Particle uniform distribution adjustment feedback method based on microwave radar

Abstract

The invention discloses a microwave radar-based particle uniform distribution adjustment feedback method, and relates to the technical field of ore particle size detection, and the feedback method comprises the following specific steps: S100, system construction and equipment installation: forming a linkage system by a vibration feeding motor, a feeding tray, a hopper, a belt conveyor, an FMCW radar and an image shooting assembly, by introducing combined application of the FMCW radar and the MVDR beam forming method, accurate positioning and speed measurement of ore particles in a three-dimensional space are achieved, the accuracy and real-time performance of ore particle distribution adjustment are improved, the FMCW radar emits triangular measurement waves and receives reflected waves, radar data are processed by combining the MVDR beam forming method, and the accuracy and real-time performance of ore particle distribution adjustment are improved. The position coordinates and the speed information of the ore particles on the X axis, the Y axis and the Z axis can be accurately calculated, accurate data support is provided for follow-up adjustment of the particle spacing, and the whole adjustment process is more intelligent and automatic.

Description

Technical Field

[0001] The invention relates to the technical field of ore particle size detection, and in particular to a particle uniform distribution adjustment feedback method based on microwave radar. Background Art

[0002] In the ore processing industry, the uniform distribution of ore particles is crucial to the subsequent production process. The size, shape and distribution density of ore particles directly affect the efficiency and quality of crushing, screening and grinding. With the continuous development of industrial automation, how to use advanced technical means to achieve uniform distribution adjustment of ore particles has become an urgent problem to be solved. Microwave radar technology, as a non-contact measurement method, has shown great application potential in the field of ore particle detection and distribution adjustment due to its high precision and strong real-time performance. FMCW radar has become a key component in the ore particle distribution adjustment system with its high-resolution distance and speed measurement capabilities.

[0003] The traditional method of adjusting the distribution of ore particles mainly relies on manual observation and manual adjustment. This method is not only inefficient, but also difficult to ensure the accuracy and consistency of the adjustment. In addition, the traditional method is easily affected by human factors, resulting in poor distribution adjustment of ore particles. In recent years, although some automatic adjustment systems based on sensor technology have been proposed, these systems often have problems such as insufficient measurement accuracy, poor real-time performance, and sensitivity to environmental conditions. It is difficult to meet the high requirements of the ore processing industry for uniform distribution of particles. Especially when dealing with complex and changeable ore particles, traditional technologies often cannot provide stable and reliable adjustment solutions. Therefore, developing a method that can adjust the uniform distribution of ore particles in real time, accurately and automatically is of great significance to improving ore processing efficiency and quality.

[0004] Therefore, developing a microwave radar-based particle uniform distribution adjustment feedback method will greatly improve the automation level and production efficiency of the ore processing industry, and provide strong support for the intelligent transformation of the ore processing industry. Summary of the invention

[0005] The purpose of the present invention is to make up for the shortcomings of the prior art and provide a method for adjusting the uniform distribution of particles based on microwave radar. The method realizes real-time monitoring and precise control of ore particles during the transportation process by comprehensively using FMCW radar technology, MVDR beamforming method and edge detection algorithm. It can not only automatically adjust the spacing of ore particles on the belt conveyor to ensure their uniform distribution and avoid stacking, but also accurately measure the particle shape and particle size of ore particles, providing an efficient and intelligent solution for the ore processing industry.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a feedback method for adjusting uniform distribution of particles based on microwave radar, wherein the specific steps of the feedback method are:

[0007] S100, system construction and equipment installation: The vibrating feeder motor, feeder tray, hopper, belt conveyor, FMCW radar and image camera assembly form a linkage system. The FMCW radar is installed just above the junction of the feeder tray and the belt conveyor. The image camera assembly is aligned with the image acquisition area. After the installation is completed, the lines are connected and comprehensive debugging is carried out;

[0008] S200, ore conveying and radar start: Pour the ore to be tested into the hopper, start the vibrating feeder motor and the belt conveyor in sequence, so that the ore is conveyed from the hopper to the belt conveyor through the feeder tray. At the same time, the FMCW radar starts to work, emitting triangular measurement waves and receiving reflected waves, and continuously recording the time and frequency information of the emitted and received waves;

[0009] S300, radar data processing and analysis: FMCW radar compares the transmitted wave and the reflected wave to calculate the frequency difference, calculates the Doppler frequency, distance and speed parameters of the ore particles according to the Doppler effect related formula, and further processes the radar data using the MVDR beamforming method. Based on the antenna layout, the positioning and speed measurement of the target object on three axes are achieved, and a two-dimensional reflection point vector diagram is generated;

