An automated detection system for graphite electrodes

Abstract

The present invention discloses an automated detection system for graphite electrodes, which relates to the field of graphite electrode detection. The present invention includes: an electrode basic detection module, an electrode shutdown detection module, and an electrode scrapping detection module. The present invention detects the conductance and internal temperature of the graphite electrode through the electrode basic detection module to determine whether the graphite electrode has a fault. When the graphite electrode has a fault, a shutdown detection is carried out, and the electrode shutdown detection module is used to determine whether the graphite electrode needs to be replaced. If the graphite electrode needs to be replaced, a cutting detection is carried out to analyze and obtain the cuttable area of the graphite electrode, so as to determine whether the graphite electrode needs to be scrapped according to the historical cutting data of the graphite electrode. The present invention improves the automation level of graphite electrode detection, reduces the detection error and cost, and ensures the quality control of graphite electrodes and the efficient utilization of resources.

Description

Technical Field

[0001] The present invention relates to the technical field of graphite electrode detection, and particularly relates to an automatic detection system for graphite electrodes. Background Art

[0002] In the context of the current big data era, the technology of the automatic detection system for graphite electrodes has been continuously advancing. In order to ensure the quality and safety of graphite electrodes during the production process, the detection of graphite electrodes in production has become a key link in the same type of detection systems. The automatic detection system not only affects the safety of using graphite electrodes, but also is directly related to the market sales trend of products. Therefore, it is particularly important to deeply analyze various detection indexes of graphite electrodes.

[0003] The prior art, such as the invention patent application with the publication number CN117783679B, discloses an automatic detection system for graphite electrodes, which relates to the technical field of detection. The present invention includes an information acquisition module, a conductivity test module, a conductivity analysis module, a hardness test module, a hardness analysis module, a flame retardancy test module, a flame retardancy analysis module, and an early warning terminal. By testing the conductivity of the graphite electrode and analyzing to obtain the preferred current of the graphite electrode, and then testing the hardness and flame retardancy of the graphite electrode, it is thus determined whether the hardness and flame retardancy of the graphite electrode are qualified, solving the limitation problems existing in the feasibility analysis process of the current graphite electrode detection system, realizing the comprehensive and objective analysis of the feasibility of the graphite electrode detection system, ensuring the reliability and authenticity of the analysis results of the graphite electrode detection system, and further providing a reliable basis for the targeted management and balanced development of the subsequent graphite electrode detection system.

[0004] Regarding the above solution, the present invention discovers the following technical problems in the above technology: 1. The above solution only collects data of graphite electrodes through a test chamber, requires a specific detection environment, cannot detect during the use of graphite electrodes, cannot timely detect graphite electrodes, and thus cannot timely determine whether a graphite electrode is faulty and replace it, which may cause production failures, resulting in the production environment temperature not reaching the standard temperature, causing production waste, and increasing production hidden dangers.

[0005] 2. The above solution only determines whether the various attributes of the graphite electrode are qualified, does not analyze the remaining volume inside the graphite electrode by collecting specific surface fault data and internal fault data, and at the same time does not determine whether the graphite electrode is scrapped by the remaining volume inside the graphite electrode and the cutting times of the graphite electrode in the database, only determining whether it is qualified, wasting the detection cost of the graphite electrode and easily causing waste of the graphite electrode. Summary of the Invention

[0006] Aiming at the above-mentioned existing technical deficiencies, the purpose of the present invention is to provide an automatic detection system for graphite electrodes.

[0007] To solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides an automatic detection system for graphite electrodes, including the following modules: An electrode basic detection module, which is used to collect infrared data and conductance data of the graphite electrode during the use of the graphite electrode, analyze the infrared data of the graphite electrode to obtain the temperature index of the graphite electrode, analyze the conductance data of the graphite electrode to obtain the conductance index of the graphite electrode, and judge whether the graphite electrode fails according to the temperature index and conductance index of the graphite electrode. If the graphite electrode fails, stop production for shutdown detection.

[0008] An electrode shutdown detection module, which is used to collect graphite electrode attribute data, and then judge whether the graphite electrode needs to be replaced. After the graphite electrode is replaced, collect graphite electrode cutting data, analyze the graphite electrode cutting data to obtain the remaining volume of the graphite electrode, and remind the staff to perform cutting treatment on the graphite electrode.

