A graphite electrode defect detection system

Abstract

The present invention discloses a graphite electrode defect detection system, which relates to the technical field of graphite electrode detection. The present invention includes a product detection unit, a production detection unit, a detection output unit and a database. By detecting the quality and environment of graphite electrode products in different scenarios, the quality data threshold of graphite electrode products in each scenario is confirmed. Then, the detection technology for the graphite electrodes after production is selected, and then the defects of the graphite electrodes are detected. Then, the processing scheme of the graphite electrode products is analyzed. Multiple detection technologies are used to detect the defects of the graphite electrodes, making the detection more detailed and accurate, ensuring the comprehensiveness of the defect detection. At the same time, the processing scheme of the graphite electrodes is analyzed to improve the utilization rate of the graphite electrodes, give full play to the maximum utilization value of the graphite electrodes, and ensure the quality compliance of the graphite electrodes during actual use.

Description

Technical Field

[0001] The present invention relates to the technical field of graphite electrode detection, and particularly relates to a graphite electrode defect detection system. Background Art

[0002] A graphite electrode is a high-temperature resistant graphite conductive material. Graphite electrodes work in high-temperature and high-pressure environments such as steelmaking. If there are defects or cracks, it may cause the electrode to break, thereby affecting the production process and even triggering safety accidents. Therefore, through defect detection, the quality of graphite electrodes can be understood in a timely manner, and products can be processed according to the quality for different production scenarios to ensure production safety.

[0003] An existing technology, such as a graphite electrode defect detection system disclosed in the application with the publication number CN111157622A, includes: a cloud server, a first processor module, a second processor module, a knocking mechanism and a sound detection module connected to the second processor module, and a transmission module electrically connected to the first processor module; the second processor module is adapted to control the knocking mechanism to knock the graphite electrode; the sound detection module is adapted to detect the sound emitted when the knocking mechanism knocks the graphite electrode and send the sound signal to the second processor module for the second processor module to forward to the first processor module; the first processor module is adapted to send the sound signal to the cloud server through the transmission module; the cloud server is adapted to judge the defect degree of the graphite electrode according to the sound signal, realizing automatic detection of the defect degree of the graphite electrode, avoiding the disadvantages of strong subjectivity and high missed detection rate caused by manual detection methods, and at the same time reducing the labor cost.

[0004] In the above solution, only by knocking the graphite electrode, detecting the knocking sound, and analyzing the defect degree of the graphite electrode. However, there are various defects in the graphite electrode. According to the size and type of the defects of the graphite electrode, different detection techniques need to be selected for comprehensive detection to make the detection more detailed and accurate. The above solution only uses a single detection technique for defect detection, which cannot improve the comprehensiveness and accuracy of the detection and increase the defect detection effect. At the same time, the required quality of graphite electrodes in different application scenarios is different, and the produced graphite electrodes can be processed into various graphite electrode products. Different products are suitable for different scenarios according to their quality. The above solution only detects the defects of the graphite electrode according to the knocking sound, does not analyze the subsequent processing of the graphite electrode, cannot improve the utilization rate of the graphite electrode, nor can it give full play to the maximum utilization value of the graphite electrode, and cannot guarantee the quality qualification of the graphite electrode during actual use. Summary of the Invention

[0005] Aiming at the above technical deficiencies, the purpose of the present invention is to provide a graphite electrode defect detection system.

[0006] To solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides a graphite electrode defect detection system, including: a product detection unit, a production detection unit, and a detection output unit.

[0007] The product detection unit includes a product defect detection module and a product loss analysis module.

[0008] The product defect detection module is used to detect the graphite electrode products in various scenarios and obtain the detection data of the graphite electrode products in various scenarios.

[0009] The product loss analysis module is used to obtain the production initial detection data and comprehensive environment data corresponding to the graphite electrode products in various scenarios, extract the historical application data of each scenario, and at the same time use the detection data of the graphite electrode products in various scenarios to analyze the quality data threshold corresponding to the graphite electrode products in each scenario.

