A laser-ultrasound based crusher material level detection device and method

Abstract

This invention discloses a crusher material level detection device and method based on laser-ultrasound, comprising: an X-Y dual-axis adjustment mechanism for adjusting the movement of the detection device along the X and Y axes; a vibration damping mechanism connected to the X-Y dual-axis adjustment mechanism for vibration damping; a sensor chamber installed within the vibration damping mechanism, containing several sensors for detection; and a cleaning mechanism installed on one side of the vibration damping mechanism for cleaning operations. This invention enables real-time detection of crusher material level, displays three-dimensional material information and level values, and adjusts the conveyor belt speed to maintain the material level at an ideal position, solving the problem of difficult crusher material level detection and control.

Description

Technical Field

[0001] This invention relates to a laser-ultrasound-based crusher material level detection device and method, belonging to the field of material level detection technology. Background Technology

[0002] Crushers, as key equipment in the production industries of ore, cement, and sand, are mainly used to crush stones of varying sizes. The crushed stones are then circulated multiple times in a closed loop, and screening equipment controls the particle size to meet the requirements. During operation, due to factors such as uneven feeding and inconsistent stone size, unstable loads and large fluctuations in material level can easily occur, affecting the crusher's efficiency and lifespan, and even leading to safety accidents such as stalling and material overflow. Therefore, monitoring and controlling the material level in the crusher within the ideal operating range is crucial for its safe operation.

[0003] With the development of measurement technology, active measurement technologies such as laser, ultrasonic, and microwave radar have been widely used. Laser, ultrasonic, and microwave radar offer advantages such as non-contact operation, high measurement speed, and stable performance, which can improve the efficiency and safety of detection. Summary of the Invention

[0004] To address the problems existing in the prior art, the present invention provides a crusher material level detection device and method based on laser-ultrasound, which can detect crusher material level information in real time, control the feeding belt movement, improve the detection accuracy and speed of crusher material level, and enhance the efficiency and safety of crusher operation.

[0005] To achieve the above objectives, the present invention employs a laser-ultrasound-based crusher material level detection device, comprising:

[0006] The XY two-axis adjustment mechanism is used to adjust the movement of the detection device along the X-axis and Y-axis directions.

[0007] A vibration damping mechanism is connected to the XY two-axis adjustment mechanism, and the vibration damping mechanism is used for vibration damping.

[0008] A sensor compartment is installed inside a vibration damping mechanism, and several sensors for detection are installed inside the sensor compartment.

[0009] A cleaning mechanism is installed on one side of the vibration damping mechanism and is used to perform cleaning operations.

[0010] As an improvement, the XY two-axis adjustment mechanism includes an X-axis guide rail, an X-axis mounting base plate, an X-axis slider, a Y-axis mounting base plate, an X-axis lead screw, a Y-axis slider, a Y-axis guide rail, a vibration damping mechanism base plate, and a Y-axis lead screw;

[0011] The X-axis guide rail is mounted on the X-axis mounting base plate, and an X-axis slider is mounted on the X-axis guide rail. The Y-axis mounting base plate is connected to the X-axis slider, and an X-axis lead screw is installed between the Y-axis mounting base plate and the X-axis mounting base plate. The Y-axis mounting base plate can move freely on the X-axis guide rail under the action of the X-axis lead screw.

[0012] A Y-axis guide rail is mounted on the Y-axis mounting base plate, and a Y-axis slider is mounted on the Y-axis guide rail. The vibration damping mechanism base plate is connected to the Y-axis slider, and a Y-axis lead screw is installed between the vibration damping mechanism base plate and the Y-axis mounting base plate. The vibration damping mechanism base plate can move freely on the Y-axis guide rail under the action of the Y-axis lead screw.

[0013] As an improvement, the vibration damping mechanism is mounted on the base plate of the vibration damping mechanism, and the vibration damping mechanism includes a vibration damping mechanism housing, a sensor compartment base plate, a sensor compartment housing, a buffer magnet, and a vibration damping spring;

[0014] The sensor compartment housing is mounted on the outer shell of the vibration damping mechanism, with a certain gap between them; the buffer magnet is arranged in this gap; and several vibration damping springs are installed between the outer shell of the vibration damping mechanism and the bottom plate of the sensor compartment.

[0015] As an improvement, several vibration damping spring columns are installed on the bottom plate of the sensor compartment, and corresponding annular columns are provided on the outer shell of the vibration damping mechanism. The vibration damping springs are sleeved on the columns after docking.