[0009] An electrode scrapping detection module, which is used to analyze the graphite electrode cutting historical data in the database according to the remaining volume of the graphite electrode to obtain the scrapping index of the graphite electrode. If the scrapping index of the graphite electrode is greater than or equal to the preset scrapping index, it indicates that the graphite electrode can be cut. If the scrapping index of the graphite electrode is less than the preset scrapping index, prompt the staff to perform scrapping treatment on the graphite electrode.

[0010] Preferably, the analysis of the infrared data of the graphite electrode is as follows: Calculate the average value of the gray levels of each pixel point of each normal graphite electrode at each historical working temperature in the database to obtain the standard gray level of each normal graphite electrode corresponding to each historical working temperature. Select the maximum standard gray level and the minimum standard gray level of the normal graphite electrodes at each historical working temperature and record them as the upper and lower limits of the normal gray level interval at each historical working temperature, so as to obtain the normal gray level interval at each historical working temperature. If the working temperature at a certain time point is equal to a certain historical working temperature, the normal gray level interval at this time point is the normal gray level interval at this historical working temperature, so as to obtain the normal gray level interval at each time point.

[0011] If the gray level of a certain pixel point at a certain time point does not belong to the normal gray level interval of that time point, it indicates that the pixel point is an abnormal pixel point. In this way, each abnormal pixel point at each time point is obtained, and the number of abnormal pixel points at each time point is statistically obtained. Adjacent abnormal pixel points are recorded as the same abnormal pixel block, and the number of abnormal pixel points in each abnormal pixel block at each time point is statistically obtained. If the number of abnormal pixel points in an abnormal pixel block is greater than the number of abnormal pixel points in a preset standard abnormal pixel block, it indicates that the abnormal pixel block is a faulty pixel block, and the number of faulty pixel blocks is statistically obtained. If the number of abnormal pixel points at a certain time point is greater than the preset standard number of abnormal pixel points, or the number of faulty pixel blocks at that time point is greater than the preset standard number of faulty pixel blocks, that time point is recorded as a temperature abnormal time point, and the number of occurrences A of the temperature abnormal time point is statistically obtained.

[0012] If a group of adjacent time points are all temperature abnormal time points, then the time period between this group of adjacent time points is recorded as a temperature abnormal time period. In this way, each temperature abnormal time period is obtained, and each temperature abnormal time period is statistically obtained to get the number of occurrences B of the temperature abnormal time period.

[0013] Substitute the number of occurrences of the temperature abnormal time point and the temperature abnormal time period into the temperature index calculation formula to obtain the temperature index of the graphite electrode , and are respectively the preset standard number of occurrences of the temperature abnormal time point and the preset standard number of occurrences of the temperature abnormal time period, and are respectively the weight factor of the number of occurrences of the temperature abnormal time point and the weight factor of the number of occurrences of the temperature abnormal time period, , , .

[0014] Preferably, the analysis of the conductance data of the graphite electrode is as follows: Obtain the conductivity of each normal graphite electrode at each historical working voltage from the database. Select the maximum conductivity and the minimum conductivity of the normal graphite electrodes at each historical working voltage and record them as the upper limit and the lower limit of the normal conductivity range at each historical working voltage, respectively. In this way, the normal gray level range of each historical working conductivity is obtained. If the working voltage at a certain time point is equal to a certain historical working voltage, the normal conductivity range at this time point is the normal conductivity range of this historical working voltage. In this way, the normal conductivity range of each time point is obtained. If the conductivity at a certain time point does not belong to the normal conductivity range, then this time point is a time point with abnormal conductance. Count the time points with abnormal conductance to obtain the occurrence times C of the time points with abnormal conductance. If a group of adjacent time points are all time points with abnormal conductance, then the time period between this group of adjacent time points is recorded as the time period with abnormal conductance. In this way, each time period with abnormal conductance is obtained. Count each time period with abnormal conductance to obtain the occurrence times D of each time period with abnormal conductance;

[0015] Substitute the occurrence times of the time points with abnormal conductance and the time periods with abnormal conductance into the conductance fault index calculation formula to obtain the conductance fault index of the graphite electrode , and are the preset standard occurrence times of the time points with abnormal conductance and the standard occurrence times of the time periods with abnormal conductance, respectively, and are the weight factors of the occurrence times of the time points with abnormal conductance and the weight factors of the occurrence times of the time periods with abnormal conductance, respectively, , , .

