Analysis method of barcode on metal code disk surface

Abstract

The present application provides an analysis method for barcodes on the surface of metal code disks, which relates to the field of information technology, including: using sandblasting pressure, pickling time, and roughening liquid concentration as independent variables, and barcode adhesion as a response value, obtaining the quantitative relationship between each process parameter and adhesion, and fitting with a quadratic polynomial to obtain the metal code disk surface treatment process parameters; using an adjusted barcode material formula, printing barcodes on the obtained metal code disk, preparing a batch of barcode samples, tracking and testing the samples in an actual environment, and detecting the adhesion and identification performance indicators of the samples; forming the barcode material formula and metal code disk surface treatment process parameters into enterprise standards to guide mass production, realize online early warning and quality traceability of barcode shedding, and continuously improve barcode performance and service life.

Description

Technical Field

[0001] The invention relates to the field of information technology, and in particular to an analysis method for a barcode on the surface of a metal code disk. Background Art

[0002] The barcode on the surface of the metal code disk is prone to falling off during long-term use, which seriously affects the recognition and service life of the barcode. The barcode shedding mechanism is complex and is related to many factors, including barcode materials, metal code disk surface treatment process, and environmental stress. At present, the selection of barcode materials lacks specificity and is difficult to meet actual use needs; the code disk surface treatment process parameters are not optimized enough and have poor matching with the barcode material; the influence of environmental temperature, humidity, and vibration factors is unclear, which accelerates the aging and shedding of the barcode. Therefore, it is necessary to carry out systematic and in-depth research to analyze the influence of factors such as barcode materials, code disk surface treatment processes, and environmental stress on barcode shedding, and reveal the barcode shedding failure mechanism. Summary of the invention

[0003] In order to solve the above technical problems, the present invention provides a method for analyzing the barcode on the surface of a metal code disk, which mainly includes:

[0004] According to the barcode material formula, metal code disk surface treatment process parameters, and environmental stress properties, a barcode shedding failure mechanism analysis model is established. The influence of each property on the barcode shedding is analyzed through the model, and the influencing factors of barcode shedding and the weight coefficients of each influencing factor are obtained; by changing the material components and ratios, multiple groups of barcode material samples with different formulas are prepared, and the adhesion and durability performance indicators of multiple groups of barcode material samples with different formulas are tested to determine the significance of the influence of each component on the performance, and select the barcode material formula; with sandblasting pressure, pickling time, and roughening liquid concentration as independent variables, and barcode adhesion as response value, the quantitative relationship between each process parameter and adhesion is obtained, and the metal code disk surface treatment process parameters are obtained by quadratic polynomial fitting; combined with the influencing factors of barcode shedding and the weight coefficients of each influencing factor and the environmental temperature, humidity, and vibration stress data, the barcode shedding situation is investigated under high and low temperature, high humidity, and random vibration acceleration environments. Obtain the failure time under different environmental stress levels, fit the relationship between failure time and stress, and predict the barcode shedding life; analyze the barcode shedding failure mechanism based on the selected barcode material formula and the obtained metal code disk surface treatment process parameters, simulate the barcode shedding probability under different environmental stress fluctuations, and further adjust the barcode material formula and metal code disk surface treatment process parameters. If the simulation results meet the preset requirements, apply the adjusted metal code disk surface treatment process parameters to the production and manufacturing process of the metal code disk to obtain the metal code disk; use the adjusted barcode material formula to print barcodes on the obtained metal code disk, prepare a batch of barcode samples, track and test the samples in the actual environment, and detect the adhesion and recognition performance indicators of the samples; form the barcode material formula and metal code disk surface treatment process parameters into enterprise standards to guide mass production, realize online early warning and quality traceability of barcode shedding, and continuously improve the performance and service life of barcodes.

[0005] The technical solution provided by the embodiment of the present invention may have the following beneficial effects:

[0006] The present invention discloses a method for analyzing a barcode on the surface of a metal code disk. The method first establishes a barcode shedding failure mechanism analysis model, analyzes the influence of material formula, surface treatment process and environmental stress on shedding, and obtains the weight coefficient of each factor. Then, by changing the material composition ratio and surface treatment parameters, multiple groups of samples are prepared and tested to determine the optimal barcode material formula and metal code disk surface treatment process. On this basis, the present invention examines the barcode shedding situation under an accelerated environment, establishes a failure time and stress relationship model, and realizes life prediction. Through simulation analysis and actual testing, the process parameters are further optimized, and finally an enterprise standard is formed to guide production. The present invention realizes online early warning and quality traceability of barcode shedding, effectively improves the adhesion and service life of the barcode, and provides reliable guarantee for mass production. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Figure 1 A flowchart of a method for analyzing barcode surface of the metal code disc of the present invention. DETAILED DESCRIPTION

[0008] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0009] like Figure 1 The method for analyzing the barcode on the surface of the metal code disk in this embodiment may specifically include:

[0010] S101. According to the barcode material formula, metal code disk surface treatment process parameters, and environmental stress properties, a barcode shedding failure mechanism analysis model is established. The influence of each property on the barcode shedding is analyzed through the model, and the influencing factors of the barcode shedding and the weight coefficients of each influencing factor are obtained.

[0011] The surface stress distribution data and the Vickers hardness value of the protective coating collected by the metal substrate surface stress strain sensor are obtained; the friction stress coefficient of the metal surface is calculated according to the surface stress distribution data and the stress tensor equation; the anti-corrosion strength and surface cleanliness values ​​of the barcode printing surface are collected, and a linear regression equation y*=a*x*+b* is established according to the surface stress and ink viscosity, wherein y* represents the ink viscosity, x* represents the material surface stress, a* is the slope, and b* is the intercept; according to the environmental parameters collected by the environmental temperature and humidity sensor, the least squares method is used to establish the mapping relationship h(x)=∑[f(x)-g(x)]² between the surface stress state function f(x) and the environmental parameter function g(x); if the environmental stress value of the metal surface is within the preset stress threshold range, the surface stress distribution result of the metal substrate is calculated according to the hardness data of the multi-layer protective coating and the friction stress coefficient.