[0010] S400, reflection point analysis and spacing adjustment: obtain a two-dimensional reflection point vector diagram based on the measurement results, classify the reflection points and identify the point groups, calculate the point group centroid and the Y-axis spacing WY between each point group i , set the initial vibration frequency of the vibrating feeder motor and the maximum particle size of the ore set by the user, according to the information of the difference between the current minimum Y-axis spacing and the target spacing, adjust the vibration frequency of the vibrating feeder motor through the vibration frequency adjustment formula until the minimum Y-axis spacing meets the requirements, set the initial speed of the belt conveyor motor and the X-axis spacing WX set by the user i Minimum requirement: according to the particle speed deviation and spacing deviation in the X-axis direction, the belt conveyor speed is adjusted through the belt conveyor speed adjustment formula to minimize the spacing of the ore in the X-axis direction on the belt conveyor to meet the requirements;

[0011] S500, real-time adjustment of particle spacing: The reflection point analysis and spacing adjustment calculation results are converted into analog signals by the DAC inside the FMCW radar module and transmitted to the controllers of the vibrating feeder motor and the belt conveyor respectively. The controller adjusts the motor vibration frequency and speed according to the signal to control the spacing of the ore particles in the Y-axis direction and the X-axis direction until the ore particles are not stacked in the belt conveyor image acquisition area;

[0012] S600, image acquisition and analysis: monitors the image acquisition area of ​​the belt conveyor. When the distance between ore particles meets the non-stacking condition, the image camera component is triggered to acquire images according to preset parameters and transmit the images to the analysis system. The analysis system uses edge detection algorithms to outline the contours of ore particles and calculate the particle shape and size.

[0013] Furthermore, in the S100, the FMCW radar in the system construction and equipment installation is designed with 6 receiving antennas rx and 3 transmitting antennas tx. The transmitting antenna tx transmits a triangular measurement wave. The frequency of the transmitted microwave moves from low frequency to high frequency, reaches the highest point and then moves downward.

[0014] Furthermore, in the S300, the Doppler frequency, distance and speed parameters of the ore particles are obtained according to the Doppler effect related formula in the radar data processing and analysis. The frequency formula is: 2f D =Δf1-Δf2, where f D It represents the Doppler frequency generated during the movement of the target object. Δf1 and Δf2 are the frequency differences between the received wave and the transmitted wave under different conditions. The distance formula is: R represents the distance of the target object, that is, the straight-line distance between the radar and the target object, c represents the speed of light, Δf1 and Δf2 are the frequency differences between the received wave and the transmitted wave at different times, and K is the slope of the rising frequency of the transmitted wave; speed formula: v represents the speed of the target object, λ is the wavelength of the transmitted wave, and Δf1 and Δf2 are the frequency differences between the received wave and the transmitted wave at different times.

[0015] Furthermore, the specific steps of applying the MVDR beamforming method in radar data processing and analysis in S300 are as follows:

[0016] (1) Based on the layout of 6 receiving antennas placed at equal intervals of λ / 2 on the Y axis, the receiving antenna of the FMCW radar simultaneously receives the reflected wave signals from the ore particles, pre-processes the original signals collected by the receiving antenna, and converts the analog signals into digital signals;

[0017] (2) According to the MVDR algorithm principle, the covariance matrix is ​​constructed, the weight vector is calculated, and the preprocessed receiving antenna signal and the calculated weight vector are weighted summed;

[0018] (3) Taking advantage of the fact that the transmitting antennas are placed at equal intervals of 2λ on the X-axis, the MVDR beamforming method is used to locate and measure the ore particle targets in the X-axis direction. By processing the received signals of each antenna in the X-axis direction, the position information and related parameters of the ore particles in the X-axis direction are obtained;

[0019] The measurement data obtained by the MVDR beamforming method in the X-axis and Y-axis directions are fused and processed, combined with the calculated distance information between the ore particles and the radar, and the spatial geometric relationship is used to calculate the position coordinates of the ore particles in three-dimensional space (X-axis, Y-axis, and Z-axis).

[0020] Furthermore, in the above S400, the vibration frequency f of the vibration feeder motor is adjusted by the vibration frequency adjustment formula in the reflection point analysis and spacing adjustment. vib , let the difference between the current Y-axis particle spacing and the target spacing be ΔWY, the time interval be Δt, and the distance between the target particle and the radar be R new , the frequency adjustment coefficient related to the ore characteristics is Y, and the formula is:

[0021] Furthermore, in the above S400, the speed v of the belt conveyor is adjusted by the belt conveyor speed adjustment formula in the reflection point analysis and spacing adjustment. belt , let the particle velocity deviation in the X-axis direction be ΔVX, the particle spacing deviation in the X-axis direction be ΔWX, and the distance between the target particle and the radar be R new , the belt conveyor speed adjustment coefficient is δ, and the formula is:

[0022] Furthermore, the specific steps of using edge detection algorithm to outline the contour of ore particles in S600 image acquisition and analysis are as follows:

[0023] (1) Determine the noise level N of the image level , calculate the new Gaussian filter standard deviation σ′ according to the formula: σ′=δN level +∈, where δ and ∈ are parameters determined empirically;

