Aluminum smelting slag treatment system and method

Abstract

The invention discloses an aluminum smelting slag removal processing system and method, and belongs to the technical field of slag removal of smelting furnaces; the invention discloses a slag removal module, a data sensing module, an execution module, an optimization judgment module and a data terminal; the data sensing module is a monitor on the slag removal module, which is used to monitor the slag data in the smelting furnace and send the acquired slag data to the execution module; after selecting a corresponding slag bucket according to a slag removal target, the invention uses the size of the slag bucket to plan the slag removal area in the smelting furnace to form a primary slag removal route, processes a plane image of the slag in the primary slag removal route to obtain the slag amount and concentrated area, and then generates a secondary slag removal route, performs secondary slag removal treatment in the smelting furnace, and compares the slag residue after slag removal with a preset slag residue standard amount to determine the conditions for continuing slag removal and ending slag removal, further optimizes the slag removal operation, and reduces the problems of low work efficiency and heat loss caused by repeated slag removal.

Description

Technical Field

[0001] The present invention relates to the technical field of slag removal of smelting furnaces, and more specifically, to a slag removal processing system and method for aluminum smelting. Background Art

[0002] Aluminum melting furnace is a new type of high-efficiency and energy-saving aluminum melting furnace developed according to the aluminum smelting process. It can well meet the requirements of strict alloy composition, discontinuous production, large single furnace capacity and other requirements in the aluminum smelting process, and achieves the effects of reducing consumption, reducing burning loss, improving product quality, reducing labor intensity, improving labor conditions and improving production efficiency. It is suitable for intermittent operation, smelting with a lot of alloys and return materials. Among them, the aluminum smelting furnace needs to perform slag removal and refining operations during smelting, so a de-slag removal device is needed to remove impurities in the aluminum water.

[0003] The invention patent with patent publication number CN116140604A discloses an intelligent slag removal system and slag removal method, the slag removal system includes: a molten iron tank car, used to load molten iron to be slag removed; a slag removal machine, used to remove slag from the molten iron tank to a slag basin; a slag basin car, used to load and transport the slag removed from the molten iron tank; the patent uses a number of sensors and visual cameras to sense external conditions and equipment operation conditions, and adjusts the operation of the equipment in real time according to the external conditions so that it can automatically adapt to changes in the external conditions without manual intervention, truly achieving intelligent slag removal, but the above patent still has the following problems: the slag surface is identified by a visual camera, and the slag surface is cleaned. When the entire slag surface needs to be completely cleaned, the slag bucket needs to be used for repeated slag removal, which causes heat loss and low work efficiency. How to determine the end of slag removal is a point that needs further discussion; second, only the surface of the molten aluminum can be slag removed, and the bottom of the furnace cannot be slag removed. How can the slag removal machine meet the needs of molten aluminum slag removal and furnace bottom slag removal? Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention aims to provide a system and method for slag removal during aluminum smelting.

[0005] The purpose of the present invention can be achieved by the following technical solutions:

[0006] Aluminum smelting slag processing system, including slag removal module, data sensing module, execution module, optimization judgment module and data terminal;

[0007] The data sensing module is a monitor on the slag removal module, which is used to monitor the slag data in the smelting furnace and send the acquired slag data to the execution module;

[0008] The execution module is used to process the slag data, obtain the concentrated area and amount of slag in the smelting furnace, and generate the slag removal route;

[0009] The optimization judgment module further optimizes the slag removal results of the execution module and generates the conditions for continuing slag removal;

[0010] The slag removal module is used to complete the slag removal function of the smelting furnace, and performs slag removal operations in the smelting furnace based on the slag removal route;

[0011] The data terminal is used to store the data recorded and generated by each module for subsequent processing and analysis.

[0012] As a further solution of the present invention, the data sensing module includes a thickness measuring unit, which measures the thickness of the slag through a laser ranging sensor; an image collection unit, which collects a plane image of the slag in the smelting furnace through a camera; and a temperature collection unit, which collects the temperature of the slag in the smelting furnace through a temperature sensor.

