Absorbance Value Estimation Method and System for Detection Reagent Containing Solid Residue

Abstract

The present invention discloses a method and system for estimating the absorbance value of a detection reagent containing solid residues, belonging to the technical field of environmental detection. The method includes: configuring N groups of known solutions with different solid residue contents; for each group of known solutions, performing M photoelectric detections respectively; calculating the probability distribution function of each group of known solutions respectively; calculating the corresponding compensation curve according to the probability distribution function of each group of known solutions respectively; performing M' photoelectric detections on the solution to be measured, calculating the correlation coefficient between the photoelectric detection signal value of the solution to be measured and the photoelectric detection signal value of each group of known solutions respectively, screening out the group of known solutions with the largest correlation coefficient, and extracting the corresponding compensation curve; compensating the photoelectric detection signal value of the solution to be measured according to the extracted compensation curve, and estimating the absorbance value of the solution to be measured according to the compensated photoelectric detection signal value. The present invention can greatly reduce the influence of solid residues in the detection reagent and improve the accuracy of absorbance estimation.

Description

Technical Field

[0001] The present invention belongs to the technical field of environmental detection, and particularly relates to a method and system for estimating the absorbance value of a detection reagent containing solid residues. Background Art

[0002] In technical fields such as environmental detection, it is often necessary to measure the absorbance of a detection reagent. For example, Chemical Oxygen Demand (COD) is the amount of reducing substances that need to be oxidized in a water sample measured by a chemical method. It represents the oxygen equivalent of substances (generally organic substances) that can be oxidized by a strong oxidant in wastewater, the effluent of a wastewater treatment plant, and polluted water. In the research of river pollution and the properties of industrial wastewater, as well as the operation management of wastewater treatment plants, it is an important and rapidly measurable organic pollution parameter.

[0003] The existing COD detection method generally involves filling a reagent bottle with a water sample and a digestion reagent. Solid residues will be generated during the high-temperature digestion of the water sample and the digestion reagent. After standing for a period of time, these residues will precipitate at the bottom of the reagent bottle, and the reagent in the upper-middle part of the reagent bottle is taken to detect the absorbance. However, some residues may be suspended in the reagent. Therefore, this sampling method still cannot ensure that there are no impurity residues in the COD reagent taken. The presence of these solid residues will affect the measurement of the absorbance value of the reagent, and at this time, a large error will occur in the detected COD concentration value.

[0004] Currently, chemical detection equipment on the market is gradually moving from being large-scale and long-cycle to being small-scale and rapid-detection, gradually reducing the cycle and operation complexity of operators for sampling, digestion treatment, and concentration detection. When some equipment is miniaturized and has no filtering structure, or there are still some micro solid residues after filtration, it will still affect the detection accuracy of absorbance, thereby interfering with COD detection.

[0005] The invention patent with the application number 202010612715.8 discloses a water quality COD prediction method. By measuring the absorbance of standard water body samples, a basic model M1 is established based on the absorbance and the corresponding COD value. Then, the absorbance of natural water samples is measured, and the absorbance of the natural water samples is substituted into the basic model M1 to determine the preliminary predicted COD value corresponding to the absorbance of the natural water samples. The COD of the natural water samples is actually measured to determine the measured COD value of the natural water samples. A calibration model M2 is linearly fitted with the preliminary predicted COD value as the independent variable and the measured COD value as the dependent variable, and the water quality COD is predicted through the calibration model M2. The invention patent with the application number 201910076587.7 discloses a wide-range and high-precision spectral detection method for COD concentration in water bodies. By analyzing and processing the full spectral data of the COD sample solution, the corresponding relationship between the absorbance at each wavelength and the concentration is established, and the COD concentration can be calculated only by measuring the unknown sample once. Although these methods have good COD prediction accuracy, they still do not eliminate the influence of solid residues on the measured COD value.

[0006] Therefore, in the case where there are solid residues in the detection reagent, how to minimize the influence of solid residues on the measurement of absorbance values has become a technical problem that needs to be solved urgently at present. Summary of the Invention

[0007] In view of this, the present invention proposes an absorbance estimation method and system for a detection reagent containing solid residues, which is used to solve the problem of excessive error in the measurement of absorbance values when there are solid residues in the detection reagent.