[0010] The production detection unit includes a production quality detection module and a product processing analysis module.

[0011] The production quality detection module is used to detect the graphite electrode after production is completed and obtain the quality data corresponding to the graphite electrode.

[0012] The product processing analysis module is used to analyze the processing scheme corresponding to the graphite electrode by using the quality data corresponding to the graphite electrode and the quality data threshold corresponding to the graphite electrode products in various scenarios.

[0013] The detection output unit is used to output the processing scheme corresponding to the graphite electrode.

[0014] The beneficial effects of the present invention are as follows: The present invention provides a graphite electrode defect detection system, which detects the quality and environment of graphite electrode products in different scenarios, confirms the quality data threshold of graphite electrode products in each scenario, then selects the detection technology for the graphite electrode after production, then detects the defect of the graphite electrode, and then analyzes the processing scheme of the graphite electrode product. Multiple detection technologies are used to detect the defect of the graphite electrode, making the detection more detailed and accurate, ensuring the comprehensiveness of the defect detection. At the same time, the processing scheme of the graphite electrode is analyzed, improving the utilization rate of the graphite electrode, giving full play to the maximum utilization value of the graphite electrode, and ensuring the quality qualification of the graphite electrode in actual use. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0016] Figure 1 It is a schematic diagram of the system structure connection of the present invention. Specific embodiments

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0018] Please refer to Figure 1 As shown, a graphite electrode defect detection system includes: a product detection unit, a production detection unit, a detection output unit, and a database.

[0019] The product detection unit includes a product defect detection module and a product loss analysis module.

[0020] The product defect detection module is used to detect the graphite electrode products in each scenario and obtain the detection data of the graphite electrode products in each scenario.

[0021] It should be added that each scenario includes an electric arc furnace smelting scenario, a metal welding scenario, and the electronics industry, etc.; the graphite electrode products for electric arc furnace smelting are rough electrodes, the graphite electrode products for the metal welding scenario are fine particle electrodes, and the graphite electrode products for the electronics industry are high-purity electrodes.

[0022] The process of detecting the graphite electrode products in each scenario is as follows: Obtain the size data corresponding to the graphite electrode products in each scenario from the database, collect the environmental data of each scenario using environmental detection equipment, and at the same time extract the appropriate size data range and appropriate environmental size data corresponding to each detection technology from the database, input them into the technology selection evaluation model, and output the adaptability results of the graphite electrode products in each scenario corresponding to each detection technology.

[0023] In the above, the expression of the technology selection evaluation model is:

[0024] In the formula represents the adaptability result of the graphite electrode product in the f-th scenario corresponding to the j-th detection technology, C f 、Hf respectively represent the dimensional data of the graphite electrode product in the f-th scenario and the environmental data of the f-th scenario, C j 、H j respectively represent the appropriate dimensional data range and the appropriate environmental dimensional data detected by the j-th detection technology. f represents the number of each scenario, and j represents the number of each detection technology. Both f and j are positive integers.

[0025] The adaptability result contains data of 1 and 0. When the adaptability result is 1, it indicates adaptation; otherwise, it indicates non-adaptation.

[0026] Select each detection technology with an adaptability result of 1 for the graphite electrode product in each scenario as the respective target detection technology for the graphite electrode product in each scenario, and use each target detection technology to detect the graphite electrode product in each scenario to obtain the detection data of the graphite electrode product in each scenario.

[0027] It should be noted that the dimensional data includes length, width, thickness, etc. It is designed by the product designer before the processing of the graphite electrode product and stored in the database.

[0028] The environmental detection equipment includes a temperature sensor, a magnetic field measuring instrument, etc.; the environmental data includes temperature, electromagnetic intensity, etc.

[0029] Each detection technology includes visual inspection, infrared detection, ultrasonic detection, X-ray detection, electromagnetic detection, acoustic emission detection, etc.