[0012] Specifically, a stress strain sensor is installed on the surface of the metal substrate, and the sampling frequency is set to 1000 Hz to obtain surface stress distribution data, Vickers hardness value of the protective coating, and surface roughness parameters. According to the stress tensor equation σij=E / (1+ν)[εij+ν / (1-2ν)εkkδij], σij represents the stress tensor, E represents the elastic modulus, v represents the Poisson's ratio, εij represents the strain tensor, δij represents the Kronecker delta function, and εkk represents the trace of the strain tensor, the surface stress distribution state is calculated, the friction stress coefficient of the metal surface is quantitatively calculated, and the surface treatment state is judged according to the preset stress threshold of 300 MPa. The anti-corrosion strength and surface cleanliness values ​​are collected from the barcode printing surface, and the relationship function y=ax+b between the barcode ink viscosity y* and the material surface stress x* is calculated by linear regression. The least squares method is used to solve the parameters a and b of the linear regression model, and the parameters are continuously updated through iterative optimization algorithms such as gradient descent until convergence to the optimal solution. After obtaining the optimal parameters of the linear regression model, the test data of corrosion resistance and surface cleanliness are input into the model to predict the corresponding barcode ink viscosity and compare it with the actual viscosity value. The coefficient of determination of the linear regression model is calculated, and the weight of the influence of ink viscosity on barcode shedding is judged according to the value of the coefficient of determination. After the environmental temperature and humidity sensor collects the environmental parameters, the surface stress function curve of the material is fitted based on the least squares method, and the mapping relationship between the surface stress state f(x) and the environmental parameter g(x) is established h(x)=∑[f(x)-g(x)]², and the weight coefficient corresponding to the stress distribution curve is calculated. According to the hardness data of the multi-layer protective coating and the friction stress coefficient calculated in the previous sequence, within the preset metal surface environmental stress threshold range of 250-350 MPa, the surface stress state of the metal substrate is numerically calculated according to the surface stress tensor equation and the weight coefficient, and the stress distribution result is output. When the stress and strain sensors are installed on the surface of the metal substrate to collect data, the sensors are arranged in an area of ​​10×10 cm to form a sensor array, with a spacing of 5 cm between adjacent sensors, a sampling frequency of 1000 Hz, and a measurement duration of 300 seconds to obtain surface stress distribution data. At the same time, the hardness value of the protective coating is measured by a Vickers hardness tester in the range of 480-520HV, and the surface roughness instrument measures the roughness parameter Ra value of 0.8 microns. The friction stress coefficient is calculated to be 0.35 and the stress threshold is 300 MPa. Then, a corrosion potential measurement probe is installed on the barcode printing surface to measure the anti-corrosion potential value of -650 mV. The cleanliness detector is used to scan the surface to obtain a cleanliness of 95%. The slope of the relationship function between the ink viscosity and the material surface stress is 0.82 and the correlation coefficient is 0.91 through linear regression fitting. The temperature and humidity sensor array is arranged in the test environment, and the ambient temperature is measured to be 25 degrees Celsius and the relative humidity is 65%. The least squares method is used to calculate the square sum of the deviations between the surface stress state curve and the environmental parameters to be 0.15, and the stress distribution weight coefficient is 0.78.Based on the above-mentioned measurement data, combined with the hardness gradient data of the multi-layer protective coating showing that the surface hardness is 500HV, the middle layer 480HV, and the bottom layer 460HV, the surface stress distribution state is calculated within the metal surface environmental stress threshold range of 250-350 MPa. The output stress cloud map shows that the maximum stress concentration area is located at the edge of the barcode, and the stress value reaches 285 MPa.

[0013] S102. Prepare multiple groups of barcode material samples with different formulations by changing material components and ratios, test the adhesion and durability performance indicators of the multiple groups of barcode material samples with different formulations, determine the significance of the impact of each component on the performance, and select the barcode material formulation.

[0014] Acquire several groups of resin formula spectral data collected by a reflectance spectrometer; use a laser thickness gauge to measure the coating thickness value based on the several groups of resin formula spectral data, and use a Shore hardness tester to measure the coating hardness value; establish a linear regression function relationship between the coating hardness value and the resin content, and the linear regression function is used to calculate the relationship between the material hardness and the resin content; test the wear resistance of the coating by a wear resistance testing machine, and the wear resistance test is carried out under the condition that the wear disk rotates at a speed of 60 revolutions per minute to obtain the material wear loss mass data; test the corrosion resistance of the coating under a constant temperature and humidity environment based on the material wear loss mass data; calculate the chemical stability index based on the coating corrosion resistance test result, and calculate the weighted average of the material adhesion strength and durability based on the chemical stability index and the material wear loss mass data.

[0015] Specifically, three sets of material formula data were collected from the reflectance spectrometer. The first set contained 75% acrylic resin, 20% epoxy resin, and 5% curing agent. The second set contained 70% acrylic resin, 25% epoxy resin, and 5% curing agent. The third set contained 65% acrylic resin, 30% epoxy resin, and 5% curing agent. The coating thickness was recorded by a laser thickness gauge in the range of 120-150 microns with a measurement accuracy of ±1 micron. The component solubility was recorded as 95% at 25 degrees Celsius from a constant temperature solubility meter. The thermal conductivity was measured at 0.35 watts per meter Kelvin to determine the material stability value. Based on the three sets of material ratio data, the material hardness values ​​collected from the Shore hardness tester ranged from 65 to 75 Shore D. Linear regression was used to calculate the relationship function Y=0.5X+30 between the material hardness Y and the resin content X. The material surface adhesion data collected from the peel strength tester were in the range of 2.5-3.0 MPa, and the material ratio data were correlated. In the wear test machine, the wear resistance index of the material was tested under the conditions of a wear disk speed of 60 revolutions per minute and a load of 4.9 Newtons. The p-value of the significance level of the influence of material ratio and material thermal conductivity on material adhesion strength was calculated by paired t test, and the wear loss mass data of each group of materials was obtained. The corrosion resistance data was collected in a constant temperature and humidity chamber with a temperature of 60 degrees Celsius and a relative humidity of 95%. The chemical stability index was calculated after 168 hours of testing. According to the material group ratio data and the wear loss mass data, the material adhesion strength and durability index were weighted averaged, and the weight coefficients were 0.6 and 0.4 respectively. In the material formulation laboratory, the scanning wavelength range of the reflection spectrometer was set to 400-700 nanometers. When collecting three sets of material formulation data, the spectral resolution was 0.1 nanometer. The first group of formulations measured the acrylic resin absorption peak at 278 nanometers, with a content of 75%, the epoxy resin absorption peak at 225 nanometers, with a content of 20%, and the curing agent absorption peak at 198 nanometers, with a content of 5%. The laser thickness gauge uses a 650-nanometer wavelength laser to measure a point every 1 cm in a 10×10 cm area, recording an average coating thickness of 135 microns with a standard deviation of ±1 micron. The constant temperature solubility tester measures the component solubility at 25 degrees Celsius to reach 95%, and the thermal conductivity meter measures the thermal conductivity of the three groups of materials to be 0.35, 0.33, and 0.32 watts per meter Kelvin, respectively. The Shore hardness tester arranges 25 test points on the surface of the material, and the average hardness of each group of materials is 70, 68, and 65 Shore D, respectively. The linear regression calculation results in a correlation coefficient of 0.92, and the peel strength tester tests 9 points in a 5×5 cm area, with an average surface adhesion of 2.8 MPa. The wear disk of the wear tester has a diameter of 50 mm, a rotation speed of 60 rpm, a load of 4.9 Newtons, and a test duration of 4 hours. The wear mass loss of the three groups of materials is recorded as 52, 48, and 45 mg, respectively, and the p value calculated by the paired t test is 0.023.After 168 hours of continuous testing in a constant temperature and humidity chamber at 60 degrees Celsius and 95% relative humidity, the chemical stability index was calculated, and the comprehensive performance score of the material was calculated using the weighted average method. The weight coefficient 0.6 was used for the adhesion strength index, and 0.4 was used for the durability index. Finally, the second group of formula materials had the highest comprehensive score.

