CN110319797B - Image domain cobalt-rich crust thickness extraction method based on dual-channel information - Google Patents
Image domain cobalt-rich crust thickness extraction method based on dual-channel information Download PDFInfo
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Abstract
The invention provides an image domain cobalt-rich crust thickness extraction method based on dual-channel information, which comprises the following steps of: s1: acquiring a primary frequency signal through a first channel, and performing signal time domain processing on the primary frequency signal to acquire a time vector of the primary frequency signal reaching the top of a cobalt-rich crust; s2: acquiring a difference frequency signal through a second channel, and carrying out image domain processing on the propagation of the difference frequency signal in a cobalt-rich crusting medium to acquire a time vector of the difference frequency signal reaching the bottom of the cobalt-rich crusting medium; s3: and combining the time vector of the primary frequency signal reaching the top of the cobalt-rich crust, the time vector of the differential frequency signal reaching the bottom of the cobalt-rich crust and the sound velocity of the differential frequency signal in the cobalt-rich crust medium to obtain the thickness of the cobalt-rich crust. The method effectively solves the problem of effective thickness estimation in the exploration of the submarine mineral resources containing the cobalt-rich crusts.
Description
Technical Field
The invention relates to a thickness estimation technology of in-situ exploration of a seabed sediment fine structure, in particular to an image domain cobalt-rich crust thickness extraction method based on dual-channel information.
Background
The cobalt-rich crust is a crust-like substance growing on the slope and top of the seahill, the sea ridge and the sea platform with the water depth of 400-4000 m, is a crust-like mineral deposit rich in metal elements such as manganese, cobalt, nickel, platinum, rare earth and the like, is an important metal strategic mineral resource, and is another 'treasury capable of mining thousands of years' after the combustible ice. The mapping and quantitative estimation of the cobalt-rich crust have important value for oceanography, geography and industrial development. The estimation means is a multivariate one, and can be performed by, for example, a multi-beam method, a side-scan sonar method, a shallow profile method, or the like. However, the effectiveness of these approaches is limited by factors such as uneven distribution of cobalt-rich encrusted minerals, thinner geometry, coverage by deposits, and the like. On the basis of measurement by using an acoustic in-situ measurement device, the thickness of the cobalt-rich crust in the area is obtained by efficiently carrying out algorithm processing on the obtained echo signal, and the method has complete feasibility.
Disclosure of Invention
The application provides an image domain cobalt-rich crust thickness extraction method based on dual-channel information, which effectively solves the problems of accuracy and stability of cobalt-rich crust thickness estimation.
The specific technical scheme is as follows:
the method comprises the following steps:
s1: acquiring a primary frequency signal through a first channel, and performing signal time domain processing on the primary frequency signal to acquire a time vector of the primary frequency signal reaching the top of a cobalt-rich crust;
s2: acquiring a difference frequency signal through a second channel, and performing image processing on the propagation of the difference frequency signal in a cobalt-rich crust medium to acquire a time vector of the difference frequency signal reaching the bottom of the cobalt-rich crust;
s3: and combining the time vector of the primary frequency signal reaching the top of the cobalt-rich crust, the time vector of the differential frequency signal reaching the bottom of the cobalt-rich crust and the sound velocity of the differential frequency signal in the cobalt-rich crust medium to obtain the thickness of the cobalt-rich crust.
Further, in S1, performing signal time domain processing on the primary frequency signal to obtain a time vector of the primary frequency signal reaching the top of the cobalt-rich crust, specifically including the steps of:
s11: extracting an envelope signal of the original frequency signal;
s12: extracting a peak value of the envelope signal;
s13: and carrying out moving average processing on the peak value according to the working frequency of the original frequency signal, and taking the averaged peak value as a time vector of the original frequency signal reaching the top of the cobalt-rich crust.
Further, the specific steps of forming the image domain in S2 are:
s21: performing energy compensation on the difference frequency signal transmitted in the cobalt-rich crust medium according to an attenuation rule;
s22: according to the signal-to-noise ratio calculation result, envelope extraction is carried out on the compensated difference frequency signal on the premise of meeting the requirement, and an envelope signal is obtained;
s23: and splicing the plurality of envelope signals according to a time sequence to form the image domain.
Further, performing image domain processing on the propagation of the difference frequency signal in the cobalt-rich crusting medium to obtain a time vector of the difference frequency signal reaching the bottom of the cobalt-rich crusting medium, specifically comprising the steps of:
s24: carrying out non-local filtering processing on the image domain;
s25: detecting the edge of the image domain by using a Sobel or Canny operator;
s26: performing disconnection connection processing on the image domain;
s27: and detecting an optimal straight line in the image domain by utilizing probability accumulation Hough transformation, wherein the optimal straight line is used as a time vector when the difference frequency signal reaches the bottom of the cobalt-rich crust.
