Graphite electrode defect detection system and method

Abstract

The invention discloses a graphite electrode defect detection system and a graphite electrode defect detection method, relates to the technical field of graphite electrodes, and aims to enable a cultivated detection marking component to have very strong pertinence, can be better and specifically combined with potential defect parts of graphite electrodes of various models, and improve the detection accuracy through the accurate detection system. The method can accurately identify the graphite electrode with the defective surface, and prevents the unqualified products from being put into use. Therefore, the problems of product quality reduction, production efficiency reduction and the like caused by the use of defective electrodes in the production process can be prevented, waste products and inferior-quality products caused by electrode defects are reduced, so that the production cost and resource waste of enterprises are reduced, and by analyzing the severity of the defects, the production efficiency of the enterprises is improved. And an enterprise can reasonably arrange the use, maintenance or scrapping plan, so that unnecessary maintenance attempts on the electrode which is seriously damaged and cannot be repaired are avoided.

Description

Technical Field

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

[0002] In the production and operation process of enterprises, strict quality control is crucial to ensure product competitiveness and economic benefits. For graphite electrode manufacturers, accurate detection of unqualified graphite electrodes can avoid putting defective products on the market or in use, thereby reducing production accidents and product rework caused by electrode defects and reducing production costs. Therefore, a graphite electrode defect detection system and method are needed.

[0003] Prior art, such as the graphite electrode defect detection system disclosed in the invention application patent with announcement 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 suitable for controlling the knocking mechanism to knock on the graphite electrode; the sound detection module is suitable for detecting the sound made by the knocking mechanism knocking on the graphite electrode, and sending the sound signal to the second processor module, so as to be forwarded by the second processor module to the first processor module; the first processor module is suitable for sending the sound signal to the cloud server through the transmission module; the cloud server is suitable for judging the degree of defect of the graphite electrode according to the sound signal, thereby realizing automatic detection of the degree of defect of the graphite electrode, avoiding the shortcomings of strong subjectivity and high missed detection rate caused by methods such as manual detection, and reducing labor costs.

[0004] In view of the above scheme, the inventors of the present application have found that the above technology has at least the following technical problems: 1. If the prior art does not have such a detection system based on biomolecule-specific recognition, it may lack the ability to accurately locate the defective part when detecting defects in graphite electrodes. For example, some traditional physical detection methods, such as appearance inspection or simple electrical performance testing, cannot distinguish the microscopic differences between defective parts and normal parts. Appearance inspection can only find relatively obvious macroscopic defects, and it is difficult to detect small cracks or local microstructural changes; although electrical performance testing can find some problems, it cannot clearly determine which part of the defect is caused, which is prone to misjudgment. Most of the prior art judges the quality of the electrode from a single dimension. For example, only acoustic detection is used to determine whether there is a problem with the internal structure, but information such as the binding of biomolecules on the electrode surface cannot be obtained. This may lead to an incomplete assessment of the defect, and it is impossible to accurately determine the type and degree of the defect, because defects of different types and degrees may have different manifestations in multi-dimensional fluorescence imaging features. At the same time, if the prior art is not cultivated for each type of graphite electrode, the detection of different types of graphite electrodes may not be flexible enough. The differences in materials, structures, etc. between different types of electrodes may make the general detection method ineffective. For example, a detection method suitable for large graphite electrodes may not be able to accurately detect small, special-shaped graphite electrodes. It is necessary to develop multiple different detection methods for different models, which increases the detection cost and time.

[0005] 2. The existing technology lacks analysis of the severity of defects in qualified electrodes. When faced with electrodes after inspection, it is difficult for enterprises to make reasonable decisions on use, repair or scrapping. Electrodes with certain defects but still repairable may be overused, resulting in failures during use, affecting production efficiency and product quality; or some electrodes with lighter defects may be easily scrapped, resulting in waste of resources. Without an accurate detection system, graphite electrodes with surface defects may be misjudged as qualified and put into use. This will lead to a decline in product quality during the production process. For example, in application scenarios such as electrolysis, defective graphite electrodes may affect electrolysis efficiency and product quality. At the same time, these defective electrodes may be damaged prematurely due to unstable performance and need to be replaced frequently, increasing the cost of electrode use and waste of resources in the production process. Due to the inability to accurately assess the severity of the defects, enterprises may perform unreasonable repairs or scrapping of electrodes. For example, excessive repairs of severely defective electrodes that cannot be effectively repaired waste manpower, material resources and time; or direct scrapping of electrodes with lighter defects that can be repaired and used, resulting in waste of resources, thereby increasing the operating costs of enterprises. Summary of the invention

[0006] In view of the above-mentioned technical deficiencies, the object of the present invention is to provide a graphite electrode defect detection system and method.

[0007] In order to solve the above technical problems, the present invention adopts the following technical solutions: In the first aspect, the present invention provides a graphite electrode defect detection system, including: a detection marker component screening module: used to cultivate detection marker components corresponding to each type of graphite electrode before surface defect detection of each type of graphite electrode in the target enterprise, the detection marker components including various biological molecules and various fluorescent groups, and then screen out qualified biological molecules and qualified fluorescent groups corresponding to each type of graphite electrode.

[0008] Uniformity judgment module: used to detect surface defects of each graphite electrode in each model, so as to analyze the uniformity value of surface biomolecules corresponding to each graphite electrode in each model, and evaluate whether the uniformity of surface biomolecules corresponding to each graphite electrode in each model is qualified.

[0009] Graphite electrode defect detection module: used to detect and analyze the surface defects of each graphite electrode in each model after the surface biological molecule uniformity corresponding to each graphite electrode in each model is qualified, so as to evaluate whether the surface corresponding to each graphite electrode in each model is defective, and record each graphite electrode in each model with surface defects as each qualified graphite electrode in each model, and then analyze the severity of the defects of each qualified graphite electrode in each model.

[0010] Preferably, the specific cultivation process of cultivating the detection mark components corresponding to each type of graphite electrode is as follows: A1. Acquisition of historical defect type information: From the historical inspection records of the target enterprise, the surface defect information of each type of graphite electrode in the historical periodic inspection process is sorted out by analyzing the inspection reports, image data and related quality feedback data in the database, and the surface defect information includes various surface defect types.

[0011] A2. Design of graphite electrode cultivation samples: Based on the surface defect types of various types of graphite electrodes obtained, simulate their real defect characteristics, and design graphite electrode cultivation samples of various types according to the corresponding surface defect types in the historical cycle detection process.