[0013] As a further solution of the present invention, the specific steps of executing the module for data comprehensive processing are as follows:

[0014] Acquire a slag plane image in the smelting furnace, and pre-process the slag plane image; the slag plane image pre-processing includes normalizing and denoising the image;

[0015] The preprocessed image is used to calculate and identify the contour and edge area features of the slag using the Canny algorithm, and a convolutional neural network is used to generate a slag heat map to observe the distribution of the slag in the smelting furnace;

[0016] The formula for generating a scum heat map using a convolutional neural network is H(x, y) = σ(W h *F(x,y)+b h );

[0017] Among them, H(x, y) is the value of the generated residue heat map at position (x, y); F(x, y) is the value of the feature map at (x, y) after feature extraction; W h Convolutional layer weights generated for heatmap; b h Bias term for heatmap generation;

[0018] Use clustering algorithms to cluster the generated slag heat map and identify the concentrated areas of slag, so as to facilitate more effective slag removal in the future;

[0019] The clustering algorithm uses the K-means algorithm, and the generation formula of the clustering algorithm is:

[0020] Where J is the clustering objective function, which indicates the compactness of clustering; k is the number of clusters, that is, the number of slag areas; C i Represents the i-th cluster; μ i is the center of the i-th cluster, μi The calculation formula is |C i | is the number of samples in the i-th cluster;

[0021] Specific steps to generate the slag removal route:

[0022] Determine the data and type of slag volume in each area according to the clustering results Q i is the slag amount of the i-th area, calculate the priority P(i) according to the priority formula, sort P(i) in descending order and generate the slag removal route, and remove the slag in the smelting furnace through the slag removal module;

[0023] Priority formula P(i) represents the priority of the i-th region; Q i is the amount of slag in the ith area; is the sum of the slag volume in all areas.

[0024] As a further solution of the present invention, the optimization judgment module performs further optimization steps as follows:

[0025] The data sensing module is used to collect the slag plane image in the smelting furnace again, and the operation steps of the module are repeated. The slag remaining amount formula R(x, y) = H t1 (x, y)-H t2 (x, y) obtain the residue remaining amount R;

[0026] Where R represents the remaining amount of slag at the location; H t1 (x, y) is the value of the slag heat map generated by the image before slagging at the location; H t2 (x, y) is the value of the slag heat map generated by the image after slag removal at the location;

[0027] By formula Calculate the total CL of the slag residue, and compare CL with the preset slag residue standard amount ST. The slag residue standard amount is a preset threshold. When CL>ST, slag removal is required again; when CL≤ST, the slag removal operation is completed.

[0028] As a further embodiment of the present invention, the standard amount of slag residue on the furnace surface is different from the standard amount of slag residue on the furnace bottom.

[0029] As a further solution of the present invention, the slag removal module is composed of an AGV trolley, a slag removal mechanism and a transplanting mechanism that drives the slag removal mechanism to move. The transplanting mechanism is arranged on the AGV trolley. The AGV trolley realizes the automatic walking function of the entire slag removal module. The slag removal mechanism switches different slag buckets according to the slag removal target.

[0030] As a further solution of the present invention, the transplanting mechanism includes a transplanting frame, one end of the transplanting frame is rotatably mounted on the AGV trolley, and the other end of the transplanting frame is equipped with a lifting hydraulic cylinder, which is rotatably mounted on the AGV trolley. A crossbeam bracket is fixedly mounted on one side of the transplanting frame, a telescopic bracket is slidably mounted on the crossbeam bracket, and a driving hydraulic cylinder for driving the telescopic bracket to move is arranged in the crossbeam bracket.

[0031] As a further solution of the present invention, the slag scraping mechanism includes a slag bucket, wherein the slag bucket is composed of a wide-spacing slag bucket and a narrow-spacing slag bucket, the length of the narrow-spacing slag bucket is greater than that of the wide-spacing slag bucket, but the width of the narrow-spacing slag bucket is less than that of the wide-spacing slag bucket, the wide-spacing slag bucket is used for scraping slag on the metal liquid surface of the furnace, and the narrow-spacing slag bucket is used for scraping slag residual at the bottom of the furnace; the wide-spacing slag bucket is fixedly installed on one side of the end plate, and the narrow-spacing slag bucket is rotatably installed on the other side of the end plate, and the narrow-spacing slag bucket is driven to rotate on the end plate by a motor, a plurality of heating wires are arranged on the narrow-spacing slag bucket, and the end plate is installed between two telescopic brackets through a connecting piece.

