An apparatus and method for measuring the concentration and particle size of deep-sea mining pulp

Abstract

The present invention discloses a device and method for measuring the concentration and particle size of deep-sea mining pulp, which includes a main pipeline and an optical detection unit. A branch pipeline is arranged on the main pipeline. The optical detection unit includes a light source and an image acquisition module arranged corresponding to the light source. The light source and the image acquisition module are respectively located on both sides of the branch pipeline. An array ultrasonic sensor is also arranged on the main pipeline. The image acquisition module and the array ultrasonic sensor are both connected to a control system. The present invention combines multiple measurement methods, namely ultrasonic, light scattering and image methods, to jointly measure the concentration and particle size information of particulate matter in the coexistence of tubercle particles, sediment particles and seawater three-phase medium. The detection accuracy is high, and it can simultaneously detect the particulate matter concentration (particle volume fraction) and particle size information in the pulp. The detection result has high accuracy and fast detection speed.

Description

Technical Field

[0001] The present invention relates to the technical field of pulp flow rate and concentration detection, and particularly to a device and method for measuring the flow rate and concentration of deep-sea mining pulp. Background Art

[0002] Deep-sea mining is the collection of mineral resources from the seabed, including polymetallic nodules, sulfide deposits, cobalt-rich crusts, etc. During the process of deep-sea mining, a large amount of seabed sediments and other materials need to be processed, and the mixture generated in this process is usually called "pulp". Pulp is a fluid substance formed by mixing the mined nodule particles, sediment particles, etc. with seawater, which is convenient for transportation through pipelines to surface vessels or onshore treatment facilities.

[0003] During the process of collecting pulp and transporting it through pipelines to the treatment station, it is necessary to detect the particle concentration (i.e., the volume fraction of particles) and the particle size of the particles in the pulp.

[0004] Existing detection methods mostly use acoustic measurement methods for detection. This detection method mostly focuses on the concentration of single-phase fluid media or monodisperse particle flows, but cannot distinguish among seawater, nodule particles, and sediment particles. The ultrasonic method can measure particle sizes from the nanometer scale to the millimeter scale and is suitable for measuring sediments. However, when the nodule particle size reaches the centimeter scale, the particles have a large attenuation effect on ultrasound, and the ultrasound signal is attenuated a lot, resulting in inaccurate measurement results.

[0005] In the deep-sea mining environment, the volume fraction of particles in the pulp is high, the average distance between nodule ores is close to the particle size order of magnitude, and the multiple scattering and inter-particle coupling effects are very significant; the collected nodule particle diameters can reach several centimeters, while the associated sediment particles may be only dozens of micrometers or even smaller; this wide particle size range and multi-peak distribution pose a great challenge to ultrasonic measurement, and traditional ultrasonic measurement methods often cannot effectively meet the measurement requirements of pulp with such a wide particle size range and multi-peak distribution.

[0006] Therefore, there is an urgent need to provide a device and method for measuring the concentration and particle size of deep-sea mining pulp, which can quickly and accurately detect the concentration and particle size of the particles in the pulp to meet the operation requirements of deep-sea mining. Summary of the Invention

[0007] The purpose of the present invention is to solve the deficiencies in the prior art and provide a device and method for measuring the concentration and particle size of deep-sea mining pulp.

[0008] The object of the present invention is achieved by the following technical solutions: A deep-sea mining pulp concentration and particle size measuring device includes a main pipeline and an optical detection unit. A branch pipeline is provided on the main pipeline. The optical detection unit includes a light source and an image acquisition module arranged corresponding to the light source. The light source and the image acquisition module are respectively located on both sides of the branch pipeline. An array ultrasonic sensor is also provided on the main pipeline. The image acquisition module and the array ultrasonic sensor are both connected to a control system.

[0009] Preferably, a temperature sensor and a pressure sensor are also provided on the main pipeline.

[0010] Preferably, the image acquisition module includes an image sensor and a multispectral camera.