Further, the step of band-pass filtering is included before the primary frequency signal is acquired through the first channel and before the step frequency signal is acquired through the second channel, and noise suppression is performed through the band-pass filtering.
Further, the specific steps of obtaining the sound velocity of the difference frequency signal in the cobalt-rich crust medium are as follows:
s31: in a test water tank, measuring the time of a signal emitted by a transmitting transducer to reach a receiving transducer when a tested cobalt-rich incrustation sample is not inserted between the transmitting transducer and the receiving transducer;
s32: inserting the cobalt-rich crusting sample to be measured into a plane wave propagation path between a transmitting transducer and a receiving transducer, and measuring the time of a signal sent by the transmitting transducer reaching the receiving transducer through the cobalt-rich crusting sample to be measured;
s33: according to the change of the arrival time of the acoustic signal, measuring the sound velocity of the measured cobalt-rich crust sample, wherein the calculation formula of the sound velocity is as follows:
wherein, c0Is the sound velocity in water, c is the sound velocity in the measured cobalt-rich incrustation sample, and L is the thickness of the measured cobalt-rich incrustation sample; delta t is the signal arrival receiving signal before and after insertion into the measured cobalt-rich crusting sampleThe time of the energy device varies.
The application provides a device corresponding to an image domain cobalt-rich crust thickness extraction method based on dual-channel information, which comprises the following steps:
the first processing module is used for acquiring a primary frequency signal through a first channel, and performing signal time domain processing on the primary frequency signal to acquire a time vector of the primary frequency signal reaching the top of the cobalt-rich crust;
the second processing module is used for acquiring a difference frequency signal through a second channel, carrying out image domain processing on the propagation of the difference frequency signal in the cobalt-rich crusting medium and acquiring a time vector of the difference frequency signal reaching the bottom of the cobalt-rich crusting;
and the thickness calculation module is used for combining the time vector of the primary frequency signal reaching the top of the cobalt-rich crust, the time vector of the differential frequency signal reaching the bottom of the cobalt-rich crust and the sound velocity of the differential frequency signal in the cobalt-rich crust medium to obtain the thickness of the cobalt-rich crust.
Further, the first processing module comprises:
the first band-pass filtering processing module is used for performing band-pass filtering processing on the first channel for acquiring the original frequency signal so as to inhibit noise;
the first envelope processing module is used for extracting an envelope signal of the original frequency signal;
a peak detection module for extracting a peak value of the envelope signal;
and the moving average processing module is used for carrying out moving average processing on the peak value according to the working frequency of the original frequency signal, and taking the averaged peak value as a time vector of the original frequency signal reaching the top of the cobalt-rich crust.
Further, the second processing module comprises:
the second band-pass filtering processing module is used for performing band-pass filtering processing on the second channel for acquiring the difference frequency signal so as to inhibit noise;
the energy compensation module is used for carrying out energy compensation on the difference frequency signal transmitted by the cobalt-rich crusting medium according to an attenuation rule;
the second envelope processing module is used for carrying out envelope extraction on the compensated difference frequency signal according to the signal-to-noise ratio calculation result on the premise of meeting the requirement to obtain an envelope signal;
the splicing module is used for splicing the envelope signals according to a time sequence to form the image domain;
the filtering processing module is used for carrying out non-local filtering processing on the image domain;
the edge detection module is used for detecting the edge of the image domain by utilizing a Sobel or Canny operator;
the broken line processing module is used for carrying out broken line connection processing on the image domain;
and the optimal straight line detection module is used for detecting the optimal straight line in the image domain by utilizing probability accumulation Hough transformation, and the optimal straight line is used as a time vector when the difference frequency signal reaches the bottom of the cobalt-rich crust.
The device further comprises a speed measurement module, wherein in the test water tank, a measured cobalt-rich incrustation sample is inserted into a plane wave propagation path between the transmitting transducer and the receiving transducer, the time of a signal sent by the transmitting transducer reaching the receiving transducer through the measured cobalt-rich incrustation sample and the time of a signal not reaching the receiving transducer through the measured cobalt-rich incrustation sample are measured, and the sound velocity in the measured cobalt-rich incrustation sample is calculated according to the change of the arrival time of the acoustic signal; the sound velocity calculation formula is specifically as follows:
wherein, c0Is the sound velocity in water, c is the sound velocity in the measured cobalt-rich incrustation sample, and L is the thickness of the measured cobalt-rich incrustation sample; at is the time change of the signal arriving at the receiving transducer before and after insertion into the measured cobalt-rich crusting sample.