[0016] Preferably, the analysis of the historical data of graphite electrode cutting in the database is as follows: The historical data of graphite electrode cutting includes the cutting times of the graphite electrode, the cutting times of each scrapped graphite electrode, and the remaining volume of each scrapped graphite electrode. Calculate the average value of the cutting times of each scrapped graphite electrode to obtain the standard scrapped cutting times , and calculate the average value of the remaining volume of each scrapped graphite electrode to obtain the standard remaining volume .

[0017] Substitute the cutting times of the graphite electrode, the standard scrapped cutting times, and the standard scrapped volume into the scrapping index calculation formula to obtain the scrapping index of the graphite electrode , where E and F are the cutting times and the remaining volume of the graphite electrode, respectively, and are the weight factors of the preset cutting times and the weight factor of the remaining volume, respectively, , , .

[0018] The beneficial effects of the present invention are as follows: During the use of the graphite electrode, the infrared data and conductance data of the graphite electrode are collected, and then the temperature index and conductance index of the graphite electrode are analyzed to determine whether the graphite electrode is faulty. When the graphite electrode is faulty, a shutdown detection is performed, and the density and hardness of the graphite electrode are collected to further determine whether replacement is needed. When the graphite electrode is replaced, the shearing data of the graphite electrode is collected and analyzed to obtain the shearing area of the graphite electrode. Then, based on the shearing area of the graphite electrode and the historical shearing data, it is determined whether to scrap. On the one hand, by performing detection during the production process to determine whether to shut down, the detection environment of the graphite electrode is expanded, the adaptability of the detection system is increased, and the production cost loss is reduced. On the other hand, through the analysis of the shearing and scrapping of the graphite electrode, the utilization rate of graphite resources is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order 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 be obtained based on these drawings.

[0020] Figure 1 It is a schematic diagram of the system structure connection of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0021] 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, not all of them. 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.

[0022] According to Figure 1 as shown, the present invention provides an automated detection system for graphite electrodes, including the following modules: an electrode basic detection module, an electrode shutdown detection module, an electrode scrap detection module, and a database.

[0023] The electrode basic detection module is respectively connected to the database and the electrode shutdown detection module, and the electrode scrap detection module is connected to the electrode shutdown detection module.

[0024] The electrode basic detection module is used to collect the infrared data and conductivity data of the graphite electrode during the use of the graphite electrode, analyze the infrared data of the graphite electrode to obtain the temperature index of the graphite electrode, analyze the conductivity data of the graphite electrode to obtain the conductivity index of the graphite electrode, and judge whether the graphite electrode fails according to the temperature index and conductivity index of the graphite electrode. If the graphite electrode fails, stop production for shutdown detection.

[0025] In a specific embodiment, the process of collecting the infrared data and conductivity data of the graphite electrode is as follows: The infrared data of the graphite electrode includes the gray scale and working temperature of each pixel point at each time point, and the conductivity data of the graphite electrode includes the conductivity and working voltage at each time point.

[0026] During the use of the electric furnace, an infrared detector is used to collect infrared images at each time point, and the gray scale of each pixel point at each time point is obtained from the infrared images at each time point. At the same time, the working temperature at each time point is collected through a temperature probe.

[0027] During the use of the electric furnace, a conductivity meter is used to collect the conductivity at each time point to obtain the conductivity at each time point. At the same time, the working voltage at each time point is collected through a voltage meter.

[0028] In a specific embodiment, the process of analyzing the infrared data of the graphite electrode is as follows: Calculate the average value of the gray scale of each pixel point of each normal graphite electrode at each historical working temperature in the database to obtain the standard gray scale of each normal graphite electrode corresponding to each historical working temperature. Select the maximum standard gray scale and the minimum standard gray scale of the normal graphite electrode at each historical working temperature and record them as the upper and lower limits of the normal gray scale interval at each historical working temperature, respectively, so as to obtain the normal gray scale interval at each historical working temperature. If the working temperature at a certain time point is equal to a certain historical working temperature, the normal gray scale interval at this time point is the normal gray scale interval at this historical working temperature, so as to obtain the normal gray scale interval at each time point.