[0011] Preferably, a dilution pipeline is provided on the branch pipeline. The dilution pipeline is used to introduce water into the branch pipeline and dilute the pulp in proportion.

[0012] A deep-sea mining pulp concentration and particle size measuring method. When detecting the concentration of particulate matter in the pulp, the specific method is as follows:

[0013] S1: The array ultrasonic sensor emits ultrasonic pulses. The ultrasonic pulses pass through the pulp in the branch pipeline, and the sound velocity of the ultrasonic pulse signal is obtained through the receiving end of the array ultrasonic sensor and the sound attenuation coefficient , and the experimental complex wave number is calculated;

[0014] S2: Set the particle concentration as Φ, set the initial value of Φ, and calculate the theoretical complex wave number related to the particle concentration Φ;

[0015] S3: Compare the theoretical complex wave number with the experimental complex wave number, and calculate the target error related to the particle concentration Φ ;

[0016] Set the target error threshold, and adjust the value of Φ; when the target error is less than or equal to the target error threshold, the value of Φ at this time is the measured value of the particle concentration;

[0017] The particulate matter in the pulp includes nodule particles and sediment particles. When detecting the particle size of nodule particles in the pulp, the multispectral camera in the optical detection unit is used to perform backlight imaging on the nodule particles in the branch pipeline, and the projection contour of the nodule particulate matter is obtained to analyze the particle size of the nodule particles; and the probability of random distribution of particles at the detection position is described by Poisson distribution;

[0018] When detecting the particle size of sediment particles in pulp, it is measured by the multi-band extinction imaging method; the Levenberg–Marquardt data inversion algorithm is used to represent the overall detection data as a weighted superposition of the respective contributions of nodule particles and sediment particles, and then the least squares method is used to fit the data after the weighted superposition, so as to obtain the particle size distributions of nodule particles and sediment particles.

[0019] Preferably, in step S3, the harmony search algorithm is used to carry out the non-linear optimization inversion of the particle concentration, and the specific method is as follows:

[0020] N1. Generate a candidate solution vector Φ=(Φ1, Φ2,…, ΦD) of the particle concentration;

[0021] N2. For each component Φ of the solution vector Φ j , it is adjusted with probability P AR to obtain a new candidate solution Φ';

[0022] N3. Use the new candidate solution Φ' to recalculate the objective error;

[0023] N4. If the current objective error is less than the objective error of the previously selected candidate solution, then replace the previously selected candidate solution with the current candidate solution;

[0024] Through continuous iteration, until the particle concentration Φ that minimizes the objective error is found.

[0025] Preferably, when measuring the particle size of sediment particles by the multi-band extinction imaging method, it is calculated by the following formula:

[0026] ;

[0027] In the formula, D is the particle diameter, f k (λ) is the spectral response function, I λ is the spectral intensity, and E(λ, D, m) is the extinction coefficient of the particle group.

[0028] Preferably, the specific method of the Levenberg–Marquardt data inversion algorithm is as follows:

[0029] P1: Given the initial particle size D0;

[0030] P2: Calculate the objective function value ;

[0031] P3: Calculate the Jacobian matrix. For each frequency, calculate

[0032] ;

[0033] P4: Solve the normal equation: and calculate the updated amount of the particle size ;

[0034] P5: Update the parameters:

[0035] ;

[0036] P6: When G ( D k ) changes less than the set threshold, stop the iteration and output the parameter vector D obtained by the final inversion.

[0037] Preferably, during the process of detecting the particle size of the particulate matter in the pulp, when the adhesion of the particulate matter causes difficulties in image segmentation, convert the RGB color space to the Lab color space, and use the K-means clustering algorithm to segment the particle image to obtain the particle size information after adhesion.

[0038] The object of the present invention is achieved by the following technical solutions: The present invention combines multiple measurement methods of ultrasonic, light scattering and image methods to jointly measure the particulate matter concentration and particle size information of the coexistence of tubercle particles, sediment particles and seawater three-phase media. The detection accuracy is high, and it can simultaneously detect the particulate matter concentration (particle volume fraction) and particle size information in the pulp. The detection result has high accuracy and fast detection speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a schematic structural diagram of a deep-sea mining pulp concentration and particle size measuring device.