According to the method, on the basis of measurement by using an acoustic in-situ measurement device, the cobalt-rich crust thickness in the area is obtained by efficiently carrying out algorithm processing on the obtained echo signals. In particular, the in-situ acoustic thickness estimation is carried out on the cobalt-rich crust, and the on-line or post-processing measurement is effectively carried out on the cobalt-rich crust thickness, which has important significance for the subsequent large-scale and high-efficiency resource exploitation in China.
Drawings
Fig. 1 is a schematic flow chart of an implementation of an image domain cobalt-rich crust thickness extraction method based on dual-channel information according to an embodiment of the present invention;
fig. 2 is a schematic diagram of an algorithm process of an image domain cobalt-rich crust thickness extraction method based on dual-channel information according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating the original frequency signal and the envelope and top arrival time vector estimation after the sliding average of the original frequency signal according to the method for extracting the cobalt-rich crust thickness in the image domain with the two-channel information in the preferred embodiment of the present invention;
FIG. 4 is a graph of the results of the non-local filtering of the two-channel information image domain cobalt-rich crust thickness extraction method in the preferred embodiment;
FIG. 5 is a top-bottom time arrival vector estimation diagram obtained after processing by the image domain cobalt-rich crust thickness extraction method of the two-channel information in the embodiment of the present invention;
fig. 6 is a thickness estimation result obtained after processing by the image domain cobalt-rich crust thickness extraction method of the two-channel information in the embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the following detailed description and accompanying drawings.
With respect to the original frequency signal and the difference frequency signal, an original frequency signal wave having a relatively high frequency and a difference frequency signal wave having a relatively low frequency can be generated by interaction between the signal wave and the signal wave. Thus, return signal waves of the original frequency signal and the difference frequency signal are received through two channels respectively.
Referring to fig. 1, an image domain cobalt-rich crust thickness extraction method based on dual-channel information includes the following steps: s1: acquiring an original frequency signal through a first channel, and performing signal time domain processing on the original frequency signal to acquire a time vector of the original frequency signal reaching the top of the cobalt-rich crust;
and acquiring the original frequency signal through the first channel for multiple times, and performing time domain processing on the original frequency signal to acquire a time vector of the original frequency signal reaching the top of the cobalt-rich crust. The original frequency signal cannot pass through the cobalt-rich crusting medium according to the self characteristics of the original frequency signal, so that the original frequency signal returns after reaching the top of the cobalt-rich crusting medium until the original frequency signal is obtained through the first channel.
Further, the original frequency signal cannot pass through the cobalt-rich crust due to high signal frequency, such as 50Hz, and is attenuated greatly, and returns at the top interface of the cobalt-rich crust, and the original frequency signal has better resolution due to strong signal, and can obtain better estimation accuracy directly through time domain processing.
S2: acquiring a difference frequency signal through a second channel, and carrying out image domain processing on the propagation of the difference frequency signal in the cobalt-rich crusting medium to acquire a time vector of the difference frequency signal reaching the bottom of the cobalt-rich crusting medium;
the method comprises the steps of utilizing signal waves transmitted for multiple times, enabling the waves to interact with each other to generate original frequency signals and difference frequency signals, enabling the original frequency signals to return after reaching a top interface of the cobalt-rich crust, enabling the difference frequency signals to enter the cobalt-rich crust medium, and enabling the difference frequency signals to return after failing to continuously penetrate after reaching the bottom of the cobalt-rich crust medium. Due to the self characteristics of the difference frequency signal, the frequency is low, so that after the difference frequency signal needs to be obtained for multiple times, the difference frequency signal is processed and spliced to obtain an image domain.
In addition, no matter the original frequency signal or the difference frequency signal, the waveforms generated by entering different media are different, and the signals obtained by different channels are different, so that the signal wave passing through the first channel can only be the original frequency signal and the signal wave passing through the second channel can only be the difference frequency signal no matter what the returned signal wave is. And because the signal frequency of the difference frequency signal is weak, the difference frequency signal image formed after the return acquired through the second channel cannot be consistent. The difference frequency signals are obtained for multiple times, processed and spliced to form an image domain, the image domain is processed, and a time vector reaching the bottom of the cobalt-rich crust is estimated.
Further, since the difference frequency signal may pass through the cobalt-rich crust with less attenuation and poorer resolution, the image domain may need to be processed, and the joint local continuity assumption is adopted to increase the accuracy and robustness of the estimation.
S3: and obtaining the thickness of the cobalt-rich crust by combining the time vector of the original frequency signal reaching the top of the cobalt-rich crust, the time vector of the difference frequency signal reaching the bottom of the cobalt-rich crust and the sound velocity of the difference frequency signal in the cobalt-rich crust medium.
