A battery aluminum foil coating detection equipment

Abstract

The present invention relates to the technical field of battery aluminum foil coating detection, and in particular to a battery aluminum foil coating detection device, comprising a visual detection platform, an information collection unit, a potential feedback unit, a front-end image supervision unit, a front-end power supply balancing unit, a detection processing unit and a management and maintenance unit; the present invention ensures the validity of the battery aluminum foil coating detection result by analyzing from the detection process, and analyzes from two perspectives of a front-end camera and a camera power supply in the detection process, and analyzes in combination with potential factors, which helps to improve the visual detection accuracy, and at the same time ensures the image acquisition quality of the acquisition end, so as to reduce the influence of the camera and the camera power supply on the detection, and at the same time, under the premise that the front-end camera and the camera power supply are normal, analyzes from the perspective of the battery aluminum foil itself to avoid interference of the battery aluminum foil itself on the detection, so as to further improve the detection accuracy, so as to ensure the stability and effectiveness of image acquisition.

Description

Technical Field

[0001] The present invention relates to the technical field of battery aluminum foil coating detection, and in particular to a battery aluminum foil coating detection device. Background Art

[0002] As a power source for new energy vehicles, power lithium batteries are currently widely used in the automotive industry. As the positive electrode material of power lithium batteries, aluminum foil has extremely high surface quality requirements from various battery manufacturers. For example, visually there must be no scratches, oil stains, pits, etc.

[0003] In the prior art, visual method and photoelectric method are mostly used to detect pinholes in aluminum foil of lithium battery soft package. The visual method generally uses industrial cameras such as CMOS linear array industrial cameras, while the photoelectric method uses analog photoelectric elements such as photodiodes and PSDs for detection. However, in the prior art, the visual method has a large deviation in the detection results, and it is impossible to supervise the interference factors in the detection process, which leads to a decrease in the detection accuracy of welding detection and dispensing detection, and it is impossible to reasonably manage the interference factors;

[0004] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0005] The purpose of the present invention is to provide a battery aluminum foil coating detection device to solve the above-mentioned technical defects. The present invention ensures the validity of the battery aluminum foil coating detection results by analyzing the detection process, and analyzes from two perspectives: the front-end camera and the camera power supply in the detection process. At the same time, the analysis is combined with potential factors to help improve the visual detection accuracy, while ensuring the image acquisition quality at the acquisition end to reduce the impact of the camera and the camera power supply on the detection. At the same time, under the premise that the front-end camera and the camera power supply are normal, the battery aluminum foil itself is analyzed to avoid interference with the detection by the battery aluminum foil itself, so as to further improve the detection accuracy.

[0006] The purpose of the present invention can be achieved by the following technical solutions: A battery aluminum foil coating detection device, including a visual detection platform, an information acquisition unit, a potential feedback unit, a front-end image supervision unit, a front-end power supply balancing unit, a detection processing unit, and a management and maintenance unit;

[0007] When the visual inspection platform generates an operation and management instruction, the operation and management instruction is sent to the information collection unit and the potential feedback unit. After receiving the operation and management instruction, the potential feedback unit immediately collects the potential interference data of the battery aluminum foil coating inspection equipment. The potential interference data includes the number of mirror cleaning times and the adjustment risk value, and performs potential collection interference evaluation analysis on the potential interference data, and sends the obtained potential impact evaluation coefficient Q to the front-end image supervision unit;

[0008] After receiving the operation and management instruction, the information collection unit immediately collects the camera interference data and stability risk data of the battery aluminum foil coating detection equipment. The camera interference data includes the image interference value and the visual risk value. The stability risk data includes the number of temperature rises and the number of voltage fluctuations. The camera interference data and the stability risk data are sent to the front-end image supervision unit and the front-end power supply balance unit. After receiving the camera interference data and the potential impact assessment coefficient Q, the front-end image supervision unit immediately performs visual image collection supervision feedback analysis and in-depth comparison analysis on the camera interference data, sends the obtained normal signal to the detection processing unit, and sends the obtained abnormal signal to the management and maintenance unit;

[0009] After receiving the stability risk data, the front-end power supply balancing unit immediately collects the stability risk data to support the imbalance risk assessment operation, sends the obtained feedback signal to the detection processing unit, and sends the obtained risk signal to the management and maintenance unit through the detection processing unit;

[0010] After receiving the normal signal and feedback signal, the detection and processing unit immediately collects the surface data of the battery aluminum foil, including the wrinkle impact value and deviation value, and performs detection interference supervision analysis on the surface data, and sends the obtained impact signal and effective signal to the management and maintenance unit.