[0016] As an improvement, the sensor compartment includes a dust measuring instrument, a lidar, an ultrasonic rangefinder, a lidar mounting bracket, and an ultrasonic rangefinder mounting bracket;

[0017] The sensor compartment is installed inside the sensor compartment shell, which is fixed to the sensor compartment bottom plate with bolts; the dust measuring instrument is installed on the sensor compartment bottom plate; the lidar is fixed to the sensor compartment bottom plate with a lidar mounting bracket; the ultrasonic rangefinder is fixed to the sensor compartment bottom plate with an ultrasonic rangefinder mounting bracket; and a sensor protective glass is installed on the sensor compartment shell.

[0018] As an improvement, the cleaning mechanism includes a cleaning device push rod, a switching motor mounting bracket, a cleaning head, a cleaning head switching motor, a cleaning head push rod fixing bracket, a cleaning head telescopic push rod, and a cleaning head mounting bracket;

[0019] The cleaning head is mounted on a cleaning head mounting bracket, which is fixedly connected to the cleaning head telescopic push rod. The cleaning head has a built-in motor that can rotate while moving. The cleaning head telescopic push rod is mounted on a cleaning head push rod fixing bracket, which is connected to a cleaning head switching motor, allowing the cleaning head to be switched according to the cleaning process. The cleaning head switching motor is mounted on the cleaning device push rod via a switching motor mounting bracket. The cleaning device push rod is mounted on the vibration damping mechanism housing, and the movement of the cleaning head is controlled by the extension and retraction of the push rod.

[0020] In addition, the present invention also provides a detection method for the laser-ultrasonic crusher material level detection device, comprising the following steps:

[0021] S1. Acquisition of LiDAR material point cloud data:

[0022] S101, LiDAR level data acquisition: The three-dimensional information of the level is continuously acquired through LiDAR, and the raw data acquired is the depth value;

[0023] S102, Depth Data Extraction: Based on the relative position of the lidar and the hopper, the depth values ​​collected by the lidar are extracted to obtain the depth data of the hopper section.

[0024] S103. Saving target location depth data: The extracted depth data is saved as a text file;

[0025] S104, Data communication: Completed via a pipeline;

[0026] S105. Depth data to point cloud data conversion: Read the extracted depth data file, combine the LiDAR intrinsic parameters and the depth value-coordinate conversion formula, calculate the three-dimensional coordinates of each point, and convert the depth data into a point cloud PCD file.

[0027] S106, Point cloud data downsampling: Divide the point cloud into multiple voxel grids, and replace the points in each voxel grid with the centroid of all the points;

[0028] S107, Point Cloud Outlier Filtering and Denoising: By dividing the threshold, the number of neighboring points is calculated, and outlier noise points are removed;

[0029] S108. Point cloud plane and cylindrical surface segmentation: By setting a segmentation model, the surface with features in the point cloud data is segmented out;

[0030] S109. Point cloud clustering to extract material point cloud: By calculating the distance between points, a portion of the point cloud that is close in distance is divided into a class. After clustering, the class with the most points can be selected to obtain the target material point cloud.

[0031] S110, Material Point Cloud Saving: The clustered point cloud is saved and uploaded to the host computer for subsequent data fusion and material level calculation;

[0032] S2. Ultrasonic rangefinder data acquisition: The ultrasonic rangefinder continuously acquires the distance information of the material level. The ultrasonic rangefinder reads a measurement value every 130ms. After measurement, the current is output to the analog signal acquisition card to obtain continuous raw measurement values.

[0033] S3. Ultrasonic rangefinder data filtering: Filters the raw measurement values ​​of the ultrasonic rangefinder to remove noise errors caused by environmental fluctuations;

[0034] S4. Environmental dust concentration measurement: The environmental dust concentration measured by the dust meter is read in real time by the material level detection device and uploaded to the host computer for subsequent data processing.

[0035] S5. Material Level Calculation and 3D Reconstruction of Material Point Cloud: Material level calculation and 3D reconstruction of material point cloud; Material level calculation involves fusing data from lidar, ultrasonic rangefinder, and dust meter on the host computer, determining the weights of the laser and ultrasonic measurement data based on the measured environmental dust concentration, and then calculating the material level value; 3D reconstruction of material point cloud uses greedy projection triangulation to calculate the material level surface, and smooths the surface to display the complete surface state of the material.