[0030] The appropriate dimensional data range and the appropriate environmental dimensional data detected by each detection technology are jointly discussed and formulated by multiple experts based on historical experience and a large amount of historical data and stored in the database.

[0031] The thickness of the graphite electrode may cause difficulty in X-ray penetration and affect the image quality. High temperature will affect the result of infrared detection of the graphite electrode. High temperature may cause a decrease in the sensitivity of the infrared detector and affect the accuracy of temperature measurement. In addition, the change in the radiation characteristics of graphite at high temperature may cause signal distortion, thus affecting defect recognition and imaging quality. Different detection technologies are suitable for different detection sizes and environments. Therefore, it is necessary to detect the dimensions and environmental data of the graphite electrode products in different scenarios, and then select the appropriate detection technology for defect detection to improve the accuracy of the detection result.

[0032] The product loss analysis module is used to obtain the production initial detection data and comprehensive environmental data corresponding to the graphite electrode product in each scenario, extract the historical application data of each scenario, and at the same time analyze the quality data threshold corresponding to the graphite electrode product in each scenario by using the detection data of the graphite electrode product in each scenario.

[0033] In a specific embodiment, the process of analyzing the quality data threshold corresponding to the graphite electrode products in each scenario is as follows: During the use of the graphite electrode products in each scenario, several acquisition moments are arranged. At each acquisition moment, an environmental detection device is used to collect the environmental data of the graphite electrode products in each scenario, and the environmental data of the graphite electrode products at each acquisition moment in each scenario is obtained as the comprehensive environmental data of each scenario.

[0034] Using the comprehensive environmental data corresponding to each scenario, analyze the environmental types of the graphite electrode products in each scenario; at the same time, use the initial production detection data and detection data corresponding to the graphite electrode products in each scenario to analyze the loss characteristic values of the graphite electrode products in each scenario.

[0035] As mentioned above, the process of analyzing the environmental types of the graphite electrode products in each scenario is as follows: Extract the environmental data of the graphite electrode products at each acquisition moment from the comprehensive environmental data corresponding to each scenario, denoted as H ft , where t represents the number of each acquisition moment, and t is a positive integer.

[0036] Compare the environmental data of the graphite electrode products at each acquisition moment in each scenario with each other, obtain the environmental data difference between the acquisition moments of the graphite electrode products in each scenario, and perform mean calculation to obtain the average environmental data difference, denoted as ΔH.

[0037] Input it into the environmental assessment model: Obtain the environmental assessment characteristic value δ of the graphite electrode products in the f-th scenario f , where p represents the total number of acquisition moments, and H f ( t-1 ) represents the environmental data of the graphite electrode products in the f-th scenario at the (t - 1)-th acquisition moment, and κ1 and κ2 are respectively the lower limit value and upper limit value of the preset environmental assessment coefficient.

[0038] It should be noted that the lower limit value and upper limit value of the environmental assessment coefficient are critical values for evaluating whether the environment is stable, which are jointly discussed and formulated by multiple experts based on historical experience and a large amount of historical data. When the value is greater than κ2, it indicates that the environmental volatility is large and the environment is unstable. When the value is between κ1 and κ2, it indicates that the environment has fluctuations but the volatility is small; when the value is less than κ1, it indicates that the environment has almost no fluctuations and the environment is stable; for example: κ1 and κ2 are 2 and 6 respectively, and the calculated value of is 3, and 3 is between 2 and 6, indicating that the environment of the graphite electrode products in the f-th scenario has fluctuations but the volatility is small.

[0039] When the environmental assessment eigenvalue is 1, it indicates that the environmental type is stable; when the environmental assessment eigenvalue is 0, it indicates that the environmental type is slightly fluctuating; when the environmental assessment eigenvalue is -1, it indicates that the environmental type is unstable; x is 1, 2, and 3 respectively, and 1, 2, and 3 represent stable type, slightly fluctuating type, and unstable type respectively, and y is 3.