[0029] If the gray scale of a certain pixel point at a certain time point does not belong to the normal gray scale interval at this time point, it indicates that this pixel point is an abnormal pixel point, so as to obtain the abnormal pixel points at each time point. Count the number of abnormal pixel points at each time point. Record adjacent abnormal pixel points as the same abnormal pixel block, and count the number of abnormal pixel points in each abnormal pixel block at each time point. If the number of abnormal pixel points in an abnormal pixel block is greater than the number of abnormal pixel points of the preset standard abnormal pixel block, it indicates that this abnormal pixel block is a faulty pixel block. Count the number of faulty pixel blocks. If the number of abnormal pixel points at a certain time point is greater than the preset standard number of abnormal pixel points, or the number of faulty pixel blocks at this time point is greater than the preset standard number of faulty pixel blocks, record this time point as a temperature abnormal time point, and count the number of occurrences A of the temperature abnormal time point;

[0030] If a group of adjacent time points are all temperature abnormal time points, then the time period between this group of adjacent time points is recorded as a temperature abnormal time period. In this way, each temperature abnormal time period is obtained, and each temperature abnormal time period is counted to obtain the occurrence times B of the temperature abnormal time period.

[0031] Substitute the occurrence times of the temperature abnormal time points and the temperature abnormal time periods into the temperature index calculation formula to obtain the temperature index of the graphite electrode , and are respectively the standard occurrence times of the preset temperature abnormal time points and the standard occurrence times of the temperature abnormal time periods, and are respectively the weight factors of the occurrence times of the preset temperature abnormal time points and the weight factors of the occurrence times of the temperature abnormal time periods, , , .

[0032] It should be noted that the average values of the occurrence times of the temperature abnormal time points and the occurrence times of the temperature abnormal time periods of each normal graphite electrode in the database are calculated respectively to obtain the standard occurrence times of the temperature abnormal time points and the standard occurrence times of the temperature abnormal time periods. The minimum occurrence times a of the temperature abnormal time points and the minimum occurrence times b of the temperature abnormal time periods of the faulty graphite electrode are obtained from the database. , .

[0033] In a specific embodiment, the analysis of the conductance data of the graphite electrode is as follows: The conductivities of each normal graphite electrode at each historical working voltage are obtained from the database, and the maximum conductivity and the minimum conductivity of the normal graphite electrodes at each historical working voltage are selected and recorded as the upper limit and the lower limit of the normal conductivity range of each historical working voltage respectively. In this way, the normal gray scale range of each historical working conductivity is obtained. If the working voltage at a certain time point is equal to a certain historical working voltage, the normal conductivity range at this time point is the normal conductivity range of this historical working voltage. In this way, the normal conductivity range of each time point is obtained. If the conductivity at a certain time point does not belong to the normal conductivity range, then this time point is a conductance abnormal time point. The occurrence times C of the conductance abnormal time points are counted. If a group of adjacent time points are all conductance abnormal time points, then the time period between this group of adjacent time points is recorded as a conductance abnormal time period. In this way, each conductance abnormal time period is obtained, and each conductance abnormal time period is counted to obtain the occurrence times D of each conductance abnormal time period.

[0034] Substitute the occurrence times of the abnormal conductance time points and the abnormal conductance time periods into the conductance fault index calculation formula to obtain the conductance fault index of the graphite electrode , and are respectively the standard occurrence times of the preset abnormal conductance time points and the standard occurrence times of the abnormal conductance time periods, and are respectively the weight factors of the occurrence times of the preset abnormal conductance time points and the weight factors of the occurrence times of the abnormal conductance time periods, , , .

[0035] It should be noted that the average values of the occurrence times of the abnormal conductance time points and the occurrence times of the abnormal conductance time periods of each normal graphite electrode in the database are calculated respectively to obtain the standard occurrence times of the abnormal conductance time points and the standard occurrence times of the abnormal conductance time periods. The minimum occurrence times c of the abnormal conductance time points and the minimum occurrence times d of the abnormal conductance time periods of the faulty graphite electrode are obtained from the database, , .