[0011] Preferably, the potential collection interference evaluation and analysis process of the potential feedback unit is as follows:

[0012] S1: After the equipment starts running, a monitoring period is set and marked as a time threshold, and the number of mirror cleaning times of the camera in the battery aluminum foil coating detection equipment within the time threshold is obtained, and then the interval time between the cleaning times is obtained, and at the same time, the environmental obstruction value of the environment in which the camera is located within each interval time is obtained. The environmental obstruction value represents the product value obtained by normalizing the mean value of the environmental dust concentration and the mean value of the environmental humidity. The product value obtained by normalizing the data of each interval time and the corresponding environmental obstruction value is marked as an interval influence value, and a set B of interval influence values ​​is constructed, and the mean value of the set B is marked as the mirror interference value;

[0013] S2: Obtain the adjustment risk value of the camera in the battery aluminum foil coating inspection equipment within the time threshold, the adjustment risk value represents the part of the focus value that deviates from the preset range, compare and analyze the adjustment risk value with the stored preset adjustment risk value, mark the part of the adjustment risk value greater than the preset adjustment risk value threshold as the deviation risk value, and label the mirror interference value and the deviation risk value as JG and PL respectively;

[0014] S3: According to the formula The potential impact assessment coefficient is obtained, where f1 and f2 are preset weight factor coefficients of the mirror interference value and the deviation risk value, respectively, f3 is the fault tolerance factor coefficient, f1, f2 and f3 are all greater than zero, and Q is the potential impact assessment coefficient.

[0015] Preferably, the visual image acquisition supervision feedback analysis process of the front-end image supervision unit is as follows:

[0016] T1: Obtain the image interference value of the camera in the battery aluminum foil coating inspection equipment within the time threshold. The image interference value represents the product of the total area of ​​the image spots and the maximum shooting area of ​​the camera after data normalization. The image interference value is compared and analyzed with the preset image interference value threshold, and the part of the image interference value greater than the preset image interference value threshold is marked as the acquisition risk value;

[0017] T2: Obtain the visual risk value of the camera in the battery aluminum foil coating inspection equipment within the time threshold. The visual risk value represents the product of the camera's shake frequency and the equipment's vibration frequency after data normalization, and then the product of the part whose average number of pixels per centimeter is lower than the preset threshold after data normalization. Compare and analyze the visual risk value with the stored preset visual risk value threshold, mark the part whose visual risk value is greater than the preset visual risk value threshold as the image quality impact value, and label the acquisition risk value and image quality impact value as CJ and TZ, respectively.

[0018] Preferably, the in-depth comparison and analysis process of the front-end image supervision unit is as follows:

[0019] According to the formula The visual risk assessment coefficient is obtained, where a1, a2 and a3 are the preset proportional factor coefficients of the acquisition risk value, image quality impact value and potential impact assessment coefficient Q respectively, a1, a2 and a3 are all greater than zero, a4 is the preset correction factor coefficient, and its value is 2.196, R is the visual risk assessment coefficient, and the visual risk assessment coefficient R is compared and analyzed with the preset visual risk assessment coefficient threshold value stored in the internal input:

[0020] If the ratio between the visual risk assessment coefficient R and the preset visual risk assessment coefficient threshold is less than 1, a normal signal is generated;

[0021] If the ratio between the visual risk assessment coefficient R and the preset visual risk assessment coefficient threshold is greater than or equal to 1, an abnormal signal is generated.