[0040] In the figure: 1, main pipeline; 2, array ultrasonic sensor; 3, branch pipeline; 4, temperature sensor; 5, optical detection unit; 6, dilution pipeline; 7, feed water pump. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0041] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art belong to the scope of protection of the present invention.

[0042] Those skilled in the art should understand that in the disclosure of the present invention, the orientation or positional relationships indicated by the terms "longitudinal", "transverse", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. are based on the orientation or positional relationships shown in the drawings. These are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, the above terms should not be construed as limiting the present invention.

[0043] It can be understood that the term "a" should be understood as "at least one" or "one or more". That is, in one embodiment, the number of an element can be one, while in other embodiments, the number of this element can be multiple. The term "a" should not be construed as limiting the quantity.

[0044] As Figure 1 shown, a device for measuring the concentration and particle size of deep - sea mining pulp includes a main pipeline 1 and an optical detection unit 5. A branch pipeline 3 is arranged on the main pipeline 1. The optical detection unit 5 includes a light source and an image acquisition module arranged corresponding to the light source. The light source and the image acquisition module are respectively located on both sides of the branch pipeline 3. An array ultrasonic sensor 2 is also arranged on the main pipeline 1. The image acquisition module and the array ultrasonic sensor 2 are both connected to a control system.

[0045] Among them, both ends of the branch pipeline 3 are connected to the main pipeline 1. When the pulp flows in the main pipeline 1, part of the pulp will enter from one end of the branch pipeline 3 and flow back into the main pipeline from the other end of the branch pipeline 3 after passing through the branch pipeline 3. The branch pipeline 3 is arranged downstream of the array ultrasonic sensor 2.

[0046] The array ultrasonic sensor 2 includes a number of multi - band ultrasonic transducers, and the multi - band ultrasonic transducers are arranged along the circumferential direction of the main pipeline. To overcome the influence of flow noise, the array ultrasonic sensor 2 uses pulse coding (such as a linear frequency modulation LFM signal) to improve the gain and obtains the attenuation and propagation time through decoding technology. Narrow - band filtering and phase - locked amplification are performed at the receiving end of the array ultrasonic sensor 2 to extract the pure amplitude and phase of each frequency component.

[0047] A temperature sensor 4 and a pressure sensor are also arranged on the main pipeline 1. The temperature sensor 4 and the pressure sensor are installed near the optical detection unit 5. The temperature sensor 4 and the pressure sensor are used to detect the temperature and pressure of seawater, for temperature compensation and pressure compensation of the detection results, and for correcting the sound speed and density parameters of seawater to ensure accurate model input.

[0048] The image acquisition module includes an image sensor and a multi - spectral camera.

[0049] In addition, a dilution pipeline 6 is provided on the branch pipeline 3. The dilution pipeline 6 is used to introduce water into the branch pipeline 3 and dilute the pulp in proportion. A water supply pump 7 is provided on the dilution pipeline 6, and the water supply pump 7 is used to control the flow rate of the dilution water.

[0050] The present invention combines multiple measurement methods using ultrasonic, light scattering, and image methods to jointly measure the concentration and particle size information of particulate matter in a three-phase medium coexisting with tubercle particles, sediment particles, and seawater.

[0051] The present invention also provides a method for measuring the concentration and particle size of deep-sea mining pulp. Among them, when measuring the pulp concentration, first dilute the pulp in the branch pipeline through the dilution pipeline, and dilute the sediment particle concentration in the branch pipeline to meet the single-scattering condition in proportion.

[0052] A small cavity is fixedly connected to the inner wall of the branch pipeline. The small cavity is filled with a reference particle liquid with a fixed concentration. Through a regular calibration program, its ultrasonic attenuation is continuously monitored as a reference to correct system drift and achieve calibration and self-check during long-term operation in the deep sea.