[0040] Preferably, the process of analyzing the loss eigenvalue of the graphite electrode product in each scenario is as follows: Extract the initial detection time of the initial detection data corresponding to the graphite electrode product in each scenario and the detection time of the detection data, and record them as T0 f and T f .

[0041] Among them, when the graphite electrode product is detected, a timestamp can be automatically generated and recorded and stored in the detection record. Thus, the initial detection time of the initial detection data corresponding to the graphite electrode product in each scenario and the detection time of the detection data are extracted from the detection record.

[0042] Obtain the initial value of various detection data from the initial detection data corresponding to the graphite electrode product in each scenario, and record it as W0 fa , obtain the detection value of various detection data from the detection data corresponding to the graphite electrode product in each scenario, and record it as W fa , set the proportionality coefficient of various detection data, and record it as γ a , a represents the number of various detection data, and a is a positive integer.

[0043] Among them, obtain the maximum value and the minimum value of various detection data from the detection values of various detection data corresponding to the graphite electrode product in each scenario, and after subtracting the minimum value from the maximum value of various detection data, divide it by the minimum value of various detection data to obtain the difference rate of various detection data. Divide the difference rate of various detection data by the sum of the difference rates of various detection data to obtain the proportionality coefficient of various detection data.

[0044] Use the analysis formula to obtain the loss eigenvalue of the graphite electrode product in the f-th scenario q represents the total number of detection data types.

[0045] Obtain the historical comprehensive environmental data and loss eigenvalue corresponding to each historical graphite electrode product from the historical application data of each scenario, and analyze the environmental type corresponding to each historical graphite electrode product in each scenario.

[0046] It should be noted that the analysis method of the environmental type corresponding to each historical graphite electrode product in each scenario is the same as the analysis method of the environmental type of the graphite electrode product in each scenario, and will not be elaborated here.

[0047] Based on the environmental types of graphite electrode products in each scenario, the loss characteristic values of graphite electrode products, the environmental types and loss characteristic values of each historical graphite electrode product, analyze the characteristic weights of each environmental type in each scenario and the set of loss characteristic values corresponding to each link type.

[0048] Preferably, the specific process of analyzing the characteristic weights of each environmental type in each scenario is as follows: Using the environmental types of graphite electrode products in each scenario and the environmental types corresponding to each historical graphite electrode product in each scenario, count the occurrence times corresponding to each environmental type in each scenario, denoted as D fx , according to the environmental types of graphite electrode products in each scenario, the loss characteristic values of graphite electrode products, the environmental types and loss characteristic values of each historical graphite electrode product, statistically obtain the set of loss characteristic values corresponding to each environmental type in each scenario, calculate the loss characteristic value volatility corresponding to each environmental type in each scenario, and the average value of loss characteristic value volatility, denoted as and

[0049] Using the analysis formula Obtain the characteristic weight ε of the xth environmental type in the fth scenario fx , where e represents the natural constant.

[0050] Select the minimum loss characteristic value from the set of loss characteristic values corresponding to each environmental type in each scenario, and extract the initial production inspection data of the graphite electrode product corresponding to the minimum loss characteristic value as the initial quality data threshold corresponding to each environmental type in each scenario.

[0051] According to the analysis formula Obtain the quality data threshold α corresponding to the graphite electrode product in the fth scenario f , where ε fx , Z fx respectively represent the characteristic weight of the xth environmental type in the fth scenario, the initial quality data threshold, f represents the number of each scenario, x represents the number corresponding to each link type, y represents the total number of environmental types, f is a positive integer, x are 1, 2, and 3 respectively, 1, 2, and 3 represent stable type, small fluctuation type, and unstable type respectively, and y is 3.

[0052] The quality requirements for graphite electrodes in different scenarios are different. For example, for applications such as electric arc furnace smelting and aluminum electrolysis, the conductivity requirements of the electrodes are relatively high, while the high-precision electronics industry has a low tolerance for surface defects. By detecting the quality of graphite electrode products in different scenarios, then detecting the quality of the produced graphite electrodes, and then carrying out targeted processing according to the graphite electrodes, the loss caused by processing a single product with graphite electrodes can be reduced, which is beneficial to improving the utilization rate of graphite electrodes.