[0022] Preferably, the collection support imbalance risk assessment operation process of the front-end power supply balancing unit is as follows:

[0023] SS1: Obtain the number of times the power supply of the camera in the battery aluminum foil coating inspection equipment is heated up within the time threshold, obtain the time interval and temperature change value between each temperature increase number, and then construct a set A of time intervals, obtain the discrete coefficient of set A and the mean of set A, and mark the product of the discrete coefficient of set A and the mean of set A after data normalization as the trend risk value, and at the same time obtain the mean of the temperature change value, and mark it as the constant disturbance mean, and mark the product of the trend risk value and the constant disturbance mean after data normalization as the imbalance ratio value;

[0024] SS2: Obtain the number of voltage fluctuations of the camera power supply in the battery aluminum foil coating inspection equipment within the time threshold, and then obtain the voltage fluctuation time corresponding to the number of voltage fluctuations. A rectangular coordinate system is established with the number of voltage fluctuations as the X-axis and the voltage fluctuation time as the Y-axis. The voltage fluctuation time curve is drawn by plotting points, and then the slope of the voltage fluctuation time curve is obtained and marked as the voltage imbalance rate;

[0025] SS3: Compare and analyze the imbalance multiplier value and voltage imbalance rate with the preset imbalance multiplier value threshold and preset voltage imbalance rate threshold stored in the system:

[0026] If the imbalance multiplier value is less than the preset imbalance multiplier value threshold, and the voltage imbalance rate is less than the preset voltage imbalance rate threshold, a feedback signal is generated;

[0027] If the imbalance multiplier value is greater than or equal to a preset imbalance multiplier value threshold, or the voltage imbalance rate is greater than or equal to a preset voltage imbalance rate threshold, a risk signal is generated.

[0028] Preferably, the detection interference supervision analysis process of the detection processing unit is as follows:

[0029] Obtain the wrinkle influence value of the battery aluminum foil coating detection equipment within the time threshold, the wrinkle influence value represents the product value of the wrinkle length and the wrinkle area of ​​the battery aluminum foil after data normalization processing, compare and analyze the wrinkle influence value with the preset wrinkle influence value threshold stored therein, and mark the part of the wrinkle influence value greater than the preset wrinkle influence value threshold as a coating interference value;

[0030] Obtain the deviation value of the battery aluminum foil coating detection equipment within the time threshold. The deviation value represents the portion of the coating speed that deviates from the preset range, and the portion of the coating pressure that deviates from the preset range. The product value is obtained after data normalization. The deviation value is compared and analyzed with the preset deviation value threshold stored internally, and the portion of the deviation value greater than the preset deviation value threshold is marked as a deformation risk value;

[0031] Compare and analyze the coating interference value and deformation risk value with the preset coating interference value threshold and preset deformation risk value threshold that are stored internally:

[0032] If the coating interference value is less than the preset coating interference value threshold, and the deformation risk value is less than the preset deformation risk value threshold, a valid signal is generated;

[0033] If the coating interference value is greater than or equal to a preset coating interference value threshold, or the deformation risk value is greater than or equal to a preset deformation risk value threshold, an influence signal is generated.

[0034] The beneficial effects of the present invention are as follows:

[0035] (1) The present invention ensures the validity of the battery aluminum foil coating test results by analyzing the test process, and analyzes from two perspectives: the front-end camera and the camera power supply in the test process. At the same time, the analysis is combined with potential factors to help improve the visual detection accuracy. At the same time, the image acquisition quality of the acquisition end is guaranteed to reduce the impact of the camera and the camera power supply on the test. At the same time, under the premise that the front-end camera and the camera power supply are normal, the battery aluminum foil itself is analyzed to avoid interference with the test by the battery aluminum foil itself, so as to further improve the detection accuracy.

