Method for obtaining surface acidity and alkalinity of mildewed paperboard

Abstract

The invention provides a method for obtaining the surface acidity and alkalinity of a mildewed paperboard, and relates to the technical field of paperboard acidity and alkalinity detection.The method comprises the steps that chromatic aberration value detection and acidity and alkalinity detection are carried out on the surface of the paperboard, multiple sets of corresponding relations between acidity and alkalinity and chromatic aberration values are obtained, a mathematical model of the acidity and alkalinity and the chromatic aberration values is fitted, and the acidity and alkalinity are calculated through the mathematical model; in this way, pH value detection is replaced by color difference value detection, the color difference value is obtained through the colorimeter, the method has the advantages of being rapid, easy to operate and non-destructive, the problem that existing paperboard surface pH value detection is complex is solved, and the method is suitable for paperboard pH value detection.

Description

Technical Field

[0001] This invention relates to the field of paperboard pH testing technology, and particularly to a method for obtaining the pH of moldy paperboard surface. Background Technology

[0002] Airborne dust particles carry a large number of mold spores. Cardboard is highly susceptible to mold growth under improper storage conditions, leading to mildew and altering its color, chemical properties, and physical properties, resulting in irreversible biological degradation. Mold growth on cardboard secretes organic acids and various enzymes, causing changes in the surface pH. The pH of the cardboard surface reflects the concentration of hydrogen ions and is a chemical property used to describe its acidity or alkalinity. The surface pH significantly affects various cardboard properties such as strength, color, and durability; therefore, measuring the surface pH of cardboard is of great importance.

[0003] Currently, the determination of pH on cardboard surfaces mainly involves placing a drop of water on the sample surface, immersing a calibrated flat-head electrode with temperature compensation function in the water droplet, maintaining a constant pressure of the electrode on the sample, and measuring the pH within a specified time. Typically, the sample is read after immersion for 5 minutes. This testing method requires specific instruments, is relatively complex and time-consuming, and residual water may potentially damage the sample. Summary of the Invention

[0004] The technical problem solved by this invention is to provide a method for obtaining the pH value of moldy cardboard surfaces, thereby solving the problem of the complexity of existing cardboard pH value detection methods.

[0005] The technical solution adopted by the present invention to solve the above-mentioned technical problems is a method for obtaining the pH value of moldy cardboard surface, comprising the following steps:

[0006] S1. Perform color difference and pH tests on the cardboard surface to obtain multiple sets of correlations between pH and color difference values;

[0007] S2. Based on the correspondence between pH and color difference value, fit a mathematical model of pH and color difference value;

[0008] S3. Obtain the color difference value of the surface of the paperboard to be tested, and calculate the acidity and alkalinity using the mathematical model.

[0009] Furthermore, the mathematical model is: y = y0 + A × |xx c | p Where y is the color difference value, x is the pH, and y0, A, x c Both p and are constants obtained from the fitting.

[0010] Furthermore, S2 also includes verifying the mathematical model through data analysis, specifically including the following steps:

[0011] S21. Calculate the residual between the experimental value and the predicted value. If the normal distribution curve of the residual is bell-shaped and within the first preset range, then the mathematical model conforms to the assumption of normal distribution.

[0012] S22. Calculate the root mean square error between the true value and the predicted value. If the root mean square error is less than the first threshold, then the mathematical model is accurate.

[0013] S23. Calculate the average absolute error between the actual value and the predicted value. If the average absolute error is less than the second threshold, then the mathematical model is accurate.

[0014] S24. Calculate the determination coefficient of the mathematical model. If the determination coefficient is greater than the third threshold, then the mathematical model is accurate.

[0015] S25. Calculate the relative error between the actual value and the predicted value. If the relative error is within a second preset range, then the mathematical model is reliable.

[0016] The beneficial effects of this invention are as follows: This invention provides a method for obtaining the pH value of moldy cardboard surfaces. By detecting color difference and pH values ​​on the cardboard surface, multiple sets of corresponding relationships between pH and color difference values ​​are obtained. A mathematical model of pH and color difference values ​​is fitted, and the pH value is calculated using the mathematical model. Thus, pH detection is replaced by color difference detection, and the color difference value is obtained using a colorimeter. This method has the advantages of being fast, simple to operate, and non-destructive, and solves the problem of the complexity of existing methods for detecting pH values ​​on cardboard surfaces. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating a method for obtaining the pH value of a moldy cardboard surface provided by the present invention.