Specifically, as shown in fig. 2-3 and 5, performing signal time domain processing on the original frequency signal in S1 to obtain a time vector of the original frequency signal reaching the top of the cobalt-rich crust specifically includes the steps of:
s11: extracting an envelope signal of the original frequency signal;
s12: the peak value of the envelope signal is extracted.
S13: and carrying out moving average processing on the peak value according to the working frequency of the original frequency signal, and taking the averaged peak value as a time vector of the original frequency signal reaching the top of the cobalt-rich crust.
For example, the frame processing of moving average is performed with a smoothing window of 5 or 10, and then the peak value of the extracted signal time domain is performed with moving average processing according to the working frequency of the original frequency signal transmission.
Wherein the moving average process is to take into account local continuity of thickness and operating high frequency of measurement. For example, if the system makes thickness measurements at a frequency of 50Hz, the assumption of local continuity holds. Thus, the error caused by single measurement can be reduced by using the moving average processing.
Further, the envelope extracted from any one signal record can obtain the peak value and the position thereof, namely the arrival time of one top; these peaks and their positions can be formed into vectors, measured over a longer period of time; further, the time vector of the top arrival with a small error can be obtained by the moving average processing.
Referring to fig. 2, the specific steps of forming the image domain in S2 are as follows:
s21: performing energy compensation on the difference frequency signal transmitted in the cobalt-rich crust medium according to an attenuation rule;
specifically, energy compensation is carried out on a difference frequency signal in the transmission of the cobalt-rich crusting medium according to an attenuation rule, as shown in a formula (1);
wherein z represents a thickness axis, γi[z]Representing the amount of energy in the signal acquisition time, ZtopRepresents the top interface value, ZbottomRepresenting the bottom boundary value, the energy to be compensated is
Top and bottom interfaces. In view of the fact that accurate bottom interface parameters cannot be obtained before the thickness processing is completed, the top interface time estimation parameters are obtained through the original frequency channel, and the bottom interface time is directly compensated to the time corresponding to the maximum thickness of the cobalt-rich crust, namely the time corresponding to the maximum thickness of the cobalt-rich crust is not more than 35 cm.
S22: according to the signal-to-noise ratio calculation result, envelope extraction is carried out on the compensated difference frequency signal to obtain an envelope signal;
for example, when the signal-to-noise ratio is high in a narrow band, which is greater than 10dB, the envelope can be extracted by using hilbert transform; when the non-narrowband or the signal-to-noise ratio is low, the envelope can be extracted by adopting complex wavelet transform, the wavelet form can generally select shannon wavelet, the total layer number is decomposed into 64 layers, and the specific envelope signal is compared and selected by adopting the results of the 7 th layer or the 9 th layer.
S23: and splicing the plurality of envelope signals according to a time sequence to form the image domain.
Specifically, since there is attenuation when the signal passes through the medium, it needs to be compensated in advance according to the attenuation law. After compensation, the signal envelopes are used as a line, and a plurality of signal envelopes are spliced according to a time sequence, so that an image can be formed.
In S2, image domain processing is further performed on the propagation of the difference frequency signal in the cobalt-rich encrusting medium to obtain a time vector of the difference frequency signal reaching the bottom of the cobalt-rich encrusting medium, which specifically includes the steps of:
s24: carrying out non-local filtering processing on the image domain;
non-local filtering processing is adopted, non-local redundant information in the image is utilized to reduce noise and enhance detail expression capability, and a foundation is provided for subsequent operations such as image edge detection and the like. Referring to fig. 4, the non-uniform filtering weight block size is 3, the search block size is 7, and the attenuation factor is 10, resulting in a processing result;
the non-local filtering is used for extracting the top-bottom arrival time vector, and because the filtering method has the capability of maintaining signal details and reducing noise, similar structural features can be found in an image domain, which is the key for reducing estimation errors.
S25: detecting the edge of the image domain by using a Sobel or Canny operator;
in edge detection, one template commonly used is the Sobel operator. The Sobel operator has two, one is used for detecting the horizontal edge; the other is to detect vertical edges. The Sobel operator weights the influence of the pixel position, so that the edge blurring degree can be reduced, and the effect is better.
Specifically, in one embodiment, the method for Sobel operator includes the following steps:
(1) carrying out primary edge detection on the filtered image by using a Sobel operator template;
(2) performing secondary edge detection on the primary edge image by using a Sobel operator template;
(3) and filtering edge points with small edge intensity and short edge chain of the secondary edge image by using edge filtering.
