Rotary blockage breaking and cleaning mechanical arm

Abstract

The invention discloses a rotary blockage breaking and cleaning mechanical arm in the technical field of blockage cleaning, which comprises a chamber, an ore storage bin and an image recognition system, the ore storage bin is positioned on one side of the chamber, a mounting seat is mounted in an inner cavity of the chamber, a breaking arm is arranged at the top of the mounting seat, and a chain plate type conveying belt is mounted in the ore storage bin; a crushing bin is arranged at the end, close to the chain plate type conveying belt, in the chamber and located below the chain plate type conveying belt. Through cooperative arrangement of the chamber, the image recognition system, the crushing arm, the crushing bin and the chain plate type conveying belt, the chain plate type conveying belt conveys ore, images of the ore are collected through the high-speed camera during falling, and then the images are transmitted to a rear-end algorithm processing node; and when the rear-end algorithm recognizes that the size of the ore exceeds the preset threshold value, the large ore alarm system is triggered, and the crushing arm intervenes in crushing the large ore, so that manual intervention is reduced, and the processing efficiency is improved.

Description

Technical Field

[0001] The invention relates to the technical field of blockage clearing, in particular to a rotary blockage breaking and clearing mechanical arm. Background Art

[0002] In the process of mineral processing, in order to ensure the working efficiency of the mill, there will be certain requirements on the ore particle size at the mill feed port. However, larger ores often block the feed port. If not handled in time, it will directly affect the storage of the ore bin, seriously affecting the working efficiency of the mill and the release of mine production capacity.

[0003] The existing cleaning method mainly relies on manual on-site blockage cleaning. Due to the high dust concentration and high temperature in the confined space on site, it is not conducive to the occupational health of workers. At the same time, the low efficiency of manual cleaning will lead to production interruption. Based on this, we propose a rotary blockage breaking and cleaning robot arm. Summary of the invention

[0004] In order to improve the above-mentioned existing cleaning method which mainly relies on manual cleaning of blockages on site, which is not conducive to the occupational health of workers due to the high dust concentration and high temperature in the confined space on site, and the low efficiency of manual cleaning will lead to production interruption, the present invention provides a rotary blockage breaking and cleaning robot arm.

[0005] The present invention provides a rotary blockage-breaking and cleaning mechanical arm, which adopts the following technical solution: A gyratory blockage-breaking and clearing mechanical arm comprises a chamber, a ore bin and an image recognition system, wherein the ore bin is located at one side of the chamber, a mounting seat is installed in the inner cavity of the chamber, a crushing arm is arranged on the top of the mounting seat, a chain plate conveyor belt is installed inside the ore bin, and the left end of the chain plate conveyor belt extends into the chamber, a crushing bin is arranged at one end of the chamber near the chain plate conveyor belt, and the crushing bin is located below the chain plate conveyor belt.

[0006] By adopting the above technical solution, the chain plate conveyor belt conveys the granite ore until the ore reaches the end of the chain plate conveyor belt. The image recognition system can capture the moment when the ore falls and analyze the collected image data using an algorithm to identify and measure the size of the ore. Under normal circumstances, if the ore is small in size, it will roll smoothly from top to bottom into the interior of the conveying channel. When the image recognition system identifies that the ore size exceeds the preset threshold, the crushing arm works to allocate the ore to the interior of the crushing bin and crush the large pieces of ore. After the large pieces of ore are crushed, they enter the feed bin through the conveying channel for storage or further processing. The entire process ensures the efficiency and safety of ore processing. Through the automated image recognition and crushing system, manual intervention is reduced and processing efficiency is improved.

[0007] Optionally, the crushing arm includes a slewing bearing, supports are installed at both front and rear ends of the top of the slewing bearing, a large arm is hinged on the top of the two groups of supports, a slewing motor is installed between the two groups of supports, and the bottom of the slewing motor is connected to the top of the slewing bearing, the end of the large arm away from the support is hinged to a small arm, and the end of the small arm away from the large arm is hinged to a hydraulic hammer through an I-beam connecting rod.