[0024] (2) The preprocessed image I processed Substitute the calculated new standard deviation σ′ into the Gaussian filter function h to obtain the Gaussian filtered image I filtered , the formula is: filtered =h(I processed ,σ′);

[0025] (3) For the filtered image I filtered Perform gradient calculation to obtain the gradient magnitude and direction of each pixel;

[0026] (4) performing non-maximum suppression in the gradient magnitude image according to the calculated gradient direction;

[0027] (5) Set two thresholds: high threshold T high and low threshold T low , traverse the image after non-maximum suppression, for the gradient amplitude greater than the high threshold Thigh The pixel point is marked as a strong edge pixel point, and the pixel point with a gradient amplitude less than the low threshold T low For pixels whose gradient amplitude is between the high threshold and the low threshold, they are marked as non-edge pixels and discarded. For pixels whose gradient amplitude is between the high threshold and the low threshold, if they are adjacent to strong edge pixels, they are marked as edge pixels, otherwise they are discarded.

[0028] (6) After the above processing, the edge image I is finally obtained. edge , outlining the contours of the ore particles.

[0029] Furthermore, in S600, the high threshold T in image acquisition and analysis high and low threshold T low The frequency of each gray level in the image is counted to obtain the gray level histogram H(i), where i represents the gray level and H(i) represents the frequency of the pixel with gray level i. The high threshold T is determined. high , calculate the average gray value μ of the image, the formula is: Where 255 is the maximum gray level assuming that the image is an 8-bit grayscale image. The standard deviation σ of the grayscale histogram is calculated as follows: High threshold T high The calculation formula is: high =μ+k1×σ, where k1 is the coefficient, the low threshold T low Determination of the low threshold T low The calculation formula is: low =k2×T high , where k2 is the coefficient.

[0030] Furthermore, in the calculation of particle shape and particle size in the image acquisition and analysis in S600, assuming that the perimeter of the ore particle is P, the area is A, the major axis length is I, and the minor axis length is S, the calculation formula of the particle shape parameter F is: The calculation formula of particle size D is:

[0031] Compared with the prior art, this method for adjusting the uniform distribution of particles based on microwave radar has the following beneficial effects:

[0032] 1. The present invention realizes the precise positioning and velocity measurement of ore particles in three-dimensional space by introducing the combined application of FMCW radar and MVDR beamforming method, thereby improving the accuracy and real-time performance of ore particle distribution adjustment. By transmitting triangular measurement waves and receiving reflected waves by FMCW radar and processing radar data in combination with the MVDR beamforming method, the position coordinates and velocity information of ore particles on the X, Y, and Z axes can be accurately calculated, which not only provides accurate data support for the subsequent adjustment of particle spacing, but also makes the entire adjustment process more intelligent and automated.

[0033] 2. The present invention achieves the goal of uniform distribution of ore particles on the belt conveyor through the coordinated work of the vibrating feeder motor and the belt conveyor, monitors and analyzes the ore particles in real time through the FMCW radar, calculates the particle distance based on the reflection point information, and controls the vibrating feeder motor and the belt conveyor in real time through the vibration frequency adjustment formula and the belt conveyor speed adjustment formula. This not only effectively solves the problems of ore particle stacking and uneven distribution, but also improves the stability and safety of the entire ore processing process. At the same time, the real-time feedback mechanism also has strong adaptability and flexibility, and can be flexibly adjusted and optimized according to different ore characteristics and processing requirements.

[0034] Other advantages, objectives and features of the present invention will be set forth in part in the following description and, in part, will be apparent to those skilled in the art based on an examination of the following or may be taught from the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0036] Figure 1 A flow chart of a feedback method for adjusting uniform distribution of particles based on microwave radar;

[0037] Figure 2 This is a schematic diagram of the linkage system equipment layout;

[0038] Figure 3 This is a schematic diagram of the principle of ore particle transportation and spacing adjustment;

[0039] Figure 4 This is the relationship diagram between the frequency changes of radar transmission and reception waves;

[0040] Figure 5 Calculate auxiliary diagrams for radar transmission and reception wave frequencies;

[0041] Figure 6 Schematic diagram for radar antenna layout and target positioning measurement;

[0042] Figure 7 It is a reflection point vector diagram and a schematic diagram of spacing calculation;

[0043] Figure 8 This is the control signal flow diagram of the linkage system.

[0044] In the figure: 1. feeding tray; 2. ore particles; 3. conveyor belt; 4. hopper; 5. vibrating feeder motor; 6. FMCW radar; 7. image camera assembly; 8. transmitting electromagnetic wave; 9. transmitting wave; 10. receiving wave; 11. the sum of the frequencies of receiving wave 10 and transmitting wave 9. DETAILED DESCRIPTION

[0045] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation mode, structure, characteristics and effects of the present invention are described in detail below in combination with the accompanying drawings and preferred embodiments.