[0036] (2) The present invention performs potential acquisition interference assessment and analysis on potential interference data so as to improve data support when performing visual image acquisition supervision feedback analysis on camera interference data to ensure the comprehensiveness of the analysis data, and rationally manages the cameras in the equipment according to the information feedback to reduce the impact of the cameras on visual detection. At the same time, an acquisition support imbalance risk assessment operation is performed on the stability risk data to understand the impact of the camera power supply on the acquisition, so as to perform rational management according to the information feedback to ensure the stability and effectiveness of image acquisition. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The present invention will be further described below in conjunction with the accompanying drawings;

[0038] Figure 1 It is a flowchart of the system of the present invention;

[0039] Figure 2 This is an information flow reference diagram of Embodiment 1 of the present invention. 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] Embodiment 1:

[0042] See also Figure 1 to Figure 2As shown, the present invention is a battery aluminum foil coating detection device, including a visual detection platform, an information collection unit, a potential feedback unit, a front-end image supervision unit, a front-end power supply balancing unit, a detection processing unit and a management and maintenance unit, the visual detection platform is connected to the information collection unit and the potential feedback unit in a one-way communication, the information collection unit is connected to the front-end image supervision unit and the front-end power supply balancing unit in a one-way communication, the front-end image supervision unit and the front-end power supply balancing unit are connected to the detection processing unit in a one-way communication, the front-end image supervision unit is connected to the management and maintenance unit in a one-way communication, and the potential feedback unit is connected to the front-end image supervision unit in a one-way communication;

[0043] When the visual inspection platform generates an operation and management instruction, it sends the operation and management instruction to the information collection unit and the potential feedback unit. After receiving the operation and management instruction, the potential feedback unit immediately collects the potential interference data of the battery aluminum foil coating inspection equipment. The potential interference data includes the number of mirror cleaning times and the adjustment risk value, and performs potential collection interference evaluation and analysis on the potential interference data to determine the impact of potential factors on the inspection. The specific potential collection interference evaluation and analysis process is as follows:

[0044] After the equipment starts running, a monitoring period is set and marked as a time threshold. The number of mirror cleaning times of the camera in the battery aluminum foil coating detection equipment within the time threshold is obtained, and then the interval time between the cleaning times is obtained. At the same time, the environmental obstruction value of the environment in which the camera is located within each interval time is obtained. The environmental obstruction value represents the product value obtained by normalizing the average value of the environmental dust concentration and the average value of the environmental humidity. The product value obtained by normalizing the data of each interval time and the corresponding environmental obstruction value is marked as an interval influence value, and a set B of interval influence values ​​is constructed, and the mean value of the set B is marked as a mirror interference value. It should be noted that the larger the value of the mirror interference value, the greater the potential detection interference risk of the camera;

[0045] Obtain the adjustment risk value of the camera in the battery aluminum foil coating inspection equipment within the time threshold, the adjustment risk value represents the part of the focus value that deviates from the preset range, compare and analyze the adjustment risk value with the stored preset adjustment risk value, mark the part of the adjustment risk value greater than the preset adjustment risk value threshold as the deviation risk value, and label the mirror interference value and the deviation risk value as JG and PL respectively;

[0046] According to the formula A potential impact assessment coefficient is obtained, wherein f1 and f2 are preset weight factor coefficients of the mirror interference value and the deviation risk value, respectively, f3 is a fault tolerance factor coefficient, f1, f2 and f3 are all greater than zero, Q is a potential impact assessment coefficient, and the potential impact assessment coefficient Q is sent to the front-end image supervision unit;

[0047] After receiving the operation and management instruction, the information collection unit immediately collects the camera interference data and stability risk data of the battery aluminum foil coating detection equipment. The camera interference data includes the image interference value and the visual risk value. The stability risk data includes the number of temperature rises and the number of voltage fluctuations. The camera interference data and stability risk data are sent to the front-end image supervision unit and the front-end power supply balance unit. After receiving the camera interference data and the potential impact assessment coefficient Q, the front-end image supervision unit immediately performs visual image collection supervision feedback analysis on the camera interference data to determine whether the visual image is affected by the camera, so as to provide timely early warning feedback management to ensure the effective collection of the camera and improve the detection accuracy. The specific visual image collection supervision feedback analysis process is as follows:

[0048] The image interference value of the camera in the battery aluminum foil coating detection equipment within the time threshold is obtained. The image interference value represents the product value of the total area of ​​the image spots and the maximum shooting area of ​​the camera after data normalization. The image interference value is compared and analyzed with the preset image interference value threshold. The part where the image interference value is greater than the preset image interference value threshold is marked as the acquisition risk value. It should be noted that the larger the value of the acquisition risk value, the deeper the impact of the camera on the detection;