[0008] By adopting the above technical solution, the oversized ore is crushed by a hydraulic hammer to reduce its size to a standard size that can pass through a conveyor belt.

[0009] Optionally, a first oil cylinder is hinged between the surface of the upper arm and the bottom of the support, a second oil cylinder is hinged between the top of the lower arm and the middle of the upper arm, and a third oil cylinder is hinged between the top of the I-shaped frame connecting rod and the lower arm.

[0010] By adopting the above technical solution, the extension of the first oil cylinder can adjust the angle between the boom and the support, the extension of the second oil cylinder can adjust the angle between the forearm and the boom, and the extension of the third oil cylinder can adjust the angle between the hydraulic hammer and the forearm, so that the angle of the hydraulic hammer can be adjusted during crushing, which is more flexible and changes the traditional way of mechanical crushing arms to crush ore from top to bottom in a vertical direction.

[0011] Optionally, a slewing base is installed at the bottom of the slewing bearing, and a plurality of anchor bolts are arranged between the slewing base and the mounting seat.

[0012] By adopting the above technical solution, the slewing base can be fixedly installed by a plurality of anchor bolts, and then the entire crushing arm can be fixedly installed.

[0013] Optionally, the surface of the crushing arm is coated with a paint layer.

[0014] By adopting the above technical solution, the crushing arm as a whole has a certain anti-corrosion performance, thereby extending the service life of the crushing arm.

[0015] Optionally, baffle plates are symmetrically installed at the front and rear ends of the top of the chain-plate conveyor belt.

[0016] By adopting the above technical solution, the ore on the chain plate conveyor belt can be protected by the baffle plate, and the ore is prevented from slipping off the chain plate conveyor belt as much as possible.

[0017] Optionally, the first oil cylinder, the second oil cylinder and the third oil cylinder all use high-hardness chrome-plated piston rods, and the exposed parts of the piston rods are installed with protective covers.

[0018] By adopting the above technical solution, the strength of the first oil cylinder, the second oil cylinder and the third oil cylinder is improved, thereby extending the service life of the first oil cylinder, the second oil cylinder and the third oil cylinder.

[0019] Optionally, a conveying channel is provided on one side of the crushing bin, a feed port is provided between the crushing bin and the conveying channel, and a feed bin is installed at the bottom of the conveying channel.

[0020] By adopting the above technical solution, the ore can be transported through the conveying channel to the interior of the feed bin for storage or unified processing, which facilitates the unified collection of the ore.

[0021] Optionally, the image recognition system includes a high-speed camera, back-end algorithm processing and a large ore alarm, the output end of the high-speed camera is electrically connected to the input end of the back-end algorithm processing, the back-end algorithm processing is electrically connected to the input end of the large ore alarm, the output end of the large ore alarm is connected to the input end of the automatic system, and the output end of the automatic system is electrically connected to the input end of the crushing arm.

[0022] By adopting the above technical solution, the high-speed camera can capture the moment when the ore falls, provide raw data for subsequent image processing, receive image data from the high-speed camera through the back-end algorithm processing, and use the algorithm for analysis to identify and measure the size of the ore. When the back-end algorithm processing identifies that the ore size exceeds the preset threshold, the large ore alarm system will be triggered to notify the operator or the automatic system to take measures, and then control the crushing arm to perform crushing work through the automatic system.

[0023] Optionally, the backend algorithm processing adopts the MaskRCNN network architecture algorithm, and the network architecture of the MaskRCNN includes a backbone network CNN (using ResNet101+FPN as a feature extractor), a region proposal network (RPN), a ROI classifier and a bounding box regressor, and a segmentation mask.

[0024] By adopting the above technical solution, the target ore detection and segmentation results are integrated to obtain a detection result that is consistent with the original image size and includes the target ore type and shape.