[0036] S6. Multi-sensor data display: The screen outputs and displays the real-time three-dimensional reconstruction model of the material, the calculated material level value and the current dust concentration value, and can view the historical material level data curve. The image display makes it easy to observe and grasp the current crusher operating status.

[0037] S7. Material level judgment and belt speed control: The calculated material level value is compared with the set material level threshold to determine whether the material level is low, ideal, high or full. The running speed of the feeding belt is controlled according to the different material level states. The belt is controlled to accelerate, maintain speed, decelerate and start and stop, so that the material level is kept within an ideal range.

[0038] As an improvement, the lidar is a solid-state lidar with a frame rate of 50fps and a resolution of 640×160.

[0039] As an improvement, the data filtering in step S3 includes the following steps:

[0040] S31, Recursive Average Filtering: By continuously reading ultrasound measurement values ​​and saving n values, each time a new value is read, the first saved value is discarded, and the average of all n values ​​is taken as the current measurement value;

[0041] S32, Limiting Extreme Values ​​and Amplitude Filtering: The measured value is filtered by limiting the extreme value range of each measurement and the difference range with the previous measurement value. If the current measurement value does not meet the filtering range, the previous measurement value is used instead. The filtered data is uploaded to the host computer for subsequent data fusion and material level calculation.

[0042] As an improvement, the material level status in step S7 includes low material level, ideal material level, high material level, and full material level.

[0043] Compared with the prior art, the beneficial effects of the present invention are:

[0044] 1) It can detect the material level of the crusher in real time, display the three-dimensional information of the material and the material level value, and adjust the belt speed of the feeding belt to keep the material level in the ideal position, thus solving the problem of difficult material level detection and control in the crusher.

[0045] 2) The material level detection device can adjust the sensor position according to the material level conditions to align it with the center of the material level; the vibration damping mechanism adopts a combination of spring vibration damping and magnetic vibration damping, which can effectively reduce the impact of horizontal and vertical vibration on the measurement; the cleaning mechanism uses electric push rods in two directions to drive the cleaning head to operate, which can completely cover the entire measuring lens, and the two cleaning heads can be switched to use, adopting a single cleaning and a double cleaning method, resulting in better cleaning effect.

[0046] 3) Accurately extract the target material point cloud through point cloud data processing and display the three-dimensional reconstruction model; adopt an ultrasonic-based material level measurement method, and effectively process noise and gross error interference in the original data through recursive average filtering and limit value-amplitude filtering; use a material level information fusion method to fuse laser and ultrasonic measurement results, and combine them with dust measurement results for comprehensive decision-making to reduce the impact of environmental dust on the measurement; control the acceleration, speed maintenance, deceleration, and start-up and shutdown actions of the feeding belt based on the measured material level value. Attached Figure Description

[0047] Figure 1 This is a diagram showing the installation location of the material level detection device of the present invention;

[0048] Figure 2 The axial measurement of the material level detection device of the present invention Figure 1 ;

[0049] Figure 3 The axial measurement of the material level detection device of the present invention Figure 2 ;

[0050] Figure 4 This is a diagram showing the internal structure of the sensor compartment in this invention;

[0051] Figure 5This is a schematic diagram of the cleaning mechanism in this invention;

[0052] Figure 6 This is a schematic diagram of the material level detection method of the present invention;

[0053] Figure 7 This is a flowchart of the lidar data processing method of the present invention;

[0054] In the diagram: 1. Mounting frame for the detection device; 2. Material level detection device; 3. Crusher hopper; 4. X-axis guide rail; 5. X-axis mounting base plate; 6. X-axis slider; 7. Y-axis mounting base plate; 8. X-axis lead screw; 9. Cleaning mechanism; 10. Y-axis slider; 11. Y-axis guide rail; 12. Vibration damping mechanism base plate; 13. Vibration damping mechanism; 14. Y-axis lead screw; 15. Vibration damping mechanism housing; 16. Sensor hopper bottom plate; 17. Sensor protective glass; 18. Sensor hopper exterior. 19. Shell; 20. Buffer magnet; 21. Sensor compartment; 22. Vibration damping spring; 23. Dust measuring instrument; 24. LiDAR; 25. Ultrasonic rangefinder; 26. LiDAR mounting bracket; 27. Ultrasonic rangefinder mounting bracket; 28. Vibration damping spring column; 29. ​​Sweeping device push rod; 30. Switching motor mounting bracket; 31. Sweeping head switching motor; 32. Sweeping head push rod fixing bracket; 33. Sweeping head telescopic push rod; 34. Sweeping head mounting bracket. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below. However, it should be understood that the specific embodiments described herein are merely illustrative and are not intended to limit the scope of the invention.