[0032] A method for treating aluminum smelting slag, the method comprising the following steps:

[0033] Step 1: Select the cleaning target, which is the aluminum liquid surface and the furnace bottom. Select the corresponding slag bucket according to the cleaning target;

[0034] When slagging the aluminum liquid level of the smelting furnace, rotate the narrow-spacing slag bucket so that the narrow-spacing slag bucket is flush with the telescopic bracket;

[0035] When the slag remaining at the bottom of the smelting furnace is being slag-removed, the narrow-spacing slag bucket is rotated so that the narrow-spacing slag bucket is flush with the wide-spacing slag bucket;

[0036] Step 2: According to the size of the slag bucket, the plane in the smelting furnace is divided into multiple cleaning areas of the same width, which are defined as a slag removal path. The slag removal module performs a slag removal process in sequence according to the cleaning area;

[0037] Step 3: obtaining a slag plane image after slag removal, and preprocessing the slag plane image; the slag plane image preprocessing is to normalize and denoise the image;

[0038] Step 4: Use the Canny algorithm to identify the contour and edge area features of the scum in the preprocessed image, and use the convolutional neural network to generate a scum heat map;

[0039] Step 5: Use a clustering algorithm to cluster the generated slag heat map and identify the concentrated area of ​​slag;

[0040] Step 6: Determine the data and type of the slag volume in each area according to the clustering results, and perform slag removal on the remaining slag in turn through the slag removal module;

[0041] Step 7: Collect the slag plane image again through the data acquisition module and calculate the total amount of slag residue, compare the total amount of slag residue with the preset slag residue standard amount, when the total amount of slag residue is greater than the slag residue standard amount, repeat steps 3 to 6, when the total amount of slag residue is less than or equal to the slag residue standard amount, the slag removal operation is completed.

[0042] Compared with the existing solutions, the present invention has the following beneficial effects:

[0043] After selecting a corresponding slag bucket according to the slag removal target, the present invention uses the size of the slag bucket to plan the slag removal area in the smelting furnace to form a primary slag removal route, processes the plane image of the slag in the primary slag removal route to obtain the slag amount and concentrated area, and then generates a secondary slag removal route, performs secondary slag removal treatment in the smelting furnace, and compares the slag residue after slag removal with the preset slag residue standard amount to determine the conditions for continuing slag removal and ending slag removal, further optimizes the slag removal operation, and reduces the problems of low work efficiency and heat loss caused by repeated slag removal;

[0044] The wide-spacing slag bucket and the rotatable narrow-spacing slag bucket in the present invention meet the requirements for slag removal on the surface of molten aluminum and the bottom of the furnace. The high-width wide-spacing slag bucket can conveniently remove the slag on the surface of molten aluminum. The heating wire filled in the narrow-spacing slag bucket can be changed according to the temperature of the slag at the bottom of the furnace. At the same time, the long narrow-spacing slag bucket meets the requirements for slag removal from deeper slag in the furnace body, thereby improving the slag removal efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 The present invention is a system block diagram of an aluminum smelting slag processing system.

[0046] Figure 2 It is a structural schematic diagram of the slag removal module in the present invention.

[0047] Figure 3 It is a structural schematic diagram of the slag removal mechanism in the present invention.

[0048] Figure 4 It is a schematic structural diagram of the slag bucket in the present invention.

[0049] Figure 5 The present invention is a flow chart of the aluminum smelting slag treatment method.

[0050] In the figure: 10, AGV trolley; 21, transplanting rack; 22, crossbeam bracket; 23, telescopic bracket; 24, lifting hydraulic cylinder; 30, slag removal mechanism; 31, wide-distance slag bucket; 32, narrow-distance slag bucket; 33, end plate; 34, heating wire; 35, connecting parts. DETAILED DESCRIPTION

[0051] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. The embodiments of the present invention are provided for the purpose of illustration and description, and are not intended to be exhaustive or to limit the present invention to the disclosed forms. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments are selected and described in order to better illustrate the principles and practical applications of the present invention, and to enable those of ordinary skill in the art to understand the present invention and thereby design various embodiments with various modifications suitable for specific uses.

[0052] Example 1

[0053] Reference Figure 1-Figure 4 As shown, the present invention is an aluminum smelting slag removal processing system, which includes a slag removal module, a data sensing module, an execution module, an optimization judgment module and a data terminal.