[0025] In summary, the present invention includes at least one of the following beneficial effects: Through the coordinated setting of the chamber, image recognition system, crushing arm, crushing bin and chain conveyor, the chain conveyor transports the ore and collects images of the ore through a high-speed camera when it falls. These images are then transmitted to the back-end algorithm processing node, which is responsible for analyzing the image and determining whether the ore is oversized. When the back-end algorithm processing identifies that the ore size exceeds the preset threshold, the large ore alarm system will be triggered. When the large ore alarm is triggered, the crushing arm will intervene to crush the large pieces of ore to ensure the efficiency and safety of ore processing. Through the automated image recognition and crushing system, manual intervention is reduced and processing efficiency is improved.

[0026] Through the coordinated arrangement of the first cylinder, the second cylinder and the third cylinder, the telescopic first cylinder can adjust the angle of the boom, the telescopic second cylinder can adjust the angle of the forearm, and the telescopic third cylinder can adjust the angle of the hydraulic hammer, so that the angle of the hydraulic hammer can be adjusted during crushing, which is more flexible and changes the traditional way of mechanical crushing arms crushing ore from top to bottom in a vertical direction. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] 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 description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0028] Figure 1 It is a schematic diagram of the overall structure of the present invention; Figure 2 It is a schematic diagram of the structure of the crushing arm of the present invention; Figure 3 It is a schematic diagram of the connection structure between the slewing bearing and the slewing motor of the present invention; Figure 4 It is a schematic diagram of the system structure of the present invention; Figure 5 is a flow chart of the stone crushing process of the present invention; Figure 6 This is a flowchart of the MaskRCNN network structure used in the present invention; Figure 7 This is a schematic diagram of the ore contour obtained by the MaskRCNN algorithm in the present invention.

[0029] In the figure: 1. Chamber; 2. High-speed camera; 3. Crushing arm; 301. Support; 302. Slewing bearing; 303. Upper arm; 304. Lower arm; 305. I-beam connecting rod; 306. Hydraulic hammer; 307. Slewing motor; 308. First oil cylinder; 309. Second oil cylinder; 310. Third oil cylinder; 4. Conveying channel; 5. Feeding bin; 6. Crushing bin; 7. Material baffle; 8. Chain conveyor belt; 9. Mounting base; 10. Ore bin. DETAILED DESCRIPTION

[0030] The following is combined with Figure 1-7 The present invention is described in further detail.

[0031] Please refer to the attached figure in the instruction manual Figure 1The present invention provides an embodiment: a gyratory blockage-breaking and clearing mechanical arm, comprising a chamber 1, a ore bin 10 and an image recognition system, wherein the ore bin 10 is located at one side of the chamber 1, a mounting seat 9 is installed in the inner cavity of the chamber 1, a crushing arm 3 is arranged on the top of the mounting seat 9, and a paint layer is coated on the surface of the crushing arm 3. The crushing arm 3 as a whole has a certain anti-corrosion performance, thereby extending the service life of the crushing arm 3.

[0032] Please refer to the attached figure in the instruction manual Figure 1 The image recognition system includes a high-speed camera 2, a back-end algorithm processing and a large ore alarm. The output end of the high-speed camera 2 is electrically connected to the input end of the back-end algorithm processing, the back-end algorithm processing is electrically connected to the input end of the large ore alarm, the output end of the large ore alarm is connected to the input end of the automatic system, and the output end of the automatic system is electrically connected to the input end of the crushing arm 3. The high-speed camera 2 can capture the moment when the ore falls and provide raw data for subsequent image processing. The image data from the high-speed camera 2 is received through the back-end algorithm processing, and the algorithm is used for analysis to identify and measure the size of the ore. When the back-end algorithm processing identifies that the ore size exceeds the preset threshold, the large ore alarm system will be triggered to notify the operator or the automatic system to take measures, and then the crushing arm 3 is controlled by the automatic system to perform crushing. The backend algorithm processing adopts the MaskRCNN network architecture algorithm. The network architecture of MaskRCNN includes the backbone network CNN (using ResNet101+FPN as the feature extractor, the region proposal network (RPN, ROI classifier and bounding box regressor and segmentation mask. Thus, the target ore detection and segmentation results are integrated to obtain a detection result that is consistent with the original image size and contains the target ore category and shape.