[0049] The visual risk value of the camera in the battery aluminum foil coating inspection equipment within the time threshold is obtained. The visual risk value represents the product value obtained by normalizing the camera's shake frequency and the equipment's vibration frequency, and then the product value obtained by normalizing the part whose average number of pixels per centimeter is lower than the preset threshold. The visual risk value is compared and analyzed with the stored preset visual risk value threshold, and the part whose visual risk value is greater than the preset visual risk value threshold is marked as the image quality impact value. It should be noted that the larger the value of the image quality impact value, the deeper the impact of the camera on the detection. The acquisition risk value and the image quality impact value are labeled CJ and TZ respectively;

[0050] According to the formula The visual risk assessment coefficient is obtained, where a1, a2 and a3 are the preset proportional factor coefficients of the acquisition risk value, image quality impact value and potential impact assessment coefficient Q respectively. The proportional factor coefficient is used to correct the deviation of various parameters in the formula calculation process, so as to make the calculation result more accurate. a1, a2 and a3 are all greater than zero. a4 is the preset correction factor coefficient, which is 2.196. R is the visual risk assessment coefficient. The visual risk assessment coefficient R is compared with the preset visual risk assessment coefficient threshold stored in the internal input:

[0051] If the ratio between the visual risk assessment coefficient R and the preset visual risk assessment coefficient threshold is less than 1, a normal signal is generated and sent to the detection processing unit;

[0052] If the ratio between the visual risk assessment coefficient R and the preset visual risk assessment coefficient threshold is greater than or equal to 1, an abnormal signal is generated and sent to the management and maintenance unit. After receiving the abnormal signal, the management and maintenance unit immediately performs the preset warning operation corresponding to the abnormal signal, so as to manage the camera in the device in time to ensure the image acquisition quality at the acquisition end, which helps to improve the visual detection accuracy.

[0053] Embodiment 2:

[0054] After receiving the stability risk data, the front-end power supply balance unit immediately performs an acquisition support imbalance risk assessment operation on the stability risk data to determine whether the risk of camera power outage or freeze is too high, so as to perform rational management according to the information feedback to ensure the stability and effectiveness of image acquisition. The specific acquisition support imbalance risk assessment operation process is as follows:

[0055] The number of times the power supply of the camera in the battery aluminum foil coating detection equipment is heated up within the time threshold is obtained, and the time interval and temperature change value between each temperature increase number are obtained, and then a set A of time interval durations is constructed, and the discrete coefficient of set A and the mean of set A are obtained, and the product value obtained by normalizing the discrete coefficient of set A and the mean of set A is marked as a trend risk value, and the mean of the temperature change value is obtained at the same time, and is marked as a constant disturbance mean, and the product value obtained by normalizing the trend risk value and the constant disturbance mean is marked as an imbalance ratio value. It should be noted that the larger the value of the imbalance ratio value, the higher the risk of camera power stability;

[0056] The number of voltage fluctuations of the camera power supply in the battery aluminum foil coating detection equipment within the time threshold is obtained, and then the voltage fluctuation moment corresponding to the number of voltage fluctuations is obtained. A rectangular coordinate system is established with the number of voltage fluctuations as the X-axis and the voltage fluctuation moment as the Y-axis. The voltage fluctuation moment curve is drawn by plotting points, and then the slope of the voltage fluctuation moment curve is obtained and marked as the voltage imbalance rate. It should be noted that the larger the value of the voltage imbalance rate, the higher the risk of camera power stability.