The image field edge represents the moment when the received signal changes abruptly, i.e. when the signal encounters a change in impedance during propagation, it is transmitted and reflected. And the acquisition of the bottom time vector is equivalent to the edges of the difference frequency signal in the image domain.
S26: performing disconnection connection processing on the image domain;
specifically, the connectivity is realized by adopting an operation such as expansion corrosion.
One example of the expansion corrosion adopts the following method:
(1) calculating identification discrete points in a single frame image, and acquiring an image frame of background identification discrete points;
(2) repeatedly expanding the image frame of the background identification discrete point to obtain an image with continuous edges;
(3) corroding the image subjected to repeated expansion for multiple times;
(4) removing the background of the corroded image, and marking a target of a closed edge;
s27: and detecting the optimal straight line in the image domain by utilizing probability accumulation Hough transformation, wherein the optimal straight line is used as a time vector when the difference frequency signal reaches the bottom of the cobalt-rich crust.
Referring to fig. 5, an optimal straight line is detected to obtain a processing result.
Specifically, the probability Hough transform is superior to other line detection operators by taking the minimum length and continuity constraints as criteria. The probabilistic Hough transform can detect the line segment with the smallest length along the start and end points as the best estimate of the bottom signal arrival time.
The line segment having the minimum length and continuity can be detected with respect to the probabilistic Hough transform. Specifically, the length of the segment is the shortest at the start and end points along the segment. In the method, all line segments which meet the conditions are detected as potential bottom time vectors as candidates through probabilistic Hough transformation. After all lines have been detected, overlapping segments and segments that are skewed more than 15 degrees from the top arrival time vector need to be discarded. After candidate determination, the final bottom time vector may be considered the bottom reflection as having the strongest reflected signal. In order to be able to determine this strongest reflection, it is necessary to define this reflection intensity as the sum of the energies of all envelope points lying on the line segment. The image is traversed horizontally to find the bottom reflection time vector. It should be noted that if there is coincidence between the line segments, the line segment with large energy is selected.
In one embodiment, the length of the minimum line segment may be set to 50cm and the maximum separation may be set to 12cm when in use. These parameters may ensure that long line segments with minor breaking characteristics may be detected.
Further, the original frequency signal is acquired in the first channel, the second channel needs to be processed before the difference frequency signal is acquired, wherein the original frequency signal channel is subjected to band-pass processing, a band-pass filter is used for carrying out noise suppression on the original frequency signal channel, so that the original frequency signal channel has a higher signal-to-noise ratio, the method for envelope extraction is determined by automatically calculating the signal-to-noise ratio parameter, the attaching degree of envelope calculation is ensured, and the accuracy of the peak value extraction position of the original frequency signal is convenient to improve.
In the present embodiment, the noise suppression is performed by the band-pass filtering processing in the step of band-pass filtering processing. Specifically, noise suppression is performed by designing a band-pass filter according to the characteristics of the acquired original frequency signal or difference frequency signal, and generally, the parameters of the band-pass filter can be set between 100Hz and 400 Hz.
Further, referring to fig. 6, a conventional physical property measuring apparatus performs measurement by using an insertion method, a transmission distance is fixed between a transmitting transducer and a receiving transducer, and time delays are measured before and after a sample with a known length is inserted, respectively, thereby obtaining a sound velocity value of the sample. However, the difference of the same cobalt-rich crust sample is small, and the average sound velocity can replace the layered sound velocity. The sound velocity measurement must use a physical property measurement device to obtain a sound velocity value. The principle of the property measuring apparatus is an insertion substitution method, that is, a change in arrival time before and after insertion of a sample is measured, and the change is obtained by a sound velocity calculation formula.
