Method for discriminating heat dissipation performance of aluminum electrolysis cell anode covering material based on image recognition
Through the method based on image recognition, a heat dissipation performance fusion evaluation model is established to evaluate the heat dissipation performance of the aluminum electrolytic cell anode cover material, solving the problems of strong subjectivity and low efficiency in the prior art evaluation results, and achieving more efficient and accurate heat dissipation performance evaluation.
Patent Information
- Application Number
- CN202411804061.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-10
- Publication Date
- 2025-03-18
AI Technical Summary
In the prior art, the evaluation of the heat dissipation performance of the anode cover of an aluminum electrolytic cell relies on manual empirical judgment and simple physical measurement, which is inefficient and has strong subjectivity in the results, making it difficult to achieve accurate and standardized judgments.
Using an image recognition method, image acquisition and pre-processing of the anode coverage area of the aluminum electrolytic cell, feature information of the anode covering layer is extracted, heat dissipation performance fusion evaluation model is established, heat dissipation performance of the anode covering material is judged, and heat dissipation performance is divided into different levels.
The efficiency and accuracy of the evaluation of heat dissipation performance are improved, the evaluation results are more objective and standardized, the influence of human factors is reduced, the heat dissipation performance of the anode cover material can be monitored in real time, the production process is adjusted in a timely manner, and the operation efficiency of the aluminum electrolytic cell is improved.
Smart Images
Figure CN119649140A_ABST
Abstract
Description
Technical Field
[0001] The invention belongs to the technical field of heat dissipation determination of anode covering materials for aluminum electrolytic cells, and relates to a method for determining the heat dissipation of anode covering materials for aluminum electrolytic cells based on image recognition. Background Art
[0002] In the aluminum electrolysis production process, the anode covering layer mainly plays the role of heat preservation of the electrolytic cell and preventing oxidation of the anode surface. The heat dissipation performance of the anode covering material directly affects the thermal balance and energy balance of the electrolytic cell. Good management of energy balance can improve the current efficiency of the electrolytic cell.
[0003] The composition of the existing anode covering material layer is a mixture of electrolyte particles and alumina particles of different particle sizes, and the covering material is mainly added by an overhead crane and manually built.
[0004] In today's electrolysis production process, pole replacement has become an almost daily necessary operation process for electrolytic cells, and it takes about 30 minutes from the preparation for pole replacement to the position of adding covering materials. In the pole replacement process, there are some steps, such as: raking out the loose covering materials on the anode surface before preparing to replace the residual pole, adding covering materials on the new pole, etc.
[0005] At the same time, the production and operation of electrolytic cells require more refined management. In the addition of anode covering materials, each factory has correspondingly standardized the ratio of each component of the covering material, the requirements for particle size, the management of thickness, etc. However, more manual participation makes it difficult to monitor and implement indicators in a quantitative manner in the actual implementation process. The evaluation of its heat dissipation performance mainly relies on manual experience judgment and simple physical measurements. These methods are not only inefficient, but also highly subjective, making it difficult to achieve accurate and standardized evaluation. Summary of the invention
[0006] The technical problem to be solved by the present invention is to provide a method for judging the heat dissipation of anode covering materials of aluminum electrolytic cells based on image recognition, so as to solve the problems existing in the prior art.
[0007] The scheme implemented by the present invention is: A method for distinguishing the heat dissipation of anode covering materials of aluminum electrolytic cells based on image recognition, which collects images of the anode covering area of the aluminum electrolytic cell in production and preprocesses the collected images, extracts image features from the preprocessed images, and builds a heat dissipation performance fusion evaluation model based on the relationship between input features and output results. The heat dissipation of the anode covering materials is evaluated by the heat dissipation performance evaluation model based on the extracted image features, and the heat dissipation is divided into different levels.