[0012] A3. Cultivation of detection labeling components: Place the designed graphite electrode cultivation samples of various types in the corresponding incubators, and then place a number of biological molecules and a number of fluorescent groups in the incubators of the corresponding types of the graphite electrode cultivation samples. At the same time, the environmental conditions of the incubator can be adjusted, and the environmental conditions of the incubator are adjusted to a suitable environment for the biological molecules and the fluorescent groups. In this way, the biological molecules and fluorescent groups corresponding to the various types of graphite electrodes are cultivated.

[0013] Preferably, the detection marker component screening module further comprises an affinity specificity analysis unit and a binding specificity analysis unit.

[0014] The biomolecule specific value analysis unit is used to obtain the detection index corresponding to each biomolecule in each type of graphite electrode incubation sample when each biomolecule corresponding to each type of graphite electrode incubation sample reaches the set standard incubation time. The detection index includes enrichment multiple, cross-reaction rate and equilibrium dissociation constant, and then analyze and obtain the affinity specific value corresponding to each biomolecule in each type of graphite electrode incubation sample.

[0015] The binding specific value analysis unit is used to obtain the binding index corresponding to each fluorescent group in each type of graphite electrode incubation sample when each fluorescent group corresponding to each type of graphite electrode incubation sample reaches the set standard incubation time. The binding index includes labeling rate, intensity change rate and spectral displacement, and then analyzes to obtain the binding specific value corresponding to each fluorescent group in each type of graphite electrode incubation sample.

[0016] Preferably, the screening out of each qualified biological molecule and each qualified fluorescent group corresponding to each type of graphite electrode is carried out in the following specific screening process: B1, the enrichment multiple, cross-reaction rate and equilibrium dissociation constant corresponding to each biological molecule in each type of graphite electrode incubation sample are input into the affinity specific analysis model, and the affinity specific value corresponding to each biological molecule in each type of graphite electrode incubation sample is output.

[0017] B2. Compare the affinity specific value corresponding to each biomolecule in each model of graphite electrode incubation sample with the affinity specific value corresponding to the set standard biomolecule. If the affinity specific value corresponding to a biomolecule in each model of graphite electrode incubation sample is greater than or equal to the affinity specific value corresponding to the set standard biomolecule, then the biomolecule in the graphite electrode incubation sample of that model is recorded as a qualified biomolecule corresponding to that model of graphite electrode. In this way, the qualified biomolecules corresponding to each model of graphite electrode are screened out.

[0018] B3. Input the labeling rate, intensity change rate and spectral shift corresponding to each fluorescent group in each type of graphite electrode incubation sample into the binding specificity analysis model, and output the binding specificity value corresponding to each fluorescent group in each type of graphite electrode incubation sample.

[0019] B4. Compare the binding specificity values ​​corresponding to each fluorescent group in each model of graphite electrode incubation samples with the binding specificity values ​​corresponding to the set standard fluorescent group. If the binding specificity value corresponding to a fluorescent group in a certain model of graphite electrode incubation samples is greater than or equal to the binding specificity value corresponding to the set standard fluorescent group, then the fluorescent group in the graphite electrode incubation samples of this model is recorded as the qualified fluorescent group corresponding to this model of graphite electrode. In this way, the qualified fluorescent groups corresponding to each model of graphite electrode are screened out.

[0020] Preferably, the analysis of the uniform value of surface biomolecules corresponding to each graphite electrode in each model is specifically performed as follows: C1. When detecting surface defects of each graphite electrode in each model, each graphite electrode in each model is immersed in a detection box corresponding to each qualified biomolecule and each qualified fluorescent group, thereby starting stirring the detection box corresponding to each graphite electrode in each model, and setting a number of collection areas at the same time, and after the standard stirring time is over, collecting the surface biomolecule attachment data corresponding to each graphite electrode in each model, the surface biomolecule attachment data includes the biomolecule coverage density and biomolecule layer thickness corresponding to each collection area.

[0021] C2, the biomolecule coverage density and biomolecule layer thickness corresponding to each collection area in each graphite electrode of each model are recorded as and h represents the number corresponding to each model, h is a positive integer, g represents the number corresponding to each graphite electrode, g is a positive integer, k represents the number corresponding to each collection area, k is a positive integer, substitute into the calculation formula: The surface biomolecule uniformity value ρ corresponding to each graphite electrode of each model is obtained hg , where Q′ and E′ are the standard biomolecule coverage density and standard biomolecule layer thickness values ​​corresponding to the set acquisition area, respectively; η1 and η2 are the weight factors corresponding to the biomolecule coverage density and biomolecule layer thickness of the set acquisition area, respectively.

[0022] Preferably, the evaluation of whether the uniformity of the surface biomolecules corresponding to each graphite electrode in each model is qualified is specifically performed as follows: D1. The uniform value of the surface biomolecules corresponding to each graphite electrode in each model is compared with the set uniform value interval of the surface biomolecules corresponding to the standard graphite electrode. If the uniform value of the surface biomolecules corresponding to a certain graphite electrode in a certain model is within the set uniform value interval of the surface biomolecules corresponding to the standard graphite electrode, it indicates that the uniformity of the surface biomolecules corresponding to the graphite electrode in the model is qualified, thereby detecting and analyzing the surface defects of each graphite electrode in each model.

[0023] D2. If the surface biomolecule uniformity value corresponding to a certain graphite electrode in a certain model is less than the minimum value of the surface biomolecule uniformity value range corresponding to the set standard graphite electrode, it indicates that the surface biomolecule uniformity corresponding to the graphite electrode in this model is unqualified. At the same time, continue to stir according to the standard stirring time, increase the stirring speed and stirring time, add 0.01% co-solvent, and after the stirring is completed, continue to evaluate whether the surface biomolecule uniformity corresponding to the graphite electrode of this model is qualified according to the evaluation process until the surface biomolecule uniformity corresponding to the graphite electrode of this model is qualified.

[0024] D3. If the surface biomolecule uniformity value corresponding to a certain graphite electrode in a certain model is greater than the maximum value of the surface biomolecule uniformity value range corresponding to the set standard graphite electrode, it indicates that the surface biomolecule uniformity corresponding to the graphite electrode in this model is unqualified. At the same time, continue stirring according to the standard stirring time, and reduce the stirring speed and stirring time to reduce the biomolecule concentration to about 3 / 4 of the original. After the stirring is completed, continue to evaluate whether the surface biomolecule uniformity corresponding to the graphite electrode of this model is qualified according to the evaluation process until the surface biomolecule uniformity corresponding to the graphite electrode of this model is qualified.