[0008] In the first aspect of the present invention, an absorbance value estimation method for a detection reagent containing solid residues is disclosed. The method includes:

[0009] Configure N groups of known solutions with different solid residue contents;

[0010] For each group of known solutions, perform M optoelectronic detections respectively to obtain M optoelectronic detection signal values of each group of known solutions;

[0011] Calculate the probability distribution function F(n) of each group of known solutions respectively according to the M optoelectronic detection signal values of each group of known solutions, where n = 1, 2,..., N, to obtain the probability distribution functions of N groups of known solutions;

[0012] Calculate the corresponding compensation curve B(n) respectively according to the probability distribution function F(n) of each group of known solutions, so that F [n] B [n] T = A, where F [n] is the matrix form of the probability distribution function F(n), and B[n] is the coefficient matrix of the compensation curve, where n = 1, 2, …, N, and A is a constant matrix composed of the optoelectronic detection signal values of the solvent with a solid residue content of 0;

[0013] Perform M' optoelectronic detections on the solution to be measured to obtain M' optoelectronic detection signal values;

[0014] Calculate the correlation coefficients between the M' optoelectronic detection signal values of the solution to be measured and the M optoelectronic detection signal values of each group of known solutions respectively, select the group of known solutions with the largest correlation coefficient, and extract the corresponding compensation curve;

[0015] Compensate the optoelectronic detection signal values of the solution to be measured according to the extracted compensation curve to obtain the compensated optoelectronic detection signal values;

[0016] Estimate the absorbance value of the solution to be measured according to the compensated optoelectronic detection signal values.

[0017] Based on the above technical solutions, preferably, the method is implemented based on a microfluidic disk chip.

[0018] Based on the above technical solutions, preferably, for each group of known solutions, centrifugation is performed before each optoelectronic detection.

[0019] Based on the above technical solutions, preferably, the calculation of the probability distribution function F(n) of each group of known solutions according to the M optoelectronic detection signal values of each group of known solutions specifically includes:

[0020] Let the M optoelectronic detection signal values of the nth group of known solutions be y [n] (1), y [n] (2), …, y [n] (m), …, y [n] (M), where n = 1, 2, …, N and m = 1, 2, …, M;

[0021] Statistically count the frequency of occurrence of each optoelectronic detection signal value of the nth group of known solutions where P[y [n] (m)] is the frequency of occurrence of y [n] (m), and statistically count the probability distribution of the optoelectronic detection signal values according to the frequency;

[0022] Take the limiting distribution when M is greater than the set threshold as the probability distribution function F(n) of the M optoelectronic detection signal values of the nth group of known solutions, and the limiting distribution F(n) is a normal distribution.

[0023] Based on the above technical solutions, preferably, the calculation of the corresponding compensation curve B(n) according to the probability distribution function F(n) of each group of known solutions specifically includes:

[0024] For the probability distribution function F(n) of the nth group of known solutions, sample at equal step lengths along the abscissa to obtain a set of discrete optoelectronic detection signal values. Divide the discrete optoelectronic detection signal values according to the set number of rows and columns and convert them into matrix form, denoted as F [n] ;

[0025] Obtain multiple optoelectronic detection signal values of the solvent with a solid residue content of 0 and form a constant matrix A;

[0026] Let the coefficients of the compensation curve form a one-dimensional coefficient matrix B [n] , according to F [n] B [n] T = A to calculate the coefficient matrix B of the compensation curve [n] , n = 1, 2,..., N.

[0027] On the basis of the above technical solutions, preferably, the process of the correlation coefficient between the M' optoelectronic detection signal values of the solution to be measured and the M optoelectronic detection signal values of each group of known solutions is specifically as follows:

[0028] Let the optoelectronic detection signal values corresponding to N groups of known solutions be y [n] (m), m = 1, 2,..., M, and calculate its autocorrelation coefficient ryy [n] (m'):

[0029]

[0030] where m' represents the displacement. When m' = 0:

[0031]

[0032] Let the M' optoelectronic detection signal values of the solution to be measured be x(1), x(2),..., x(k),..., x(M'), and calculate its autocorrelation coefficient:

[0033]

[0034] Calculate the covariance ryx(m') between the optoelectronic detection signal values corresponding to the known solutions and the M' optoelectronic detection signal values of the solution to be measured:

[0035]

[0036] Calculate the correlation coefficient ρ [n] (m') between the M' optoelectronic detection signal values of the solution to be measured and the M optoelectronic detection signal values of each group of known solutions:

[0037]

[0038] where n = 1, 2, …, N.