[0016] S103, using sandblasting pressure, pickling time, and roughening liquid concentration as independent variables, and barcode adhesion as response value, obtaining the quantitative relationship between each process parameter and adhesion, and using quadratic polynomial fitting to obtain the metal code disk surface treatment process parameters.

[0017] The pressure value collected by the sandblasting pressure sensor array is obtained, and the pressure value is used for scanning the hardening degree of the metal surface by a surface roughness meter; according to the surface hardening degree measurement result, the pickling corrosion depth data is obtained by a laser depth meter, and the corrosion depth data is measured by a scanning electron microscope to obtain the metal surface purity value and cleanliness value; the coarsening liquid concentration data collected by the conductivity sensor is received, and the coarsening liquid concentration data is used to record the surface grain size value, and the surface reaction activity function is obtained by multivariate regression calculation; a process parameter response surface equation is established for the surface reaction activity function; three groups of data, namely, surface roughness value, corrosion depth value and grain size value, of the metal surface detector are collected, and the pressure value, time value and concentration value in the optimal process parameter combination are calculated by the process parameter response surface equation.

[0018] Specifically, a KH-3000 pressure sensor array is installed on the surface of the metal code disk, with a sensor spacing of 5 mm and an accuracy of 0.01 MPa. The surface roughness value is recorded when the sandblasting pressure changes by 0.1 MPa every time within the range of 0.4-0.8 MPa. The RT-200 surface roughness meter with a measurement accuracy of 0.01 micron is used to scan and obtain the degree of metal surface hardening. The surface stress distribution state is quantitatively calculated to obtain a stress value range of 250-350 MPa. According to the pickling duration of 0-30 minutes, the HD-2000 laser depth meter is used to measure the pickling corrosion depth every 5 minutes with a detection accuracy of 0.1 micron. The metal purity value of 98.5% and the surface cleanliness of 95% are measured by the SX-5000 scanning electron microscope with a magnification of 5000 times. The least squares method is used to fit the pickling time t and corrosion depth h curve function h=0.5t²+0.8t+0.2. The data of the change of the concentration of the roughening liquid in the range of 5%-25% was collected from the YG-800 conductivity sensor, with a measurement accuracy of 0.1%. The surface grain size was recorded every 5%. The relationship function of the roughening liquid concentration x1 and the surface reaction activity y1 was calculated by multivariate linear regression, and the surface adhesion strength was calculated in the range of 2.5-3.0 MPa. The quadratic polynomial equation z=ax²+by²+cxy+dx+ey+f was used to fit the process parameter response surface, where x is the pressure value, y is the time value, z is the concentration value, a is the coefficient of x², b is the coefficient of y², c is the coefficient of xy, d is the coefficient of x, e is the coefficient of y, and f is the constant term. Three sets of data of surface roughness 0.8 microns, corrosion depth 15 microns, and grain size 45 microns were collected from the LM-600 metal surface detector, and the optimal parameter combination pressure 0.6 MPa, time 20 minutes, and concentration 15% were calculated. In the metal code disk surface treatment production line, the KH-3000 pressure sensor array is arranged in a 10×10 cm area at a 5 mm pitch, recording the sandblasting pressure starting from 0.4 MPa, increasing every 0.1 MPa until 0.8 MPa. The RT-200 surface roughness meter scans and measures the roughness value at each pressure value from 0.5 microns to 1.2 microns, and measures the surface stress distribution in the range of 250-350 MPa. Subsequently, in the pickling process, the HD-2000 laser depth meter records the corrosion depth data every 5 minutes, increasing from 0 microns at 0 minutes to 15 microns at 30 minutes. The SX-5000 scanning electron microscope observed a metal purity value of 98.5% and a surface cleanliness of 95% at a magnification of 5000 times. The least squares method fits the corrosion depth over time curve with a determination coefficient of 0.95. The YG-800 conductivity sensor collected data every 5% concentration during the roughening process, with a total of 5 concentration points from 5% to 25%, corresponding to the recorded grain size increasing from 25 microns to 65 microns. Multiple linear regression calculations showed that the correlation coefficient between concentration and reaction activity was 0.92, and the surface adhesion strength was stable at 2.8 MPa.Finally, the LM-600 metal surface detector collected the optimal process parameter combination: sandblasting pressure of 0.6 MPa, pickling time of 20 minutes, and roughening liquid concentration of 15%, with a surface roughness of 0.8 microns, corrosion depth of 15 microns, and grain size of 45 microns.

[0019] S104. Combining the factors affecting barcode shedding and the weight coefficients of the factors, as well as the ambient temperature, humidity, and vibration stress data, the barcode shedding condition is investigated in high and low temperature, high humidity, and random vibration acceleration environments, the failure time under different environmental stress levels is obtained, the relationship between the failure time and stress is fitted, and the barcode shedding life is predicted.

[0020] The ambient temperature data and relative humidity data collected by the temperature and humidity sensor are obtained, and the ambient temperature data is generated after the vibration acceleration sensor collects the vibration frequency and vibration amplitude data; a linear regression function is established according to the ambient temperature data and relative humidity data to obtain a relationship function between environmental parameters and surface strain values, and the surface strain value relationship function is used to calculate the surface strain value of the material; the surface strain value of the material is recorded by a surface strain sensor, and a correlation coefficient is established between the surface strain value and the ultraviolet spectrum absorption value to obtain the humidity penetration rate and the temperature aging coefficient; a shedding detection sensor is used to measure the surface crack length of the barcode, and if the surface crack length is greater than a preset threshold, the material fatigue failure is determined, and a stress action degree and shedding rate relationship function is established according to the material fatigue failure; Weibull distribution parameters are calculated according to the material fatigue failure time data, and temperature tolerance, humidity penetration, and material fatigue limit parameters are collected, and the service life of the barcode is calculated through the stress and life function.