[0008] A method for determining the heat dissipation of an aluminum electrolytic cell anode covering material based on image recognition, the specific method comprising the following steps: Step 1: Image acquisition: collect images of the surface of the anode covering material of the aluminum electrolytic cell to obtain a high-definition image of the surface of the covering material; Step 2: Image processing, preprocessing the collected images; Step 3: Feature extraction: using image recognition technology to extract feature information of the anode covering material layer surface from the preprocessed image. The feature information includes the degree of coverage of the anode covering material layer on the anode steel claw, the particle size distribution of the covering material layer, and the temperature characteristic distribution; Step 4: Establish a heat dissipation performance fusion evaluation model. According to the relationship between the input characteristics and output results of the heat dissipation performance of the anode covering material, establish a heat dissipation performance fusion evaluation model and train it to the optimal model; Step 5. Evaluation results: input the surface image of the anode covering material to be evaluated into the trained optimal heat dissipation performance fusion evaluation model to obtain the evaluation results of the heat dissipation performance of the anode covering material. The evaluation results include the weak, moderate, strong and upper heat dissipation performance of the covering material insulation layer.
[0009] Furthermore, based on the evaluation results, the production process of the anode covering material is adjusted and optimized.
[0010] Furthermore, the preprocessing in the above step 2 includes grayscale conversion, filtering and denoising, and edge enhancement.
[0011] Furthermore, the above-mentioned heat dissipation performance fusion evaluation model establishes a heat dissipation performance fusion evaluation model according to the coverage degree, the particle size distribution of the covering material layer and the temperature characteristic distribution.
[0012] Furthermore, the above heat dissipation performance fusion evaluation model is evaluated as follows: 1) Classify the coverage degree of anode steel claws according to the anode covering material layer: 1.1) When the upper edge of the steel beam of the anode steel claw is completely covered by the anode covering material, it belongs to the strong insulation type; 1.2) When the upper edge of the steel beam of the anode steel claw is not completely covered by the anode covering material, and the lower edge of the steel beam is completely covered by the anode covering material, it belongs to the type with strong thermal insulation; 1.3) When the lower edge of the steel beam of the anode steel claw is not completely covered by the anode covering material, it belongs to the general type of thermal insulation; 1.4) When the anode covering material does not contact the lower edge of the steel beam of the anode steel claw, it belongs to the weak insulation type; 2) Classification based on the particle size distribution of the covering material layer: 2.1) When the distribution ratio of particles larger than 8 mm in the covering material layer is greater than the set value, the thermal insulation performance is weak; 2.2) When the distribution ratio of alumina powder in the covering material layer is high, the thermal insulation performance is strong; 3) Classification based on the extracted temperature feature distribution: The temperature characteristics include the temperature distribution characteristics of the anode guide rod, anode steel beam, anode steel claw and anode covering material layer; the temperature benchmark and grading are set for the temperature of each area; the temperature T grading is set to three layers: high, medium and low, and the high, medium and low temperatures correspond to the temperature ranges of 350<T≤500℃, 250<T≤350℃ and 150≤T≤250℃, respectively, corresponding to the weak, moderate and strong classifications of the covering material insulation layer.
[0013] The effects of the present invention are as follows: the present invention utilizes image recognition technology and a fusion evaluation model to judge the heat dissipation performance of the anode covering material, which can improve the evaluation efficiency and accuracy, and the evaluation results are objective and standardized, reducing the influence of human factors; the heat dissipation performance of the anode covering material can be monitored in real time, the production process can be adjusted in time, and the operating efficiency of the aluminum electrolytic cell can be improved. BRIEF DESCRIPTION OF THE DRAWINGS
[0014] Figure 1 It is a schematic diagram of anode covering for aluminum electrolytic cell; Figure 2 This is a schematic diagram of the anode structure for aluminum electrolysis cells; Figure 3 This is a schematic diagram of an aluminum electrolytic cell for adding anode covering material; Figure 4 is a schematic diagram of the structure of an image acquisition device; Figure 5 It is a schematic diagram of the side structure of the image acquisition device.