[0053] The production detection unit includes a production quality detection module and a product processing analysis module.

[0054] The production quality detection module is used to detect the graphite electrodes after production is completed, and obtain the quality data corresponding to the graphite electrodes.

[0055] In a specific embodiment, the detection of the graphite electrodes after production is completed is as follows: obtain the set of detection techniques corresponding to various detection data from the database; at the same time, obtain the historical detection records from the database; thus, obtain the appearance data and production data of the historical graphite electrodes corresponding to each historical detection from the historical detection records.

[0056] Among them, the set of detection techniques corresponding to various detection data is set by experts. For example, if the detection data is the apparent crack size, the detection techniques in the set of detection techniques include visual detection techniques, ultrasonic detection, infrared thermal imaging, magnetic particle detection, and coating penetration detection, etc.

[0057] It should be noted that the appearance data includes shape and size, etc., and the production data includes the production data corresponding to each production stage. For example, each production stage includes raw material calcination, crushing and grinding, batching, kneading, molding, roasting, and impregnation, etc.; the production data of raw material calcination is the calcination temperature and calcination duration, etc.; the production data of crushing and grinding is the crushing particle size and grinding particle size, etc.

[0058] Extract the appearance data and production data corresponding to the graphite electrodes, and make a corresponding comparison with the appearance data and production data of the historical graphite electrodes corresponding to each historical detection, and select the historical graphite electrodes corresponding to each historical detection with the same corresponding appearance data and production data as the reference electrodes of the graphite electrodes.

[0059] Obtain the detection techniques and the number of repeated detections of each reference electrode corresponding to various detection data from the historical detection records, count the detection techniques and the repeated times of each detection technique corresponding to various detection data, calculate the average value of the repeated times of each detection technique corresponding to various detection data, and select the detection technique with the smallest average value as the detection technique corresponding to various detection data.

[0060] Divide the graphite electrode into grids to obtain each partition; thus, use the detection techniques corresponding to various detection data to detect each partition, and obtain the quality data of each analysis as the quality data corresponding to the graphite electrode.

[0061] Among them, the quality data includes various detection data, and various detection data includes apparent crack size, internal crack size, and internal corrosion size, etc.

[0062] The product processing analysis module is used to analyze the processing scheme corresponding to the graphite electrode by using the quality data corresponding to the graphite electrode and the quality data threshold corresponding to the graphite electrode products in each scenario.

[0063] In a specific embodiment, the analysis of the processing scheme corresponding to the graphite electrode is as follows: Using the quality data of each partition and the quality data threshold corresponding to the graphite electrode products in each scenario, analyze the adaptability of each partition to each scenario, and select the set of preferred adaptation scenarios corresponding to each partition.

[0064] Preferably, the process of selecting the set of preferred adaptation scenarios corresponding to each partition is as follows: Denote the quality data of each partition and the quality data threshold corresponding to the graphite electrode products in each scenario as Z b and Z f , b is the number of each partition, b is a positive integer. According to the analysis formula obtain the adaptability θ bf of the b-th partition to the f-th scenario, where v1 represents the preset quality data difference rate threshold.

[0065] When the adaptability is greater than 1, it indicates adaptation, otherwise it indicates non - adaptation. Select the scenarios with an adaptability of 1 in each partition as the preferred adaptation scenarios, and integrate them to obtain the set of preferred adaptation scenarios corresponding to each partition.

[0066] Compare the sets of preferred adaptation scenarios corresponding to adjacent partitions. When there is at least one identical preferred adaptation scenario in the sets of preferred adaptation scenarios corresponding to adjacent partitions, regard the adjacent partitions as a processing partition, and regard the identical preferred adaptation scenarios as the preferred scenarios; thus, obtain each processing partition and the preferred scenarios corresponding to each processing partition.