[0021] Specifically, the TH-2000 temperature and humidity sensor collects ambient temperature data of -40 to 80 degrees Celsius and relative humidity data of 20% to 95% every 5 minutes. The VA-500 vibration acceleration sensor records data within the range of 10-2000 Hz and 0.5-2.0 gravitational acceleration per second. The linear regression is used to calculate the relationship function between the environmental parameters and the surface strain value: environmental parameters = 0.8*surface strain value + 0.2, and the strain value measurement range is 0.1%-1.0%. According to the DH-800 surface strain sensor with a sensitivity of 0.01%, the material surface strain value is recorded in the range of 0.2%-0.5% under the conditions of accelerated ambient temperature of 75 degrees Celsius and humidity of 90%. The ultraviolet spectrum absorption value is collected from the LM-300 surface aging detector, and the humidity penetration rate is calculated to be 0.5 grams per square meter per day and the temperature aging coefficient is 0.8 through the Pearson correlation coefficient. The crack length of the barcode surface recorded by the SD-600 shedding detection sensor is greater than 1 mm, which is used to determine the fatigue failure of the material. The least squares method is used to fit the relationship function between the stress action σ and the shedding rate v = 0.6σ + 0.3, and the failure time is calculated to be 168 hours at a stress level of 250 MPa. The Weibull distribution shape parameter β = 2.5 and the scale parameter η = 200 are calculated based on the failure time data. The temperature tolerance of 75 degrees Celsius, the humidity permeability of 0.5 grams per square meter per day, and the material fatigue limit of 200 MPa are collected from the GM-800 surface detector. The barcode service life t is calculated according to the stress and life function t = a1e^(-b1σ), where a1 and b1 are parameters related to the characteristics of the material and the test conditions, and parameters related to the sensitivity of the material to stress. In the barcode life test laboratory, the TH-2000 temperature and humidity sensor is set to a 5-minute sampling interval, starting from -40 degrees Celsius and recording a temperature point every 20 degrees Celsius until 80 degrees Celsius, and the relative humidity is recorded every 15% from 20% to 95%. At the same time, the VA-500 vibration acceleration sensor records vibration parameters at a sampling frequency of 1000 Hz, and takes a test point every 200 Hz within the frequency range of 10-2000 Hz. The vibration amplitude is recorded every 0.3 gravity acceleration from 0.5 gravity acceleration to 2.0 gravity acceleration. Linear regression calculation shows that the correlation coefficient between environmental parameters and surface strain values ​​is 0.92. The DH-800 surface strain sensor records strain data once an hour in an accelerated environment of 75 degrees Celsius and 90% humidity, and the strain value gradually increases from 0.2% to 0.5%. The LM-300 surface aging detector simultaneously records the ultraviolet spectrum absorption peak at 280 nanometers, and the humidity penetration rate is calculated to be 0.5 grams per square meter per day. The SD-600 shedding detection sensor records the failure time point when the crack length exceeds 1 mm in the scanning area. The failure time is recorded to be 168 hours at a stress level of 250 MPa. The least squares method is used to fit the stress and shedding rate curve, and the determination coefficient is 0.95.Data collected by the GM-800 surface detector showed that when the temperature tolerance was 75 degrees Celsius and the material fatigue limit was 200 MPa, the Weibull distribution calculation predicted that the barcode life would reach 500 hours.

[0022] S105. Based on the selected barcode material formula and the obtained metal code disc surface treatment process parameters, the barcode shedding failure mechanism is analyzed to simulate the barcode shedding probability under different environmental stress fluctuations to further adjust the barcode material formula and the metal code disc surface treatment process parameters. If the simulation results meet the preset requirements, the adjusted metal code disc surface treatment process parameters are applied to the production and manufacturing process of the metal code disc to obtain the metal code disc.

[0023] The material formula component ratio data is obtained, and the sandblasting pressure value, pickling time value and roughening liquid concentration value are set according to the formula component ratio data; the process parameters are calculated using a polynomial regression function to obtain the material hardness value, surface roughness value and surface adhesion value; the environmental parameter data are collected through an environmental temperature sensor, a humidity sensor and a vibration sensor, and an environmental stress action curve is obtained by fitting according to the least squares method. The environmental stress action curve is used to calculate the material stability coefficient value and the stress bearing limit value; the surface stress distribution data is collected from a surface stress detector, and the Weibull distribution function is used to calculate the shedding probability value according to the stress fluctuation range value, the surface temperature value and the surface roughness value; if the shedding probability value exceeds the preset threshold value, the sandblasting pressure value, the pickling time value and the roughening liquid concentration value are adjusted to the target parameter value according to the linear relationship value between the failure probability and the process parameters.

[0024] Specifically, the barcode material formula component ratio data is read from the raw material ratio database, with a resin content of 75%, a curing agent content of 20%, and an additive content of 5%. The three sets of process parameters are set by sandblasting pressure of 0.6 MPa, pickling time of 20 minutes, and roughening liquid concentration of 15%. The polynomial regression y2=0.8x2²+0.5x2+0.2 is used to calculate the material hardness value of 70 Shore D, surface roughness of 0.8 microns, and surface adhesion of 2.8 MPa, and the material performance and stress fluctuation correlation curve is established. According to the TH-2000 environmental temperature sensor collecting data in the range of -40 to 80 degrees Celsius every 5 minutes, the HD-500 humidity sensor collecting data from 20% to 95% every 5 minutes, and the VA-800 vibration sensor recording 10-2000 Hz frequency data per second, the environmental stress action curve h(t)=a3t²+b3t+c3 is fitted by the least squares method, and the material stability coefficient of 0.85 and the stress bearing limit of 320 MPa are calculated. a3, b3, and c3 are parameters to be determined, which are obtained by fitting historical data using the least squares method. The surface stress distribution data with a measurement accuracy of 0.1 MPa is collected from the SD-900 surface stress detector. According to the three groups of parameters with a stress fluctuation range of 250-350 MPa, a surface temperature of 75 degrees Celsius, and a surface roughness of 0.8 microns, the shedding probability P(t)=1-e^(-t / η)^β is calculated in combination with the Weibull distribution function, and η=200 hours, β=2.5 are obtained, and e is the base of the natural logarithm. Under the preset shedding probability threshold of 0.1%, according to the GM-600 machining center accuracy value of 0.01 mm, and based on the linear relationship between failure probability and process parameters R²=0.92, the process parameters are adjusted to a sandblasting pressure of 0.65 MPa, a pickling time of 22 minutes, and a roughening liquid concentration of 16%, and the surface treatment parameters of the metal code disk are numerically set. On the metal code disc production line, the raw material ratio database records three sets of data at 5-minute intervals: resin content 75%, curing agent content 20%, and additive content 5%. At the same time, the sandblasting pressure is recorded at 0.6 MPa, the pickling time is 20 minutes, and the coarsening liquid concentration is 15%. The polynomial regression calculation obtains the material hardness value of 70 Shore D, the surface roughness is 0.8 microns, and the surface adhesion is 2.8 MPa. The correlation coefficient reaches 0.95. The TH-2000 ambient temperature sensor records a data point every 20 degrees in the range of -40 to 80 degrees Celsius, the HD-500 humidity sensor records a data point every 15% in the range of 20% to 95%, and the VA-800 vibration sensor records 10-2000 Hz frequency data at a sampling frequency of 1000 Hz. The least squares fitting shows that the material stability coefficient reaches 0.85 at a temperature of 60 degrees Celsius, a humidity of 85%, and a vibration frequency of 1000 Hz. The SD-900 surface stress detector records a set of stress data every 10 MPa in the range of 250-350 MPa, with a measurement accuracy of 0.1 MPa. Weibull distribution calculation shows that the probability of shedding after 200 hours of use at a stress level of 320 MPa is 0.08%.When the GM-600 machining center was optimizing parameters, the sandblasting pressure was increased by 0.01 MPa, the pickling time was increased by 0.5 minutes, and the roughening liquid concentration was increased by 0.2% each time. When the sandblasting pressure reached 0.65 MPa, the pickling time was 22 minutes, and the roughening liquid concentration was 16%, the probability of falling off dropped to 0.05%, meeting the preset threshold requirements.