[0025] Preferably, the evaluation of whether the surface corresponding to each graphite electrode in each model is defective is performed by the following specific evaluation process: S1. Using a fluorescent imaging device, a fluorescent image corresponding to each model of graphite electrode is obtained, and the surface of each graphite electrode in each model is divided into multiple sub-regions, thereby obtaining surface detection data corresponding to each sub-region in each graphite electrode in each model, the surface detection data including fluorescence intensity attenuation and fluorescence intensity change rate, the fluorescence intensity attenuation and fluorescence intensity change rate corresponding to each sub-region in each graphite electrode in each model are input into a defect assessment value evaluation model, and the defect assessment value results corresponding to each graphite electrode in each model are output.

[0026] S2. The defect assessment value result includes the values ​​of 1 and -1. When the defect assessment value result corresponding to a certain graphite electrode in a certain model is 1, it means that the surface corresponding to the graphite electrode in the model has no defects. Conversely, when the defect assessment value result corresponding to a certain graphite electrode in a certain model is -1, it means that the surface corresponding to the graphite electrode in the model has defects.

[0027] Preferably, the expression of the defect assessment value evaluation model is:

[0028] In the formula, π hg represents the defect assessment result corresponding to the hth graphite electrode in the gth model, γ hg represents the defect assessment value corresponding to the h-th graphite electrode in the g-th model, γ′ is the set defect assessment value threshold, h represents the number corresponding to each model, h is a positive integer, and g represents the number corresponding to each graphite electrode, g is a positive integer.

[0029] The fluorescence intensity attenuation and fluorescence intensity change rate corresponding to each sub-region in each graphite electrode of each model are recorded as and y represents the number corresponding to each sub-region. y is a positive integer. Substitute it into the calculation formula: The defect assessment value γ corresponding to the hth graphite electrode in the gth model is obtained hg, where F′ and Z′ are the standard fluorescence intensity attenuation and standard fluorescence intensity change rate corresponding to the set sub-region, ν1 and ν2 are the weight factors corresponding to the fluorescence intensity attenuation and fluorescence intensity change rate of the set sub-region, σ1 and σ2 are the adjustment factors corresponding to the fluorescence intensity attenuation and fluorescence intensity change rate of the set sub-region, respectively, and e represents a natural constant.

[0030] Preferably, the defect severity of each qualified graphite electrode in each model is analyzed, and the specific analysis process is as follows: the defect assessment value corresponding to each qualified graphite electrode in each model is calculated with the set standard defect assessment value threshold, so as to obtain the difference between the defect assessment value corresponding to each qualified graphite electrode in each model and the set standard defect assessment value threshold, and the difference is compared with the difference interval corresponding to each defect severity in the database. If the difference is within the difference interval corresponding to a defect severity in the database, the defect severity in the database is recorded as the defect severity of the qualified graphite electrode in the model.

[0031] In a second aspect, the present invention provides a graphite electrode defect detection method, comprising: step one, screening of detection marker components: before surface defect detection of various types of graphite electrodes in a target enterprise, cultivating detection marker components corresponding to various types of graphite electrodes, the detection marker components including various biological molecules and various fluorescent groups, and then screening out various qualified biological molecules and various qualified fluorescent groups corresponding to various types of graphite electrodes.

[0032] Step 2: Uniformity determination: Detect surface defects of each graphite electrode in each model, analyze the uniformity of surface biomolecules corresponding to each graphite electrode in each model, and evaluate whether the uniformity of surface biomolecules corresponding to each graphite electrode in each model is qualified.

[0033] Step 3. Detection of graphite electrode defects: When the surface biomolecule uniformity corresponding to each graphite electrode in each model is qualified, the surface defects of each graphite electrode in each model are detected and analyzed to evaluate whether the surface corresponding to each graphite electrode in each model is defective, and each graphite electrode in each model with surface defects is recorded as a qualified graphite electrode in each model, and then the severity of the defects of each qualified graphite electrode in each model is analyzed.

[0034] The beneficial effects of the present invention are as follows: 1. In the embodiment of the present invention, the historical defect type information of each type of graphite electrode is obtained from the historical detection records of the target enterprise, and the real defect characteristics are simulated to design the culture sample, and then the corresponding biomolecules and fluorescent groups are cultured under a suitable environment. This method makes the cultivated detection marker components highly targeted, and can better specifically bind to the potential defect sites of each type of graphite electrode, thereby greatly improving the accuracy of the detection and effectively avoiding the misjudgment caused by non-specific binding. At the same time, the detection marker components are customized for the cultivation of different types of graphite electrodes, and the differences in materials, structures, and use environments of each type are fully considered to ensure that the detection system can adapt to the characteristics of different types of electrodes, and provide enterprises with more accurate detection services that are more in line with actual needs, and carry out detailed index analysis of biomolecules and fluorescent groups, such as the enrichment multiples, cross-reaction rates, equilibrium dissociation constants of biomolecules, and the labeling rate, intensity change rate, and spectral displacement of fluorescent groups. By comparing these indicators with the set standard values ​​for screening, it can be ensured that the selected qualified biomolecules and qualified fluorescent groups have excellent performance, further improving the reliability and accuracy of the detection system.

[0035] 2. The embodiment of the present invention ensures that the biomolecules can be evenly distributed on the electrode surface, avoiding detection errors caused by uneven distribution of biomolecules, such as local biomolecule aggregation may cause false positive results, and local biomolecule loss may cause false negative results. When the surface biomolecule uniformity is detected to be unqualified, the system can take corresponding adjustment measures according to the specific situation, such as increasing or decreasing the stirring speed and duration, adjusting the biomolecule concentration, etc., until the uniformity is qualified. This dynamic adjustment mechanism effectively guarantees the accuracy of subsequent defect detection, thereby fully guaranteeing the quality inspection effect of graphite electrodes. Fluorescent images of graphite electrodes of various models are obtained using fluorescent imaging equipment, and the electrode surface is divided into multiple sub-areas for analysis. By inputting the fluorescence intensity attenuation and fluorescence intensity change rate of each sub-area into the defect assessment value evaluation model, it can accurately determine whether the electrode surface is defective. Compared with the traditional single overall judgment method, this method based on multi-region data and model evaluation can more accurately capture the local defects on the electrode surface, improve the accuracy of defect detection, analyze the defect severity of each qualified graphite electrode in each model, and determine the electrode defect severity by calculating the difference between the defect assessment value and the standard defect assessment value threshold, and comparing it with the difference interval corresponding to each defect severity in the database. This helps companies make reasonable use, maintenance or scrapping decisions based on the actual situation of the electrode, thereby better ensuring the quality and performance of the electrode during use.