[0015] In the figure, 1, electrolytic cell; 2, anode aluminum guide rod; 3, anode steel claw, 3 (1), steel beam, 3 (2), steel claw head; 4, anode covering material; 5, anode. DETAILED DESCRIPTION
[0017] The present invention is further described below in conjunction with specific embodiments.
[0018] Example 1: Figure 1-5 As shown, a method for distinguishing the heat dissipation of anode covering materials of aluminum electrolytic cells based on image recognition is provided. The method collects images of the anode covering area of the aluminum electrolytic cell in production and preprocesses the collected images, extracts image features from the preprocessed images, and constructs a heat dissipation performance fusion evaluation model based on the relationship between the input features and the output results. The heat dissipation of the anode covering materials is evaluated by the heat dissipation performance evaluation model based on the extracted image features, and the heat dissipation is divided into different levels.
[0019] A method for determining the heat dissipation of an aluminum electrolytic cell anode covering material based on image recognition, the specific method comprising the following steps: Step 1: Image acquisition, collect images of the surface of the anode covering material of the aluminum electrolytic cell to obtain a high-definition image of the covering material surface; the image acquisition uses a high-resolution industrial-grade high-definition camera, and the image preprocessing uses Gaussian filtering to remove noise and Sobel operator edge enhancement. When extracting features, focus on the partitioning of the anode covering area, distinguish the shape of each object (such as anode guide rods, anode steel claws, covering material layer), the thickness and uniformity of the covering material, and the particle size, and calculate the average thickness and standard deviation of the covering material through image processing algorithms; use a CCD (charge coupled device) probe to collect images, and the probe is set to be adjustable within a certain range of angles up and down. The optical imaging field of view is initially designed to be 10°, which can ensure sufficient effective pixels, and extract temperature features through image digital processing technology and dual-color temperature measurement algorithms; use the temperature image information captured by the infrared thermal imager to extract the temperature distribution characteristics of each area of the anode covering; like Figure 4-5 As shown, the industrial-grade high-definition camera 101 and the infrared thermal imager 102 are installed on the mounting plate 103, and the mounting plate 103 is fixedly connected to the lower end of the push rod of the electric push rod 104. The housing of the electric push rod 104 is fixedly connected to the horizontal sliding plate 105. The horizontal sliding plate 105 is connected to the horizontal beam 107 through two slider guide pairs 106. The horizontal beam 107 is installed on one side of the overhead crane beam 108. The horizontal sliding plate 105 is driven to move by the connected screw nut pair 109. The nut of the screw nut pair 109 is fixedly connected to the nut seat at the bottom of the horizontal sliding plate 105, and the two ends of the screw of the screw nut pair 108 are fixedly connected to the horizontal beam through the bearing seat. 107 and one end extends out of the bearing seat and is connected to the drive motor 110. The drive motor 110 is installed on the horizontal beam 107 through the motor frame. The two ends of the overhead crane beam 108 move through the walking mechanism 111. Through the walking mechanism, the industrial-grade high-definition camera 101 and the infrared thermal imager 102 can move longitudinally, thereby realizing the acquisition of images of different electrolytic cells. The horizontal sliding plate driven by the drive motor moves horizontally (walking along the length direction of the electrolytic cell), which can realize the image acquisition of different positions of a single electrolytic cell. The telescopic mechanism of the electric push rod can realize the acquisition of the best distance control, which can avoid damage to the image acquisition equipment and realize the best image quality acquisition. When in use, open the electrolytic cell cover, control the position of the camera horizontally and vertically, and realize the image acquisition of different electrolytic cells and a single electrolytic cell.
[0020] Limit baffles 113 are provided at both ends of the horizontal beam 107, and travel limit switches 112 are installed on the limit baffles 113. When the slider of the slider guide pair 106 touches the travel limit switch 112, the driving motor stops moving, which can realize the control of the safe travel and play a protective role.