Therefore, the specific steps of acquiring the sound velocity of the difference frequency signal in the cobalt-rich crust medium in the embodiment are as follows:
s31: in a test water tank, measuring the time of a signal emitted by a transmitting transducer to reach a receiving transducer when a tested cobalt-rich incrustation sample is not inserted between the transmitting transducer and the receiving transducer;
s32: inserting the cobalt-rich crusting sample to be measured into a plane wave propagation path between a transmitting transducer and a receiving transducer, and measuring the time of a signal sent by the transmitting transducer reaching the receiving transducer through the cobalt-rich crusting sample to be measured;
s33: according to the change of the arrival time of the acoustic signal, measuring the sound velocity of the measured cobalt-rich crust sample, wherein the calculation formula of the sound velocity is as follows:
wherein, c0Is the sound velocity in water, c is the sound velocity in the measured cobalt-rich incrustation sample, and L is the thickness of the measured cobalt-rich incrustation sample; Δ T is the time change (T) of arrival at the receiving transducer of the signal before and after insertion into the cobalt rich crusting sample being measuredRear end-TFront side)。
Using the formula dthickness＝0.5v·(tbottom-ttop) The thickness of the cobalt-rich crust is calculated,
wherein d isthicknessIs the thickness of the cobalt-rich crust, v is the velocity in the cobalt-rich crust, tbottomIs the time vector, t, of the arrival of the difference frequency signal at the bottom of the cobalt-rich crusttopThe time vector of the original frequency signal reaching the top of the cobalt-rich crust;
the invention provides an image domain cobalt-rich crust thickness extraction device based on dual-channel information, aiming at an image domain cobalt-rich crust thickness extraction method based on dual-channel information, comprising the following steps:
the first processing module is used for acquiring a primary frequency signal through a first channel, and performing signal time domain processing on the primary frequency signal to acquire a time vector of the primary frequency signal reaching the top of the cobalt-rich crust;
the second processing module is used for acquiring a difference frequency signal through a second channel, carrying out image domain processing on the propagation of the difference frequency signal in the cobalt-rich crust medium and acquiring a time vector of the difference frequency signal reaching the bottom of the cobalt-rich crust;
and the thickness calculation module is used for combining the time vector of the primary frequency signal reaching the top of the cobalt-rich crust, the time vector of the differential frequency signal reaching the bottom of the cobalt-rich crust and the sound velocity of the differential frequency signal in the cobalt-rich crust medium to obtain the thickness of the cobalt-rich crust.
Further, the first processing module comprises:
the first band-pass filtering processing module is used for performing band-pass filtering processing on a first channel for acquiring the original frequency signal so as to inhibit noise;
the first envelope processing module is used for extracting an envelope signal of the original frequency signal;
the peak value detection module is used for extracting the peak value of the envelope signal;
and the moving average processing module is used for carrying out moving average processing on the peak value according to the working frequency of the original frequency signal, and taking the peak value after the average processing as a time vector of the original frequency signal reaching the top of the cobalt-rich crust.
Further, the second processing module includes:
the second band-pass filtering processing module is used for performing band-pass filtering processing on the second channel for acquiring the difference frequency signal so as to inhibit noise;
the energy compensation module is used for performing energy compensation on the difference frequency signal transmitted by the cobalt-rich crusting medium according to an attenuation rule;
the second envelope processing module is used for carrying out envelope extraction on the compensated difference frequency signal according to the signal-to-noise ratio calculation result on the premise of meeting the requirement to obtain an envelope signal;
the splicing module is used for splicing the plurality of envelope signals according to a time sequence to form an image domain;
the filtering processing module is used for carrying out non-local filtering processing on the image domain;
the edge detection module is used for detecting and processing the edge of the image domain by utilizing a Sobel or Canny operator;
the broken line processing module is used for carrying out broken line connection processing on the image domain;
and the optimal straight line detection module detects an optimal straight line in the image domain by utilizing probability accumulation Hough transformation, and the optimal straight line is used as a time vector when the difference frequency signal reaches the bottom of the cobalt-rich crust.
The device further comprises a speed measurement module, wherein in the test water tank, a measured cobalt-rich incrustation sample is inserted into a plane wave propagation path between the transmitting transducer and the receiving transducer, the time of a signal sent by the transmitting transducer reaching the receiving transducer through the measured cobalt-rich incrustation sample and the time of a signal not reaching the receiving transducer through the measured cobalt-rich incrustation sample are measuredCalculating the sound velocity in the measured cobalt-rich crust sample according to the change of the arrival time of the acoustic signal; the sound velocity calculation formula is specifically as follows:
wherein, c0Is the sound velocity in water, c is the sound velocity in the measured cobalt-rich incrustation sample, and L is the thickness of the measured cobalt-rich incrustation sample; at is the time change of the signal arriving at the receiving transducer before and after insertion into the measured cobalt-rich crusting sample.
The present invention has been described in terms of specific examples, which are provided to aid understanding of the invention and are not intended to be limiting. For a person skilled in the art to which the invention pertains, several simple deductions, modifications or substitutions may be made according to the idea of the invention.