[0053] When detecting the concentration of particulate matter in the pulp, the specific method is as follows:

[0054] S1: The array ultrasonic sensor emits ultrasonic pulses. The ultrasonic pulses pass through the pulp in the branch pipeline, and the sound velocity of the ultrasonic pulse signal is obtained through the receiving end of the array ultrasonic sensor and the acoustic attenuation coefficient , and the experimental complex wave number k meas ( ω ) is calculated;

[0055] The experimental complex wave number k meas ( ω ) is calculated according to the following formula:

[0056] ;

[0057] S2: Set the particle concentration to Φ, set the initial value of Φ, and calculate the theoretical complex wave number related to the particle concentration Φ;

[0058] The calculation formula of the theoretical complex wave number is as follows:

[0059] ;

[0060] Among them, k 0 represents the reference wave number in pure seawater, is the correction term brought by the scattering and absorption effects of particles, which depends on the sound frequency ω and the particle concentration Φ.

[0061] S3: Compare the theoretical complex wave number with the experimental complex wave number k meas ( ω ) and calculate the target error related to the particle concentration Φ . The calculation formula of the target error is as follows:

[0062] ;

[0063] Set the target error threshold and adjust the value of Φ; when the target error is less than or equal to the target error threshold, the value of Φ at this time is the measured value of the particle concentration.

[0064] Among them, in step S3, the harmony search algorithm is used to carry out the non-linear optimization inversion of the particle concentration. The specific method is as follows:

[0065] N1. Generate a candidate solution vector Φ = (Φ1, Φ2,..., ΦD) of the particle concentration;

[0066] N2. For each component Φ j of the solution vector Φ, adjust it with probability P AR . The adjustment formula is:

[0067] ;

[0068] Among them, r is a random number uniformly distributed in [0, 1], and the new candidate solution Φ' is obtained accordingly; b w represents the bandwidth, which is the adjustment amplitude when adjusting each component of the solution vector. b w controls the adjustment step size.

[0069] Among them, P AR represents a probability calculation method. By generating a random number r and substituting it into the adjustment formula, make meet the P AR probability.

[0070] N3. Use the new candidate solution Φ' to recalculate the target error. The calculation formula is as follows:

[0071] ;

[0072] N4. If the current target error is less than the target error of the previously selected candidate solution, replace the previously selected candidate solution with the current candidate solution; through continuous iteration, until the particle concentration Φ that minimizes the target error is found.

[0073] When performing particle size measurement, the particulate matter in the pulp includes nodule particles and sediment particles. The nodule particles have a relatively large particle size, usually in the millimeter or centimeter range, or even larger, and the nodule particles can be recognized by the image sensor and multi-spectral camera in the optical detection unit. While the sediment particles have a relatively small particle size, usually in the micron range, or even smaller, and their size is equal to or less than the imaging resolution of the optical detection unit.

[0074] When detecting the particle size of nodule particles in the pulp, the multi-spectral camera in the optical detection unit is used to perform backlight imaging on the nodule particles in the branch pipeline. The multi-spectral camera performs backlight imaging on the particle group in the branch pipeline in the 0° direction, and obtains the projection contour of the nodule particulate matter to analyze the particle size of the nodule particles; and the probability of random distribution of particles at the detection position is described by Poisson distribution; its calculation formula is as follows:

[0075] ;

[0076] In the formula, C 2 is the corrected true particle concentration, C 1 is the particle concentration before correction, is the average particle diameter, σ is the variance.

[0077] When detecting the particle size of sediment particles in the pulp, the particle size of the sediment particles is smaller than the imaging resolution of the optical detection unit and cannot be resolved by a traditional optical camera; the present invention measures the sediment particles by the multi-band extinction imaging method; wherein, when measuring the particle size of the sediment particles by the multi-band extinction imaging method, it is calculated by the following formula:

[0078] ;

[0079] In the formula, D is the particle diameter, f k (λ) is the spectral response function, I λ is the spectral intensity, and E(λ, D, m) is the extinction coefficient of the particle group.