[0039] Based on the above technical solutions, preferably, compensating the optoelectronic detection signal value of the solution to be measured according to the extracted compensation curve to obtain the compensated optoelectronic detection signal value specifically includes:

[0040] Let X be the matrix form of M' optoelectronic detection signal values x(1), x(2), …, x(M') of the solution to be measured, is the coefficient matrix of the compensation curve corresponding to a set of known solutions with the largest correlation coefficient, then the matrix A' composed of the compensated optoelectronic detection signal values is:

[0041]

[0042] The elements of the matrix A' are the compensated optoelectronic detection signal values.

[0043] Based on the above technical solutions, preferably, calculating the absorbance value of the solution to be measured according to the compensated optoelectronic detection signal value specifically includes:

[0044]

[0045] where A i is the absorbance value of the solution to be measured, V0 is the optoelectronic detection signal value of the solvent with a solid residue content of 0, and A'(i) is the element of A', that is, the optoelectronic detection signal value after each optoelectronic detection compensation.

[0046] In the second aspect of the present invention, an absorbance value estimation system for a detection reagent containing solid residues is disclosed, and the system includes:

[0047] A data acquisition module: configured to acquire N groups of known solutions with different solid residue contents; for each group of known solutions, perform M optoelectronic detections respectively to obtain M optoelectronic detection signal values of each group of known solutions; perform M' optoelectronic detections on the solution to be measured to obtain M' optoelectronic detection signal values;

[0048] A data processing module: configured to calculate the probability distribution function F(n) of each group of known solutions respectively according to the M optoelectronic detection signal values of each group of known solutions, n = 1, 2, …, N, to obtain the probability distribution functions of N groups of known solutions; calculate the corresponding compensation curve B(n) respectively according to the probability distribution function F(n) of each group of known solutions, so that F [n] B [n] T = A, where F [n] is the matrix form of the probability distribution function F(n), B [n] is the coefficient matrix of the compensation curve, and A is a constant matrix composed of the optoelectronic detection signal values of the solvent with a solid residue content of 0;

[0049] Data compensation module: used to calculate the correlation coefficients between the M' photoelectric detection signal values of the solution to be measured and the M photoelectric detection signal values of each group of known solutions respectively, screen out the group of known solutions with the largest correlation coefficient, and extract the corresponding compensation curve; compensate the photoelectric detection signal values of the solution to be measured according to the extracted compensation curve to obtain the compensated photoelectric detection signal values.

[0050] Absorbance estimation module: used to estimate the absorbance value of the solution to be measured according to the compensated photoelectric detection signal values.

[0051] In the third aspect of the present invention, an electronic device is disclosed, including: at least one processor, at least one memory, a communication interface, and a bus;

[0052] Wherein, the processor, the memory, and the communication interface complete communication with each other through the bus;

[0053] The memory stores program instructions executable by the processor, and the processor calls the program instructions to implement the method as described in the first aspect of the present invention.

[0054] In the fourth aspect of the present invention, a computer-readable storage medium is disclosed, and the computer-readable storage medium stores computer instructions, and the computer instructions enable a computer to implement the method as described in the first aspect of the present invention.

[0055] The present invention has the following beneficial effects compared with the prior art:

[0056] 1) The present invention calculates the probability distribution function of each group of known solutions respectively according to the photoelectric detection signal values of multiple groups of known solutions with different solid residue contents, then calculates the corresponding compensation curve according to the probability distribution function of each group of known solutions respectively, compares the similarity of the probability distribution of the solution to be measured and each group of known solutions respectively, and takes the compensation curve corresponding to the known solution with the largest correlation coefficient to compensate the photoelectric detection signal values of the solution to be measured, so that the compensated photoelectric detection signal values are the same as the photoelectric detection signal values of the solvent with a solid residue content of 0, thereby eliminating the influence of solid residues on absorbance detection and improving the accuracy of absorbance calculation;

[0057] 2) The present invention can realize the compensation of the photoelectric detection signal values of COD reagents and various detection reagents containing residues through the estimation and identification of sampling data, so as to perform accurate absorbance estimation, and further reduce the detection error of the concentration of detection reagents. Description of the Drawings

[0058] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0059] Figure 1 Flow chart of the method for estimating the absorbance value of the detection reagent containing solid residues of the present invention;

[0060] Figure 2 Schematic diagram of the normalized probability distribution of the present invention. Detailed implementation manners

[0061] The following will combine 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 a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0062] Taking the COD reagent as an example, the embodiments of the present invention use clear water without concentration as the solvent, and perform COD reagent data detection based on a disk microfluidic chip.