[0056] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention.

[0057] like Figure 1 As shown, a crusher material level detection device based on laser-ultrasound includes a detection device mounting frame 1, a material level detection device 2, and a crusher hopper 3;

[0058] The material level detection device 2 is installed above the crusher hopper 3 via the detection device mounting frame 1. The height can be adjusted arbitrarily on the mounting frame to align with the position to be measured in order to collect the material level information of the crusher hopper 3.

[0059] As an improvement to the embodiment, such as Figure 2As shown, the material level detection device 2 includes an XY axis adjustment mechanism, a vibration damping mechanism 13, a sensor chamber 20, and a cleaning mechanism. The XY axis adjustment mechanism is fixedly connected to the vibration damping mechanism 13. The sensor chamber 20 is installed inside the vibration damping mechanism 13, and the cleaning mechanism 6 is installed on one side of the vibration damping mechanism 13.

[0060] As an improvement to the embodiment, such as Figure 2 As shown, the XY two-axis adjustment mechanism includes an X-axis guide rail 4, an X-axis mounting base plate 5, an X-axis slider 6, a Y-axis mounting base plate 7, an X-axis lead screw 8, a Y-axis slider 10, a Y-axis guide rail 11, a vibration damping mechanism base plate 12, and a Y-axis lead screw 14.

[0061] The X-axis guide rail 4 is mounted on the X-axis mounting base plate 5, and an X-axis slider 6 is mounted on the X-axis guide rail 4. The Y-axis mounting base plate 7 is connected to the X-axis slider 6, and an X-axis lead screw 8 is installed between the Y-axis mounting base plate 7 and the X-axis mounting base plate 5. The Y-axis mounting base plate 7 can move freely on the X-axis guide rail 4 under the action of the X-axis lead screw 8 to adjust the measurement position of the sensor on the X-axis.

[0062] A Y-axis guide rail 11 is mounted on the Y-axis mounting base plate 7, and a Y-axis slider 10 is mounted on the Y-axis guide rail 11. The vibration damping mechanism base plate 12 is connected to the Y-axis slider 10. A Y-axis lead screw 14 is installed between the vibration damping mechanism base plate 12 and the Y-axis mounting base plate 7. The vibration damping mechanism base plate 12 can move freely on the Y-axis guide rail 11 under the action of the Y-axis lead screw 14 to adjust the measurement position of the sensor on the Y-axis.

[0063] As an improvement to the embodiment, such as Figure 3 As shown, the vibration damping mechanism 13 includes a vibration damping mechanism housing 15, a sensor compartment bottom plate 16, a sensor protective glass 17, a sensor compartment housing 18, a buffer magnet 19, a sensor compartment 20, and a vibration damping spring 21.

[0064] The vibration damping mechanism housing 15 has a square notch in the center. The sensor chamber housing 18 is fixed in the square notch of the vibration damping mechanism housing 15, and a certain gap is maintained between the two. The buffer magnet 19 is arranged in this gap. Each set of buffer magnets 19 is installed on both the vibration damping mechanism housing 15 and the sensor chamber housing 18. Multiple sets of buffer magnets 19 are symmetrically and evenly arranged on the outside of the sensor chamber housing 18. The repulsive force between the buffer magnet pairs keeps the sensor chamber stable when the external structure vibrates, reducing the impact of the horizontal vibration of the crusher on the sensor measurement.

[0065] The sensor compartment 20 is located inside the sensor compartment shell 18, which is fixed to the sensor compartment base plate 16 by bolts. The sensor compartment shell 18 has a notch in the sensor mounting part, and a sensor protective glass 17 is installed at the notch. This can protect the sensor while ensuring the measurement function, prevent water mist, dust and other particles from entering the sensor compartment, and facilitate cleaning and maintenance by the cleaning mechanism 9.

[0066] As an improvement to the embodiment, such as Figure 4 As shown, the sensor compartment 20 includes a vibration damping mechanism base plate 12, a sensor compartment base plate 16, a vibration damping spring 21, a dust measuring instrument 22, a lidar 23, an ultrasonic rangefinder 24, a lidar mounting bracket 25, an ultrasonic rangefinder mounting bracket 26, and a vibration damping spring column 27.