[0033] Please refer to the attached figure in the instruction manual Figure 1 A chain plate conveyor belt 8 is installed inside the ore bin 10, and the left end of the chain plate conveyor belt 8 extends into the interior of the chamber 1. Baffle plates 7 are symmetrically installed at the front and rear ends of the top of the chain plate conveyor belt 8. The baffle plates 7 can protect the ore on the chain plate conveyor belt 8 and try to prevent the ore from sliding off the chain plate conveyor belt 8. A crushing bin 6 is provided at one end of the chamber 1 near the chain plate conveyor belt 8, and the crushing bin 6 is located below the chain plate conveyor belt 8.

[0034] Please refer to the attached figure in the instruction manual Figure 1 A conveying channel 4 is provided on one side of the crushing bin 6, a feeding port is provided between the crushing bin 6 and the conveying channel 4, and a feeding bin 5 is installed at the bottom of the conveying channel 4. The ore can be transported to the inside of the feeding bin 5 through the conveying channel 4 for storage or unified processing, which is convenient for unified collection of the ore.

[0035] Please refer to the attached figure in the instruction manual Figure 1 , Figure 2 and Figure 3 The crushing arm 3 includes a slewing bearing 302, and supports 301 are installed at both ends of the top of the slewing bearing 302. A large arm 303 is hinged on the top of the two sets of supports 301. A slewing motor 307 is installed between the two sets of supports 301, and the bottom of the slewing motor 307 is connected to the top of the slewing bearing 302. A small arm 304 is hinged on the end of the large arm 303 away from the support 301, and a hydraulic hammer 306 is hinged on the end of the small arm 304 away from the large arm 303 through an I-shaped frame connecting rod 305. The oversized ore is crushed by the hydraulic hammer 306 to reduce its size to a standard size that can pass through the conveyor belt.

[0036] Please refer to the attached figure in the instruction manual Figure 1 and Figure 2 A plurality of anchor bolts are arranged between the swing base and the mounting seat 9. Thus, the swing base can be fixedly installed by the plurality of anchor bolts, and then the entire crushing arm 3 can be fixedly installed.

[0037] Please refer to the attached figure in the instruction manual Figure 1 and Figure 2 The surface of the boom 303 and the bottom of the support 301 are hinged with a first oil cylinder 308, the top of the arm 304 and the middle of the boom 303 are hinged with a second oil cylinder 309, and the top of the I-shaped frame connecting rod 305 and the arm 304 are hinged with a third oil cylinder 310. The first oil cylinder 308 can adjust the angle between the boom 303 and the support 301 by telescoping, the second oil cylinder 309 can adjust the angle between the arm 304 and the boom 303 by telescoping, and the third oil cylinder 310 can adjust the angle between the hydraulic hammer 306 and the arm 304 by telescoping, so that the hydraulic hammer 306 can be adjusted in angle during crushing, which is more flexible and changes the traditional way of crushing ore from top to bottom in the vertical direction by the mechanical crushing arm.

[0038] Please refer to the attached figure in the instruction manual Figure 2 The first oil cylinder 308, the second oil cylinder 309 and the third oil cylinder 310 all use high-hardness chrome-plated piston rods, and the exposed parts of the piston rods are all installed with protective sleeves. This makes the first oil cylinder 308, the second oil cylinder 309 and the third oil cylinder 310 high in strength, thereby extending the service life of the first oil cylinder 308, the second oil cylinder 309 and the third oil cylinder 310.