[0025] Based on the analysis results of the barcode failure mechanism, the basic data of the barcode failure probability under different environmental stress fluctuations are simulated. The barcode failure probability is predicted by combining the adhesion and durability test results of the barcode material formula and environmental stress fluctuations.

[0026] The three basic parameters of the barcode material resin content, curing agent content and additive content are obtained from the database, and the surface stress data of the barcode material is collected by the SD-900 surface stress distribution detector; according to the surface stress data of the barcode material, the material hardness value and the surface adhesion strength are calculated by a linear regression function, and a material performance and environmental stress coupling relationship curve is established; for the material performance and environmental stress coupling relationship curve, the ambient temperature data are collected by a TH-800 temperature and humidity sensor and the vibration frequency data are recorded by a VA-500 vibration sensor, and an environmental stress fluctuation curve is obtained by fitting a third-order polynomial; according to the environmental stress fluctuation curve, under the conditions of temperature, humidity and vibration frequency, the sum of squares of stress deviation is calculated by the least squares method to obtain the environmental stress influence coefficient at the material fatigue limit value; for the environmental stress influence coefficient, the surface crack length data is recorded by an LM-600 shedding detection sensor, and the barcode shedding probability density value is calculated by a Weibull distribution function.

[0027] Specifically, three sets of basic parameters of the barcode material, namely, resin content of 75%, curing agent content of 20%, and additive content of 5%, were obtained from the database. The surface stress data within the range of 250-350 MPa were collected using the SD-900 surface stress distribution detector with an accuracy of 0.1 MPa. The linear regression function y3=0.8x3+0.2 was used to calculate the material hardness value of 70 Shore D and the surface adhesion strength of 2.8 MPa, and the coupling relationship curve between material performance and environmental stress was established. According to the TH-800 temperature and humidity sensor, the data of the ambient temperature range of -40 to 80 degrees Celsius and humidity range of 20% to 95% are collected every 5 minutes. The VA-500 vibration sensor is used to record the gravity acceleration data with a sampling frequency of 1000 Hz and an amplitude of 0.5-2.0. The third-order polynomial y4=a4x4³+b4x4²+c4x4+d4 is used to fit the environmental stress fluctuation curve, with coefficients a4=0.5, b4=0.8, c4=0.3, and d4=0.1. The durability index is extracted from the durability test database. Under the conditions of temperature of 75 degrees Celsius, humidity of 85%, and vibration frequency of 1000 Hz, the sum of squares of stress deviation is calculated by the least squares method, which is 0.15, and the environmental stress influence coefficient of 0.82 is obtained when the material fatigue limit value is 250 MPa. According to the preset failure threshold of 0.1%, the LM-600 shedding detection sensor records the surface crack length greater than 1 mm. Within 200 hours of stress, the shape parameter β=2.5 and the scale parameter η=150 are calculated according to the Weibull distribution function, and the probability density of the barcode shedding probability is calculated. In the barcode detection laboratory, the database records three sets of data at 5-minute intervals: 75% resin content, 20% curing agent content, and 5% additive content of the barcode material. The SD-900 surface stress distribution detector has an accuracy of 0.1 MPa, and records a set of data every 10 MPa in the range of 250-350 MPa. The linear regression calculation shows that the surface adhesion strength reaches 2.8 MPa when the material hardness value is 70 Shore D, and the correlation coefficient is 0.95. The TH-800 temperature and humidity sensor records a temperature point every 20 degrees in the range of -40 to 80 degrees Celsius, and a humidity point every 15% in the range of 20% to 95%. The VA-500 vibration sensor has a sampling frequency of 1000 Hz, and records a set of vibration data every 200 Hz in the range of 10-2000 Hz. The third-order polynomial fitting obtains an environmental stress fluctuation curve fitting goodness of 0.92 at a temperature of 60 degrees Celsius, a humidity of 80%, and a vibration frequency of 1000 Hz. The durability test data shows that under the conditions of a temperature of 75 degrees Celsius, a humidity of 85%, and a vibration frequency of 1000 Hz, the environmental stress influence coefficient is 0.82 when the material fatigue limit value is 250 MPa, and the sum of squares of stress deviations calculated by the least squares method is 0.15.The LM-600 shedding detection sensor scans the surface status once an hour and records the area percentage of the crack length exceeding 1 mm. When the stress time reaches 200 hours, the Weibull distribution calculation shows that the probability of barcode shedding is 0.08%, which is lower than the preset failure threshold of 0.1%.

[0028] S106. Using the adjusted barcode material formula, print barcodes on the obtained metal code discs, prepare a batch of barcode samples, conduct tracking tests on the samples in an actual environment, and detect the adhesion and recognition performance indicators of the samples.

[0029] The barcode printing density value, glossiness value and ink adhesion value are measured by an online detector; based on the printing density value, glossiness value and ink adhesion value, the least squares method is used to fit the functional relationship between printing parameters and recognition rate, and the functional relationship is used to determine the barcode printing speed value; the ambient temperature value and relative humidity value are collected by a temperature and humidity sensor, and based on the barcode printing speed value, the barcode integrity value is obtained from a surface detector; the Weibull distribution function is used to calculate the durability prediction value of the barcode integrity value under the ambient temperature value and relative humidity value, and the barcode integrity attenuation curve is obtained through shape parameters and scale parameters; according to the barcode integrity attenuation curve, environmental stress distribution data is obtained from a surface stress monitor, and based on the barcode surface strain value, deformation and cracking length parameters, the dynamic life value is calculated using a life prediction correction function.