[0067] Obtain the size data of the graphite electrodes in each preferred scenario corresponding to each processing partition, predict the loss value of the graphite electrode products processed in each processing partition for each preferred scenario, select the graphite electrode product in the preferred scenario corresponding to the minimum loss value as the graphite electrode product to be processed in each processing partition, and regard the graphite electrode products to be processed in each processing partition as the processing scheme corresponding to the graphite electrode.

[0068] Among them, count the sizes of each processing partition, divide the size of each processing partition by the size data of the graphite electrodes in the corresponding preferred scenarios. If there is a remainder, regard the remainder as the loss value of the graphite electrode products processed in each processing partition for each preferred scenario. If there is no remainder, record the loss value of the graphite electrode products processed in each processing partition for each preferred scenario as 0.

[0069] The detection and output unit is used to output the processing scheme corresponding to the graphite electrode.

[0070] A database for storing the dimensional data corresponding to graphite electrode products in various scenarios, storing the appropriate dimensional data ranges and appropriate environmental dimensional data detected by various detection technologies, storing the set of detection technologies corresponding to various types of detection data, and storing historical detection records.

[0071] In the embodiments of the present invention, the quality and environment of graphite electrode products in different scenarios are detected to confirm the quality data thresholds of graphite electrode products in each scenario. Then, the detection technology for the graphite electrodes after production is selected, and then the defects of the graphite electrodes are detected. Then, the processing scheme of the graphite electrode products is analyzed. Multiple detection technologies are used to detect the defects of the graphite electrodes, making the detection more detailed and accurate, ensuring the comprehensiveness of defect detection. At the same time, the processing scheme of the graphite electrodes is analyzed to improve the utilization rate of the graphite electrodes, maximize the utilization value of the graphite electrodes, and ensure the quality compliance of the graphite electrodes during actual use.

[0072] The above content is only an example and explanation of the concept of the present invention. Those skilled in the art of the present technology can make various modifications, supplements, or use similar methods to replace the specific embodiments described, as long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all belong to the protection scope of the present invention.