[0018] Figure 2 This is a diagram showing the correspondence between pH and color difference values ​​in an embodiment of a method for obtaining the pH of moldy cardboard surface provided by the present invention.

[0019] Figure 3 This is a fitting curve diagram corresponding to the mathematical model fitted in an embodiment of the method for obtaining the pH of moldy cardboard surface provided by the present invention. Detailed Implementation

[0020] This invention addresses the problems of complex and time-consuming existing methods for detecting the pH of cardboard, and the potential for residual water to damage samples. It provides a method for obtaining the pH of moldy cardboard surfaces. By fitting a mathematical model of pH and color difference values, pH detection is transformed into color difference detection. Color difference values ​​are then obtained using a simple and fast colorimeter, and the pH is calculated using the mathematical model, thus solving the problem of complex pH detection on cardboard surfaces.

[0021] This invention provides a method for obtaining the pH value of a moldy cardboard surface, wherein the cardboard is a moldy single-sided white industrial cardboard, such as... Figure 1 As shown, it includes the following steps:

[0022] S1. Perform color difference and pH tests on the cardboard surface to obtain multiple sets of correlations between pH and color difference values;

[0023] S2. Based on the correspondence between pH and color difference value, fit a mathematical model of pH and color difference value;

[0024] S3. Obtain the color difference value of the surface of the paperboard to be tested, and calculate the acidity and alkalinity using the mathematical model.

[0025] Specifically, the mathematical model is: y = y0 + A × |xx c | p Where y is the color difference value, x is the pH, and y0, A, x c Both p and are constants obtained from the fitting.

[0026] S2 also includes verifying the mathematical model through data analysis, specifically including the following steps:

[0027] S21. Calculate the residual between the experimental value and the predicted value. If the normal distribution curve of the residual is bell-shaped and within the first preset range, then the mathematical model conforms to the assumption of normal distribution.

[0028] S22. Calculate the root mean square error between the true value and the predicted value. If the root mean square error is less than the first threshold, then the mathematical model is accurate.

[0029] S23. Calculate the average absolute error between the actual value and the predicted value. If the average absolute error is less than the second threshold, then the mathematical model is accurate.

[0030] S24. Calculate the determination coefficient of the mathematical model. If the determination coefficient is greater than the third threshold, then the mathematical model is accurate.

[0031] S25. Calculate the relative error between the actual value and the predicted value. If the relative error is within a second preset range, then the mathematical model is reliable.

[0032] Example:

[0033] A measured amount of a mixed bacterial suspension of *Aspergillus niger*, *Penicillium expansum*, *Penicillium oxalate*, *Basilaria cordifolia*, *Rhizopus cremastoides*, *Alternaria alternata*, *Cladosporium filamentosa*, *Cladosporium oxysporum*, and *Basilaria filamentosa* was inoculated onto cardboard at a concentration of 10. 7 The concentration of CFU / ml was incubated at 25℃ and 95% humidity for 30 days. Paperboard samples were taken every five days. The pH value of the paperboard surface was measured according to GB / T 13528-2015, and the color difference of the paperboard surface was measured using a colorimeter. The correspondence between the obtained pH and color difference values ​​is shown in Table 1. Figure 2 As shown, pH value represents acidity / alkalinity, CLE Lab* represents color difference, denoted by ΔE, and mold growth time is denoted by d.

[0034] Table 1. Correspondence between multiple sets of pH values ​​and color difference values

[0035] 5 days 10 days 15 days 20 days 25 days 30 days Color difference 8.54 14.65 14.10 15.63 12.36 12.75 pH value (acidity / alkalinity) 8.60 8.96 8.89 9.04 8.72 8.87

[0036] Analyze the data in Table 1 and try to use a power function as the mathematical model for fitting the pH and color difference values. The mathematical model is: y = y0 + A × |xx c | p Where y is the color difference value, x is the pH, and y0, A, x c Both p and are constants obtained from the fitting process. The specific fitting process is as follows: In Origin software, input the color difference value and pH level, select the "Power0" function in the Power function, and obtain the mathematical model: y = 8.56539 + 10.46808 × |x - 8.60333| 0.53021 That is, y0 = 8.56539, A = 10.46808, x c =8.60333, p=0.53021, sorted by pH from smallest to largest, the corresponding color difference points were obtained and the curve corresponding to the mathematical model was fitted, such as Figure 3 As shown.