[0063] The general processing process of the disk microfluidic chip is as follows:

[0064] 1. COD reagent injection: The operator injects the reagent to be tested into the injection pool through a pipette.

[0065] 2. Quantitative pool quantification: The microfluidic chip performs low-speed centrifugation on the centrifuge table to make the reagent enter the quantitative pool.

[0066] 3. Filter large particles: During the process of entering the quantitative pool, if there are large particles, they will be centrifuged into the large particle bin.

[0067] 4. High-speed centrifugation: When the quantitative pool is completely filled, high-speed centrifugation is performed to make the reagent pass through the valve and enter the detection pool.

[0068] 5. Re-filter: The valve will filter out particles with a diameter greater than 10 microns.

[0069] 6. Detection in the detection pool. The detection pool contains COD reagent with particles (suspended or precipitated) with a diameter less than 10 microns. Based on the COD reagent in the detection pool, absorbance detection can be performed.

[0070] Please refer to Figure 1, the present invention provides a method for estimating the absorbance value of a detection reagent containing solid residues, the method comprising:

[0071] S1. Prepare N groups of known solutions with different solid residue contents.

[0072] Specifically, using clear water with a concentration of 0 as the solvent, artificially add N kinds of powdery solid residues with different but known contents. The solid residue is particulate matter with a diameter less than 10 microns, which can be suspended or precipitated in the reagent to form known solutions with different solid residue contents. For example, prepare known solutions with solid residue contents of 1%, 2%, 3%, …, 22% respectively, and inject them into the detection cell.

[0073] S2. For each group of known solutions, perform M photoelectric detections respectively to obtain M photoelectric detection signal values for each group of known solutions.

[0074] For each group of known solutions in the detection cell, perform M photoelectric detections using spectrophotometry to obtain M photoelectric detection signal values respectively, denoted as y [n] (1), y [n] (2), …, y [n] (m), …, y [n] (M), where n = 1, 2, …, N and m = 1, 2, …, M.

[0075] For example: perform 1 photoelectric detection on the solution with a solid residue content of 1% in the detection cell to obtain the signal value y [1] (1) = V(1);

[0076] Perform a centrifugation operation on the disk microfluidic chip to randomly redistribute the solid residues in the 1% solution, and perform the 2nd photoelectric detection to obtain the signal value y [1] (2) = V(2);

[0077] Perform a centrifugation operation on the disk microfluidic chip to randomly redistribute the solid residues in the 1% solution, and perform the 3rd photoelectric detection to obtain the signal value y [1] (3) = V(3);

[0078] After repeating the operation M times in this way, a total of M photoelectric detection signal values {V(1), V(2),..., V(m),..., V(M)} of the 1% solution can be obtained.

[0079] For each group of known solutions with different solid residue contents, repeat the above operation process respectively, and then obtain all the data values of y [n] (1), y [n] (2), …, y [n] (m), …, y [n] (M).

[0080] S3. Calculate the probability distribution function of each group of known solutions based on the M optoelectronic detection signal values of each group of known solutions respectively.

[0081] Based on the M optoelectronic detection signal values y [n] (1), y [n] (2), …, y [n] (m), …, y [n] (M) of the nth group of known solutions, count the frequency of occurrence of each optoelectronic detection signal value of the nth group of known solutions where P[y [n] (m)] is the frequency of occurrence of y [n] (m). According to the frequency statistics, obtain the probability distribution of each optoelectronic detection signal value, and take the limiting distribution when M is greater than the set threshold as the probability distribution function F(n) of the optoelectronic detection signal values of the nth group of known solutions.

[0082] Although the distribution of the solid residue is random during each optoelectronic detection, this process belongs to a stationary random process. When M is large enough, its distribution law gradually approaches the normal distribution. Therefore, the limiting distribution of the probability distribution function F(n) is the normal distribution.

[0083] After performing M optoelectronic detections on each of the N groups of known solutions, calculate the probability distribution functions F(1), F(2),..., F(n),..., F(N), n ∈ [1, N] respectively. As Figure 2 shown in the figure, when M = 100 and N = 4, the probability distribution diagram of normalizing the probability distributions of 4 different residue contents of 1%, 2%, 5%, and 10% to one graph.

[0084] S4. Calculate the corresponding compensation curves according to the probability distribution functions of each group of known solutions respectively.