[0080] The Levenberg–Marquardt data inversion algorithm is adopted to represent the overall detection data as a weighted superposition of the respective contributions of nodule particles and sediment particles, and then the least squares method is used to fit the data after weighted superposition, so as to obtain the particle size distribution of nodule particles and sediment particles.

[0081] Among them, the specific method of the Levenberg–Marquardt data inversion algorithm is as follows:

[0082] P1: Given the initial particle diameter D0;

[0083] P2: Calculate the objective function value, and the calculation formula is as follows:

[0084] ;

[0085] P3: Calculate the Jacobian matrix. For each frequency, calculate

[0086] ;

[0087] P4: Solve the normal equation:

[0088] ;

[0089] And calculate the updated amount of the particle size ;

[0090] P5: Update the parameters:

[0091] ;

[0092] P6: When G ( D k ) changes less than the set threshold, stop the iteration and output the parameter vector D obtained by the final inversion.

[0093] In the present invention, for tubercle particles (with larger diameters), backlight imaging can highlight the outline of the particles, making them more obvious in the background. This helps to more accurately obtain the projected area and shape information of the tubercle particles, so as to accurately analyze their particle sizes. For sediment particles, the multi-band extinction imaging method can effectively distinguish particles of different sizes by measuring the light absorption or scattering at different wavelengths. Since sediment particles are very small, it is difficult to directly distinguish them by traditional imaging methods, while the extinction imaging method can indirectly determine the particle size distribution by analyzing the interaction between light and particles. The present invention combines two different technical means (backlight imaging and multi-band extinction imaging), which are respectively applicable to larger-sized tubercle particles and sediment particles in the micron scale or even smaller. This combination method broadens the detection range of particle sizes, enabling the system to handle a wide range of particle size distributions from millimeters to the micron scale, meeting the complex detections in actual operations.

[0094] During the process of detecting the particle size of particulate matter in pulp, when particle adhesion causes difficulties in image segmentation, the RGB color space is converted to the Lab color space, and the K-means clustering algorithm is used to segment the particle image to obtain the particle size information of the adhered particles. The color information in the RGB color space is easily affected by changes in lighting conditions, while the Lab color space performs better in this regard. By converting to the Lab color space, the interference caused by uneven or changing lighting can be reduced to a certain extent, improving the accuracy of image segmentation. The K-means clustering algorithm performs well when dealing with data with a relatively concentrated color distribution. Since the Lab color space can better capture color differences, applying the K-means clustering in this color space can more effectively identify and separate adhered particulate matter, thus improving the accuracy of particle size analysis. For samples with complex compositions such as pulp, the colors, shapes, and sizes of particles can vary greatly. By using the Lab color space in combination with the K-means clustering algorithm, these changes can be more flexibly addressed, improving the ability to identify particles with different characteristics, and thus accurately obtaining the particle size information of adhered particulate matter.

[0095] The present invention combines multiple measurement methods, namely ultrasonic, light scattering, and image methods, to jointly measure the concentration and particle size information of particulate matter coexisting in tubercle particles, sediment particles, and seawater three-phase media. The detection accuracy is high, and it can simultaneously detect the particulate matter concentration (particle volume fraction) and particle size information in pulp, with high detection accuracy and fast detection speed.

[0096] The present invention is not limited to the above-mentioned optimal implementation manner. Anyone can obtain various other forms of products under the inspiration of the present invention. However, no matter what changes are made in its shape or structure, as long as it has a technical solution identical or similar to that of this application, it falls within the protection scope of the present invention.