[0039] Please refer to the attached figure in the instruction manual Figure 4 , the system consists of three main subsystems: conveyor belt system, image recognition system and crushing system. The following is a detailed description of each subsystem and its components: 1. Conveyor belt system: Chain conveyor 8: This is the main part of the system and is responsible for transporting the ore from the mining site to the processing area. The ore moves on the chain conveyor 8 until it reaches the end of the chain conveyor 8.

[0040] 2. Image recognition system: 1) High-speed image acquisition: Located at the end of the chain conveyor belt 8, it is used to capture the image of the ore in real time. The high-speed camera 2 can capture the moment when the ore falls and provide raw data for subsequent image processing.

[0041] 2) Back-end algorithm processing: receiving image data from the high-speed camera 2 and applying algorithms to analyze it to identify and measure the size of the ore.

[0042] 3) Large Ore Alarm: When the back-end algorithm processing identifies that the ore size exceeds the preset threshold, the large ore alarm system will be triggered to notify the operator or the automatic system to take action.

[0043] The MaskRCNN target detection algorithm based on the masked region convolutional neural network is used in high-speed image acquisition. MaskRCNN is a target detection and segmentation algorithm that adopts a two-stage framework: the first stage scans the image and generates proposals (Proposals, that is, the area that may contain an object); the second stage classifies the proposals and generates bounding boxes and masks. MaskRCNN adds a semantic segmentation branch on the basis of FasterR-CNN to achieve semantic segmentation while performing target detection. The network architecture of MaskRCNN mainly consists of four parts: the backbone network CNN (using ResNet101+FPN as a feature extractor), the region proposal network (RPN), the ROI classifier and bounding box regressor, and the segmentation mask. The network structure is as follows: Figure 6 shown.

[0044] The ore image is transmitted to the CNN network for feature extraction. Due to the complex background of the ore image environment, the deep residual network ResNet101 with stronger feature extraction capability is combined with FPN as a feature extraction module to extract features from the ore image. ResNet101 can extract low-level features (ore edges, corners) and high-level features (ore types and shapes, background, etc.), forming 5 layers of feature layers with different sizes and dimensions. The addition of FPN is to make up for the fact that ResNet101 cannot detect the features of smaller ores, and can better integrate the features of each layer, make full use of the features extracted by each feature layer of ResNet101, and transmit the feature map extracted by the CNN network to the regional candidate network. The regional candidate network divides the image into two categories: target ore and background, and selects the ore with a box that fits the target ore. At this time, only the approximate area of ​​the target ore can be obtained, and detailed classification and target ore segmentation cannot be performed. After the candidate region network, multiple candidate boxes containing the target ore can be obtained, and then pooled into a fixed-size feature map by ROIAlign. The obtained feature maps are input into the subsequent two branches respectively. One of the branch networks uses the region of interest (ROI) classifier and the bounding box regressor to identify the target ore. The region of interest (ROI) classifier and the bounding box regressor are both composed of a fully connected layer. The region of interest (ROI) classifier obtains the accurate target ore category through the fully connected layer, and the bounding box regressor selects the appropriate center point coordinates and aspect ratio of the region of interest through the fully connected layer to make the region of interest fit the edge of the target ore as closely as possible; the other branch is the segmentation mask generation network, which is composed of a fully convolutional network. The network will generate a mask that is consistent with the size and shape of the target ore to perform instance segmentation on the target ore. Finally, the target ore detection and segmentation results will be merged to obtain a detection result that is consistent with the original image size and contains the target ore category and shape. The specific situation is as follows Figure 7 The example given above is a graphic representation of the ore outline obtained using this algorithm.

[0045] 3. Crushing system: Crushing Arm 3: When the large ore alarm is triggered, Crushing Arm 3 will intervene to crush the oversized ore, reducing its size to a standard size that can pass through the conveyor belt.