[0036] In a specific embodiment, the judgment of whether the graphite electrode fails is as follows: Obtain the temperature indices and conductance fault indices of the graphite electrode during normal use from the database. Denote the maximum temperature index and the maximum conductance fault index of the graphite electrode during normal use as the standard temperature index and the standard conductance fault index of the graphite electrode respectively. If the temperature index of the graphite electrode is greater than or equal to the standard temperature index and the conductance fault index is greater than or equal to the standard conductance fault index, it indicates that the graphite electrode does not fail. If the temperature index of the graphite electrode is greater than the standard temperature index or the conductance fault index is greater than the standard conductance fault index, it indicates that the graphite electrode fails.

[0037] It should be noted that this judgment is to prevent the graphite electrode from affecting production. Therefore, the attributes of the graphite electrode related to production are collected. The conductivity will affect the production cost, and the temperature will affect the production rate.

[0038] The electrode shutdown detection module is used to collect the attribute data of the graphite electrode, and then judge whether the graphite electrode needs to be replaced. After the graphite electrode is replaced, the cutting data of the graphite electrode is collected, and the cutting data of the graphite electrode is analyzed to obtain the remaining volume of the graphite electrode, and the staff is reminded to perform cutting treatment on the graphite electrode.

[0039] It should be noted that cutting refers to processing the faulty graphite electrode, such as washing and cutting, to generate a graphite electrode of a smaller size, and the graphite electrode of the smaller size is recycled.

[0040] In a specific embodiment, the process of collecting the attribute data of the graphite electrode is as follows: measure the density of the graphite electrode by the low-pressure exhaust method and measure the hardness of the graphite electrode by the rebound method.

[0041] In a specific embodiment, the process of determining whether the graphite electrode needs to be replaced is as follows: the attribute data of the graphite electrode includes the density of the graphite electrode and the hardness of each collection point. If the density of the graphite electrode belongs to the normal graphite electrode standard density range and the hardness of each collection point belongs to the normal graphite electrode standard hardness range, it indicates that the graphite electrode does not need to be replaced. If the density of the graphite electrode does not belong to the normal graphite electrode standard density range or the hardness of a certain collection point does not belong to the normal graphite electrode standard hardness range, it indicates that the graphite electrode needs to be replaced.

[0042] It should be noted that this judgment is to detect the material of the graphite. When the degree of change in the material of the graphite is too large, it will affect production and replacement is required.

[0043] In a specific embodiment, the process of collecting the cutting data of the graphite electrode is as follows: the cutting data of the graphite electrode includes the number and depth of surface defects of the graphite electrode, the position of internal defects, and the volume of internal defects.

[0044] Clean the graphite electrode, dry it, and then collect the surface image of the graphite electrode through a camera. Obtain the number and depth of surface defects of the graphite electrode from the surface image of the graphite electrode, and use an internal defect detector to obtain the position and volume of internal defects.

[0045] In a specific embodiment, the process of analyzing the cutting data of the graphite electrode is as follows: select the maximum number and depth of surface defects of the graphite electrode as the cutting depth of the graphite electrode. Obtain the historical cutting depth and surface recovery rate of each cutting from the database, and statistically obtain the surface recovery rate of each historical cutting depth. Denote the minimum surface recovery rate of each historical cutting depth as the basic surface recovery rate of each historical cutting depth. If the cutting depth of the graphite electrode is equal to a certain historical cutting depth, the surface recovery rate of the graphite electrode is equal to the basic surface recovery rate corresponding to that historical cutting depth. Multiply the volume of the graphite electrode by the surface recovery rate to obtain the remaining surface cutting volume of the graphite electrode.

[0046] Obtain the internal recovery rates of each historical volume in each region from the database, calculate the average value of the internal recovery rates of each volume corresponding to the internal defects at each position, and obtain the basic internal recovery rates of each volume corresponding to the internal defects at each position. If the position of the internal defect in the graphite electrode belongs to a certain region and the volume of the internal defect in the graphite electrode is equal to a certain historical volume in that region, then the internal recovery rate of the graphite electrode is equal to the basic internal recovery rate of that historical volume in that region. Multiply the remaining volume of the surface cut of the graphite electrode by the basic internal recovery rate to obtain the remaining volume of the graphite electrode.

[0047] The electrode scrapping detection module is used to analyze the graphite electrode cutting historical data in the database according to the remaining volume of the graphite electrode to obtain the scrapping index of the graphite electrode. If the scrapping index of the graphite electrode is greater than or equal to the preset scrapping index, it indicates that the graphite electrode can be cut. If the scrapping index of the graphite electrode is less than the preset scrapping index, the staff is prompted to scrap the graphite electrode.