Claims (7)
1. A method for extracting the thickness of cobalt-rich crusts in an image domain based on dual-channel information is characterized in that,
the method comprises the following steps:
s1: acquiring a primary frequency signal through a first channel, and performing signal time domain processing on the primary frequency signal to acquire a time vector of the primary frequency signal reaching the top of a cobalt-rich crust;
s2: acquiring a difference frequency signal through a second channel, and carrying out image domain processing on the propagation of the difference frequency signal in a cobalt-rich crusting medium to acquire a time vector of the difference frequency signal reaching the bottom of the cobalt-rich crusting medium;
the specific steps of forming the image domain in step S2 are as follows:
s21: performing energy compensation on the difference frequency signal transmitted in the cobalt-rich crust medium according to an attenuation rule;
s22: according to the signal-to-noise ratio calculation result, on the premise of meeting the requirement, envelope extraction is carried out on the compensated difference frequency signal to obtain an envelope signal;
s23: splicing the plurality of envelope signals according to a time sequence to form the image domain;
in step S2, the image domain processing is further performed on the propagation of the difference frequency signal in the cobalt-rich encrusting medium to obtain a time vector of the difference frequency signal reaching the bottom of the cobalt-rich encrusting medium, and the method specifically includes the steps of:
s24: carrying out non-local filtering processing on the image domain;
s25: detecting the edge of the image domain by using a Sobel or Canny operator;
s26: performing disconnection connection processing on the image domain;
s27: detecting an optimal straight line in the image domain by utilizing probability accumulation Hough transformation, wherein the optimal straight line is used as a time vector when the difference frequency signal reaches the bottom of the cobalt-rich crust;
s3: and combining the time vector of the primary frequency signal reaching the top of the cobalt-rich crust, the time vector of the differential frequency signal reaching the bottom of the cobalt-rich crust and the sound velocity of the differential frequency signal in the cobalt-rich crust medium to obtain the thickness of the cobalt-rich crust.
2. The method according to claim 1, wherein the step of performing signal time domain processing on the original frequency signal in S1 to obtain a time vector of the original frequency signal reaching the top of the cobalt-rich crust comprises the steps of:
s11: extracting an envelope signal of the original frequency signal;
s12: extracting a peak value of the envelope signal;
s13: and carrying out moving average processing on the peak value according to the working frequency of the original frequency signal, and taking the averaged peak value as a time vector of the original frequency signal reaching the top of the cobalt-rich crust.
3. The method of claim 1, wherein the step of bandpass filtering by which to perform noise suppression is included both before the primary frequency signal is acquired by the first channel and before the difference frequency signal is acquired by the second channel.
4. The method of claim 1, wherein the step of obtaining the speed of sound of the difference frequency signal in the cobalt-rich crust medium comprises:
s31: in a test water tank, measuring the time of a signal emitted by a transmitting transducer to reach a receiving transducer when a tested cobalt-rich incrustation sample is not inserted between the transmitting transducer and the receiving transducer;
s32: inserting the cobalt-rich crusting sample to be measured into a plane wave propagation path between a transmitting transducer and a receiving transducer, and measuring the time of a signal sent by the transmitting transducer reaching the receiving transducer through the cobalt-rich crusting sample to be measured;
s33: according to the change of the arrival time of the acoustic signal, measuring the sound velocity of the measured cobalt-rich crust sample, wherein the calculation formula of the sound velocity is as follows:
wherein, c0Is the sound velocity in water, c is the sound velocity in the measured cobalt-rich incrustation sample, and L is the thickness of the measured cobalt-rich incrustation sample; at is the time change of the signal arriving at the receiving transducer before and after insertion into the measured cobalt-rich crusting sample.
5. An image domain cobalt-rich crust thickness extraction device based on dual-channel information is characterized by comprising:
the first processing module is used for acquiring a primary frequency signal through a first channel, and performing signal time domain processing on the primary frequency signal to acquire a time vector of the primary frequency signal reaching the top of the cobalt-rich crust;
the second processing module is used for acquiring a difference frequency signal through a second channel, carrying out image domain processing on the propagation of the difference frequency signal in the cobalt-rich crusting medium and acquiring a time vector of the difference frequency signal reaching the bottom of the cobalt-rich crusting;
the second processing module comprises:
the second band-pass filtering processing module is used for performing band-pass filtering processing on the second channel for acquiring the difference frequency signal so as to inhibit noise;
the energy compensation module is used for carrying out energy compensation on the difference frequency signal transmitted by the cobalt-rich crusting medium according to an attenuation rule;
the second envelope processing module is used for carrying out envelope extraction on the compensated difference frequency signal according to a signal-to-noise ratio calculation result to obtain an envelope signal;
the splicing module is used for splicing the envelope signals according to a time sequence to form the image domain;
the filtering processing module is used for carrying out non-local filtering processing on the image domain;
the edge detection module is used for detecting the edge of the image domain by utilizing a Sobel or Canny operator;
the broken line processing module is used for carrying out broken line connection processing on the image domain;
the optimal straight line detection module is used for detecting an optimal straight line in the image domain by utilizing probability accumulation Hough transformation, and the optimal straight line is used as a time vector when the difference frequency signal reaches the bottom of the cobalt-rich crust;
and the thickness calculation module is used for combining the time vector of the primary frequency signal reaching the top of the cobalt-rich crust, the time vector of the differential frequency signal reaching the bottom of the cobalt-rich crust and the sound velocity of the differential frequency signal in the cobalt-rich crust medium to obtain the thickness of the cobalt-rich crust.