[0054] The data sensing module is a monitor on the slag removal module, which is used to monitor the slag data in the smelting furnace and send the acquired slag data to the execution module; the slag data includes slag thickness, slag plane image and slag temperature; the data sensing module includes a thickness measuring unit, which is used to measure the distance from the slag surface to the sensor, and then calculate the thickness of the slag; the thickness measuring unit is obtained by a laser ranging sensor, and the laser ranging sensor is set on the slag bucket of the slag removal module;

[0055] An image collection unit is used to collect a planar image of the slag in the smelting furnace. The position and distribution of the slag in the smelting furnace can be determined by image analysis. The image collection unit is obtained by a camera, and the camera is arranged on the crossbeam support 22 of the slag removal module.

[0056] The temperature collection unit is used to collect the temperature of the slag in the smelting furnace and determine the temperature of the slag; the temperature collection unit is obtained through a temperature sensor, and the temperature sensor is arranged on the slag bucket of the slag removal module.

[0057] The execution module is used to comprehensively process the data in the data sensor module, obtain the concentrated area and amount of slag in the smelting furnace, and generate a slag removal route;

[0058] The specific steps of the execution module for data comprehensive processing are:

[0059] Acquire a slag plane image in the smelting furnace and pre-process the slag plane image; the slag plane image pre-processing is to normalize and denoise the image to improve the image clarity;

[0060] The preprocessed image is calculated by the Canny algorithm to identify the contour and edge area features of the slag, and the convolutional neural network is used to generate the slag heat map to observe the distribution of the slag in the smelting furnace; the formula for generating the slag heat map using the convolutional neural network is H(x, y) = σ(W h *F(x,y)+b h );

[0061] Among them, H(x, y) is the value of the generated residue heat map at position (x, y); F(x, y) is the value of the feature map at (x, y) after feature extraction; W h Convolutional layer weights generated for heatmap; b h The bias term for heat map generation; σ is the activation function, usually ReLU or sigmoid, and the value range can be between 1-5;

[0062] Use clustering algorithms to cluster the generated slag heat map and identify the concentrated areas of slag, so as to facilitate more effective slag removal in the future;

[0063] The clustering algorithm uses the K-means algorithm, and the generation formula of the clustering algorithm is:

[0064] Where J is the clustering objective function, which indicates the compactness of clustering; k is the number of clusters, that is, the number of slag areas; C i Represents the i-th cluster; μ i is the center of the i-th cluster, μ i The calculation formula is |C i | is the number of samples in the i-th cluster;

[0065] Determine the data and type of slag volume in each area according to the clustering results Q i is the slag amount of the i-th area, calculate the priority P(i) according to the priority formula, sort P(i) in descending order and generate the slag removal route, and remove the slag in the smelting furnace through the slag removal module;

[0066] Priority formula P(i) represents the priority of the i-th region; Q i is the amount of slag in the ith area; is the sum of the slag volume in all areas.

[0067] The optimization judgment module is used to further optimize the slag removal results and determine the conditions for continuing slag removal;

[0068] The steps for further optimization of the optimization judgment module are as follows:

[0069] The data sensing module is used to collect the slag plane image in the smelting furnace again, and the operation steps of the module are repeated. The slag remaining amount formula R(x, y) = H t1 (x, y)-H t2 (x, y) to obtain the residue remaining amount R(x, y), where R(x, y) represents the residue remaining amount at the position (x, y), H t1 (x, y) is the value of the slag heat map generated by the image before slag removal at the position (x, y), H t2 (x, y) is the value of the slag heat map generated by the image after slag removal at the position (x, y);

[0070] By formula Calculate the total slag residue amount CL, and compare CL with the preset slag residue standard amount ST. The slag residue standard amount is a preset threshold. The slag residue standard amount on the furnace surface is different from the slag residue standard amount at the furnace bottom. When CL>ST, slag removal is required again; when CL≤ST, the slag removal operation is completed.

[0071] The data terminal is used to store the data recorded and generated by each module for subsequent processing and analysis.

[0072] The slag removal module is a device for removing slag from the smelting furnace. The slag removal module is composed of an AGV trolley 10, a slag removal mechanism 30, and a transfer mechanism for driving the slag removal mechanism 30 to move. The transfer mechanism is arranged on the AGV trolley 10, and the AGV trolley 10 realizes the automatic walking function of the entire slag removal module.