[0021] In order to achieve accurate acquisition, a plurality of vibration-damping grooves 114 are arranged on the horizontal beam 107. Steel balls 115 of different diameters are installed in each vibration-damping groove 114, which can reduce the vibration generated by the movement of the entire overhead crane or the operation of its motor, thereby improving the stability and accuracy of image acquisition. In addition, a shock-absorbing rubber pad 116 is arranged on the connecting surface between the horizontal beam 107 and the overhead crane beam 108 to further achieve a vibration isolation effect.
[0022] Step 2: Image processing, preprocessing the collected images; the preprocessing of images collected by industrial-grade high-definition cameras includes grayscale, filtering and denoising, and edge enhancement; Step 3: Feature extraction: using image recognition technology to extract feature information of the anode covering material layer surface from the preprocessed image. The feature information includes the degree of coverage of the anode covering material layer on the anode steel claw, the particle size distribution of the covering material layer, and the temperature characteristic distribution; Step 4: Establish a heat dissipation performance fusion evaluation model. According to the relationship between the input characteristics and output results of the heat dissipation performance of the anode covering material, establish a heat dissipation performance fusion evaluation model and train it to the optimal model; Step 5. Evaluation results: input the surface image of the anode covering material to be evaluated into the trained optimal heat dissipation performance fusion evaluation model to obtain the evaluation results of the heat dissipation performance of the anode covering material. The evaluation results include the weak, moderate, strong and upper heat dissipation performance of the covering material insulation layer.
[0023] Based on the evaluation results, the production process of anode covering materials is adjusted and optimized.
[0024] The thermal performance fusion evaluation model is evaluated as follows: 1) Classify the coverage degree of anode steel claws according to the anode covering material layer: 1.1) When the upper edge of the steel beam of the anode steel claw is completely covered by the anode covering material, it belongs to the strong insulation type; 1.2) When the upper edge of the steel beam of the anode steel claw is not completely covered by the anode covering material, and the lower edge of the steel beam is completely covered by the anode covering material, it belongs to the type with strong thermal insulation; 1.3) When the lower edge of the steel beam of the anode steel claw is not completely covered by the anode covering material, it belongs to the general type of thermal insulation; 1.4) When the anode covering material does not contact the lower edge of the steel beam of the anode steel claw, it belongs to the weak insulation type; 2) Classification based on the particle size distribution of the covering material layer: 2.1) When the distribution ratio of particles larger than 8 mm in the covering material layer is greater than the set value, the thermal insulation performance is weak; 2.2) When the distribution ratio of alumina powder in the covering material layer is high, the thermal insulation performance is strong; 3) Classification based on the extracted temperature feature distribution: The temperature characteristics include the temperature distribution characteristics of the anode guide rod, anode steel beam, anode steel claw and anode covering material layer; the temperature benchmark and grading are set for the temperature of each area; the temperature T grading is set to three layers: high, medium and low, and the high, medium and low temperatures correspond to the temperature ranges of 350<T≤500℃, 250<T≤350℃ and 150≤T≤250℃, respectively, corresponding to the weak, moderate and strong classifications of the covering material insulation layer.
[0025] In addition, heat transfer resistance analysis: extracting image features and distinguishing objects can obtain new types of information such as the surface area distribution of each object (such as anode guide rods, anode steel claws, covering material layer), the particle size distribution of the material, the height of the covering layer material, etc., and analyze the heat transfer thermal resistance through a calculation model to evaluate the heat dissipation of the electrolytic cell covering layer.
[0026] Radiation and convection heat transfer analysis: Extract image features and distinguish objects to obtain the surface area distribution of each object (such as anode guide rod, anode steel claw, and covering material layer); extract temperature features to determine the temperature distribution of each surface. According to the characteristics of each material and the surface temperature, analyze its radiation and convection heat transfer to evaluate the heat dissipation of the electrolytic cell covering layer.
[0027] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.