[0030] Specifically, three sets of data were obtained from the production database, including the barcode material formula resin content of 75%, curing agent of 20%, and additive of 5%. The barcode printing density value of 1.2, smoothness of 0.8 microns, and ink adhesion of 2.8 MPa were measured by the LM-800 printing online detector with an accuracy of 0.01. The least squares method was used to fit the printing parameters and the recognition rate function y=0.9x+0.1, with a correlation coefficient of 0.95, and the barcode printing speed was determined to be 4.2 meters per minute. According to the TH-500 temperature and humidity sensor, the ambient temperature of 25 degrees Celsius and the relative humidity of 65% were collected every 5 minutes. The VA-200 speed sensor was used to record the flow speed of 4.2 meters per minute with a sampling frequency of 100 Hz. The barcode integrity value of 95% was collected from the SD-600 surface detector, and the scanning area integrity rate and edge clarity score were calculated. The barcode surface state data was collected from the BC-900 barcode reader, and the durability prediction value under different environmental temperature and humidity was calculated using the Weibull distribution function. The barcode integrity decay curve with a running time of 600 hours was calculated using the shape parameter β=2.5 and the scale parameter η=600. The environmental stress distribution data of 250-350 MPa was collected using the GM-500 surface stress monitor with a measurement accuracy of 0.01 MPa. Based on the three groups of parameters of the barcode surface strain value of 0.2%, deformation of 0.5 mm, and crack length of 0.8 mm, the dynamic life value was calculated according to the life prediction correction function L(t)=L0(1-kt), where L(t) is the remaining life of the material or equipment at time t, L0 is the initial life, k is the correction factor, and t is time. On the barcode production line, the production database records the material formula data every 5 minutes. The accuracy of the LM-800 printing detector reaches 0.01. The measurement shows that under the formula of 75% resin content, 20% curing agent, and 5% additive, the printing density value is stable at 1.2, the surface finish is 0.8 microns, and the ink adhesion is 2.8 MPa. The least squares fitting method obtains the best printing speed of 4.2 meters per minute when the recognition rate is 98%. Under the conditions of ambient temperature of 25 degrees Celsius and relative humidity of 65%, the TH-500 temperature and humidity sensor, the VA-200 speed sensor sampling frequency of 100 Hz, records that the production line speed fluctuation range is 4.2±0.1 meters per minute, and the SD-600 surface detector scans and shows that the barcode pattern edge clarity score is 0.92, and the complete area accounts for 95%. The BC-900 barcode reader uses a 12-megapixel image sensor to record the surface state of the barcode at a frequency of once an hour. Weibull distribution calculations show that the integrity of the barcode is maintained at 92% after 600 hours of operation, with a decay rate of 0.015% per hour. The GM-500 surface stress monitor has a measurement accuracy of 0.01 MPa and records a set of data every 10 MPa in the range of 250-350 MPa. It is found that the predicted value of the barcode life is 800 hours when the surface strain value is 0.2%, the deformation is 0.5 mm, and the crack length is 0.8 mm, with a dynamic correction factor of 0.85.

[0031] S107. Establish enterprise standards for barcode material formulas and metal code disc surface treatment process parameters to guide mass production, implement online early warning and quality traceability of barcode shedding, and continuously improve barcode performance and service life.

[0032] Obtain the barcode material formula resin content, curing agent content, additive content and sandblasting pressure, pickling time, and roughening liquid concentration process parameters in the production database, and store the process parameters in the database according to a tree structure; obtain the material performance index value m through polynomial regression calculation based on the process parameter n, wherein the polynomial regression is calculated using the formula m=a5n²+b5n+w, a5 is the coefficient of n², b5 is the coefficient of n, w is a constant, and the correlation coefficient corresponds to the accuracy of the material performance index; use LM-600 online detection equipment to collect the material performance index at the monitoring position, and use a third-order polynomial to simulate the material performance index. The quality standard execution curve is obtained by combining the surface state data using the BC-800 barcode detector, and the life prediction curve L(t) is obtained by Weibull distribution calculation according to the adhesion standard value, wear resistance index, and recognition rate parameter, wherein L(t) is determined by the shape parameter β and the scale parameter η; the surface stress range data is collected using the GM-500 online monitor, and if the surface stress data exceeds the preset shedding warning threshold, the life prediction curve L(t) is corrected according to the product batch number and the production time, and the correction is calculated using the correction coefficient k.

[0033] Specifically, the barcode material formula resin content 75%, curing agent 20%, additive 5%, sandblasting pressure 0.65 MPa, pickling time 22 minutes, roughening liquid concentration 16% process parameters are read from the production database, and the material performance indicators are calculated through polynomial regression m=0.8n²+0.5n+0.2, with a correlation coefficient of 0.95, and a tree structure is established in the database to store the production parameters. At the eight monitoring locations of the production process, including raw material inspection points, ingredient metering points, spraying process points, surface treatment points, printing process points, inspection and testing points, packaging warehousing points, and quality traceability points, the LM-600 online detection equipment samples every 5 minutes, and uses third-order polynomial fitting to calculate the quality standard execution curve to determine the product batch traceability code. The surface state data was collected from the BC-800 barcode detector with an accuracy of 0.01 mm. According to the three groups of parameters of adhesion standard value 2.8 MPa, wear resistance index 250 MPa, and recognition rate 98%, the life prediction curve L(t)=L0(1-kt) was established by calculating the shape parameter β=2.5 and scale parameter η=600 through Weibull distribution. According to the GM-500 online monitor, the surface stress range data of 250-350 MPa was collected. Under the condition of the preset fall-off warning threshold of 0.1%, the product batch number and production time were recorded, and the life prediction value L(t) of the batch exceeding the threshold was dynamically corrected, and the correction coefficient k=0.85. In the barcode production management platform, the production database uses a tree structure to store material formula data, recording the basic formula of 75% resin content, 20% curing agent, and 5% additive every 5 minutes, and recording the process parameters of sandblasting pressure 0.65 MPa, pickling time 22 minutes, and roughening liquid concentration 16%. Polynomial regression calculation shows that the correlation coefficient of product performance indicators reaches 0.95 under this parameter combination. The LM-600 online detection equipment collects data at 8 key monitoring points on the production line. The raw material inspection point records the material purity of 99.5%, the ingredient metering point records the ratio error of 0.1%, the spraying process point records the coverage of 98%, the surface treatment point records the roughness of 0.8 microns, the printing process point records the ink adhesion of 2.8 MPa, the inspection and testing point records the recognition rate of 98%, the packaging storage point records the intact rate of 99%, and the quality traceability point records the batch code. The BC-800 barcode detector has an accuracy of 0.01 mm. Under the condition of a wear resistance index of 250 MPa, the Weibull distribution calculation predicts that the intact rate after 600 hours of use is 95%. The GM-500 online monitor records a set of data every 10 MPa within the stress range of 250-350 MPa. When it is detected that the surface stress of the product batch number 20240423-001 exceeds 300 MPa, it automatically triggers the warning signal and the life prediction value is corrected by 0.85 times.