[0036] 3. The embodiment of the present invention can accurately identify graphite electrodes with surface defects through a precise detection system to avoid putting these unqualified products into use. This can prevent problems such as product quality degradation and reduced production efficiency caused by the use of defective electrodes during the production process, reduce waste and defective products caused by electrode defects, thereby reducing the production cost and resource waste of the enterprise. By analyzing the severity of its defects, the enterprise can reasonably arrange its use, maintenance or scrapping plan, avoid unnecessary maintenance attempts on electrodes with severe defects that cannot be repaired, and can also promptly process the repairable electrodes, further optimizing resource utilization efficiency and reducing overall operating costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0038] Figure 1 This is a schematic diagram of the connection of the system modules of the present invention.

[0039] Figure 2 The present invention is a flowchart of the steps for implementing the method. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] Embodiments of the present invention Figure 1 As shown, a graphite electrode defect detection system includes: a detection mark component screening module, a uniformity judgment module, a graphite electrode defect detection module and a database.

[0042] The uniformity judgment module is connected to the detection mark component screening module and the graphite electrode defect detection module respectively, and the database is connected to the graphite electrode defect detection module.

[0043] Detection marker component screening module: It is used to cultivate the detection marker components corresponding to each type of graphite electrode in the target enterprise before surface defect detection of each type of graphite electrode. The detection marker components include various biological molecules and various fluorescent groups, and then screen out various qualified biological molecules and various qualified fluorescent groups corresponding to various types of graphite electrodes.

[0044] In a specific embodiment, the detection mark components corresponding to each type of graphite electrode are cultivated, and the specific cultivation process is as follows: A1. Acquisition of historical defect type information: From the historical inspection records of the target enterprise, the surface defect information of each type of graphite electrode in the historical cycle inspection process is sorted out by analyzing the inspection reports, image data and related quality feedback data in the database, and the surface defect information includes various surface defect types.

[0045] A2. Design of graphite electrode cultivation samples: Based on the surface defect types of various types of graphite electrodes obtained, simulate their real defect characteristics, and design graphite electrode cultivation samples of various types according to the corresponding surface defect types in the historical cycle detection process.

[0046] A3. Cultivation of detection labeling components: Place the designed graphite electrode cultivation samples of various types in the corresponding incubators, and then place a number of biological molecules and a number of fluorescent groups in the incubators of the corresponding types of the graphite electrode cultivation samples. At the same time, the environmental conditions of the incubator can be adjusted, and the environmental conditions of the incubator are adjusted to a suitable environment for the biological molecules and the fluorescent groups. In this way, the biological molecules and fluorescent groups corresponding to the various types of graphite electrodes are cultivated.

[0047] In another specific embodiment, the detection marker component screening module further includes an affinity specificity analysis unit and a binding specificity analysis unit.

[0048] The biomolecule specific value analysis unit is used to obtain the detection index corresponding to each biomolecule in each type of graphite electrode incubation sample when each biomolecule corresponding to each type of graphite electrode incubation sample reaches the set standard incubation time. The detection index includes enrichment multiple, cross-reaction rate and equilibrium dissociation constant, and then analyze and obtain the affinity specific value corresponding to each biomolecule in each type of graphite electrode incubation sample.

[0049] The binding specific value analysis unit is used to obtain the binding index corresponding to each fluorescent group in each type of graphite electrode incubation sample when each fluorescent group corresponding to each type of graphite electrode incubation sample reaches the set standard incubation time. The binding index includes labeling rate, intensity change rate and spectral displacement, and then analyzes to obtain the binding specific value corresponding to each fluorescent group in each type of graphite electrode incubation sample.

[0050] It should be noted that the enrichment factor refers to the ratio of the concentration of the target biomolecule in the sample to the background concentration. The steps to obtain the enrichment factor are as follows: Sample preparation: First, prepare standard solutions of biomolecules of different concentrations and react them with graphite electrode samples. Detection: Use a suitable detection method to determine the concentration of the target biomolecule in the sample. Calculate the enrichment factor: The enrichment factor can be calculated by the following formula: Enrichment factor = target molecule concentration in the sample ÷ background concentration. The cross-reaction rate refers to the degree of influence of non-target biomolecules on the detection results during the detection process. The steps to obtain the cross-reaction rate are as follows: Select non-target molecules: Select non-target biomolecules similar to the target molecules. Experimental design: Under the same conditions, measure the responses of target molecules and non-target molecules respectively. Calculate the cross-reaction rate: The cross-reaction rate can be calculated by the following formula: Cross-reaction rate = non-target molecule detection signal ÷ target molecule detection signal × 100%. The equilibrium dissociation constant is an important parameter for describing the binding affinity of biomolecules. The steps to obtain Kd are as follows: Binding experiment: Under different concentrations of target biomolecules, measure the signal changes after binding to the fluorescent group. Data fitting: Use the binding isotherm to fit the experimental data to obtain the equilibrium state of the binding reaction. Calculate Kd: Calculate Kd through the fitting results. Usually Kd is defined as: Kd = [bound molecules] ÷ [free molecules], where the concentrations of free molecules and bound molecules can be extracted from the experimental data.

[0051] It should also be noted that the labeling rate refers to the ratio of the fluorescent group successfully bound to the target molecule. The steps to obtain the labeling rate are as follows: Sample preparation: react the fluorescent group with the target biological molecule under certain conditions to ensure that the reaction is sufficient. Detection of fluorescence signal: use a fluorescence spectrometer to measure the fluorescence signal intensity of the sample. Calculation of labeling rate: labeling rate = concentration of bound fluorescent group ÷ total fluorescent group concentration × 100%, where the concentration of bound fluorescent group is obtained through a control experiment. The intensity change rate refers to the degree of change in the intensity of the fluorescent signal before and after binding. The steps to obtain the intensity change rate are as follows: Determination of the fluorescence signal before binding: measure the initial fluorescence intensity (I0) of the sample before the fluorescent group binds to the target molecule. Determination of the fluorescence signal after binding: measure the final fluorescence intensity (If) of the sample after the fluorescent group binds to the target molecule. Calculation of the intensity change rate: intensity change rate = (I0-If) ÷ I0 × 100%, this formula can help evaluate the effectiveness of the binding reaction. The spectral shift refers to the change in the wavelength of the fluorescence signal, which usually reflects the change in the molecular binding state. The steps to obtain the spectral shift are as follows: Determine the fluorescence spectrum before binding: Before the fluorescent group binds to the target molecule, record the peak wavelength (λ0) of the fluorescence spectrum. Determine the fluorescence spectrum after binding: After the fluorescent group binds to the target molecule, record the peak wavelength (λf) of the fluorescence spectrum. Calculate the spectral shift: Spectral shift = λf-λ0.