[0048] It should be noted that the scrapping refers to the scrapping of the graphite electrode. After the graphite electrode is cut, if the remaining volume of the graphite electrode meets the production requirements, the graphite electrode can continue to be used as a graphite electrode on other devices. If the remaining volume of the graphite electrode cannot meet the production requirements, the graphite electrode is scrapped, but the graphite can still be recycled.

[0049] In a specific embodiment, the analysis of the graphite electrode cutting historical data in the database is as follows: The graphite electrode cutting historical data includes the cutting times of the graphite electrode, the cutting times of each scrapped graphite electrode, and the remaining volume of each scrapped graphite electrode. Calculate the average value of the cutting times of each scrapped graphite electrode to obtain the standard scrapping cutting times , calculate the average value of the remaining volume of each scrapped graphite electrode to obtain the standard remaining volume .

[0050] Substitute the cutting times, standard scrapping cutting times, and standard scrapping volume of the graphite electrode into the scrapping index calculation formula to obtain the scrapping index of the graphite electrode , where E and F are the cutting times and remaining volume of the graphite electrode respectively, and are the weight factors of the preset cutting times and the remaining volume respectively, , , .

[0051] A database for storing the gray levels of each pixel of each normal graphite electrode corresponding to each historical working temperature, each temperature index during the normal use of the graphite electrode, each conductance fault index during the normal use of the graphite electrode, the historical shearing depths of each shearing, the surface recovery rates of each shearing, the internal recovery rates of each historical volume corresponding to internal defects at each position, the number of shearing times of the graphite electrode, the number of shearing times of each scrapped graphite electrode, and the remaining volume of each scrapped graphite electrode.

[0052] The above content is only an example and illustration of the concept of the present invention. Those skilled in the art of this technology can make various modifications or supplements to the described specific embodiments or use similar methods for substitution, as long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should fall within the protection scope of the present invention.

Claims

1. An automated detection system for graphite electrodes, characterized in that: Includes the following modules: The basic electrode detection module is used to collect infrared data and conductivity data of the graphite electrode during the use of the graphite electrode, analyze the infrared data of the graphite electrode to obtain the temperature index of the graphite electrode, analyze the conductivity data of the graphite electrode to obtain the conductivity index of the graphite electrode, and judge whether the graphite electrode is faulty according to the temperature index and conductivity index of the graphite electrode. If the graphite electrode is faulty, the production is stopped for shutdown detection; The electrode shutdown detection module is used to collect graphite electrode property data to determine whether the graphite electrode needs to be replaced. After the graphite electrode is replaced, the graphite electrode cutting data is collected and analyzed to obtain the remaining volume of the graphite electrode, and the staff is reminded to cut the graphite electrode. The electrode scrap detection module is used to analyze the historical data of graphite electrode cutting in the database according to the remaining volume of the graphite electrode to obtain the scrap index of the graphite electrode. If the scrap index of the graphite electrode is greater than or equal to the preset scrap index, it indicates that the graphite electrode can be cut. If the scrap index of the graphite electrode is less than the preset scrap index, the staff is prompted to scrap the graphite electrode.

2. The automatic detection system for graphite electrodes according to claim 1, characterized in that: The specific collection process of collecting graphite electrode infrared data and graphite electrode conductivity data is as follows: The graphite electrode infrared data includes the grayscale and operating temperature of each pixel at each time point, and the graphite electrode conductivity data includes the conductivity and operating voltage at each time point; During the use of the electric furnace, an infrared detector is used to collect infrared images at each time point, and the grayscale of each pixel at each time point is obtained from the infrared image at each time point. At the same time, the working temperature at each time point is collected through a temperature probe; During the use of the electric furnace, a conductivity meter is used to collect the conductivity at each time point to obtain the conductivity at each time point, and a voltage meter is used to collect the working voltage at each time point.