[0046] Embodiment 1

[0047] Copper ore dressing plant ore particle size adjustment

[0048] In a large copper ore dressing plant, with the increase of mining depth and the change of ore properties, the traditional particle size control method can hardly meet the production needs, and the concentrate grade and recovery rate fluctuate greatly. To solve this problem, a particle uniform distribution adjustment feedback method based on microwave radar is introduced.

[0049] System construction and equipment installation: The technicians of the ore dressing plant strictly follow the invention requirements to assemble the vibrating feeder motor, feeder tray, hopper, belt conveyor, FMCW radar and image camera components. Figure 2 ), the operation process is that the ore to be tested is put into the hopper, the vibrating feeder motor is started, and the ore in the hopper is transported by the belt conveyor through the feeding tray. The whole process is monitored by the FMCW radar. The FMCW radar controls the frequency of the vibrating feeder motor to adjust the distance between the ore particles, ensuring that there is no overlap between the ore particles in the image sampled by the image sensor. The vibrating feeder motor controls the Y-axis spacing between the ore particles in the feeding tray, and controls the speed of the belt conveyor to adjust the X-axis spacing between the ore particles (such as Figure 3 ), the radar is designed with 6 receiving antennas rx and 3 transmitting antennas tx. The transmitting antenna tx transmits a triangular measurement wave. The frequency of the transmitted microwave moves from low frequency to high frequency, reaches the highest point and then moves downward. The frequency change is like a triangular curve. When the transmitted electromagnetic wave encounters ore particles and is reflected to the receiving antenna, (such as Figure 4), when installing the FMCW radar, high-precision measuring tools are used to ensure that it is located directly above the junction of the feed tray and the belt conveyor, and the deviation is controlled within a very small range; the image camera component is aligned with the image acquisition area on the belt conveyor through professional calibration equipment to ensure that the acquisition field of view covers the key area. After completing the hardware installation, the technicians carefully connect the lines, conduct conductivity tests and signal interference inspections for each line, and then comprehensively debug the entire system to check the operating status of each device, including whether the motor starts and stops smoothly, whether the radar signal transmission and reception are normal, and whether the image camera component can form a clear image, to ensure the normal operation of all parts of the system.

[0050] Ore transportation and radar start-up: The copper ore to be tested is transported from the mining area to the hopper, and the ore is slowly poured into the hopper by a loader to avoid uneven ore accumulation affecting the feeding effect. The operator starts the vibrating feeder motor and belt conveyor in turn in the control room. When the motor starts, pay close attention to its starting current and speed changes to ensure smooth start-up of the equipment. As the equipment runs, the ore is evenly transported from the hopper to the belt conveyor through the feeding tray. At the same time, the FMCW radar starts working, emitting triangular measurement waves and receiving reflected waves. The high-precision clock and frequency measurement module inside the radar continuously records the time and frequency information of the transmitted and received waves to provide raw data for subsequent data analysis.

[0051] The signal processing chip built into the FMCW radar uses the Doppler effect-related formula to derive the Doppler frequency, distance and speed parameters of the ore particles. The frequency formula is: 2f D =Δf1-Δf2, where f D It represents the Doppler frequency generated during the movement of the target object. Δf1 and Δf2 are the frequency differences between the received wave and the transmitted wave under different conditions. The distance formula is: R represents the distance of the target object, that is, the straight-line distance between the radar and the target object, c represents the speed of light, Δf1 and Δf2 are the frequency differences between the received wave and the transmitted wave at different times, and K is the slope of the rising frequency of the transmitted wave; speed formula: v represents the speed of the target object, λ is the wavelength of the transmitted wave, Δf1 and Δf2 are the frequency differences between the received wave and the transmitted wave at different times. When the MVDR beamforming method is used, based on the layout of 6 receiving antennas placed at equal intervals of λ / 2 in the Y-axis direction, the receiving antennas simultaneously receive the reflected wave signals from the ore particles. First, the original analog signal collected by the receiving antenna is preprocessed and converted into a digital signal through the analog-to-digital conversion module. Then, the covariance matrix is ​​constructed according to the principle of the MVDR algorithm, and the weight vector is calculated using complex mathematical operations. After that, the preprocessed receiving antenna signal is compared with the calculated weight vector. The weighted summation is performed, and the ore particle target in the X-axis direction is located and measured by using the characteristic that the transmitting antennas are placed at equal intervals of 2λ in the X-axis direction. The position information and related parameters of the ore particles in the X-axis direction are obtained by processing the received signals of each antenna in the X-axis direction. Finally, the measurement data obtained by the MVDR beamforming method in the X-axis and Y-axis directions are fused and processed. Combined with the calculated distance information between the ore particles and the radar, the spatial geometric relationship is used to accurately calculate the position coordinates of the ore particles in three-dimensional space (X-axis, Y-axis, Z-axis), and generate a two-dimensional reflection point vector diagram (such as Figure 6 ).