[0052] In another specific embodiment, the qualified biological molecules and qualified fluorescent groups corresponding to each type of graphite electrode are screened out, and the specific screening process is as follows: B1. The enrichment multiple, cross-reaction rate and equilibrium dissociation constant corresponding to each biological molecule in each type of graphite electrode incubation sample are input into the affinity specific analysis model, and the affinity specific value corresponding to each biological molecule in each type of graphite electrode incubation sample is output.

[0053] It should be noted that the analysis process of the affinity specific value corresponding to each biomolecule in each type of graphite electrode incubation sample is as follows: the enrichment multiple, cross-reaction rate and equilibrium dissociation constant corresponding to each biomolecule in each type of graphite electrode incubation sample are normalized, and the enrichment multiple, cross-reaction rate and equilibrium dissociation constant corresponding to each biomolecule in each type of graphite electrode incubation sample after treatment are recorded as and Substitute into the analysis formula Obtain the affinity specific value corresponding to each biomolecule in the samples incubated with each type of graphite electrode ω1, ω2, and ω3 are weight coefficients corresponding to the set biomolecule enrichment multiple, the cross-reaction rate, and the equilibrium dissociation constant, respectively, where h represents the number corresponding to each model, h is a positive integer, and j represents the number corresponding to each biomolecule, j is a positive integer.

[0054] It should be noted that ω1, ω2, and ω3 are all greater than 0 and less than 1.

[0055] It should also be noted that, based on the expertise and research of experts in the field, and after discussion and confirmation with industry organizations or professional institutions, the experts set the weight coefficients corresponding to the biomolecule enrichment multiple, the cross-reaction rate, and the equilibrium dissociation constant based on their own experience and knowledge.

[0056] B2. Compare the affinity specific value corresponding to each biomolecule in each model of graphite electrode incubation sample with the affinity specific value corresponding to the set standard biomolecule. If the affinity specific value corresponding to a biomolecule in each model of graphite electrode incubation sample is greater than or equal to the affinity specific value corresponding to the set standard biomolecule, then the biomolecule in the graphite electrode incubation sample of that model is recorded as a qualified biomolecule corresponding to that model of graphite electrode. In this way, the qualified biomolecules corresponding to each model of graphite electrode are screened out.

[0057] B3. Input the labeling rate, intensity change rate and spectral shift corresponding to each fluorescent group in each type of graphite electrode incubation sample into the binding specificity analysis model, and output the binding specificity value corresponding to each fluorescent group in each type of graphite electrode incubation sample.

[0058] It should be noted that the analysis process of the binding specific value corresponding to each fluorescent group in each type of graphite electrode incubation sample is as follows: the labeling rate, intensity change rate and spectral shift corresponding to each fluorescent group in each type of graphite electrode incubation sample are normalized, and the labeling rate, intensity change rate and spectral shift corresponding to each fluorescent group in each type of graphite electrode incubation sample after treatment are recorded as and Substitute into the analysis formula Obtain the binding specificity values ​​corresponding to each biomolecule in the samples incubated with each type of graphite electrode They are respectively the weight coefficient corresponding to the set fluorescent group labeling rate, the weight coefficient corresponding to the intensity change rate, and the weight coefficient corresponding to the spectral shift, wherein h represents the number corresponding to each model, h is a positive integer, and l represents the number corresponding to each biological molecule, l is a positive integer.

[0059] It should be noted that Both are greater than 0 and less than 1.

[0060] It should also be noted that, based on the expertise and research of experts in the field, and after discussion and confirmation with industry organizations or professional institutions, the experts set the weight coefficients corresponding to the fluorescent group labeling rate, the intensity change rate, and the spectral shift amount according to their own experience and knowledge.

[0061] B4. Compare the binding specificity values ​​corresponding to each fluorescent group in each model of graphite electrode incubation samples with the binding specificity values ​​corresponding to the set standard fluorescent group. If the binding specificity value corresponding to a fluorescent group in a certain model of graphite electrode incubation samples is greater than or equal to the binding specificity value corresponding to the set standard fluorescent group, then the fluorescent group in the graphite electrode incubation samples of this model is recorded as the qualified fluorescent group corresponding to this model of graphite electrode. In this way, the qualified fluorescent groups corresponding to each model of graphite electrode are screened out.

[0062] Uniformity judgment module: used to detect surface defects of each graphite electrode in each model, so as to analyze the uniformity value of surface biomolecules corresponding to each graphite electrode in each model, and evaluate whether the uniformity of surface biomolecules corresponding to each graphite electrode in each model is qualified.

[0063] In a specific embodiment, the analysis of the uniform value of surface biomolecules corresponding to each graphite electrode in each model is performed as follows: C1. When detecting surface defects of each graphite electrode in each model, each graphite electrode in each model is immersed in a detection box corresponding to each qualified biomolecule and each qualified fluorescent group, so that the detection box corresponding to each graphite electrode in each model is started to stir, and several collection areas are set at the same time. After the standard stirring time is over, the surface biomolecule attachment data corresponding to each graphite electrode in each model is collected, and the surface biomolecule attachment data includes the biomolecule coverage density and biomolecule layer thickness corresponding to each collection area.

[0064] C2, the biomolecule coverage density and biomolecule layer thickness corresponding to each collection area in each graphite electrode of each model are recorded as and h represents the number corresponding to each model, h is a positive integer, g represents the number corresponding to each graphite electrode, g is a positive integer, k represents the number corresponding to each collection area, k is a positive integer, substitute into the calculation formula: The surface biomolecule uniformity value ρ corresponding to each graphite electrode of each model is obtained hg , where Q′ and E′ are the standard biomolecule coverage density and standard biomolecule layer thickness values ​​corresponding to the set acquisition area, respectively; η1 and η2 are the weight factors corresponding to the biomolecule coverage density and biomolecule layer thickness of the set acquisition area, respectively.

[0065] It should be noted that η1 and η2 are both greater than 0 and less than 1.

[0066] It should also be noted that through the summary of a large amount of research data and experimental data, the standard biomolecule coverage density and standard biomolecule layer thickness values ​​corresponding to the collection area are set according to professional institutions and research institutions. At the same time, based on the professional knowledge and research basis of experts in the field, and discussed and confirmed with industry organizations or professional institutions, the experts set the weight factors corresponding to the biomolecule coverage density of the collection area and the weight factors corresponding to the biomolecule layer thickness according to their own experience and knowledge.