[0085] Although each group of known solutions contains reagents with N different solid residue contents, if the influence of the solid residue is eliminated, they are reagents of the same concentration (such as pure water). For reagents of the same concentration under the condition that other environmental factors remain unchanged, the signal values detected optoelectronically can only be the same value a.

[0086] Therefore, form the constant matrix A from the optoelectronic detection signal values of the solvent with a solid residue content of 0. Introduce the compensation curve B(n) such that F [n] B [n] T = A, where F [n] is the matrix form of the probability distribution function F(n), B [n] is the coefficient matrix of the compensation curve, and n = 1, 2, …, N.

[0087] Specifically, for the probability distribution function F(n) of the nth group of known solutions, sampling is performed at equal step lengths along the abscissa to obtain a set of discrete optoelectronic detection signal values. The discrete optoelectronic detection signal values are divided according to the set number of rows and columns and converted into a matrix form, denoted as F [n] ;

[0088] Obtain multiple optoelectronic detection signal values of the solvent with a solid residue content of 0 and form a constant matrix A;

[0089] Let the coefficients of the compensation curve form a one-dimensional coefficient matrix B [n] , according to F [n] B [n] T = A to calculate the coefficient matrix B of the compensation curve [n] , n = 1, 2, …, N.

[0090] Taking N = 1, M = 20 as an example below, the specific method for calculating the corresponding compensation curve is described.

[0091] When N = 1, M = 20, sample the corresponding probability distribution function F(1) to obtain a set of optoelectronic detection signal values as F [1] = {F1 F2 F3... F 20};

[0092] Assume that the compensation curve is a fourth-degree curve, then the compensation curve has 5 coefficients. Let the coefficient matrix of the compensation curve B(1) be B [1] = [g b c d e], that is, the expression of B(1) is y = gx 4 + bx 3 + cx 2 + dx + e, where x represents the optoelectronic detection signal value and y represents the compensated optoelectronic detection signal value.

[0093] Convert F [1] into a 5*4 matrix form. The constant matrix A composed of the optoelectronic detection signal values of the solvent with a solid residue content of 0 is A = [a a... a] T , then F [1] B [1] T = A can be expressed as:

[0094] Then

[0095] According to the above formula, the value of the coefficient matrix B of the compensation curve B(1) is obtained, thereby obtaining the expression of the compensation curve B(1). [1] The value, thereby obtaining the expression of the compensation curve B(1).

[0096] S5. Perform M' optoelectronic detections on the solution to be measured to obtain M' optoelectronic detection signal values.

[0097] Obtain the solution to be measured, process it through a disk microfluidic chip, and perform M' optoelectronic detections on the solution to be measured in the detection cell using the same wavelength band and method as in step S2 to obtain M' optoelectronic detection signal values of the solution to be measured.

[0098] S6. Calculate the correlation coefficients between the M' optoelectronic detection signal values of the solution to be measured and the M optoelectronic detection signal values of each group of known solutions respectively, select the group of known solutions with the largest correlation coefficient, and extract the corresponding compensation curve.

[0099] Step S6 specifically includes the following sub-steps:

[0100] S61. Calculate the autocorrelation coefficients ryy [n] (1), y [n] (2), …, y [n] (m), …, y [n] (M) of the optoelectronic detection signal values corresponding to N groups of known solutions: [n] (m'):

[0101]

[0102] where m = 1, 2, …, M, m' represents the displacement deviating from m, the displacement step size is 1, the maximum value of m' is m - 1, and when m' = 0, it means no displacement:

[0103]

[0104] S62. Let the M' optoelectronic detection signal values of the solution to be measured be x(1), x(2),..., x(k),..., x(M'), k = 1, 2, …, M', and calculate its autocorrelation coefficient:

[0105]

[0106] S63. Calculate the cross-correlation coefficient ryx(m') between the optoelectronic detection signal values corresponding to the known solution and the M' optoelectronic detection signal values of the solution to be measured:

[0107]

[0108] S64. Calculate the correlation coefficient ρ [n] (m') between the M' optoelectronic detection signal values of the solution to be measured and the M optoelectronic detection signal values of each group of known solutions:

[0109]

[0110] where n = 1, 2, …, N.

[0111] Calculate N correlation coefficients ρ in this way [1](m'), ρ [2] (m'), …, ρ [N] (m').