[0057] Compare and analyze the imbalance multiplier value and voltage imbalance rate with the preset imbalance multiplier value threshold and preset voltage imbalance rate threshold that are stored internally:

[0058] If the imbalance ratio value is less than the preset imbalance ratio value threshold, and the voltage imbalance ratio is less than the preset voltage imbalance ratio threshold, a feedback signal is generated and sent to the detection processing unit;

[0059] If the imbalance magnification value is greater than or equal to the preset imbalance magnification value threshold, or the voltage imbalance rate is greater than or equal to the preset voltage imbalance rate threshold, a risk signal is generated, and the risk signal is sent to the management and maintenance unit through the detection and processing unit. After receiving the risk signal, the management and maintenance unit immediately performs a preset early warning operation corresponding to the risk signal, so as to rationally manage the camera power supply according to the information feedback, so as to ensure the stability and effectiveness of image acquisition;

[0060] After receiving the normal signal and feedback signal, the detection processing unit immediately collects the surface data of the battery aluminum foil, including the wrinkle impact value and the deviation value, and performs detection interference supervision analysis on the surface data to determine whether the battery aluminum foil itself interferes with the detection, so as to make feedback adjustments in time to ensure the accuracy of the detection results. The specific detection interference supervision analysis process is as follows:

[0061] The wrinkle influence value of the battery aluminum foil coating detection equipment within the time threshold is obtained. The wrinkle influence value represents the product value of the wrinkle length and the wrinkle area of ​​the battery aluminum foil after data normalization. The wrinkle influence value is compared and analyzed with the preset wrinkle influence value threshold stored therein, and the part of the wrinkle influence value that is greater than the preset wrinkle influence value threshold is marked as a coating interference value. It should be noted that the larger the value of the coating interference value, the greater the risk of abnormal detection accuracy of the detection equipment;

[0062] The deviation value of the battery aluminum foil coating detection equipment within the time threshold is obtained. The deviation value represents the part of the coating speed that deviates from the preset range, and the part of the coating pressure that deviates from the preset range. The product value is obtained after data normalization. The deviation value is compared and analyzed with the preset deviation value threshold stored internally, and the part of the deviation value that is greater than the preset deviation value threshold is marked as a deformation risk value. It should be noted that the larger the value of the deformation risk value, the greater the risk of abnormal detection accuracy of the detection equipment;

[0063] Compare and analyze the coating interference value and deformation risk value with the preset coating interference value threshold and preset deformation risk value threshold that are stored internally:

[0064] If the coating interference value is less than the preset coating interference value threshold, and the deformation risk value is less than the preset deformation risk value threshold, a valid signal is generated;

[0065] If the coating interference value is greater than or equal to the preset coating interference value threshold, or the deformation risk value is greater than or equal to the preset deformation risk value threshold, an impact signal is generated, and the impact signal and the effective signal are sent to the management and maintenance unit. After receiving the impact signal and the effective signal, the management and maintenance unit immediately performs the preset warning operation corresponding to the impact signal and the effective signal, so as to manage the equipment according to the information feedback, so as to reduce the interference of the battery aluminum foil itself to the detection, so as to ensure the accuracy of the detection result;

[0066] In summary, the present invention ensures the validity of the battery aluminum foil coating detection results by analyzing the detection process, and analyzes from two perspectives of the front-end camera and camera power supply in the detection process, and analyzes in combination with potential factors, which helps to improve the visual detection accuracy, while ensuring the image acquisition quality at the acquisition end to reduce the impact of the camera and camera power supply on the detection. At the same time, under the premise that the front-end camera and camera power supply are normal, the battery aluminum foil itself is analyzed to avoid interference with the detection by the battery aluminum foil itself, so as to further improve the detection accuracy, and by performing potential acquisition interference assessment analysis on potential interference data, so as to improve data support when performing visual image acquisition supervision feedback analysis on camera interference data to ensure the comprehensiveness of the analysis data, and rationally manage the cameras in the equipment according to the information feedback to reduce the impact of the camera on visual detection, and at the same time, perform acquisition support imbalance risk assessment operations on stable risk data to understand the impact of camera power on acquisition, so as to perform rational management according to the information feedback to ensure the stability and effectiveness of image acquisition.

[0067] The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technicians in this field for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0068] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula that is close to the actual value. The coefficients in the formula are set by technical personnel in this field according to actual conditions. The above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited to this. Any technical personnel familiar with the technical field within the technical scope disclosed by the present invention, according to the technical solution and the inventive concept of the present invention, make equivalent replacement or change, which should be covered within the protection scope of the present invention.