Claims

1. A graphite electrode defect detection system, characterized in that: include: Product testing unit, production testing unit and testing output unit; The product inspection unit includes a product defect detection module and a product loss analysis module; The product defect detection module is used to detect the graphite electrode products in each scene and obtain the detection data of the graphite electrode products in each scene; The product loss analysis module is used to obtain the initial production inspection data and comprehensive environmental data corresponding to the graphite electrode products in each scenario, and extract the historical application data of each scenario, and use the inspection data of the graphite electrode products in each scenario to analyze the quality data threshold corresponding to the graphite electrode products in each scenario; The production inspection unit includes a production quality inspection module and a product processing analysis module; The production quality detection module is used to detect the graphite electrode after production and obtain the quality data corresponding to the graphite electrode; The product processing analysis module is used to analyze the processing scheme corresponding to the graphite electrode by using the quality data corresponding to the graphite electrode and the quality data threshold corresponding to the graphite electrode product in each scene; The detection output unit is used to output the processing plan corresponding to the graphite electrode; The specific process of analyzing the quality data thresholds corresponding to graphite electrode products in each scenario is as follows: During the use of the graphite electrode products in each scene, several collection moments are arranged, and environmental detection equipment is used at each collection moment to collect environmental data of the graphite electrode products in each scene, so as to obtain the environmental data of the graphite electrode products in each scene at each collection moment as the comprehensive environmental data of each scene; The environmental type of the graphite electrode products in each scenario is analyzed using the comprehensive environmental data corresponding to each scenario; at the same time, the loss characteristic values ​​of the graphite electrode products in each scenario are analyzed using the initial production test data and test data corresponding to the graphite electrode products in each scenario; Obtain the historical comprehensive environmental data and loss characteristic values ​​corresponding to each historical graphite electrode product from the historical application data of each scenario, and analyze the environmental type corresponding to each historical graphite electrode product in each scenario; Based on the environmental type of graphite electrode products in each scenario, the loss characteristic value of graphite electrode products, the environmental type and loss characteristic value of each historical graphite electrode product, the characteristic weight of each environmental type in each scenario and the set of loss characteristic values ​​corresponding to each link type are analyzed; Select the minimum loss characteristic value from the loss characteristic value set corresponding to each environment type in each scene, and extract the initial production inspection data of the graphite electrode product corresponding to the minimum loss characteristic value as the initial quality data threshold corresponding to each environment type in each scene; According to the analysis formula Get the quality data threshold α corresponding to the graphite electrode product in the fth scene f , where ε fx , Z fx They represent the feature weight and initial quality data threshold of the x-th environment type in the f-th scene, respectively. f represents the number of each scene, x represents the number corresponding to each link type, y represents the total number of environment types, f is a positive integer, x is 1, 2 and 3, 1, 2 and 3 represent stable, small fluctuation and unstable types respectively, and y is 3; The specific process of analyzing the environmental types of graphite electrode products in each scenario is as follows: The environmental data of graphite electrode products at each collection time are extracted from the comprehensive environmental data corresponding to each scene, denoted as H ft , t represents the number of each acquisition moment, and t is a positive integer; The environmental data at each collection time of the graphite electrode products in each scenario are compared with each other to obtain the environmental data difference between each collection time of the graphite electrode products in each scenario, and the mean is calculated to obtain the average environmental data difference, which is recorded as ΔH; Input to the environmental assessment model: Get the environmental assessment characteristic value δ of the graphite electrode product in the fth scenario f , where p represents the total number of acquisition moments, H f ( t-1 ) represents the environmental data of the graphite electrode product in the fth scenario at the t-1th collection time, κ1 and κ2 are the lower limit and upper limit of the preset environmental assessment coefficient respectively; When the environmental assessment characteristic value is 1, it indicates that the environment type is stable; when the environmental assessment characteristic value is 0, it indicates that the environment type is small fluctuation type; when the environmental assessment characteristic value is -1, it indicates that the environment type is unstable; x is 1, 2 and 3, 1, 2 and 3 represent stable type, small fluctuation type and unstable type respectively, and y is 3; The specific process of analyzing the loss characteristic values ​​of graphite electrode products in each scenario is as follows: Extract the initial detection time and detection time of the initial detection data of the production of graphite electrode products corresponding to each scene, and record them as T0 and T1 respectively. f and T f ; The initial values ​​of various test data are obtained from the initial production test data corresponding to the graphite electrode products in each scenario, and are recorded as W0 fa , obtain the detection values ​​of various detection data from the detection data corresponding to the graphite electrode products in each scene, denoted as W fa , set the proportional coefficient of each type of detection data, denoted as γ a , a represents the number of each type of test data, and a is a positive integer; Using analytical formula Get the loss characteristic value of the graphite electrode product in the fth scenario q represents the total number of detected data types.

2. A graphite electrode defect detection system according to claim 1, characterized in that: The specific process of testing the graphite electrode products in each scenario is as follows: Obtain the size data corresponding to the graphite electrode products in each scenario from the database, and use environmental detection equipment to collect environmental data for each scenario. At the same time, extract the appropriate size data interval and appropriate environmental size data corresponding to each detection technology from the database, input them into the technology selection evaluation model, and output the compatibility results of the graphite electrode products in each scenario and each detection technology; The adaptability result contains data of 1 and 0. When the adaptability result is 1, it indicates adaptability, otherwise it indicates incompatibility. The detection technologies whose corresponding adaptability results for the graphite electrode products in each scene are 1 are selected as the target detection technologies for the graphite electrode products in each scene, and the graphite electrode products in each scene are detected using the target detection technologies to obtain the detection data of the graphite electrode products in each scene.

3. A graphite electrode defect detection system according to claim 2, characterized in that: The expression of the technology selection evaluation model is: In the formula represents the compatibility result of the graphite electrode product in the fth scenario and the jth detection technology, C f , H f They represent the size data of the graphite electrode product in the fth scene and the environmental data of the fth scene, respectively. j , H j They respectively represent the appropriate size data interval and the appropriate environment size data corresponding to the j-th detection technology, f represents the number of each scene, j represents the number of each detection technology, and both f and j are positive integers.

