bandwidth wavelet includes: The zero-phase bandwidth wavelet is emitted into the water, and the travel time of different receiving channels is calculated by the observation system through the speed of sound in the water; Given the attenuation factor in water, the amplitudes of different receiving channels are calculated using the observation system; The expected waveform of each receiving channel is determined according to the travel time and amplitude of different channels to form a reference sound field.

4. The method for analyzing the acoustic characteristics of seafloor sediments based on wavelet consistency joint calibration according to claim 1 is characterized in that: The process of solving the matched filter between the actual underwater sound field and the reference sound field is expressed as: Among them, O 水 represents the actual underwater sound field, M 水 represents the reference sound field in water, 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.

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

6. The method for analyzing the acoustic characteristics of seafloor sediments based on wavelet consistency joint calibration according to claim 1 is characterized in that: The calculation formula for the acoustic characteristic parameters of the inverted 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 the sound attenuation factor, v match , α match is the sound velocity and sound attenuation factor to be solved, Ts i , T i As is the fitted travel time and measured travel time of the corresponding channel i, i , A i are the fitted amplitude and measured amplitude corresponding to channel i.

7. The method for analyzing the acoustic characteristics of seafloor sediments based on wavelet consistency joint calibration according to claim 6 is characterized in that: The fitting travel time is obtained by taking the given 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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