3. The automatic detection system for graphite electrodes according to claim 2, characterized in that: The infrared data of the graphite electrode is analyzed, and the specific analysis process is as follows: The average grayscale of each pixel of each normal graphite electrode at each historical working temperature in the database is calculated to obtain the standard grayscale of each normal graphite electrode corresponding to each historical working temperature, and the maximum standard grayscale and the minimum standard grayscale of the normal graphite electrode at each historical working temperature are selected and recorded as the upper limit and the lower limit of the normal grayscale interval of each historical working temperature, respectively, so as to obtain the normal grayscale interval of each historical working temperature. If the working temperature at a certain time point is equal to a certain historical working temperature, the normal grayscale interval at the time point is the normal grayscale interval of the historical working temperature, so as to obtain the normal grayscale interval at each time point; If the grayscale of a certain pixel at a certain time point does not belong to the normal grayscale interval of the time point, it indicates that the pixel is an abnormal pixel, so as to obtain the abnormal pixels at each time point, and obtain the number of abnormal pixels at each time point by statistics, and record the adjacent abnormal pixels as the same abnormal pixel block, and obtain the number of abnormal pixels of each abnormal pixel block at each time point by statistics, if the number of abnormal pixels of an abnormal pixel block is greater than the number of abnormal pixels of a preset standard abnormal pixel block, it indicates that the abnormal pixel block is a faulty pixel block, and obtain the number of faulty pixel blocks by statistics, if the number of abnormal pixels at a certain time point is greater than the preset standard number of abnormal pixels, or the number of faulty pixel blocks at the time point is greater than the preset standard number of faulty pixel blocks, the time point is recorded as a temperature abnormal time point, and the number of occurrences A of the temperature abnormal time point is obtained by statistics; If a group of adjacent time points are all temperature abnormal time points, the time period between the group of adjacent time points is recorded as the temperature abnormal time period, so as to obtain each temperature abnormal time period, and count each temperature abnormal time period to obtain the number of occurrences B of the temperature abnormal time period; Substitute the number of occurrences of abnormal temperature time points and abnormal temperature time periods into the temperature index calculation formula In the figure, the temperature index α of the graphite electrode is obtained, A′ and B′ are the standard number of occurrences of the preset temperature anomaly time point and the standard number of occurrences of the temperature anomaly time period, ε1 and ε2 are the weight factors of the number of occurrences of the preset temperature anomaly time point and the weight factors of the number of occurrences of the temperature anomaly time period, ε1>0, ε2>0, ε1+ε2=1.

4. The automatic detection system for graphite electrodes according to claim 2, characterized in that: The specific analysis process of analyzing the graphite electrode conductivity data is as follows: Obtain the conductivity of each normal graphite electrode at each historical working voltage from the database, select the maximum conductivity and the minimum conductivity of the normal graphite electrode at each historical working voltage and record them as the upper limit and the lower limit of the normal conductivity interval of each historical working voltage, so as to obtain the normal grayscale interval of each historical working conductivity; if the working voltage at a certain time point is equal to a certain historical working voltage, then the normal conductivity interval at this time point is the normal conductivity interval of the historical working voltage, so as to obtain the normal conductivity interval at each time point; if the conductivity at a certain time point does not belong to the normal conductivity interval, then this time point is a time point of conductivity abnormality, and each time point of conductivity abnormality is counted to obtain the number of occurrences C of the conductivity abnormal time point; if a group of adjacent time points are all conductivity abnormal time points, then the time period between the group of adjacent time points is recorded as the conductivity abnormal time period, so as to obtain each conductivity abnormal time period, and each conductivity abnormal time period is counted to obtain the number of occurrences D of each conductivity abnormal time period; Substitute the number of times the conductivity abnormal time point and the conductivity abnormal time period occur into the conductivity fault index calculation formula In the figure, the conductivity fault index β of the graphite electrode is obtained, C′ and D′ are the standard occurrence times of the preset conductivity abnormal time points and the standard occurrence times of the conductivity abnormal time period, φ1 and φ2 are the weight factors of the occurrence times of the preset conductivity abnormal time points and the weight factors of the occurrence times of the conductivity abnormal time period, φ1>0, φ2>0, φ1+φ2=1.

5. The automatic detection system for graphite electrodes according to claim 4, characterized in that: The specific process of judging whether the graphite electrode is faulty is as follows: The temperature indexes and conductivity fault indexes of the normal use of the graphite electrode are obtained from the database, and the maximum temperature index and the maximum conductivity fault index of the normal use of the graphite electrode are recorded as the standard temperature index and the standard conductivity fault index of the graphite electrode, respectively. If the temperature index of the graphite electrode is less than or equal to the standard temperature index and the conductivity fault index is less than or equal to the standard conductivity fault index, it indicates that the graphite electrode has no fault. If the temperature index of the graphite electrode is greater than the standard temperature index or the conductivity fault index is greater than the standard conductivity fault index, it indicates that the graphite electrode has a fault.