[0034] Obviously, those skilled in the art can make various changes and modifications to the embodiments of the present application without departing from the spirit and scope of the embodiments of the present application. Thus, if these modifications and variations of the embodiments of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for analyzing a barcode on the surface of a metal code disk, characterized in that: The method comprises: According to the barcode material formula, metal code disk surface treatment process parameters, and environmental stress properties, a barcode shedding failure mechanism analysis model is established. The influence of each property on the barcode shedding is analyzed through the model, and the influencing factors of barcode shedding and the weight coefficients of each influencing factor are obtained; by changing the material components and ratios, multiple groups of barcode material samples with different formulas are prepared, and the adhesion and durability performance indicators of multiple groups of barcode material samples with different formulas are tested to determine the significance of the influence of each component on the performance, and select the barcode material formula; with sandblasting pressure, pickling time, and roughening liquid concentration as independent variables, and barcode adhesion as response value, the quantitative relationship between each process parameter and adhesion is obtained, and the metal code disk surface treatment process parameters are obtained by quadratic polynomial fitting; combined with the influencing factors of barcode shedding and the weight coefficients of each influencing factor and the environmental temperature, humidity, and vibration stress data, the barcode shedding situation is investigated under high and low temperature, high humidity, and random vibration acceleration environments. Obtain the failure time under different environmental stress levels, fit the relationship between failure time and stress, and predict the barcode shedding life; analyze the barcode shedding failure mechanism based on the selected barcode material formula and the obtained metal code disk surface treatment process parameters, simulate the barcode shedding probability under different environmental stress fluctuations, and further adjust the barcode material formula and metal code disk surface treatment process parameters. If the simulation results meet the preset requirements, apply the adjusted metal code disk surface treatment process parameters to the production and manufacturing process of the metal code disk to obtain the metal code disk; use the adjusted barcode material formula to print barcodes on the obtained metal code disk, prepare a batch of barcode samples, track and test the samples in the actual environment, and detect the adhesion and recognition performance indicators of the samples; form the barcode material formula and metal code disk surface treatment process parameters into enterprise standards to guide mass production, realize online early warning and quality traceability of barcode shedding, and continuously improve the performance and service life of barcodes.

2. The method according to claim 1, characterized in that According to the barcode material formula, metal code disk surface treatment process parameters, and environmental stress properties, a barcode shedding failure mechanism analysis model is established. The influence of each property on the barcode shedding is analyzed through the model, and the influencing factors of the barcode shedding and the weight coefficients of each influencing factor are obtained, including: Obtain surface stress distribution data collected by stress and strain sensors on the metal substrate surface and Vickers hardness values ​​of the protective coating; Calculating the metal surface friction stress coefficient according to the surface stress distribution data and the stress tensor equation; Collect the anti-corrosion strength and surface cleanliness values ​​of the barcode printing surface, and establish a linear regression equation based on the surface stress and ink viscosity; According to the environmental parameters collected by the environmental temperature and humidity sensor, the least squares method is used to establish the mapping relationship between the surface stress state function f(x) and the environmental parameter function g(x): h(x)=∑[f(x)-g(x)]²; If the environmental stress value of the metal surface is within the preset stress threshold range, the stress distribution result of the metal substrate surface is calculated based on the hardness data of the multi-layer protective coating and the friction stress coefficient.

3. The method according to claim 1, characterized in that: The method of preparing multiple groups of barcode material samples with different formulations by changing the material components and ratios, testing the adhesion and durability performance indicators of the multiple groups of barcode material samples with different formulations, determining the significance of the influence of each component on the performance, and selecting the barcode material formulation includes: Acquire several groups of resin formula spectrum data collected by a reflectance spectrometer; According to several sets of resin formula spectrum data, the coating thickness value is measured by a laser thickness gauge, and the coating hardness value is measured by a Shore hardness tester; Establishing a linear regression function relationship between the coating hardness value and the resin content, wherein the linear regression function is used to calculate the relationship between the material hardness and the resin content; The wear resistance of the coating is tested by a wear tester, wherein the wear resistance test is performed under the condition that the rotation speed of the wear disc is 60 revolutions per minute to obtain the material wear loss mass data; According to the wear loss quality data of the material, the corrosion resistance of the coating is tested under a constant temperature and humidity environment; The chemical stability index is calculated based on the coating corrosion resistance test results, and the weighted average of the material adhesion strength and durability is calculated based on the chemical stability index and the material wear loss mass data.

4. The method according to claim 1, characterized in that The sandblasting pressure, pickling time, and roughening liquid concentration are used as independent variables, and the barcode adhesion is used as the response value. By obtaining the quantitative relationship between each process parameter and the adhesion, and fitting with a quadratic polynomial, the metal code disk surface treatment process parameters are obtained, including: Obtaining pressure values ​​collected by a sandblasting pressure sensor array, wherein the pressure values ​​are used for a surface roughness meter to scan the hardening degree of a metal surface; According to the surface hardening degree measurement results, a laser depth meter is used to obtain pickling corrosion depth data, and the corrosion depth data is measured by a scanning electron microscope to obtain the metal surface purity value and cleanliness value; Receiving roughening liquid concentration data collected by a conductivity sensor, wherein the roughening liquid concentration data is used to record the surface grain size value, and obtaining a surface reaction activity function through multivariate regression calculation; Establishing a process parameter response surface equation according to the surface reaction activity function; Three sets of data, namely, surface roughness value, corrosion depth value and grain size value, are collected from a metal surface detector, and the pressure value, time value and concentration value in the optimal process parameter combination are calculated using the process parameter response surface equation.