6. The apparatus of claim 5, wherein the first processing module comprises:
the first band-pass filtering processing module is used for performing band-pass filtering processing on the first channel for acquiring the original frequency signal so as to inhibit noise;
the first envelope processing module is used for extracting an envelope signal of the original frequency signal;
a peak detection module for extracting a peak value of the envelope signal;
and the moving average processing module is used for carrying out moving average processing on the peak value according to the working frequency of the original frequency signal, and taking the averaged peak value as a time vector of the original frequency signal reaching the top of the cobalt-rich crust.
7. The device as claimed in claim 5, comprising a speed measurement module, wherein the speed measurement module is used for measuring the time of a signal sent by the transmitting transducer reaching the receiving transducer through the cobalt-rich crust sample to be measured and the time of a signal not reaching the receiving transducer through the cobalt-rich crust sample to be measured by inserting the cobalt-rich crust sample to be measured on a plane wave propagation path between the transmitting transducer and the receiving transducer in the test water tank, and calculating the sound velocity in the cobalt-rich crust sample to be measured according to the change of the sound signal reaching time; the sound velocity calculation formula is specifically as follows:
wherein, c0Is the sound velocity in water, c is the sound velocity in the measured cobalt-rich incrustation sample, and L is the thickness of the measured cobalt-rich incrustation sample; at is the time change of the signal arriving at the receiving transducer before and after insertion into the measured cobalt-rich crusting sample.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5460034A (en) * | 1992-07-21 | 1995-10-24 | The United States Of America As Represented By The Secretary Of The Air Force | Method for measuring and analyzing surface roughness on semiconductor laser etched facets |
| JP5246801B2 (en) * | 2009-12-01 | 2013-07-24 | 八光オートメーション株式会社 | Sheet number inspection device |
| CN104539394A (en) * | 2015-01-09 | 2015-04-22 | 哈尔滨工程大学 | Pattern time delay coding underwater acoustic communication method based on parameter array |
| WO2018182360A1 (en) * | 2017-03-30 | 2018-10-04 | 한양대학교 산학협력단 | Thickness measurement apparatus, thickness measurement method, and thickness measurement program |
| CN109031462A (en) * | 2017-06-08 | 2018-12-18 | 道达尔公司 | Method for assessing the geophysical reconnaissance acquisition geometry on interested region |
| CN109036360A (en) * | 2018-06-29 | 2018-12-18 | 中国船舶重工集团公司第七〇五研究所 | A kind of truncation parameter battle array pressure-resistant acoustic filter and design method |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE4345242A1 (en) * | 1993-09-15 | 1995-04-06 | Endress Hauser Gmbh Co | Frequency conversion circuit for a radar distance measuring device |
-
2019
- 2019-08-13 CN CN201910743691.7A patent/CN110319797B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5460034A (en) * | 1992-07-21 | 1995-10-24 | The United States Of America As Represented By The Secretary Of The Air Force | Method for measuring and analyzing surface roughness on semiconductor laser etched facets |
| JP5246801B2 (en) * | 2009-12-01 | 2013-07-24 | 八光オートメーション株式会社 | Sheet number inspection device |
| CN104539394A (en) * | 2015-01-09 | 2015-04-22 | 哈尔滨工程大学 | Pattern time delay coding underwater acoustic communication method based on parameter array |
| WO2018182360A1 (en) * | 2017-03-30 | 2018-10-04 | 한양대학교 산학협력단 | Thickness measurement apparatus, thickness measurement method, and thickness measurement program |
| CN109031462A (en) * | 2017-06-08 | 2018-12-18 | 道达尔公司 | Method for assessing the geophysical reconnaissance acquisition geometry on interested region |
| CN109036360A (en) * | 2018-06-29 | 2018-12-18 | 中国船舶重工集团公司第七〇五研究所 | A kind of truncation parameter battle array pressure-resistant acoustic filter and design method |
Non-Patent Citations (2)
| Title |
|---|
| 参量阵浅剖仪及其信号预处理方法研究;祝鸿浩等;《现代电子技术》;20150501;第38卷(第9期);第48页右栏第2段-第50页倒数第2段，附图1、4-6 * |
| 大洋富钴结壳的超声测厚;潘文超等;《无损检测》;20181231;第40卷(第7期);第32页第4-第33页倒数第2段，附图1、4 * |
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