Claims

1. A battery aluminum foil coating detection device, characterized in that: It includes visual inspection platform, information collection unit, potential feedback unit, front-end image supervision unit, front-end power supply balancing unit, inspection and processing unit, and management and maintenance unit; When the visual inspection platform generates an operation and management instruction, the operation and management instruction is sent to the information collection unit and the potential feedback unit. After receiving the operation and management instruction, the potential feedback unit immediately collects the potential interference data of the battery aluminum foil coating inspection equipment. The potential interference data includes the number of mirror cleaning times and the adjustment risk value, and performs potential collection interference evaluation analysis on the potential interference data, and sends the obtained potential impact evaluation coefficient Q to the front-end image supervision unit; After receiving the operation and management instruction, the information collection unit immediately collects the camera interference data and stability risk data of the battery aluminum foil coating detection equipment. The camera interference data includes the image interference value and the visual risk value. The stability risk data includes the number of temperature rises and the number of voltage fluctuations. The camera interference data and the stability risk data are sent to the front-end image supervision unit and the front-end power supply balance unit. After receiving the camera interference data and the potential impact assessment coefficient Q, the front-end image supervision unit immediately performs visual image collection supervision feedback analysis and in-depth comparison analysis on the camera interference data. The visual image collection supervision feedback analysis process of the front-end image supervision unit is as follows: T1: Obtain the image interference value of the camera in the battery aluminum foil coating inspection equipment within the time threshold. The image interference value represents the product of the total area of ​​the image spots and the maximum shooting area of ​​the camera after data normalization. The image interference value is compared and analyzed with the preset image interference value threshold, and the part of the image interference value greater than the preset image interference value threshold is marked as the acquisition risk value; T2: Obtain the visual risk value of the camera in the battery aluminum foil coating inspection equipment within the time threshold. The visual risk value represents the product of the camera's jitter frequency and the equipment's vibration frequency after data normalization, and then the product of the part whose average number of pixels per centimeter is lower than the preset threshold after data normalization. Compare and analyze the visual risk value with the stored preset visual risk value threshold, mark the part whose visual risk value is greater than the preset visual risk value threshold as the image quality impact value, and label the acquisition risk value and the image quality impact value as CJ and TZ respectively; The in-depth comparison and analysis process of the front-end image supervision unit is as follows: According to the formula The visual risk assessment coefficient is obtained, where a1, a2 and a3 are the preset proportional factor coefficients of the acquisition risk value, image quality impact value and potential impact assessment coefficient Q respectively, a1, a2 and a3 are all greater than zero, a4 is the preset correction factor coefficient, and its value is 2.196, R is the visual risk assessment coefficient, and the visual risk assessment coefficient R is compared and analyzed with the preset visual risk assessment coefficient threshold value stored in the internal input: If the ratio between the visual risk assessment coefficient R and the preset visual risk assessment coefficient threshold is less than 1, a normal signal is generated; If the ratio between the visual risk assessment coefficient R and the preset visual risk assessment coefficient threshold is greater than or equal to 1, an abnormal signal is generated, the obtained normal signal is sent to the detection processing unit, and the obtained abnormal signal is sent to the management and maintenance unit; After receiving the stability risk data, the front-end power supply balancing unit immediately performs a collection support imbalance risk assessment operation on the stability risk data. The collection support imbalance risk assessment operation process of the front-end power supply balancing unit is as follows: SS1: Obtain the number of times the power supply of the camera in the battery aluminum foil coating inspection equipment is heated up within the time threshold, obtain the time interval and temperature change value between each temperature increase number, and then construct a set A of time intervals, obtain the discrete coefficient of set A and the mean of set A, and mark the product of the discrete coefficient of set A and the mean of set A after data normalization as the trend risk value, and at the same time obtain the mean of the temperature change value, and mark it as the constant disturbance mean, and mark the product of the trend risk value and the constant disturbance mean after data normalization as the imbalance ratio value; SS2: Obtain the number of voltage fluctuations of the camera power supply in the battery aluminum foil coating