[0067] In another specific embodiment, the evaluation of whether the surface biomolecule uniformity corresponding to each graphite electrode in each model is qualified is performed as follows: D1. The surface biomolecule uniformity value corresponding to each graphite electrode in each model is compared with the set surface biomolecule uniformity value range corresponding to the standard graphite electrode. If the surface biomolecule uniformity value corresponding to a certain graphite electrode in a certain model is within the set surface biomolecule uniformity value range corresponding to the standard graphite electrode, it indicates that the surface biomolecule uniformity corresponding to the graphite electrode in the model is qualified, thereby detecting and analyzing the surface defects of each graphite electrode in each model.

[0068] D2. If the surface biomolecule uniformity value corresponding to a certain graphite electrode in a certain model is less than the minimum value of the surface biomolecule uniformity value range corresponding to the set standard graphite electrode, it indicates that the surface biomolecule uniformity corresponding to the graphite electrode in this model is unqualified. At the same time, continue to stir according to the standard stirring time, increase the stirring speed and stirring time, add 0.01% co-solvent, and after the stirring is completed, continue to evaluate whether the surface biomolecule uniformity corresponding to the graphite electrode of this model is qualified according to the evaluation process until the surface biomolecule uniformity corresponding to the graphite electrode of this model is qualified.

[0069] D3. If the surface biomolecule uniformity value corresponding to a certain graphite electrode in a certain model is greater than the maximum value of the surface biomolecule uniformity value range corresponding to the set standard graphite electrode, it indicates that the surface biomolecule uniformity corresponding to the graphite electrode in this model is unqualified. At the same time, continue stirring according to the standard stirring time, and reduce the stirring speed and stirring time to reduce the biomolecule concentration to about 3 / 4 of the original. After the stirring is completed, continue to evaluate whether the surface biomolecule uniformity corresponding to the graphite electrode of this model is qualified according to the evaluation process until the surface biomolecule uniformity corresponding to the graphite electrode of this model is qualified.

[0070] Graphite electrode defect detection module: used to detect and analyze the surface defects of each graphite electrode in each model after the surface biological molecule uniformity corresponding to each graphite electrode in each model is qualified, so as to evaluate whether the surface corresponding to each graphite electrode in each model is defective, and record each graphite electrode in each model with surface defects as each qualified graphite electrode in each model, and then analyze the severity of the defects of each qualified graphite electrode in each model.

[0071] In a specific embodiment, the evaluation of whether the surface corresponding to each graphite electrode in each model is defective is performed as follows: S1. Using a fluorescent imaging device, a fluorescent image corresponding to each model of graphite electrode is obtained, and the surface of each graphite electrode in each model is divided into multiple sub-regions, thereby obtaining surface detection data corresponding to each sub-region in each graphite electrode in each model, the surface detection data including fluorescence intensity attenuation and fluorescence intensity change rate, the fluorescence intensity attenuation and fluorescence intensity change rate corresponding to each sub-region in each graphite electrode in each model are input into a defect assessment value evaluation model, and the defect assessment value results corresponding to each graphite electrode in each model are output.

[0072] S2. The defect assessment value result includes the values ​​of 1 and -1. When the defect assessment value result corresponding to a certain graphite electrode in a certain model is 1, it means that the surface corresponding to the graphite electrode in the model has no defects. Conversely, when the defect assessment value result corresponding to a certain graphite electrode in a certain model is -1, it means that the surface corresponding to the graphite electrode in the model has defects.

[0073] In another specific embodiment, the expression of the defect assessment value evaluation model is: In the formula, π hg represents the defect assessment result corresponding to the hth graphite electrode in the gth model, γ hg represents the defect assessment value corresponding to the h-th graphite electrode in the g-th model, γ′ is the set defect assessment value threshold, h represents the number corresponding to each model, h is a positive integer, and g represents the number corresponding to each graphite electrode, g is a positive integer;

[0074] The fluorescence intensity attenuation and fluorescence intensity change rate corresponding to each sub-region in each graphite electrode of each model are recorded as and y represents the number corresponding to each sub-region. y is a positive integer. Substitute it into the calculation formula: The defect assessment value γ corresponding to the hth graphite electrode in the gth model is obtained hg , where F′ and Z′ are the standard fluorescence intensity attenuation and standard fluorescence intensity change rate corresponding to the set sub-region, ν1 and ν2 are the weight factors corresponding to the fluorescence intensity attenuation and fluorescence intensity change rate of the set sub-region, σ1 and σ2 are the adjustment factors corresponding to the fluorescence intensity attenuation and fluorescence intensity change rate of the set sub-region, respectively, and e represents a natural constant.

[0075] It should be noted that σ1 and σ2 are both greater than 0 and less than 1.

[0076] It should also be noted that through the summary of a large amount of research data and experimental data, the standard fluorescence intensity attenuation and standard fluorescence intensity change rate corresponding to the sub-region are set according to professional institutions and research institutions. At the same time, based on the professional knowledge and research basis of experts in the field, they are discussed and confirmed with industry organizations or professional institutions. Experts set the weight factor corresponding to the fluorescence intensity attenuation of the sub-region and the weight factor corresponding to the fluorescence intensity change rate according to their own experience and knowledge, as well as the adjustment factor corresponding to the fluorescence intensity attenuation of the sub-region and the adjustment factor corresponding to the fluorescence intensity change rate.

[0077] In another specific embodiment, the defect severity of each qualified graphite electrode in each model is analyzed, and the specific analysis process is as follows: the defect assessment value corresponding to each qualified graphite electrode in each model is calculated with the set standard defect assessment value threshold, so as to obtain the difference between the defect assessment value corresponding to each qualified graphite electrode in each model and the set standard defect assessment value threshold, and compare the difference with the difference interval corresponding to each defect severity in the database; if the difference is within the difference interval corresponding to a defect severity in the database, the defect severity in the database is recorded as the defect severity of the qualified graphite electrode in the model.

[0078] Embodiments of the present invention Figure 2 As shown, a graphite electrode defect detection method includes: step one, screening of detection marker components: before surface defect detection of various types of graphite electrodes in a target enterprise, detection marker components corresponding to various types of graphite electrodes are cultivated, the detection marker components include various biological molecules and various fluorescent groups, and then qualified biological molecules and qualified fluorescent groups corresponding to various types of graphite electrodes are screened out.

[0079] Step 2: Uniformity determination: Detect surface defects of each graphite electrode in each model, analyze the uniformity of surface biomolecules corresponding to each graphite electrode in each model, and evaluate whether the uniformity of surface biomolecules corresponding to each graphite electrode in each model is qualified.