[0067] The dust measuring instrument 22 is mounted on the sensor hopper bottom plate 16; the lidar 23 is fixed on the sensor hopper bottom plate 16 via the lidar mounting bracket 25; the ultrasonic rangefinder 24 is fixed on the sensor hopper bottom plate 16 via the ultrasonic rangefinder mounting bracket 26; the sensor hopper bottom plate 16 has several vibration damping spring columns 27, the upper end of the vibration damping spring 21 is in contact with the vibration damping mechanism housing 15, the vibration damping mechanism housing 15 has annular columns corresponding to those on the sensor hopper bottom plate 16, which can be docked and positioned with each other, and the vibration damping spring 21 is fitted onto the docked columns to prevent the vibration damping spring 21 from deviating and reduce the influence of the vertical vibration of the crusher on the sensor measurement.

[0068] As an improvement to the embodiment, such as Figure 5 As shown, the cleaning mechanism 9 is used to clean the sensor, and includes a cleaning device push rod 28, a switching motor mounting bracket 29, a cleaning head 30, a cleaning head switching motor 31, a cleaning head push rod fixing bracket 32, a cleaning head telescopic push rod 33, and a cleaning head mounting bracket 34.

[0069] The cleaning head 30 is mounted on the cleaning head mounting bracket 34, and the cleaning head mounting bracket 34 is fixedly connected to the cleaning head telescopic push rod 33. The cleaning head telescopic push rod 33 can control the extension and retraction of the cleaning head. The cleaning head 30 has a built-in motor, which can rotate itself while moving to increase the cleaning effect.

[0070] The sweeping head telescopic push rod 33 is mounted on the sweeping head push rod fixing frame 32, and the sweeping head push rod fixing frame 32 is fixedly connected to the sweeping head switching motor 31, which can switch the sweeping head 30 according to the sweeping process; there are two sweeping heads 30, which are divided into a primary sweeping head and a secondary sweeping head. The two sweeping heads are used alternately to improve sweeping efficiency, and the switching is controlled by the sweeping head switching motor 31.

[0071] The cleaning head switching motor 31 is fixed to the cleaning device push rod via the switching motor mounting bracket 29. The cleaning device push rod 28 is fixedly installed on the vibration damping mechanism housing 15. The movement of the cleaning head 30 is controlled by the extension and retraction of the push rod to cover the entire outer surface of the sensor protective glass 17. The cleaning mechanism 9 is programmed to perform timed cleaning, which effectively prevents dust and other particles from adhering to the sensor protective glass 17 and interfering with the measurement.

[0072] Example 1

[0073] like Figure 6 As shown, a detection method for a crusher material level detection device based on laser-ultrasound includes the following steps: acquiring material point cloud data from lidar, collecting data from an ultrasonic rangefinder, filtering data from an ultrasonic rangefinder, measuring environmental dust concentration, calculating material level and reconstructing the material point cloud in three dimensions, displaying data from multiple sensors, determining material level, and controlling belt speed.