Claims

1. A method for measuring slurry concentration and particle size in deep sea mining, characterized in that: It comprises a deep-sea mining slurry concentration and particle size measuring device, which comprises a main pipeline and an optical detection unit, wherein a branch pipeline is arranged on the main pipeline, and the optical detection unit comprises a light source and an image acquisition module arranged corresponding to the light source, wherein the light source and the image acquisition module are respectively arranged on both sides of the branch pipeline; an array ultrasonic sensor is also arranged on the main pipeline; the image acquisition module and the array ultrasonic sensor are both connected to a control system; The method for measuring the concentration and particle size of deep-sea mining slurry is as follows when detecting the concentration of particles in the slurry: S1: The array ultrasonic sensor emits ultrasonic pulses, which pass through the slurry in the branch pipe. The sound velocity of the ultrasonic pulse signal is obtained through the receiving end of the array ultrasonic sensor. Sound attenuation coefficient , and calculate the experimental complex wave number; S2: setting the particle concentration to Φ, setting the initial value of Φ, and calculating the theoretical complex wave number related to the particle concentration Φ; S3: Compare the theoretical complex wave number with the experimental complex wave number and calculate the target error related to the particle concentration Φ ; The nonlinear optimization inversion of particle concentration is carried out using the harmony search algorithm. The specific method is as follows: N1, generate candidate solution vector Φ=(Φ 1, Φ 2,…, Φ D) for particle concentration; N2, for each component Φ of the solution vector Φ j , with probability P AR Make adjustments to obtain a new candidate solution Φ'; N3. Recalculate the target error using the new candidate solution Φ'; N4. If the current target error is less than the target error of the last selected candidate solution, the last candidate solution is replaced with the current candidate solution; Through continuous iteration, the particle concentration Φ that minimizes the target error is found; Set the target error threshold and adjust the value of Φ; when the target error When it is less than or equal to the target error threshold, the value of Φ is the measured value of the particle concentration; The particles in the ore slurry include nodule particles and sediment particles. When detecting the particle size of nodule particles in the ore slurry, the multispectral camera in the optical detection unit is used to perform backlight imaging of the nodule particles in the branch pipe, and the projection profile of the nodule particles is obtained to analyze the particle size of the nodule particles; and the probability of random distribution of particles at the detection position is described by Poisson distribution; in the process of detecting the particle size of particles in the ore slurry, when the particles are adhered and the image segmentation is difficult, the RGB color space is converted to the Lab color space, and the K-means clustering algorithm is used to segment the particle image to obtain the particle size information of the adhered particles; When detecting the particle size of sediment particles in the slurry, the multi-band extinction imaging method is used for measurement; the Levenberg–Marquardt data inversion algorithm is used to express the overall detection data as a weighted superposition of the contributions of nodule particles and sediment particles, and then the least squares method is used to fit the weighted superposition data to obtain the particle size distribution of nodule particles and sediment particles; When the particle size of sediment particles is measured by multi-band extinction imaging, it is calculated using the following formula: ； Where D is the particle diameter, f k (λ) is the spectral response function, I λ is the spectral intensity, and E(λ, D, m) is the extinction coefficient of the particle group.

2. A method for measuring slurry concentration and particle size in deep sea mining according to claim 1, characterized in that: The main pipeline is also provided with a temperature sensor and a pressure sensor.

3. A method for measuring slurry concentration and particle size in deep sea mining according to claim 1, characterized in that: The image acquisition module includes an image sensor and a multispectral camera.

4. A method for measuring slurry concentration and particle size in deep sea mining according to claim 1, characterized in that: A dilution pipeline is provided on the branch pipeline, and the dilution pipeline is used to introduce water into the branch pipeline and dilute the slurry in proportion.

5. A method for measuring slurry concentration and particle size in deep sea mining according to claim 1, characterized in that: The specific method of the Levenberg–Marquardt data inversion algorithm is as follows: P1: given initial particle size D0; P2: Calculate the objective function value ; P3: Calculate the Jacobian matrix. For each frequency, calculate ； P4: Solve the normal equation: and calculate the updated amount of particle size ; P5: Update parameters: ； P6: When G ( D k ) is less than the set threshold, the iteration is stopped and the parameter vector D obtained in the final inversion is output.

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