[0052] Reflection point analysis and spacing adjustment: According to the two-dimensional reflection point vector diagram, (such as Figure 7 ) The system's built-in analysis software intelligently classifies reflection points and identifies point groups, and uses algorithms to calculate the centroid of point groups and the Y-axis spacing WY between each point group. i According to the long-term production experience and subsequent mineral processing requirements, the ore dressing plant sets the initial vibration frequency of the vibrating feeder motor and the maximum particle size of the copper ore set by the user. The analysis software adjusts the vibration frequency of the vibrating feeder motor according to the information of the difference between the current minimum spacing in the Y-axis direction and the target spacing using the vibration frequency adjustment formula. The formula is: The frequency adjustment coefficient Y related to the ore characteristics is determined by experimental testing of a large number of copper ore samples, the time interval Δt is accurately measured by the system clock, and the distance R between the target particle and the radar is new The radar measurement data is updated in real time. At the same time, the initial speed of the belt conveyor motor and the user-set X-axis spacing WX are set. i The minimum requirement is to adjust the speed of the belt conveyor according to the particle speed deviation and spacing deviation in the X-axis direction through the belt conveyor speed adjustment formula. The formula is: The belt conveyor speed adjustment coefficient δ is also optimized through experimental testing to ensure the accuracy and stability of the adjustment, so that the copper ore on the belt conveyor has the minimum X-axis spacing to meet the requirements (such as Figure 8 ).

[0053] Real-time adjustment of particle spacing: The calculation results of reflection point analysis and spacing adjustment are converted into analog signals by the internal DAC of the FMCW radar module and transmitted to the controllers of the vibrating feeder motor and the belt conveyor respectively. The controller adopts advanced intelligent control algorithms to accurately adjust the motor vibration frequency and speed according to the received analog signals. During the adjustment process, the distribution of ore particles on the belt conveyor is continuously monitored, and the control parameters are optimized in real time through the feedback mechanism to control the spacing of copper ore particles in the Y-axis and X-axis directions until the ore particles are not stacked in the image acquisition area of ​​the belt conveyor, thereby ensuring uniform distribution of ore particles.

[0054] Image acquisition and analysis: The system monitors the image acquisition area of ​​the belt conveyor in real time through the image sensor. When the distance between the copper ore particles meets the non-stacking condition, the image camera component is triggered to acquire images according to the preset parameters. After the image is acquired, the image is transmitted to the analysis system through a high-speed data transmission line. The analysis system first uses the edge detection algorithm to outline the ore particle contour and determine the image noise level N. level , calculate the new Gaussian filter standard deviation σ′ according to the formula: σ′=δN level +∈, preprocessed image I processed Substitute the calculated new standard deviation σ′ into the Gaussian filter function h to obtain the Gaussian filtered image I filtered , the formula is: filtered =h(I processed ,σ′), for the filtered image I filtered Perform gradient calculation to obtain the gradient magnitude and direction of each pixel. According to the calculated gradient direction, perform non-maximum suppression in the gradient magnitude image and set two thresholds: high threshold T high and low threshold T low , high threshold T low =k2×T high The calculation formula is: high =μ+k1×σ, low threshold T low The calculation formula is: low =k2×T high , traverse the image after non-maximum suppression, for the gradient amplitude greater than the high threshold T high The pixel point is marked as a strong edge pixel point, and the pixel point with a gradient amplitude less than the low threshold T lowPixels with gradient amplitude between the high threshold and the low threshold are marked as non-edge pixels and discarded. For pixels whose gradient amplitude is between the high threshold and the low threshold, if they are adjacent to strong edge pixels, they are marked as edge pixels, otherwise they are discarded to obtain edge images and outline the contours of stone particles. At the same time, the high threshold and the low threshold are determined according to the grayscale histogram obtained by statistically analyzing the grayscale frequency of the image. The particle shape and particle size are calculated according to the perimeter, area, major axis length and minor axis length of the ore particles using the particle shape parameter calculation formula and the particle size calculation formula. The formula is: The analysis system compares the calculation results with the quality standards of the ore dressing plant and generates a detailed analysis report, providing accurate data support for the parameter adjustment of the subsequent ore dressing process. In this way, the pertinence and effectiveness of the ore dressing process are improved, the concentrate grade and recovery rate are stabilized, the production cost is reduced, and the economic benefits of the ore dressing plant are improved.

[0055] In summary, in the application scenario of copper ore dressing plant, the feedback method based on microwave radar particle uniform distribution adjustment shows significant advantages. By accurately building the system, using FMCW radar to collect data and processing it through complex algorithms, the accurate acquisition of ore particle parameters is achieved. Based on these data, specific formulas are used to adjust the operating parameters of the vibrating feeder motor and belt conveyor, effectively controlling the spacing between ore particles and avoiding stacking. Finally, through image acquisition and analysis, the particle shape and size data are obtained, providing key support for subsequent mineral processing. This method stabilizes the concentrate grade and recovery rate, reduces production costs, and improves the overall economic benefits and market competitiveness of the dressing plant.