[0074] like Figure 7As shown, the laser radar material point cloud data acquisition steps include laser radar material level data acquisition, depth data extraction, target location depth data storage, data communication, depth data conversion to point cloud data, point cloud data downsampling, point cloud outlier filtering and noise reduction, point cloud plane and cylindrical surface segmentation, point cloud clustering to extract material point cloud, and material point cloud storage. To accelerate laser radar data acquisition, the laser radar data acquisition and data processing are separated into two programs that run simultaneously, and program synchronization and data transfer are achieved through inter-process communication. The laser radar material level data acquisition step is completed by the detection device, which continuously acquires the three-dimensional information of the material level through laser radar. The laser radar used is a solid-state laser radar with a frame rate of up to 50. At fps and a resolution of 640×160, the raw data collected is depth value, which can completely reflect the surface information of the entire material level. The depth data interception step intercepts the depth value collected by the lidar based on the relative position of the lidar and the hopper to obtain the depth data of the hopper section, reducing the data volume and speeding up subsequent data processing. The target position depth data saving step saves the intercepted depth data as a text file for easy data communication and transmission. The data communication step is completed through a pipeline. The data acquisition program runs quickly. After data acquisition, it waits for the data processing program to complete its current round of processing before data communication occurs to achieve time synchronization between the two programs, and then the next round of data acquisition begins. The depth data to point cloud data conversion steps read the truncated depth data file, combine the LiDAR intrinsic parameters and the depth-coordinate conversion formula, calculate the 3D coordinates of each point, and convert the depth data into a point cloud PCD file; the point cloud data downsampling step divides the entire point cloud into multiple voxel squares, and replaces these points with the centroid of all points in each voxel square, reducing the point cloud data while maintaining the shape characteristics of the point cloud; the point cloud outlier filtering and noise reduction step removes outlier noise points by setting a threshold and calculating the number of neighboring points, preventing noise from affecting data segmentation; the point cloud plane and cylindrical surface segmentation step segments the feature-rich surfaces in the point cloud data by setting a segmentation model, mainly... The process involves segmenting and removing the planar point cloud of the hopper platform and the cylindrical point cloud of the hopper's inner wall. By setting the characteristic parameters of the planar and cylindrical surfaces to be segmented, the point cloud segmentation is made effective and accurate. Simultaneously, the target material point cloud is separated from other point clouds for easier extraction. The point cloud clustering extraction step calculates the distance between points, grouping points that are closer together into a single category. After steps such as truncation, filtering, and segmentation, the target material point cloud is the main component, separated from other point clouds. The clustered point cloud with the largest number of points is then selected to obtain the target material point cloud. The material point cloud saving step saves the clustered point cloud and uploads it to the host computer for subsequent data fusion and material level calculation.

[0075] The ultrasonic rangefinder data acquisition step is completed by the detection device. The ultrasonic rangefinder continuously acquires the distance information of the material level. The ultrasonic rangefinder reads a measurement value every 130ms. After the measurement, the current is output to the analog signal acquisition card to obtain continuous raw measurement values.

[0076] The ultrasonic rangefinder data filtering step filters the raw measurement values ​​to remove noise errors caused by environmental fluctuations. The data filtering method includes two steps: recursive averaging filtering and extreme value-amplitude limiting filtering. The recursive averaging filtering step continuously reads the ultrasonic measurement values, saves n values, and discards the first saved value each time a new value is read. The average of all n values ​​is then taken as the current measurement value. The extreme value-amplitude limiting filtering step filters the measurement values ​​by limiting the extreme value range of each measurement value and the difference range with the previous measurement value. If the current measurement value does not meet the filtering range, the previous measurement value is used instead. The filtered data is then uploaded to the host computer for subsequent data fusion and material level calculation.

[0077] The aforementioned environmental dust concentration measurement step involves reading the environmental dust concentration in real time from the material level detection device using a dust meter and uploading it to the host computer for subsequent data processing.

[0078] The material level calculation and material point cloud 3D reconstruction steps include material level calculation and material point cloud 3D reconstruction. The material level calculation is performed by the host computer by fusing data from the lidar, ultrasonic rangefinder, and dust concentration meter. The weights of the laser and ultrasonic measurement data are determined based on the measured environmental dust concentration values, and then the material level value is calculated. The material point cloud 3D reconstruction uses greedy projection triangulation to calculate the material level surface and smooths the surface to display the complete surface state of the material.

[0079] The multi-sensor data display step outputs and displays the real-time three-dimensional reconstruction model of the material, the calculated material level value and the current dust concentration value on the screen, and allows viewing of historical material level data curves. The image display facilitates observation and understanding of the current crusher operating status.

[0080] The material level judgment and belt speed control steps compare the calculated material level value with the set material level threshold to determine whether the material level is in several states such as low material level, ideal material level, high material level, and full material level. Based on different states, the running speed of the feeding belt is controlled to perform actions such as acceleration, speed maintenance, deceleration, and start-stop, so that the material level is kept within an ideal material level range.

[0081] This invention can detect the material level in a crusher in real time, display the three-dimensional information and level value of the material, and adjust the belt speed of the feeding belt to keep the material level in an ideal position, thus solving the problem of difficult material level detection and control in crushers.