[0112] S7. Compare the magnitudes of N correlation coefficients, and screen out the set of known solutions with the largest correlation coefficient to extract the corresponding compensation curve.

[0113] Specifically, if there exist n = n1 and m' = m1 such that max{ρ [n] (m') | n ∈ [1, N]} is closest to 1, then the n = n1 set of known solutions is the set of solutions closest to the probability distribution curve of the solution to be measured, and extract the corresponding compensation curve B(n1) and the corresponding coefficient matrix for subsequent compensation of the photoelectric detection signal value.

[0114] S8. Compensate the photoelectric detection signal value of the solution to be measured according to the extracted compensation curve to obtain the compensated photoelectric detection signal value.

[0115] Let X be the matrix form of the M' photoelectric detection signal values x(1), x(2),..., x(k),..., x(M') of the solution to be measured. According to the selected compensation curve B(n1) and the corresponding coefficient matrix compensate the value of X. Let the compensated matrix be A', then the compensation formula is:

[0116]

[0117] In the matrix A' after compensating the M' photoelectric detection signal values, the values of the matrix elements A'(i) are the same, all being a', i = 1, 2,..., M'.

[0118] S9. Estimate the absorbance value of the solution to be measured according to the compensated photoelectric detection signal value.

[0119] Estimate the absorbance value of the solution to be measured through the following formula:

[0120]

[0121] where, A i is the absorbance value of the solution to be measured, V0 = a is the photoelectric detection signal value of the solvent with a solid residue content of 0, A'(i) = a' is the compensated photoelectric detection signal value. Since the influence of the solid residue is eliminated, the compensated photoelectric detection signal values are the same each time, and the accuracy of the estimated absorbance value of the solution to be measured is higher.

[0122] The effectiveness of the present invention will be described below with specific experimental data.

[0123] Table 1 below shows the data sampled at every 10 points of the corresponding probability distribution function.

[0124] Table 1 Sampling Results of Photoelectric Detection Signal Values at Different Solid Residue Contents

[0125]

[0126] Basically, it can be seen from Table 1 that when the content of solid residue is less, the measurement data fluctuates more significantly and is concentrated near the center point. This is because when the residue content is less, the probability of not blocking the light source signal is greater, so the numerical change is larger. On the contrary, when the residue content is more, the measurement data fluctuates less and the data distribution is wider. This is also because when the residue content increases, the chance of blocking the light source is greater and the data change is closer. Since this embodiment configures a known solution of 1% - 22%, when the residue content exceeds 22%, no matter how the solution redistributes, the residue will completely block the light source and this algorithm is no longer applicable. When the light source is completely blocked by the residue, absorbance detection cannot be performed.

[0127] Table 2 shows the data after compensation using the method of the present invention. It can be seen from Table 2 that after compensation by the corresponding compensation curve, the photoelectric detection signal value is close to the target value with a solid residue content of 0, and the more the number of photoelectric detections M of the known solution, the more accurate the compensation. This is because the larger M is, the more accurate its probability distribution function is and the more accurate the compensation curve is. Therefore, the present invention directly takes the limit distribution when M is greater than the preset threshold as its probability distribution function.

[0128] Table 2 Photoelectric Detection Data after Compensation

[0129] Solid residue content (%) 1.0 2.0 5.0 10.0 Initial measurement value 0.942 0.875 0.847 0.802 Target value 1.0 1.0 1.0 1.0 M = 100 compensation value 0.998 0.941 0.862 0.813 M = 200 compensation value 0.999 0.958 0.922 0.884 M = 300 compensation value 0.999 0.989 0.957 0.931

[0130] Corresponding to the above method embodiment, the present invention also proposes an absorbance value estimation system for a detection reagent containing solid residue, and the system includes:

[0131] Data acquisition module: used to acquire N groups of known solutions with different solid residue contents; for each group of known solutions, perform M photoelectric detections respectively to obtain M photoelectric detection signal values of each group of known solutions; perform M' photoelectric detections on the solution to be measured to obtain M' photoelectric detection signal values;

[0132] Data processing module: used to calculate the probability distribution function F(n) of each group of known solutions respectively according to the M photoelectric detection signal values of each group of known solutions, where n = 1, 2,..., N, to obtain the probability distribution functions of N groups of known solutions; calculate the corresponding compensation curve B(n) respectively according to the probability distribution function F(n) of each group of known solutions, so that F [n] B [n]T = A, where F [n] is the matrix form of the probability distribution function F(n), B [n] is the coefficient matrix of the compensation curve, and A is the constant matrix composed of the optoelectronic detection signal values of the solvent with a solid residue content of 0;