[0056] Embodiment 2:

[0057] Optimization of stone particles in building stone processing plants

[0058] In a building stone processing plant, as the construction industry's requirements for stone quality continue to increase, the existing stone particle control technology cannot meet market demand, causing the product to be at a disadvantage in market competition. In order to improve product quality, a microwave radar-based particle uniform distribution adjustment feedback method was introduced.

[0059] System construction and equipment installation: According to the invention requirements, the processing plant technicians built a linkage system with the vibrating feeder motor, feed tray, hopper, belt conveyor, specially designed FMCW radar and image camera components. When installing the FMCW radar, a level and rangefinder were used to ensure the accuracy of its installation position. The image camera component was aligned with the image acquisition area through professional image calibration software. After completing the equipment installation, the technicians carefully connected the lines and checked each connection point to prevent looseness and false connection. Subsequently, the entire system was fully debugged, including checking whether the vibration amplitude of the motor meets the requirements, whether the signal strength of the radar is stable, and whether the image clarity of the image camera component meets the standards, to ensure the normal operation of all parts of the system.

[0060] Ore transportation and radar start-up: The mined stones to be processed are transported to the hopper by transport vehicles, and poured into the hopper by crane. The operator starts the vibrating feeder motor and belt conveyor in sequence on the console. During the startup process, the operating status of the motor is closely observed to ensure the normal startup of the equipment. As the equipment runs, the stones are transported from the hopper to the belt conveyor via the feed tray. At the same time, the FMCW radar starts working, emitting triangular measurement waves and receiving reflected waves. The radar's signal acquisition module continuously records the time and frequency information of the transmitted and received waves to provide basic data for subsequent data processing.

[0061] Radar data processing and analysis: FMCW radar obtains the Doppler frequency, distance and speed parameters of ore particles according to the Doppler effect related formula. The frequency formula is: 2f D =Δf1-Δf2, where f D Indicates the Doppler frequency generated during the movement of the target object. The distance formula is: R represents the distance of the target object, that is, the straight-line distance between the radar and the target object; the speed formula is: When using the MVDR beamforming method, the original signal collected by the receiving antenna is preprocessed according to the antenna layout. After being converted into a digital signal, the covariance matrix is ​​constructed, the weight vector is calculated, and weighted summation is performed. The characteristics of the transmitting antenna are used to locate and measure the stone particle target in the X-axis direction. Finally, the measurement data in the X-axis and Y-axis directions are fused, combined with the distance information, the position coordinates of the stone particles in the three-dimensional space are calculated, and a two-dimensional reflection point vector diagram is generated.

[0062] Reflection point analysis and spacing adjustment: Based on the two-dimensional reflection point vector diagram, the system classifies the reflection points and identifies the point groups, calculates the point group centroid and the Y-axis spacing WY between each point group iThe processing plant sets the initial vibration frequency of the vibrating feeder motor and the maximum particle size requirement of the stone according to the quality standard of the building stone. According to the difference between the current minimum spacing in the Y-axis direction and the target spacing, the vibration frequency of the vibrating feeder motor is adjusted using the vibration frequency adjustment formula. The formula is: At the same time, set the initial speed of the belt conveyor motor and the user-defined X-axis direction spacing WX i The minimum requirement is to adjust the speed of the belt conveyor according to the particle speed deviation and spacing deviation in the X-axis direction through the belt conveyor speed adjustment formula. The formula is: Make the distance between stones on the belt conveyor in the X-axis direction as small as possible to meet the requirements.

[0063] Real-time adjustment of particle spacing: The calculation results of reflection point analysis and spacing adjustment are converted into analog signals by the DAC inside the FMCW radar module and transmitted to the controller of the vibrating feeder motor and the belt conveyor. The controller adjusts the motor vibration frequency and speed according to the analog signals, and adjusts the spacing of the stone particles in the Y-axis and X-axis directions in real time through the feedback control mechanism until the stone particles are not stacked in the image acquisition area of ​​the belt conveyor, thereby achieving uniform distribution of the stone particles.

[0064] Image acquisition and analysis: The system monitors the image acquisition area of ​​the belt conveyor. When the spacing between stone particles meets the non-stacking condition, the image camera component is triggered to acquire images according to the preset parameters and transmit the images to the analysis system. The analysis system uses the edge detection algorithm to outline the stone particle contours. By determining the image noise level, the new Gaussian filter standard deviation is calculated, and Gaussian filtering, gradient calculation, non-maximum suppression and double threshold processing are performed to obtain the edge image and outline the stone particle contours. At the same time, the high threshold and low threshold are determined based on the grayscale histogram obtained by statistically analyzing the grayscale frequency of the image. The particle shape and particle size are calculated based on the perimeter, area, major axis length and minor axis length of the stone particles using the particle shape parameter calculation formula and the particle size calculation formula. The formula is: The analysis system compares the calculation results with the quality standards of building stones and provides data support for the optimization of the production process. In this way, the quality of building stones is improved, the competitiveness of products in the market is enhanced, and more market share and economic benefits are brought to the processing plant.