4. A graphite electrode defect detection system according to claim 1, characterized in that: The specific process of analyzing the feature weights of each environment type in each scene is as follows: Using the environmental type of the graphite electrode products in each scenario and the environmental type corresponding to each historical graphite electrode product in each scenario, the number of occurrences of each environmental type in each scenario is counted, recorded as D fx According to the environmental type of graphite electrode products in each scenario, the loss characteristic value of graphite electrode products, the environmental type and loss characteristic value of each historical graphite electrode product, the loss characteristic value set corresponding to each environmental type in each scenario is statistically obtained, and the loss characteristic value volatility corresponding to each environmental type in each scenario and the average loss characteristic value volatility are calculated, which are recorded as and Using analytical formula Get the feature weight ε of the xth environment type in the fth scene fx , where e represents a natural constant.

5. A graphite electrode defect detection system according to claim 1, characterized in that: The specific process of testing the graphite electrode after production is as follows: Obtain a set of detection technologies corresponding to various types of detection data from the database; and simultaneously obtain historical detection records from the database; thereby obtaining appearance data and manufacturing data of historical graphite electrodes corresponding to each historical detection from the historical detection records; Extracting appearance data and manufacturing data corresponding to the graphite electrode, and comparing them with the appearance data and manufacturing data of historical graphite electrodes corresponding to each historical test, and selecting the historical graphite electrodes corresponding to each historical test with the same appearance data and manufacturing data as the reference electrodes of the graphite electrode; Obtaining the detection technology and repeated detection times corresponding to each type of detection data of each reference electrode from the historical detection records, counting the detection technology and repeated detection times corresponding to each type of detection data, calculating the mean of the repeated detection times corresponding to each type of detection data, and selecting the detection technology with the smallest mean as the detection technology corresponding to each type of detection data; The graphite electrode is divided into grids to obtain partitions; each partition is then tested using a test technology corresponding to each type of test data to obtain quality data for each analysis as quality data corresponding to the graphite electrode.

6. A graphite electrode defect detection system according to claim 5, characterized in that: The processing scheme corresponding to the analysis of graphite electrode, the specific analysis process is as follows: Using the quality data of each partition and the quality data threshold corresponding to the graphite electrode products in each scene, analyze the adaptability of each partition to each scene, and select the priority adaptation scene set corresponding to each partition; The priority adaptation scene sets corresponding to adjacent partitions are compared. When at least one priority adaptation scene in the priority adaptation scene sets corresponding to adjacent partitions is the same, the adjacent partition is taken as a processing partition, and the same priority adaptation scenes are taken as preferred scenes; thereby obtaining each processing partition and each preferred scene corresponding to each processing partition; Obtain the size data of the graphite electrode in each preferred scenario corresponding to each processing zone, predict the loss value of the graphite electrode product in each preferred scenario processed in each processing zone, select the graphite electrode product in the preferred scenario corresponding to the minimum loss value as the graphite electrode product processed in each processing zone, and use the graphite electrode product processed in each processing zone as the processing plan corresponding to the graphite electrode.

7. A graphite electrode defect detection system according to claim 6, characterized in that: The specific process of selecting the priority adaptation scene set corresponding to each partition is as follows: The quality data of each partition and the quality data threshold corresponding to the graphite electrode product in each scene are respectively recorded as Z b and Z f , b is the number of each partition, b is a positive integer, according to the analysis formula Get the degree of fit θ between the bth partition and the fth scene bf , where v1 represents the preset quality data difference rate threshold; When the degree of adaptation is greater than 1, it indicates adaptation, otherwise it indicates incompatibility. The scenes with a degree of adaptation of 1 in each partition are selected as the priority adaptation scenes, and the priority adaptation scene sets corresponding to each partition are obtained by integration.

Images