[0073] The transplanting mechanism includes a transplanting frame 21, one end of which is rotatably mounted on the AGV trolley 10, and the other end of the transplanting frame 21 is installed with a lifting hydraulic cylinder 24, which is rotatably mounted on the AGV trolley 10. The rotation of the transplanting frame 21 is realized by lifting and lowering the lifting hydraulic cylinder 24, thereby realizing the rotation function of the slag removal mechanism 30, so that the slag removal mechanism 30 can perform slag removal operations on the furnace surface and furnace bottom;

[0074] A beam support 22 is fixedly installed on one side of the transplanting frame 21, and a telescopic support 23 is slidably installed on the beam support 22. A driving hydraulic cylinder for driving the telescopic support 23 is provided in the beam support 22, and the extension and retraction action of the slag scraping mechanism 30 at the end of the telescopic support 23 is realized by driving the hydraulic cylinder, so as to realize the slag scraping function;

[0075] The slag removal mechanism 30 includes a slag bucket, wherein the slag bucket is composed of a wide-distance slag bucket 31 and a narrow-distance slag bucket 32. The wide-distance slag bucket 31 is fixedly installed on one side of the end plate 33, and the narrow-distance slag bucket 32 ​​is rotatably installed on the other side of the end plate 33. The narrow-distance slag bucket 32 ​​is driven by a motor to rotate on the end plate 33. The length of the narrow-distance slag bucket 32 ​​is greater than that of the wide-distance slag bucket 31, but the width of the narrow-distance slag bucket 32 ​​is less than that of the wide-distance slag bucket 31. A plurality of heating wires 34 are arranged on the narrow-distance slag bucket 32. The heating wires 34 are used to The narrow-spacing slag bucket 32 ​​is heated so that the narrow-spacing slag bucket 32 ​​can better handle the slag cooled in the furnace bottom. When the temperature sensor detects that the slag temperature at the bottom of the furnace body is low and the slag viscosity affects the slag removal efficiency, the heating wire 34 is heated to facilitate the subsequent slag removal operation. The wide-spacing slag bucket 31 and the narrow-spacing slag bucket 32 ​​are respectively adapted to different slag removal scenes. The wide-spacing slag bucket 31 is used for slag removal operations on the molten metal surface of the furnace, and the narrow-spacing slag bucket 32 ​​is used for slag removal operations of residual slag at the bottom of the furnace.

[0076] The end plate 33 is installed between the two telescopic brackets 23 through the connecting piece 35;

[0077] The wide-spacing slag bucket 31 and the narrow-spacing slag bucket 32 ​​are both provided with temperature sensors and laser distance sensors, which are used to measure the thickness and temperature of the slag in the smelting furnace. The laser distance sensor monitors the distance between the slag and the slag bucket and the thickness of the slag, thereby controlling the lifting height of the lifting hydraulic cylinder 24, so that the slag at one end of the transplanting frame 21 can contact the slag after rotation and perform slag removal operations. A camera is provided on the beam bracket 22 for collecting the plane image of the slag in the smelting furnace.

[0078] Example 2

[0079] Reference Figure 5 As shown, the present invention discloses a method for aluminum smelting slag treatment;

[0080] Step 1: Select a cleaning target, which is the aluminum liquid surface and the furnace bottom, switch the angle of the narrow-distance slag bucket 32, and select a corresponding slag bucket according to the cleaning target;

[0081] When it is necessary to slag the aluminum liquid level of the smelting furnace, the narrow-distance slag bucket 32 ​​is rotated so that the narrow-distance slag bucket 32 ​​and the telescopic bracket 23 are flush, that is, in the same horizontal plane;

[0082] When it is necessary to remove the slag remaining at the bottom of the smelting furnace, the narrow-spacing slag bucket 32 ​​is rotated so that the narrow-spacing slag bucket 32 ​​is flush with the wide-spacing slag bucket 31, that is, they are in the same vertical plane;

[0083] Step 2: According to the size of the slag bucket, the plane in the smelting furnace is divided into multiple cleaning areas of the same width, that is, the width of the cleaning area is the same as the width of the slag bucket, which is defined as a slag removal path. The slag removal module performs a slag removal process in sequence according to the cleaning area;

[0084] Step 3: Obtain the slag plane image after the slag removal process, and pre-process the slag plane image; the slag plane image pre-processing is to normalize and denoise the image to improve the image clarity;