[0080] Step 3. Detection of graphite electrode defects: When the surface biomolecule uniformity corresponding to each graphite electrode in each model is qualified, the surface defects of each graphite electrode in each model are detected and analyzed to evaluate whether the surface corresponding to each graphite electrode in each model is defective, and each graphite electrode in each model with surface defects is recorded as a qualified graphite electrode in each model, and then the severity of the defects of each qualified graphite electrode in each model is analyzed.

[0081] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they shall all fall within the protection scope of the present invention.

Claims

1. A graphite electrode defect detection system, characterized in that: include: Detection marker component screening module: used to cultivate detection marker components corresponding to various types of graphite electrodes in target enterprises before surface defect detection of various types of graphite electrodes. The detection marker components include various biological molecules and various fluorescent groups, and then screen out various qualified biological molecules and various qualified fluorescent groups corresponding to various types of graphite electrodes; Uniformity judgment module: used to detect surface defects of each graphite electrode in each model, so as to analyze the uniformity value of surface biomolecules corresponding to each graphite electrode in each model, and evaluate whether the uniformity of surface biomolecules corresponding to each graphite electrode in each model is qualified; Graphite electrode defect detection module: used to detect and analyze the surface defects of each graphite electrode in each model after the surface biological molecule uniformity corresponding to each graphite electrode in each model is qualified, so as to evaluate whether the surface corresponding to each graphite electrode in each model is defective, and record each graphite electrode in each model with surface defects as each qualified graphite electrode in each model, and then analyze the severity of the defects of each qualified graphite electrode in each model.

2. A graphite electrode defect detection system as claimed in claim 1, characterized in that: The specific cultivation process of cultivating the detection marker components corresponding to each type of graphite electrode is as follows: A1. Acquisition of historical defect type information: From the historical inspection records of the target enterprise, the surface defect information of various types of graphite electrodes during the historical periodic inspection process is sorted out by analyzing the inspection reports, image data and related quality feedback data in the database. The surface defect information includes various surface defect types; A2. Design of graphite electrode cultivation samples: Based on the surface defect types of various types of graphite electrodes obtained, simulate their real defect characteristics, and design graphite electrode cultivation samples of various types of graphite electrodes according to the corresponding surface defect types in the historical cycle detection process; A3. Cultivation of detection labeling components: Place the designed graphite electrode cultivation samples of various types in the corresponding incubators, and then place a number of biological molecules and a number of fluorescent groups in the incubators of the corresponding types of the graphite electrode cultivation samples. At the same time, the environmental conditions of the incubator can be adjusted, and the environmental conditions of the incubator are adjusted to a suitable environment for the biological molecules and the fluorescent groups. In this way, the biological molecules and fluorescent groups corresponding to the various types of graphite electrodes are cultivated.

3. A graphite electrode defect detection system as claimed in claim 2, characterized in that: The detection marker component screening module also includes an affinity specificity analysis unit and a binding specificity analysis unit; The biomolecule specific value analysis unit is used to obtain the detection index corresponding to each biomolecule in each type of graphite electrode incubation sample when each biomolecule corresponding to each type of graphite electrode incubation sample reaches the set standard incubation time, and the detection index includes enrichment multiple, cross-reaction rate and equilibrium dissociation constant, and then analyze and obtain the affinity specific value corresponding to each biomolecule in each type of graphite electrode incubation sample; The binding specific value analysis unit is used to obtain the binding index corresponding to each fluorescent group in each type of graphite electrode incubation sample when each fluorescent group corresponding to each type of graphite electrode incubation sample reaches the set standard incubation time. The binding index includes labeling rate, intensity change rate and spectral displacement, and then analyzes to obtain the binding specific value corresponding to each fluorescent group in each type of graphite electrode incubation sample.

4. A graphite electrode defect detection system as claimed in claim 3, characterized in that: The qualified biomolecules and qualified fluorescent groups corresponding to the graphite electrodes of various types are screened out, and the specific screening process is as follows: B1. Input the enrichment multiple, cross-reaction rate and equilibrium dissociation constant corresponding to each biomolecule in each type of graphite electrode incubation sample into the affinity specific analysis model, and output the affinity specific value corresponding to each biomolecule in each type of graphite electrode incubation sample; B2. Compare the affinity specific value corresponding to each biomolecule in the samples cultivated with each type of graphite electrode with the affinity specific value corresponding to the set standard biomolecule. If the affinity specific value corresponding to a biomolecule in the samples cultivated with each type of graphite electrode is greater than or equal to the affinity specific value corresponding to the set standard biomolecule, the biomolecule in the samples cultivated with the graphite electrode of the model is recorded as the qualified biomolecule corresponding to the graphite electrode of the model. In this way, the qualified biomolecules corresponding to the graphite electrodes of the models are screened out. B3, inputting the labeling rate, intensity change rate and spectral shift corresponding to each fluorescent group in each type of graphite electrode incubation sample into the binding specific analysis model, and outputting the binding specific value corresponding to each fluorescent group in each type of graphite electrode incubation sample; B4. Compare the binding specificity values ​​corresponding to each fluorescent group in each model of graphite electrode incubation samples with the binding specificity values ​​corresponding to the set standard fluorescent group. If the binding specificity value corresponding to a fluorescent group in a certain model of graphite electrode incubation samples is greater than or equal to the binding specificity value corresponding to the set standard fluorescent group, then the fluorescent group in the graphite electrode incubation samples of this model is recorded as the qualified fluorescent group corresponding to this model of graphite electrode. In this way, the qualified fluorescent groups corresponding to each model of graphite electrode are screened out.

5. A graphite electrode defect detection system as claimed in claim 1, characterized in that: The specific analysis process of analyzing the uniform value of surface biomolecules corresponding to each graphite electrode in each model is as follows: C1. When detecting the surface defects of each graphite electrode in each model, immerse each graphite electrode in each model into the corresponding detection box of each qualified biomolecule and each qualified fluorescent group, so as to start stirring the detection box corresponding to each graphite electrode in each model, and set a number of collection areas at the same time, and after the standard stirring time is over, collect the surface biomolecule attachment data corresponding to each graphite electrode in each model, and the surface biomolecule attachment data includes the biomolecule coverage density and biomolecule layer thickness corresponding to each collection area; C2, the biomolecule coverage density and biomolecule layer thickness corresponding to each collection area in each graphite electrode of each model are recorded as and h represents the number corresponding to each model, h is a positive integer, g represents the number corresponding to each graphite electrode, g is a positive integer, k represents the number corresponding to each collection area, k is a positive integer, substitute into the calculation formula: The surface biomolecule uniformity value ρ corresponding to each graphite electrode of each model is obtained hg , where Q′ and E′ are the standard biomolecule coverage density and standard biomolecule layer thickness values ​​corresponding to the set acquisition area, respectively; η1 and η2 are the weight factors corresponding to the biomolecule coverage density and biomolecule layer thickness of the set acquisition area, respectively.