[0065] In summary, the introduction of this feedback method in the building stone processing plant has achieved remarkable results. From system construction and debugging to radar startup to collect stone particle data, and then data processing and analysis to achieve particle positioning and parameter measurement, the entire process is closely coordinated. By adjusting the motor vibration frequency and belt conveyor speed, the stone particles are evenly distributed, and image acquisition and analysis are used to obtain particle shape and size information. After comparison with quality standards, production is optimized. This not only improves the quality of building stones and meets the market demand for high-quality stones, but also enhances the competitiveness of products in the market, brings more market share and economic benefits to the processing plant, and promotes the sustainable and healthy development of the enterprise.

[0066] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A method for adjusting feedback of uniform distribution of particles based on microwave radar, characterized in that: The specific steps of this feedback method are: S100, system construction and equipment installation: The vibrating feeder motor, feeder tray, hopper, belt conveyor, FMCW radar and image camera assembly form a linkage system. The FMCW radar is installed just above the junction of the feeder tray and the belt conveyor. The image camera assembly is aligned with the image acquisition area. After the installation is completed, the lines are connected and comprehensive debugging is carried out; S200, ore conveying and radar start: Pour the ore to be tested into the hopper, start the vibrating feeder motor and the belt conveyor in sequence, so that the ore is conveyed from the hopper to the belt conveyor through the feeder tray. At the same time, the FMCW radar starts to work, emitting triangular measurement waves and receiving reflected waves, and continuously recording the time and frequency information of the emitted and received waves; S300, radar data processing and analysis: FMCW radar compares the transmitted wave and the reflected wave to calculate the frequency difference, calculates the Doppler frequency, distance and speed parameters of the ore particles according to the Doppler effect related formula, and further processes the radar data using the MVDR beamforming method. Based on the antenna layout, the positioning and speed measurement of the target object on three axes are achieved, and a two-dimensional reflection point vector diagram is generated; S400, reflection point analysis and spacing adjustment: obtain a two-dimensional reflection point vector diagram based on the measurement results, classify the reflection points and identify the point groups, calculate the point group centroid and the Y-axis spacing WY between each point group i , set the initial vibration frequency of the vibrating feeder motor and the maximum particle size of the ore set by the user, adjust the vibration frequency of the vibrating feeder motor through the vibration frequency adjustment formula according to the information of the difference between the current minimum Y-axis spacing and the target spacing, set the initial speed of the belt conveyor motor and the X-axis spacing WX set by the user i Minimum requirement: adjust the speed of the belt conveyor by the belt conveyor speed adjustment formula; S500, real-time adjustment of particle spacing: The reflection point analysis and spacing adjustment calculation results are converted into analog signals by the DAC inside the FMCW radar module and transmitted to the controllers of the vibrating feeder motor and the belt conveyor respectively. The controller adjusts the motor vibration frequency and speed according to the signal to control the spacing of the ore particles in the Y-axis direction and the X-axis direction until the ore particles are not stacked in the belt conveyor image acquisition area; S600, image acquisition and analysis: monitors the image acquisition area of ​​the belt conveyor. When the distance between ore particles meets the non-stacking condition, the image camera component is triggered to acquire images according to preset parameters and transmit the images to the analysis system. The analysis system uses edge detection algorithms to outline the contours of ore particles and calculate the particle shape and size.

2. The method for adjusting and feedbacking uniform distribution of particles based on microwave radar according to claim 1, characterized in that: The S100, system construction and equipment installation of the FMCW radar is designed with 6 receiving antennas rx and 3 transmitting antennas tx. The transmitting antenna tx transmits a triangular measurement wave. The frequency of the transmitted microwave moves from low frequency to high frequency, reaches the highest point and then moves downward.

3. The method for adjusting and feedbacking uniform distribution of particles based on microwave radar according to claim 1, characterized in that: In the S300, the Doppler frequency, distance and speed parameters of the ore particles are obtained according to the Doppler effect related formula in the radar data processing and analysis. The frequency formula is: 2f D =Δf1-Δf2, where f D It represents the Doppler frequency generated during the movement of the target object. Δf1 and Δf2 are the frequency differences between the received wave and the transmitted wave under different conditions. The distance formula is: R represents the distance of the target object, c represents the speed of light, Δf1 and Δf2 are the frequency differences between the received wave and the transmitted wave at different times, and K is the slope of the rising frequency of the transmitted wave; speed formula: v represents the speed of the target object, λ is the wavelength of the transmitted wave, and Δf1 and Δf2 are the frequency differences between the received wave and the transmitted wave at different times.