[0082] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions or improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A detection method of a laser-ultrasound based crusher level detection apparatus, characterized by, include: XY two-axis adjustment mechanism, the XY two-axis adjustment mechanism is used to adjust the movement of the detection device along the X-axis and Y-axis directions; vibration damping mechanism (13), the vibration damping mechanism (13) is connected to the XY two-axis adjustment mechanism, the vibration damping mechanism (13) is used for vibration damping; sensor compartment (20), the sensor compartment (20) is installed in the vibration damping mechanism (13), the sensor compartment (20) is equipped with a number of sensors for detection; cleaning mechanism (6), the cleaning mechanism (6) is installed on one side of the vibration damping mechanism (13), the cleaning mechanism (6) is used for cleaning operations; The vibration damping mechanism (13) is mounted on the vibration damping mechanism base plate (12). The vibration damping mechanism (13) includes a vibration damping mechanism housing (15), a sensor compartment base plate (16), a sensor compartment housing (18), a buffer magnet (19), and vibration damping springs (21). The sensor compartment housing (18) is mounted on the vibration damping mechanism housing (15), and a certain gap is maintained between the two. The buffer magnet (19) is arranged in this gap. Several vibration damping springs (21) are installed between the vibration damping mechanism housing (15) and the sensor compartment base plate (16). Includes the following steps: S1. Acquisition of LiDAR material point cloud data: S101, LiDAR level data acquisition: The three-dimensional information of the level is continuously acquired through LiDAR, and the raw data acquired is the depth value; S102, Depth Data Extraction: Based on the relative position of the lidar and the hopper, the depth values ​​collected by the lidar are extracted to obtain the depth data of the hopper section. S103. Saving target location depth data: The extracted depth data is saved as a text file; S104, Data communication: Completed via a pipeline; S105. Depth data to point cloud data conversion: Read the extracted depth data file, combine the LiDAR intrinsic parameters and the depth value-coordinate conversion formula, calculate the three-dimensional coordinates of each point, and convert the depth data into a point cloud PCD file. S106, Point cloud data downsampling: Divide the point cloud into multiple voxel grids, and replace the points in each voxel grid with the centroid of all the points; S107, Point Cloud Outlier Filtering and Denoising: By dividing the threshold, the number of neighboring points is calculated, and outlier noise points are removed; S108. Point cloud plane and cylindrical surface segmentation: By setting a segmentation model, the surface with features in the point cloud data is segmented out; S109. Point cloud clustering to extract material point cloud: By calculating the distance between points, a portion of the point cloud that is close in distance is divided into a class. After clustering, the class with the most points can be selected to obtain the target material point cloud. S110, Material Point Cloud Saving: The clustered point cloud is saved and uploaded to the host computer for subsequent data fusion and material level calculation; S2. Ultrasonic rangefinder data acquisition: The ultrasonic rangefinder continuously acquires the distance information of the material level. The ultrasonic rangefinder reads a measurement value every 130ms. After measurement, the current is output to the analog signal acquisition card to obtain continuous raw measurement values. S3. Ultrasonic rangefinder data filtering: Filters the raw measurement values ​​of the ultrasonic rangefinder to remove noise errors caused by environmental fluctuations; S4, environmental dust concentration measurement: the environmental dust concentration measured by the material level detection device is read in real time by the dust measuring instrument and uploaded to the upper computer for subsequent data processing; S5, material level calculation and material point cloud three-dimensional reconstruction: material level calculation and material point cloud three-dimensional reconstruction; the material level calculation fuses the data of the laser radar, ultrasonic range finder and dust measuring instrument on the upper computer, determines the weight of the laser and ultrasonic measurement data according to the measured environmental dust concentration value, and then calculates the material level value; the material point cloud three-dimensional reconstruction adopts a greedy projection triangulation to calculate a material level surface, and the surface is smoothed to facilitate the display of the complete surface state of the material; S6, multi-sensor data display: the real-time material three-dimensional reconstruction model, the calculated material level value and the current dust concentration value are output and displayed on the screen, and the historical material level data curve can be viewed, so that the current crusher running state can be observed and mastered through image display; S7, material level judgment and belt speed control: the calculated material level value is compared with the set material level threshold value to judge whether the material level is in a low material level, ideal material level, high material level or full material level state, and the running speed of the feeding belt is controlled according to different material level states to control the belt to accelerate, maintain speed, decelerate, control start-stop actions, so that the material level is kept in an ideal material level range.

2. The method of claim 1, wherein the laser-ultrasonic based crusher level detection apparatus is configured to detect the level of the material in the crusher by: The laser radar adopts a solid-state laser radar, the frame rate is 50 fps, and the resolution is 640*160.