[0085] Step 4: Use the Canny algorithm to identify the contour and edge area features of the slag in the preprocessed image, use the convolutional neural network to generate a slag heat map, and observe the distribution of slag in the smelting furnace;

[0086] Step 5: Use a clustering algorithm to cluster the generated slag heat map and identify the concentrated area of ​​slag;

[0087] Step 6: Determine the data and type of the slag volume in each area according to the clustering results, and perform slag removal on the remaining slag in turn through the slag removal module;

[0088] Step 7: Collect the slag plane image again through the data acquisition module and calculate the total amount of slag residue, compare the total amount of slag residue with the preset slag residue standard amount, when the total amount of slag residue is greater than the slag residue standard amount, repeat steps 3 to 6, when the total amount of slag residue is less than or equal to the slag residue standard amount, the slag removal operation is completed.

[0089] 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 simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. Aluminum smelting slag treatment system, characterized in that: It includes a slag removal module, a data sensing module, an execution module, an optimization judgment module and a data terminal; The data sensing module is a monitor on the slag removal module, which is used to monitor the slag data in the smelting furnace and send the acquired slag data to the execution module; The execution module is used to process the slag data, obtain the concentrated area and amount of slag in the smelting furnace, and generate the slag removal route; The optimization judgment module further optimizes the results of the slag removal by the execution module and generates the conditions for continuing the slag removal; The slag removal module is used to complete the slag removal function of the smelting furnace, and performs slag removal operations in the smelting furnace based on the slag removal route; The data terminal is used to store the data recorded and generated by each module for subsequent processing and analysis; The data sensing module includes a thickness measuring unit, which measures the thickness of the slag through a laser range finder; an image collection unit, which collects a plane image of the slag in the smelting furnace through a camera; and a temperature collection unit, which collects the temperature of the slag in the smelting furnace through a temperature sensor. The specific steps of the execution module for data comprehensive processing are: Acquire a slag plane image in the smelting furnace, and pre-process the slag plane image; the slag plane image pre-processing includes normalizing and denoising the image; The preprocessed image is used to calculate and identify the contour and edge area features of the slag using the Canny algorithm, and a convolutional neural network is used to generate a slag heat map to observe the distribution of the slag in the smelting furnace; The formula for generating a scum heat map using a convolutional neural network is H(x, y) = σ(W h *F(x,y)+b h ); Among them, H(x, y) is the value of the generated residue heat map at position (x, y); F(x, y) is the value of the feature map at (x, y) after feature extraction; W h Convolutional layer weights generated for heatmap; b h is the bias term for heat map generation; σ is the activation function, and its value range is between 1-5.

2. The aluminum smelting slag processing system according to claim 1 is characterized in that: Use clustering algorithms to cluster the generated slag heat map and identify the concentrated areas of slag, so as to facilitate more effective slag removal in the future; The clustering algorithm uses the K-means algorithm, and the generation formula of the clustering algorithm is: Where J is the clustering objective function, which indicates the compactness of clustering; k is the number of clusters, that is, the number of slag areas; C i Represents the i-th cluster; μ i is the center of the ith cluster, μ i The calculation formula is |C i | is the number of samples in the i-th cluster; Specific steps to generate the slag removal route: Determine the data and type of slag volume in each area according to the clustering results Q i is the slag amount of the i-th area, calculate the priority P(i) according to the priority formula, sort P(i) in descending order and generate the slag removal route, and remove the slag in the smelting furnace through the slag removal module; Priority formula P(i) represents the priority of the i-th region; Q i is the amount of slag in the ith area; is the sum of the slag volume in all areas.

3. The aluminum smelting slag processing system according to claim 2 is characterized in that: The steps for further optimization of the optimization judgment module are as follows: The data sensing module is used to collect the slag plane image in the smelting furnace again, and the operation steps of the module are repeated. The slag remaining amount formula R(x, y) = H t1 (x, y)-H t2 (x, y) obtain the residue remaining amount R(x, y); Where R(x, y) represents the remaining amount of slag at the position (x, y); H t1 (x, y) is the value of the slag heat map generated by the image before slag removal at the position (x, y); H t2 (x, y) is the value of the slag heat map generated by the image after slag removal at the position (x, y); By formula Calculate the total CL of the slag residue, and compare CL with the preset slag residue standard amount ST. The slag residue standard amount is a preset threshold. When CL>ST, slag removal is required again; when CL≤ST, the slag removal operation is completed.