4. The method for adjusting and feedbacking uniform distribution of particles based on microwave radar according to claim 1, characterized in that: The specific steps of applying the MVDR beamforming method in the radar data processing and analysis in S300 are as follows: (1) Based on the layout of 6 receiving antennas placed at equal intervals of λ / 2 on the Y axis, the receiving antenna of the FMCW radar simultaneously receives the reflected wave signals from the ore particles, pre-processes the original signals collected by the receiving antenna, and converts the analog signals into digital signals; (2) According to the MVDR algorithm principle, the covariance matrix is ​​constructed, the weight vector is calculated, and the preprocessed receiving antenna signal and the calculated weight vector are weighted summed; (3) Taking advantage of the fact that the transmitting antennas are placed at equal intervals of 2λ on the X-axis, the MVDR beamforming method is used to locate and measure the ore particle targets in the X-axis direction. By processing the received signals of each antenna in the X-axis direction, the position information and related parameters of the ore particles in the X-axis direction are obtained; (4) The measurement data obtained by the MVDR beamforming method in the X-axis and Y-axis directions are fused and processed, combined with the calculated distance information between the ore particles and the radar, and the spatial geometric relationship is used to calculate the position coordinates of the ore particles in three-dimensional space (X-axis, Y-axis, and Z-axis).

5. The method for adjusting and feedbacking uniform distribution of particles based on microwave radar according to claim 1, characterized in that: In the above S400, the vibration frequency f of the vibration feeder motor is adjusted by the vibration frequency adjustment formula in the reflection point analysis and spacing adjustment. vib , let the difference between the current Y-axis particle spacing and the target spacing be ΔWY, the time interval be Δt, and the distance between the target particle and the radar be R new , the frequency adjustment coefficient related to the ore characteristics is γ, and the formula is:

6. The method for adjusting and feedbacking uniform distribution of particles based on microwave radar according to claim 1, characterized in that: In the above S400, the speed v of the belt conveyor is adjusted by the belt conveyor speed adjustment formula in the reflection point analysis and spacing adjustment. belt , let the particle velocity deviation in the X-axis direction be ΔVX, the particle spacing deviation in the X-axis direction be ΔWX, and the distance between the target particle and the radar be R new , the belt conveyor speed adjustment coefficient is δ, and the formula is:

7. The method for adjusting and feedbacking uniform distribution of particles based on microwave radar according to claim 1, characterized in that: The specific steps of using edge detection algorithm to outline the contour of ore particles in S600 in image acquisition and analysis are as follows: (1) Determine the noise level N of the image level , calculate the new Gaussian filter standard deviation σ′ according to the formula: σ′=δN level +∈, where δ and ∈ are parameters determined empirically; (2) The preprocessed image I processed Substitute the calculated new standard deviation σ′ into the Gaussian filter function h to obtain the Gaussian filtered image I filtered , the formula is: filtered =h(I processed ,σ′); (3) For the filtered image I filtered Perform gradient calculation to obtain the gradient magnitude and direction of each pixel; (4) performing non-maximum suppression in the gradient magnitude image according to the calculated gradient direction; (5) Set two thresholds: high threshold T high and low threshold T low , traverse the image after non-maximum suppression, for the gradient amplitude greater than the high threshold T high The pixel point is marked as a strong edge pixel point, and the pixel point with a gradient amplitude less than the low threshold T low For pixels whose gradient amplitude is between the high threshold and the low threshold, they are marked as non-edge pixels and discarded. For pixels whose gradient amplitude is between the high threshold and the low threshold, if they are adjacent to strong edge pixels, they are marked as edge pixels, otherwise they are discarded. (6) After the above processing, the edge image I is finally obtained edge , outlining the contours of the ore particles.

8. The method for adjusting and feedbacking uniform distribution of particles based on microwave radar according to claim 7, characterized in that: S600, image acquisition and analysis, high threshold T high and low threshold T low The frequency of each gray level in the image is counted to obtain the gray level histogram H(i), where i represents the gray level and H(i) represents the frequency of the pixel with gray level i. The high threshold T is determined. high , calculate the average gray value μ of the image, the formula is: Where 255 is the maximum gray level assuming that the image is an 8-bit grayscale image. The standard deviation σ of the grayscale histogram is calculated as follows: High threshold T high The calculation formula is: high =μ+k1+σ, where k1 is the coefficient, the low threshold T low Determination of the low threshold T low The calculation formula is: low =k2×T high , where k2 is the coefficient.

9. The method for adjusting and feedbacking uniform distribution of particles based on microwave radar according to claim 1, characterized in that: In the calculation of particle shape and particle size in the image acquisition and analysis in S600, assuming that the perimeter of the ore particle is P, the area is A, the major axis length is I, and the minor axis length is S, the calculation formula of the particle shape parameter F is: The calculation formula of particle size D is:

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