6. A graphite electrode defect detection system as claimed in claim 5, characterized in that: The specific evaluation process of evaluating whether the surface biomolecule uniformity corresponding to each graphite electrode in each model is qualified is as follows: D1. Compare the surface biomolecule uniformity value corresponding to each graphite electrode in each model with the set surface biomolecule uniformity value interval corresponding to the standard graphite electrode. If the surface biomolecule uniformity value corresponding to a graphite electrode in a certain model is within the set surface biomolecule uniformity value interval corresponding to the standard graphite electrode, it indicates that the surface biomolecule uniformity corresponding to the graphite electrode in this model is qualified, so as to detect and analyze the surface defects of each graphite electrode in each model; D2. If the surface biomolecule uniformity value corresponding to a certain graphite electrode in a certain model is less than the minimum value of the surface biomolecule uniformity value interval corresponding to the set standard graphite electrode, it indicates that the surface biomolecule uniformity corresponding to the graphite electrode in this model is unqualified. At the same time, continue to stir according to the standard stirring time, increase the stirring speed and stirring time, add 0.01% co-solvent, and after the stirring is completed, continue to evaluate whether the surface biomolecule uniformity corresponding to the graphite electrode of this model is qualified according to the evaluation process until the surface biomolecule uniformity corresponding to the graphite electrode of this model is qualified; D3. If the surface biomolecule uniformity value corresponding to a certain graphite electrode in a certain model is greater than the maximum value of the surface biomolecule uniformity value range corresponding to the set standard graphite electrode, it indicates that the surface biomolecule uniformity corresponding to the graphite electrode in this model is unqualified. At the same time, continue stirring according to the standard stirring time, and reduce the stirring speed and stirring time to reduce the biomolecule concentration to about 3 / 4 of the original. After the stirring is completed, continue to evaluate whether the surface biomolecule uniformity corresponding to the graphite electrode of this model is qualified according to the evaluation process until the surface biomolecule uniformity corresponding to the graphite electrode of this model is qualified.

7. A graphite electrode defect detection system as claimed in claim 6, characterized in that: The specific evaluation process of evaluating whether the surface corresponding to each graphite electrode in each model is defective is as follows: S1. Use a fluorescent imaging device to obtain fluorescent images corresponding to each model of graphite electrode, divide the surface of each graphite electrode in each model into multiple sub-areas, so as to obtain surface detection data corresponding to each sub-area in each graphite electrode in each model, the surface detection data including fluorescence intensity attenuation and fluorescence intensity change rate, input the fluorescence intensity attenuation and fluorescence intensity change rate corresponding to each sub-area in each graphite electrode in each model into a defect assessment value evaluation model, and output the defect assessment value results corresponding to each graphite electrode in each model; S2. The defect assessment value result includes the values ​​of 1 and -1. When the defect assessment value result corresponding to a certain graphite electrode in a certain model is 1, it means that the surface corresponding to the graphite electrode in the model has no defects. Conversely, when the defect assessment value result corresponding to a certain graphite electrode in a certain model is -1, it means that the surface corresponding to the graphite electrode in the model has defects.

8. A graphite electrode defect detection system as claimed in claim 7, characterized in that: The expression of the defect evaluation value evaluation model is: In the formula, π hg represents the defect assessment result corresponding to the hth graphite electrode in the gth model, γ hg represents the defect assessment value corresponding to the h-th graphite electrode in the g-th model, γ′ is the set defect assessment value threshold, h represents the number corresponding to each model, h is a positive integer, and g represents the number corresponding to each graphite electrode, g is a positive integer; The fluorescence intensity attenuation and fluorescence intensity change rate corresponding to each sub-region in each graphite electrode of each model are recorded as and y represents the number corresponding to each sub-region. y is a positive integer. Substitute it into the calculation formula: The defect assessment value γ corresponding to the hth graphite electrode in the gth model is obtained hg , where F′ and Z′ are the standard fluorescence intensity attenuation and standard fluorescence intensity change rate corresponding to the set sub-region, ν1 and ν2 are the weight factors corresponding to the fluorescence intensity attenuation and fluorescence intensity change rate of the set sub-region, σ1 and σ2 are the adjustment factors corresponding to the fluorescence intensity attenuation and fluorescence intensity change rate of the set sub-region, respectively, and e represents a natural constant.

9. A graphite electrode defect detection system as claimed in claim 8, characterized in that: The severity of defects of each qualified graphite electrode of each model is analyzed, and the specific analysis process is as follows: The difference between the defect assessment value corresponding to each qualified graphite electrode in each model and the set standard defect assessment value threshold is calculated to obtain the difference between the defect assessment value corresponding to each qualified graphite electrode in each model and the set standard defect assessment value threshold, and the difference is compared with the difference interval corresponding to each defect severity in the database. If the difference is within the difference interval corresponding to a certain defect severity in the database, the defect severity in the database is recorded as the defect severity of the qualified graphite electrode in this model.

10. A graphite electrode defect detection method implementing the graphite electrode defect detection system according to any one of claims 1 to 9, characterized in that: include: Step 1: Screening of detection marker components: Before surface defect detection of various types of graphite electrodes in the target enterprise, the detection marker components corresponding to each type of graphite electrode are cultivated. The detection marker components include various biomolecules and various fluorescent groups, and then the qualified biomolecules and qualified fluorescent groups corresponding to each type of graphite electrode are screened out; Step 2: Uniformity determination: Detect surface defects of each graphite electrode in each model, analyze the uniformity of surface biomolecules corresponding to each graphite electrode in each model, and evaluate whether the uniformity of surface biomolecules corresponding to each graphite electrode in each model is qualified; Step 3. Detection of graphite electrode defects: When the surface biomolecule uniformity corresponding to each graphite electrode in each model is qualified, the surface defects of each graphite electrode in each model are detected and analyzed to evaluate whether the surface corresponding to each graphite electrode in each model is defective, and each graphite electrode in each model with surface defects is recorded as a qualified graphite electrode in each model, and then the severity of the defects of each qualified graphite electrode in each model is analyzed.

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