[0133] Data compensation module: used to calculate the correlation coefficients between the M' optoelectronic detection signal values of the solution to be measured and the M optoelectronic detection signal values of each group of known solutions respectively, select the group of known solutions with the largest correlation coefficient, and extract the corresponding compensation curve; compensate the optoelectronic detection signal values of the solution to be measured according to the extracted compensation curve to obtain the compensated optoelectronic detection signal values;

[0134] Absorbance estimation module: used to estimate the absorbance value of the solution to be measured according to the compensated optoelectronic detection signal values.

[0135] The above system embodiments and method embodiments correspond one by one. For the brief description of the system embodiments, please refer to the method embodiments.

[0136] The present invention also discloses an electronic device, including: at least one processor, at least one memory, a communication interface, and a bus; wherein, the processor, the memory, and the communication interface complete communication with each other through the bus; the memory stores program instructions executable by the processor, and the processor calls the program instructions to implement the method described above in the present invention.

[0137] The present invention also discloses a computer-readable storage medium, and the computer-readable storage medium stores computer instructions, and the computer instructions enable the computer to implement all or part of the steps of the method described in the embodiments of the present invention. The storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory ROM, random access memory RAM, magnetic disks, or optical discs that can store program codes.

[0138] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be distributed to multiple network units. Those of ordinary skill in the art can, without creative efforts, select some or all of the modules according to actual needs to achieve the purpose of the solution of this embodiment.

[0139] The above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for estimating the absorbance value of a detection reagent containing solid residues, characterized in that The method includes: Configuring N groups of known solutions with different solid residue contents; For each group of known solutions, performing M optoelectronic detections respectively to obtain M optoelectronic detection signal values for each group of known solutions; Calculating the probability distribution function F(n) of each group of known solutions respectively according to the M optoelectronic detection signal values of each group of known solutions, where n = 1, 2, …, N, to obtain the probability distribution functions of N groups of known solutions; Calculate the corresponding compensation curve B(n) according to the probability distribution function F(n) of each group of known solutions, so that F [n] B [n] T = A, where F [n] is the matrix form of the probability distribution function F(n), B [n] is the coefficient matrix of the compensation curve, and A is the constant matrix composed of the photoelectric detection signal values of the solvent with a solid residue content of 0; Performing M' optoelectronic detections on the solution to be measured to obtain M' optoelectronic detection signal values; Calculating the correlation coefficients between the M' optoelectronic detection signal values of the solution to be measured and the M optoelectronic detection signal values of each group of known solutions respectively, screening out the group of known solutions with the largest correlation coefficient, and extracting the corresponding compensation curve; Compensating the optoelectronic detection signal values of the solution to be measured according to the extracted compensation curve to obtain the compensated optoelectronic detection signal values; Estimating the absorbance value of the solution to be measured according to the compensated optoelectronic detection signal values.

2. The method for estimating the absorbance value of the detection reagent containing solid residues according to claim 1, characterized in that, For each group of known solutions, centrifugation is performed before each optoelectronic detection.

3. The method for estimating the absorbance value of the detection reagent containing solid residues according to claim 1, wherein, The specific process of calculating the probability distribution function F(n) of each group of known solutions according to the M optoelectronic detection signal values of each group of known solutions includes: Let the M optoelectronic detection signal values of the nth group of known solutions be y [n] (1), y [n] (2), …, y [n] (m), …, y [n] (M), where n = 1, 2, …, N and m = 1, 2, …, M; Statistically count the frequency of occurrence of each optoelectronic detection signal value in the nth group of known solutions where P[y [n] (m)] is the frequency of occurrence of y [n] (m), and statistically count the probability distribution of optoelectronic detection signal values according to the frequency Taking the limiting distribution when M is greater than the set threshold as the probability distribution function F(n) of the M optoelectronic detection signal values of the nth group of known solutions, and the limiting distribution F(n) is a normal distribution.