Claims
1. A method for determining the heat dissipation of anode covering materials of aluminum electrolytic cells based on image recognition, characterized in that: By collecting images of the anode covering area of the aluminum electrolytic cell in production and preprocessing the collected images, image features are extracted from the preprocessed images. According to the relationship between the input features and the output results, a heat dissipation performance fusion evaluation model is constructed. The heat dissipation of the anode covering material is evaluated based on the extracted image features through the heat dissipation performance evaluation model, and the heat dissipation is divided into different levels.
2. The method for determining the heat dissipation of anode covering materials of aluminum electrolytic cells based on image recognition according to claim 1, characterized in that: The specific method includes the following steps: Step 1: Image acquisition: collect images of the surface of the anode covering material of the aluminum electrolytic cell to obtain a high-definition image of the surface of the covering material; Step 2: Image processing, preprocessing the collected images; Step 3: Feature extraction: using image recognition technology to extract feature information of the anode covering material layer surface from the preprocessed image. The feature information includes the degree of coverage of the anode covering material layer on the anode steel claw, the particle size distribution of the covering material layer, and the temperature characteristic distribution; Step 4: Establish a heat dissipation performance fusion evaluation model. According to the relationship between the input characteristics and output results of the heat dissipation performance of the anode covering material, establish a heat dissipation performance fusion evaluation model and train it to the optimal model; Step 5. Evaluation results: input the surface image of the anode covering material to be evaluated into the trained optimal heat dissipation performance fusion evaluation model to obtain the evaluation results of the heat dissipation performance of the anode covering material. The evaluation results include the weak, moderate, strong and upper heat dissipation performance of the covering material insulation layer.
3. The method for determining the heat dissipation of anode covering materials of aluminum electrolysis cells based on image recognition according to claim 1, characterized in that: Based on the evaluation results, the production process of anode covering materials is adjusted and optimized.
4. The method for determining the heat dissipation of anode covering materials of aluminum electrolysis cells based on image recognition according to claim 1, characterized in that: The preprocessing in step 2 includes grayscale, filtering denoising and edge enhancement.
5. The method for determining the heat dissipation of anode covering materials of aluminum electrolytic cells based on image recognition according to claim 1, characterized in that: The heat dissipation performance fusion evaluation model is a fusion evaluation model established with the coverage degree, particle size distribution of the covering material layer and temperature characteristic distribution as input and the heat dissipation performance of the covering material insulation layer as output.
6. The method for determining the heat dissipation of anode covering materials of aluminum electrolytic cells based on image recognition according to claim 2, characterized in that: The thermal performance fusion evaluation model is evaluated as follows: 1) Classify the coverage degree of anode steel claws according to the anode covering material layer: 1.1) When the upper edge of the steel beam of the anode steel claw is completely covered by the anode covering material, it belongs to the strong insulation type; 1.2) When the upper edge of the steel beam of the anode steel claw is not completely covered by the anode covering material, and the lower edge of the steel beam is completely covered by the anode covering material, it belongs to the type with strong thermal insulation; 1.3) When the lower edge of the steel beam of the anode steel claw is not completely covered by the anode covering material, it belongs to the general type of thermal insulation; 1.4) When the anode covering material does not contact the lower edge of the steel beam of the anode steel claw, it belongs to the weak insulation type; 2) Classification based on the particle size distribution of the covering material layer: 2.1) When the distribution ratio of particles larger than 8 mm in the covering material layer is greater than the set value, the thermal insulation performance is weak; 2.2) When the distribution ratio of alumina powder in the covering material layer is high, the thermal insulation performance is strong; 3) Classification based on the extracted temperature feature distribution: The temperature characteristics include the temperature distribution characteristics of the anode guide rod, anode steel beam, anode steel claw and anode covering material layer; The temperature benchmark and grading are set for the temperature of each area; the temperature T grading is set to three layers: high, medium and low. The high, medium and low temperatures correspond to the temperature ranges of 350<T≤500℃, 250<T≤350℃ and 150≤T≤250℃, respectively, corresponding to the weak, moderate and strong classifications of the covering material insulation layer.