inspection equipment within the time threshold, and then obtain the voltage fluctuation time corresponding to the number of voltage fluctuations. A rectangular coordinate system is established with the number of voltage fluctuations as the X-axis and the voltage fluctuation time as the Y-axis. The voltage fluctuation time curve is drawn by plotting points, and then the slope of the voltage fluctuation time curve is obtained and marked as the voltage imbalance rate; SS3: Compare and analyze the imbalance multiplier value and voltage imbalance rate with the preset imbalance multiplier value threshold and preset voltage imbalance rate threshold stored in the system: If the imbalance multiplier value is less than the preset imbalance multiplier value threshold, and the voltage imbalance rate is less than the preset voltage imbalance rate threshold, a feedback signal is generated; If the imbalance ratio value is greater than or equal to the preset imbalance ratio value threshold, or the voltage imbalance ratio is greater than or equal to the preset voltage imbalance ratio threshold, a risk signal is generated, and the obtained feedback signal is sent to the detection processing unit, and the obtained risk signal is sent to the management and maintenance unit via the detection processing unit; After receiving the normal signal and the feedback signal, the detection processing unit immediately collects the surface data of the battery aluminum foil, the surface data including the wrinkle impact value and the deviation value, and performs detection interference supervision analysis on the surface data. The detection interference supervision analysis process of the detection processing unit is as follows: Obtain the wrinkle influence value of the battery aluminum foil coating detection equipment within the time threshold, the wrinkle influence value represents the product value of the wrinkle length and the wrinkle area of ​​the battery aluminum foil after data normalization processing, compare and analyze the wrinkle influence value with the preset wrinkle influence value threshold stored therein, and mark the part of the wrinkle influence value greater than the preset wrinkle influence value threshold as a coating interference value; Obtain the deviation value of the battery aluminum foil coating detection equipment within the time threshold. The deviation value represents the portion of the coating speed that deviates from the preset range, and the portion of the coating pressure that deviates from the preset range. The product value is obtained after data normalization. The deviation value is compared and analyzed with the preset deviation value threshold stored internally, and the portion of the deviation value greater than the preset deviation value threshold is marked as a deformation risk value; Compare and analyze the coating interference value and deformation risk value with the preset coating interference value threshold and preset deformation risk value threshold that are stored internally: If the coating interference value is less than the preset coating interference value threshold, and the deformation risk value is less than the preset deformation risk value threshold, a valid signal is generated; If the coating interference value is greater than or equal to the preset coating interference value threshold, or the deformation risk value is greater than or equal to the preset deformation risk value threshold, an influence signal is generated, and the obtained influence signal and effective signal are sent to the management and maintenance unit; The potential collection interference evaluation and analysis process of the potential feedback unit is as follows: S1: After the equipment starts running, a monitoring period is set and marked as a time threshold, and the number of mirror cleaning times of the camera in the battery aluminum foil coating detection equipment within the time threshold is obtained, and then the interval time between the cleaning times is obtained, and at the same time, the environmental obstruction value of the environment in which the camera is located within each interval time is obtained. The environmental obstruction value represents the product value obtained by normalizing the mean value of the environmental dust concentration and the mean value of the environmental humidity. The product value obtained by normalizing the data of each interval time and the corresponding environmental obstruction value is marked as an interval influence value, and a set B of interval influence values ​​is constructed, and the mean value of the set B is marked as the mirror interference value; S2: Obtain the adjustment risk value of the camera in the battery aluminum foil coating inspection equipment within the time threshold, the adjustment risk value represents the part of the focus value that deviates from the preset range, compare and analyze the adjustment risk value with the stored preset adjustment risk value, mark the part of the adjustment risk value greater than the preset adjustment risk value threshold as the deviation risk value, and label the mirror interference value and the deviation risk value as JG and PL respectively; S3: According to the formula The potential impact assessment coefficient is obtained, where f1 and f2 are preset weight factor coefficients of the mirror interference value and the deviation risk value, respectively, f3 is the fault tolerance factor coefficient, f1, f2 and f3 are all greater than zero, and Q is the potential impact assessment coefficient.

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