4. The method for estimating the absorbance value of the detection reagent containing solid residues according to claim 1, characterized in that, The specific process of calculating the corresponding compensation curve B(n) respectively according to the probability distribution function F(n) of each group of known solutions includes: For the probability distribution function F(n) of the nth group of known solutions, sample at equal step lengths along the abscissa to obtain a set of discrete optoelectronic detection signal values. Divide the discrete optoelectronic detection signal values according to the set number of rows and columns and convert them into matrix form, denoted as F [n] ; Obtaining multiple optoelectronic detection signal values of a solvent with a solid residue content of 0 and forming a constant matrix A; Let the coefficients of the compensation curve form a one-dimensional coefficient matrix B [n] , according to F [n] B [n] T = A to calculate the coefficient matrix B of the compensation curve [n] .

5. The method for estimating the absorbance value of a detection reagent containing solid residues according to claim 1, wherein The process of the correlation coefficients between the M' optoelectronic detection signal values of the solution to be measured and the M optoelectronic detection signal values of each group of known solutions is specifically: Let the optoelectronic detection signal values corresponding to N groups of known solutions be y [n] (m), where m = 1, 2, …, M, and calculate its autocorrelation coefficient ryy [n] (m'): Where m' represents the displacement, the displacement step size is 1, and when m' = 0: Let the M' optoelectronic detection signal values of the solution to be measured be x(1), x(2),..., x(k),..., x(M'), where k = 1, 2, …, M', and calculate its autocorrelation coefficient: Calculating the covariance ryx(m') between the optoelectronic detection signal values corresponding to the known solution and the M' optoelectronic detection signal values of the solution to be measured: Calculate the correlation coefficient ρ between the M' optoelectronic detection signal values of the solution to be measured and the M optoelectronic detection signal values of each group of known solutions [n] (m'): Where, n = 1, 2, …, N.

6. The method for estimating the absorbance value of the detection reagent containing solid residues according to claim 4, characterized in that, The specific process of compensating the optoelectronic detection signal values of the solution to be measured according to the extracted compensation curve to obtain the compensated optoelectronic detection signal values is: Let \(X\) be the matrix form of \(M'\) optoelectronic detection signal values \(x(1), x(2), \cdots, x(k), \cdots, x(M')\) of the solution to be measured. It is the coefficient matrix of the compensation curve corresponding to a set of known solutions with the largest correlation coefficient. Then, the matrix \(A'\) composed of the compensated optoelectronic detection signal values is: The elements of matrix A' are the compensated optoelectronic detection signal values.

7. The method for estimating the absorbance value of the detection reagent containing solid residues according to claim 6, characterized in that, The specific process of calculating the absorbance value of the solution to be measured according to the compensated optoelectronic detection signal values is: Among them, A i is the absorbance value of the solution to be measured, V0 is the photoelectric detection signal value of the solvent with a solid residue content of 0, i = 1, 2,..., M', and A'(i) is an element of A', that is, the photoelectric detection signal value after each photoelectric detection compensation.

8. An absorbance value estimation system for a detection reagent containing solid residues, characterized in that, The system includes: A data acquisition module: used to acquire N groups of known solutions with different solid residue contents; for each group of known solutions, performing M optoelectronic detections respectively to obtain M optoelectronic detection signal values for each group of known solutions; performing M' optoelectronic detections on the solution to be measured to obtain M' optoelectronic detection signal values; Data processing module: used to calculate the probability distribution function F(n) of each group of known solutions based on the M optoelectronic detection signal values of each group of known solutions, where n = 1, 2, …, N, and obtain the probability distribution functions of N groups of known solutions; calculate the corresponding compensation curve B(n) based on the probability distribution function F(n) of each group of known solutions, so that F [n] B [n] T = A, where F [n] is the matrix form of the probability distribution function F(n), B [n] is the coefficient matrix of the compensation curve, and A is the constant matrix composed of the optoelectronic detection signal values of the solvent with a solid residue content of 0; Data compensation module: used to calculate the correlation coefficients between the M' photoelectric detection signal values of the solution to be measured and the M photoelectric detection signal values of each group of known solutions respectively, select the group of known solutions with the largest correlation coefficient, and extract the corresponding compensation curve; compensate the photoelectric detection signal values of the solution to be measured according to the extracted compensation curve to obtain the compensated photoelectric detection signal values; Absorbance estimation module: used to estimate the absorbance value of the solution to be measured according to the compensated photoelectric detection signal values.

9. An electronic device, characterized in that, Comprising: At least one processor, at least one memory, a communication interface and a bus; Wherein, the processor, the memory and the communication interface complete mutual communication through the bus; The memory stores program instructions executable by the processor, and the processor calls the program instructions to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions, and the computer instructions cause the computer to implement the method according to any one of claims 1 to 7.

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