4. The aluminum smelting slag processing system according to claim 3 is characterized in that: The standard amount of slag residue on the furnace surface is different from the standard amount of slag residue on the furnace bottom.

5. The aluminum smelting slag processing system according to claim 1, characterized in that: The slag removal module is composed of an AGV trolley (10), a slag removal mechanism (30), and a transfer mechanism for driving the slag removal mechanism (30) to move. The transfer mechanism is arranged on the AGV trolley (10). The AGV trolley (10) realizes the automatic walking function of the entire slag removal module. The slag removal mechanism (30) switches different slag buckets according to the target of slag removal.

6. The aluminum smelting slag processing system according to claim 5, characterized in that: The transplanting mechanism comprises a transplanting frame (21), one end of the transplanting frame (21) is rotatably mounted on an AGV trolley (10), the other end of the transplanting frame (21) is mounted with a lifting hydraulic cylinder (24), the lifting hydraulic cylinder (24) is rotatably mounted on the AGV trolley (10), a crossbeam bracket (22) is fixedly mounted on one side of the transplanting frame (21), a telescopic bracket (23) is slidably mounted on the crossbeam bracket (22), and a driving hydraulic cylinder for driving the telescopic bracket (23) to move is arranged in the crossbeam bracket (22).

7. The aluminum smelting slag processing system according to claim 6, characterized in that: The slag removal mechanism (30) comprises a slag bucket, wherein the slag bucket is composed of a wide-spacing slag bucket (31) and a narrow-spacing slag bucket (32); the length of the narrow-spacing slag bucket (32) is greater than that of the wide-spacing slag bucket (31), but the width of the narrow-spacing slag bucket (32) is less than that of the wide-spacing slag bucket (31); the wide-spacing slag bucket (31) is used for slag removal operations on the molten metal surface of the furnace, and the narrow-spacing slag bucket (32) is used for slag removal operations on the residual slag at the bottom of the furnace; the wide-spacing slag bucket (31) is fixedly mounted on one side of the end plate (33), and the narrow-spacing slag bucket (32) is rotatably mounted on the other side of the end plate (33); the narrow-spacing slag bucket (32) is driven to rotate on the end plate (33) by a motor; a plurality of heating wires (34) are arranged on the narrow-spacing slag bucket (32); and the end plate (33) is mounted between two telescopic brackets (23) through a connecting piece (35).

8. A method for aluminum smelting slag treatment according to any one of claims 1 to 7, characterized in that: The processing method comprises the following steps: Step 1: Select the cleaning target, which is the aluminum liquid surface and the furnace bottom. Select the corresponding slag bucket according to the cleaning target; When slagging the aluminum liquid level of the smelting furnace, the narrow-distance slag bucket (32) is rotated so that the narrow-distance slag bucket (32) is flush with the telescopic support (23); When the slag remaining at the bottom of the smelting furnace is being slag-removed, the narrow-spacing slag bucket (32) is rotated so that the narrow-spacing slag bucket (32) is flush with the wide-spacing slag bucket (31); Step 2: According to the size of the slag bucket, the plane in the smelting furnace is divided into multiple cleaning areas of the same width, which are defined as a slag removal path. The slag removal module performs a slag removal process in sequence according to the cleaning area; Step 3: Obtain the slag plane image after the slag removal process, and pre-process the slag plane image; the slag plane image pre-processing is to normalize and denoise the image; Step 4: Use the Canny algorithm to identify the contour and edge area features of the scum in the preprocessed image, and use the convolutional neural network to generate a scum heat map; Step 5: Use clustering algorithm to cluster the generated slag heat map and identify the concentrated area of ​​slag; Step 6: Determine the data and type of the slag volume in each area according to the clustering results, and perform slag removal on the remaining slag in turn through the slag removal module; Step 7: Collect the slag plane image again through the data acquisition module and calculate the total amount of slag residue, compare the total amount of slag residue with the preset slag residue standard amount, when the total amount of slag residue is greater than the slag residue standard amount, repeat steps 3 to 6, when the total amount of slag residue is less than or equal to the slag residue standard amount, the slag removal operation is completed.

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