6. The automatic detection system for graphite electrodes according to claim 1, characterized in that: The specific process of judging whether the graphite electrode needs to be replaced is as follows: The graphite electrode property data include the density of the graphite electrode and the hardness of each collection point. If the density of the graphite electrode belongs to the standard density range of normal graphite electrodes and the hardness of each collection point belongs to the standard hardness range of normal graphite electrodes, it indicates that the graphite electrode does not need to be replaced. If the density of the graphite electrode does not belong to the standard density range of normal graphite electrodes or the hardness of a certain collection point does not belong to the standard hardness range of normal graphite electrodes, it indicates that the graphite electrode needs to be replaced.

7. The automatic detection system for graphite electrodes according to claim 1, characterized in that: The specific collection process of collecting graphite electrode shearing data is as follows: The graphite electrode shearing data includes the number and depth of each surface defect of the graphite electrode, the location of internal defects and the volume of internal defects; The graphite electrode is cleaned and dried, and then the surface image of the graphite electrode is collected through a camera. The number and depth of each surface defect of the graphite electrode are obtained from the surface image of the graphite electrode, and the position and volume of the internal defects are obtained through an internal defect detector.

8. The automatic detection system for graphite electrodes according to claim 7, characterized in that: The graphite electrode shearing data is analyzed, and the specific analysis process is as follows: The depth of the maximum number of surface defects of the graphite electrode is selected as the cutting depth of the graphite electrode, the historical cutting depth and surface recovery rate of each cutting are obtained from the database, and the surface recovery rates of each historical cutting depth are statistically obtained. The minimum surface recovery rate of each historical cutting depth is recorded as the basic surface recovery rate of each historical cutting depth. If the cutting depth of the graphite electrode is equal to a certain historical cutting depth, the surface recovery rate of the graphite electrode is equal to the basic surface recovery rate corresponding to the historical cutting depth. The volume of the graphite electrode is multiplied by the surface recovery rate to obtain the surface shearing residual volume of the graphite electrode; The internal recovery rates of the historical volumes in each region are obtained from the database, and the internal recovery rates of the volumes corresponding to the internal defects at each position are calculated by the average value to obtain the basic internal recovery rates of the volumes corresponding to the internal defects at each position. If the position of the internal defects of the graphite electrode belongs to a certain region, and the volume of the internal defects of the graphite electrode is equal to a historical volume in the region, then the internal recovery rate of the graphite electrode is equal to the basic internal recovery rate of the historical volume in the region. The residual volume of the surface shearing of the graphite electrode is multiplied by the basic internal recovery rate to obtain the residual volume of the graphite electrode.

9. The automatic detection system for graphite electrodes according to claim 8, characterized in that: The graphite electrode cutting history data in the database is analyzed, and the specific analysis process is as follows: The graphite electrode cutting history data includes the cutting times of the graphite electrode, the cutting times of each scrapped graphite electrode and the residual volume of each scrapped graphite electrode. The cutting times of each scrapped graphite electrode are averaged to obtain the standard scrap cutting times E′, and the residual volumes of each scrapped graphite electrode are averaged to obtain the standard residual volume F′. Substitute the number of shearing times, standard scrap shearing times and standard scrap volume of the graphite electrode into the scrap index calculation formula The scrap index γ of the graphite electrode is obtained, E and F are the number of shearing times and the remaining volume of the graphite electrode, respectively. and are the weight factors of the preset number of cuts and the remaining volume, 10. The automatic detection system for graphite electrodes according to claim 1, characterized in that: It also includes a database for storing the grayscale of each pixel of each normal graphite electrode corresponding to each historical working temperature, each temperature index of normal use of the graphite electrode, each conductivity fault index of normal use of the graphite electrode, the historical cutting depth of each cut, the surface recovery rate of each cut, the internal recovery rate of each historical volume corresponding to the internal defects at each position, the number of cutting times of the graphite electrode, the number of cutting times of each scrapped graphite electrode and the remaining volume of each scrapped graphite electrode.

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