[0046] In this system, the chain conveyor 8 transports the ore to the high-speed image acquisition node, which detects the ore's fall and captures images. These images are then passed to the back-end algorithm processing node, which is responsible for analyzing the image and determining whether the ore is oversized. If a large ore is detected, the system will send an alarm signal through the large ore alarm node, triggering the crushing arm 3 for processing. The entire process is designed to ensure the efficiency and safety of ore processing, reduce manual intervention and improve processing efficiency through automated image recognition and crushing systems.

[0047] Please refer to the attached figure in the instruction manual Figure 5 , the ore processing process, which involves the conveying, testing, crushing (if necessary), and final destination of the ore. The following is a detailed description of this process: 1. Conveyor belt transports ore: The process starts with a chain conveyor 8, which is responsible for transporting ore from the mining site or storage area to the processing area.

[0048] 2. Ore falls on the conveyor belt: The ore falls at the end of the chain plate conveyor belt 8, and this action triggers the subsequent detection process.

[0049] 3. High-speed camera 2 and back-end algorithm processing: At the moment the ore falls, the high-speed camera 2 captures images of the ore, which are then transmitted to the back-end algorithm processing system. The system is responsible for analyzing the size of the ore to determine whether it exceeds the set size threshold.

[0050] 4. Identify and mark oversized ores: If the backend algorithm processing system identifies that the ore size exceeds the standard, the system will mark these oversized ores.

[0051] 5. Ore size determination: The system will determine whether the ore exceeds the size threshold. If the ore size exceeds the threshold, the process will enter the "yes" branch; if the ore size is within the normal range, it will enter the "no" branch.

[0052] 6. Yes Branch: If the ore size exceeds the standard, the system will issue a large ore alarm, indicating that it needs to be processed. Then, the crushing arm 3 (external system) will be activated to crush the large pieces of ore to reduce their size. After processing, the system will check the size of the ore again to ensure that it meets the standard.

[0053] 7. No branch: If the ore size is within the normal range, the ore will roll smoothly into the feed port without further processing.

[0054] 8. Ore enters the silo: Regardless of whether the ore has been crushed or not, it will eventually enter the silo 5 for storage or further processing.

[0055] The entire process is designed to automate the processing of ore, ensuring that only ore that meets the size requirements can enter the silo, thereby improving the efficiency and safety of ore processing. Through the combination of high-speed cameras2 and back-end algorithms, the system can effectively identify and process oversized ore, reduce manual intervention, and reduce operating costs.

[0056] Working principle: When in use, turn on the high-speed camera 2 and the chain plate conveyor belt 8. The chain plate conveyor belt 8 is working to convey the granite ore. During the conveying process, the ore is blocked by two sets of baffle plates 7 to prevent the ore from falling from the chain plate conveyor belt 8. Until the ore reaches the end of the chain plate conveyor belt 8, the high-speed camera 2 can capture the moment when the ore falls and pass the collected image data to the back-end algorithm processing. The back-end algorithm processing receives the image data from the high-speed camera 2 and uses the algorithm for analysis to identify and measure the size of the ore. Under normal circumstances, if the ore is small in size, it will roll smoothly from top to bottom into the interior of the conveying channel 4. When the back-end algorithm identifies that the ore size exceeds the preset threshold, the large ore alarm system will be triggered. When the large ore alarm is triggered, the operator or the automatic system is notified to take measures. At this time, the first cylinder 308, the second cylinder 309 and the third cylinder 310 are controlled to work, so that the ore can be allocated to the inside of the crushing bin 6, and the large pieces of ore are crushed by the hydraulic hammer 306. After the large pieces of ore are crushed, they enter the conveying channel 4 through the feeding port on the crushing bin 6, and finally enter the inside of the feeding bin 5 for storage or further processing. The whole process ensures the efficiency and safety of ore processing, and reduces manual intervention and improves processing efficiency through automated image recognition and crushing systems.