5. The method according to claim 1, characterized in that The barcode shedding condition is investigated in high and low temperature, high humidity, and random vibration acceleration environments by combining the influencing factors of barcode shedding and the weight coefficients of the influencing factors with the ambient temperature, humidity, and vibration stress data, obtaining the failure time under different environmental stress levels, fitting the relationship between the failure time and the stress, and predicting the barcode shedding life, including: Acquire the ambient temperature data and relative humidity data collected by the temperature and humidity sensor, wherein the ambient temperature data is generated after the vibration acceleration sensor collects the vibration frequency and vibration amplitude data; A linear regression function is established according to the ambient temperature data and the relative humidity data to obtain a relationship function between the ambient parameters and the surface strain value, wherein the surface strain value relationship function is used to calculate the surface strain value of the material; The surface strain value of the material is recorded by a surface strain sensor, and a correlation coefficient is established between the surface strain value and the ultraviolet spectrum absorption value to obtain the humidity penetration rate and the temperature aging coefficient; A shedding detection sensor is used to measure the crack length of the barcode surface. If the crack length of the surface is greater than a preset threshold, the material is judged to have fatigue failure, and a relationship function between stress action degree and shedding rate is established according to the material fatigue failure. The Weibull distribution parameters are calculated based on the material fatigue failure time data, the temperature tolerance, humidity permeability and material fatigue limit parameters are collected, and the barcode service life is calculated through the stress and life function.

6. The method according to claim 1, characterized in that The barcode shedding failure mechanism analysis is performed based on the selected barcode material formula and the obtained metal code disk surface treatment process parameters, and the barcode shedding probability under different environmental stress fluctuations is simulated to further adjust the barcode material formula and the metal code disk surface treatment process parameters. If the simulation result meets the preset requirements, the adjusted metal code disk surface treatment process parameters are applied to the production process of the metal code disk to obtain the metal code disk, including: Obtain material formula component ratio data, and set the sandblasting pressure value, pickling time value and roughening liquid concentration value according to the formula component ratio data; The polynomial regression function is used to calculate the process parameters to obtain the material hardness value, surface roughness value and surface adhesion value; Environmental parameter data are collected through an environmental temperature sensor, a humidity sensor and a vibration sensor, and an environmental stress action curve is obtained by fitting according to the least square method. The environmental stress action curve is used to calculate the material stability coefficient value and the stress bearing limit value; The surface stress distribution data is collected from the surface stress detector, and the shedding probability value is calculated using the Weibull distribution function according to the stress fluctuation range value, the surface temperature value and the surface roughness value; If the shedding probability value exceeds a preset threshold, the sandblasting pressure value, the pickling time value, and the roughening liquid concentration value are adjusted to the target parameter values ​​according to the linear relationship between the failure probability and the process parameters.

7. The method according to claim 6, characterized in that The barcode shedding failure mechanism analysis is performed based on the selected barcode material formula and the obtained metal code disk surface treatment process parameters, and the barcode shedding probability under different environmental stress fluctuations is simulated to further adjust the barcode material formula and the metal code disk surface treatment process parameters. If the simulation result meets the preset requirements, the adjusted metal code disk surface treatment process parameters are applied to the production process of the metal code disk to obtain the metal code disk, and the metal code disk is also included: Based on the analysis results of the barcode failure mechanism, the basic data of the barcode failure probability under different environmental stress fluctuations are simulated. The barcode failure probability is predicted by combining the adhesion and durability test results of the barcode material formula and environmental stress fluctuations.

8. The method according to claim 7, characterized in that The method is based on the analysis results of the barcode shedding failure mechanism, simulating the basic data of the barcode shedding probability under different environmental stress fluctuations, and predicting the barcode shedding probability by combining the test results of the adhesion and durability of the barcode material formula and the environmental stress fluctuations, including: The three basic parameters of the barcode material resin content, curing agent content and additive content are obtained from the database, and the surface stress data of the barcode material is collected by the SD-900 surface stress distribution detector; according to the surface stress data of the barcode material, the material hardness value and the surface adhesion strength are calculated by a linear regression function, and a material performance and environmental stress coupling relationship curve is established; for the material performance and environmental stress coupling relationship curve, the ambient temperature data are collected by a TH-800 temperature and humidity sensor and the vibration frequency data are recorded by a VA-500 vibration sensor, and an environmental stress fluctuation curve is obtained by fitting a third-order polynomial; according to the environmental stress fluctuation curve, under the conditions of temperature, humidity and vibration frequency, the sum of squares of stress deviation is calculated by the least squares method to obtain the environmental stress influence coefficient at the material fatigue limit value; for the environmental stress influence coefficient, the surface crack length data is recorded by an LM-600 shedding detection sensor, and the barcode shedding probability density value is calculated by a Weibull distribution function.

9. The method according to claim 1, characterized in that: The adjusted barcode material formula is used to print barcodes on the obtained metal code discs to prepare a batch of barcode samples, and the samples are tracked and tested in an actual environment to detect the adhesion and recognition performance indicators of the samples, including: Measure the barcode printing density, glossiness and ink adhesion through an online detector; According to the printing density value, the glossiness value and the ink adhesion value, a least squares method is used to fit the functional relationship between the printing parameters and the recognition rate, and the functional relationship is used to determine the barcode printing speed value; The ambient temperature and relative humidity are collected by a temperature and humidity sensor, and based on the barcode printing speed, a barcode integrity value is obtained from a surface detector; The durability prediction value of the barcode integrity value under the ambient temperature and relative humidity is calculated by using the Weibull distribution function, and the barcode integrity attenuation curve is obtained by using the shape parameter and the scale parameter; According to the barcode integrity decay curve, environmental stress distribution data is obtained from a surface stress monitor, and based on the barcode surface strain value, deformation amount and crack length parameters, a life prediction correction function is used to calculate the dynamic life value.

10. The method according to claim 1, characterized in that The barcode material formula and metal code disk surface treatment process parameters are formed into enterprise standards to guide mass production, realize online early warning and quality traceability of barcode shedding, and continuously improve barcode performance and service life, including: Obtain the barcode material formula resin content, curing agent content, additive content and sandblasting pressure, pickling time and roughening liquid concentration process parameters in the production database, and the process parameters are stored in the database according to a tree structure; Obtaining material performance index values ​​through polynomial regression calculation according to the process parameters; The material performance index is collected at the monitoring position by using LM-600 online detection equipment, and the quality standard execution curve is obtained by third-order polynomial fitting, and the quality standard execution curve corresponds to the product batch traceability code; According to the surface state data collected by the BC-800 barcode detector, the life prediction curve L(t) is calculated by Weibull distribution according to the adhesion standard value, wear resistance index and recognition rate parameter, where L(t) is determined by the shape parameter β and the scale parameter η; The GM-500 online monitor is used to collect surface stress range data. If the surface stress data exceeds the preset fall-off warning threshold, the life prediction curve L(t) is corrected according to the product batch number and production time. The correction is calculated using the correction coefficient k.

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