[0037] Furthermore, through data analysis, the equation y = 8.56539 + 10.46808 × |x - 8.60333| was analyzed. 0.53021 The verification process includes the following steps:

[0038] S21. Calculate the residual between the experimental value and the predicted value. If the normal distribution curve of the residual is bell-shaped and within the first preset range, then the mathematical model conforms to the assumption of normal distribution. Specifically, the residual between the experimental value and the predicted value is shown in Table 2, where the independent variable is acidity / alkalinity (pH value).

[0039] Table 2 Residuals between experimental and predicted values

[0040] Independent variable 8.60 8.72 8.87 8.89 8.96 9.04 residual mean residual -0.023 0.447 -0.976 0.192 0.028 0.349 0.003

[0041] As shown in Table 2, the mean residual is 0.003. Calculated using MATLAB, μ = 0.003 and σ = 0.5123, which conforms to the assumption of a normal distribution. Approximately 95% of the data values ​​fall within two standard deviations (μ ± 2σ) from the mean.

[0042] S22. Calculate the root mean square error between the true value and the predicted value. If the root mean square error is less than the first threshold, the mathematical model is accurate. Specifically, the smaller the root mean square error, the more accurate the mathematical model. The root mean square error RMSE = 0.46769 is obtained by MATLAB calculation, which meets the expectation.

[0043] S23. Calculate the mean absolute error between the actual value and the predicted value. If the mean absolute error is less than the second threshold, the mathematical model is accurate. Specifically, the smaller the mean absolute error, the more accurate the mathematical model. The mean absolute error MAE = 0.336 is calculated using MALTAB, which meets the expectation.

[0044] S24. Calculate the coefficient of determination of the mathematical model. If the coefficient of determination is greater than the third threshold, the mathematical model is accurate. Specifically, the coefficient of determination ranges from 0 to 1. The closer the absolute coefficient is to 1, the better the model fits the true value. The coefficient of determination R is calculated using MATLAB. 2 =0.95797, which is in line with expectations.

[0045] S25. Calculate the relative error between the actual value and the predicted value. If the relative error is within a second preset range, the mathematical model is reliable. Specifically, on a certain day, the pH value of the paperboard surface was measured according to GB / T 13528-2015, and the pH value was 8.81. The color difference of the paperboard surface was measured using a colorimeter, and the color difference value was 14.85. The mathematical model y = 8.56539 + 10.46808 × |x - 8.60333| is then used. 0.53021 The calculated predicted pH value was 8.99, with a root mean square error (RMSE) of 0.18, a mean absolute error (MAE) of 0.18, and a relative error of 2.04%, which is in line with expectations.

[0046] Therefore, the mathematical model is y = 8.56539 + 10.46808 × |x - 8.60333| 0.53021 It can predict the pH of cardboard at 25℃ and 95% humidity for a good period of 30 days.

Claims

1. A method for obtaining the pH value of the surface of a moldy cardboard, characterized in that: The following steps are involved: S1. Perform color difference value detection and pH detection on the paperboard surface to obtain a correspondence between multiple groups of pH values ​​and color difference values; S2. According to the corresponding relationship between pH and color difference, a mathematical model of pH and color difference is fitted; S3, obtaining the color difference value of the surface of the paperboard to be tested, and calculating the pH value using the mathematical model.

2. The method for obtaining the pH value of the moldy cardboard surface according to claim 1, characterized in that: The mathematical model is: y=y0+A×|xx c | p , where y is the color difference value, x is the pH value, y0, A, x c and p are constants obtained from the fitting.

3. The method for obtaining the pH value of the moldy cardboard surface according to claim 2, characterized in that: S2 also includes verifying the mathematical model through data analysis, which specifically includes the following steps: S21, calculating the residual between the experimental value and the predicted value, if the normal distribution curve of the residual is bell-shaped and is within a first preset range, then the mathematical model meets the assumption of normal distribution; S22, calculating the root mean square error between the true value and the predicted value, if the root mean square error is less than a first threshold value, the mathematical model is accurate; S23, calculating the mean absolute error between the true value and the predicted value, if the mean absolute error is less than a second threshold value, the mathematical model is accurate; S24, calculating the coefficient of determination of the mathematical model, if the coefficient of determination is greater than a third threshold value, the mathematical model is accurate; S25. Calculate the relative error between the true value and the predicted value. If the relative error is within a second preset range, the mathematical model is reliable.

Images