[0057] The above are all preferred embodiments of the present invention, and are not intended to limit the protection scope of the present invention. Therefore, any equivalent changes made based on the structure, shape, and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A gyratory blockage-breaking and clearing mechanical arm, comprising a chamber (1), a mine bin (10) and an image recognition system, wherein the mine bin (10) is located on one side of the chamber (1), and is characterized in that: The inner cavity of the chamber (1) is provided with a mounting seat (9), the top of the mounting seat (9) is provided with a crushing arm (3), the interior of the ore bin (10) is provided with a chain plate conveyor belt (8), and the left end of the chain plate conveyor belt (8) extends into the interior of the chamber (1), and a crushing bin (6) is provided in the interior of the chamber (1) near one end of the chain plate conveyor belt (8), and the crushing bin (6) is located below the chain plate conveyor belt (8).

2. A gyratory blockage-breaking and cleaning mechanical arm according to claim 1, characterized in that: The crushing arm (3) comprises a slewing bearing (302), the front and rear ends of the top of the slewing bearing (302) are both installed with supports (301), the tops of the two groups of supports (301) are hinged with a large arm (303), a slewing motor (307) is installed between the two groups of supports (301), and the bottom of the slewing motor (307) is connected to the top of the slewing bearing (302), the end of the large arm (303) away from the support (301) is hinged with a small arm (304), and the end of the small arm (304) away from the large arm (303) is hinged with a hydraulic hammer (306) through an I-shaped connecting rod (305).

3. A gyratory blockage-breaking and clearing mechanical arm according to claim 2, characterized in that: A first oil cylinder (308) is hingedly connected between the surface of the upper arm (303) and the bottom of the support (301), a second oil cylinder (309) is hingedly connected between the top of the lower arm (304) and the middle of the upper arm (303), and a third oil cylinder (310) is hingedly connected between the top of the I-shaped connecting rod (305) and the lower arm (304).

4. A gyratory blockage-breaking and clearing mechanical arm according to claim 2, characterized in that: A slewing base is installed at the bottom of the slewing support (302), and a plurality of anchor bolts are arranged between the slewing base and the mounting seat (9).

5. The gyratory blockage-breaking and clearing mechanical arm according to claim 1 is characterized in that: The surface of the crushing arm (3) is coated with a paint layer.

6. The gyratory blockage-breaking and clearing mechanical arm according to claim 1, characterized in that: Material blocking plates (7) are symmetrically mounted at the front and rear ends of the top of the chain plate conveyor belt (8).

7. The gyratory blockage-breaking and clearing mechanical arm according to claim 3 is characterized in that: The first oil cylinder (308), the second oil cylinder (309) and the third oil cylinder (310) all use high-hardness chrome-plated piston rods, and the exposed parts of the piston rods are all installed with protective sleeves.

8. The gyratory blockage-breaking and clearing mechanical arm according to claim 1, characterized in that: A conveying channel (4) is provided on one side of the crushing bin (6), a material inlet is provided between the crushing bin (6) and the conveying channel (4), and a material inlet bin (5) is installed at the bottom of the conveying channel (4).

9. The gyratory blockage-breaking and clearing mechanical arm according to claim 1, characterized in that: The image recognition system comprises a high-speed camera (2), a back-end algorithm processing and a large ore alarm, wherein the output end of the high-speed camera (2) is electrically connected to the input end of the back-end algorithm processing, the back-end algorithm processing is electrically connected to the input end of the large ore alarm, the output end of the large ore alarm is connected to the input end of the automatic system, and the output end of the automatic system is electrically connected to the input end of the crushing arm (3).

10. A gyratory blockage-breaking and clearing mechanical arm according to claim 9, characterized in that: The backend algorithm processing adopts the MaskRCNN network architecture algorithm. The network architecture of the MaskRCNN includes a backbone network CNN (using ResNet101+FPN as a feature extractor), a region proposal network (RPN), a ROI classifier and a bounding box regressor, and a segmentation mask.

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