3. The method of claim 1, wherein the laser-ultrasonic based crusher level detection apparatus is configured to detect the level of the material in the crusher by: The data filtering in step S3 includes steps of: S31, recursive average filtering: by continuously reading the measurement value of the ultrasonic, n values are saved, and each time a new value is read, the first saved value is removed, and the average value of all n values is taken as the current measurement value; S32, limit value-amplitude limiting filtering: the measurement value is filtered by limiting the extreme value range of each measurement value and the difference range from the last measurement value, and if the current measurement value does not meet the filtering range, the last measurement value is used instead; The filtered data is uploaded to the upper computer for subsequent data fusion and material level calculation.

4. The method of claim 1, wherein the laser-ultrasonic based crusher level detection apparatus is characterized by, The material level state in step S7 includes low material level, ideal material level, high material level and full material level.

5. The method of claim 1, wherein the laser-ultrasonic based crusher level detection apparatus is configured to detect a level of material in the crusher. The X-Y two-axis adjustment mechanism includes an X-axis guide rail (4), an X-axis mounting bottom plate (5), an X-axis sliding block (6), a Y-axis mounting bottom plate (7), an X-axis lead screw (8), a Y-axis sliding block (10), a Y-axis guide rail (11), a damping mechanism bottom plate (12) and a Y-axis lead screw (14); The X-axis guide rail (4) is mounted on the X-axis mounting bottom plate (5), the X-axis guide rail (4) is provided with the X-axis sliding block (6), the Y-axis mounting bottom plate (7) is connected with the X-axis sliding block (6), the X-axis lead screw (8) is mounted between the Y-axis mounting bottom plate (7) and the X-axis mounting bottom plate (5), and the Y-axis mounting bottom plate (7) can freely move on the X-axis guide rail (4) under the action of the X-axis lead screw (8); The Y-axis mounting base plate (7) is provided with a Y-axis guide rail (11), and the Y-axis guide rail (11) is provided with a Y-axis sliding block (10); the damping mechanism base plate (12) is connected with the Y-axis sliding block (10), and the damping mechanism base plate (12) and the Y-axis mounting base plate (7) are provided with a Y-axis lead screw (14); and the damping mechanism base plate (12) can freely move on the Y-axis guide rail (11) under the action of the Y-axis lead screw (14).

6. The method of claim 1, wherein the laser-ultrasonic based crusher level detection apparatus is configured to detect a level of material in the crusher. The sensor compartment bottom plate (16) is provided with a plurality of damping spring columns (27), and the damping mechanism shell (15) is provided with corresponding annular columns; the damping spring (21) is sleeved on the abutted columns.

7. The method of claim 1, wherein the laser-ultrasonic based crusher level detection apparatus is configured to detect a level of material in the crusher. The sensor compartment (20) comprises a dust measuring instrument (22), a laser radar (23), an ultrasonic range finder (24), a laser radar mounting rack (25) and an ultrasonic range finder mounting rack (26). The sensor compartment (20) is mounted in the sensor compartment shell (18), and the sensor compartment shell (18) is fixed on the sensor compartment bottom plate (16) by bolts; the dust measuring instrument (22) is mounted on the sensor compartment bottom plate (16); the laser radar (23) is fixed on the sensor compartment bottom plate (16) by the laser radar mounting rack (25); the ultrasonic range finder (24) is fixed on the sensor compartment bottom plate (16) by the ultrasonic range finder mounting rack (26); and the sensor compartment shell (18) is provided with a sensor protection glass (17).

8. The method of claim 1, wherein the laser-ultrasonic based crusher level detection apparatus is configured to detect a level of material in the crusher. The cleaning mechanism (6) comprises a cleaning device push rod (28), a switching motor mounting rack (29), a cleaning head (30), a cleaning head switching motor (31), a cleaning head push rod fixing frame (32), a cleaning head telescopic push rod (33) and a cleaning head mounting rack (34). The cleaning head (30) is mounted on the cleaning head mounting rack (34), and the cleaning head mounting rack (34) is fixedly connected with the cleaning head telescopic push rod (33); the cleaning head (30) is provided with a built-in motor, which can rotate by itself while moving; the cleaning head telescopic push rod (33) is mounted on the cleaning head push rod fixing frame (32), and the cleaning head push rod fixing frame (32) is connected with the cleaning head switching motor (31), so that the cleaning head (30) can be switched according to the cleaning process; the cleaning head switching motor (31) is mounted on the cleaning device push rod (28) through the switching motor mounting rack (29), and the cleaning device push rod (28) is mounted on the damping mechanism shell (15) to control the movement of the cleaning head (30) by the push rod telescopic control.

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