Combined detection method and system for oxygen content of oxygen-free copper

Abstract

The invention relates to the technical field of material detection, in particular to an oxygen-free copper oxygen content combined detection method and system.The method comprises the steps that an oxygen-free copper casting and an aerobic copper casting are manufactured, and a plurality of oxygen-free copper sample blocks and aerobic copper sample blocks with the same mass are obtained; preparing a plurality of sample groups, mixing the oxygen-free copper sample blocks and the aerobic copper sample blocks in the plurality of sample groups according to a gradient proportion, and recording the mass fractions of the oxygen-free copper sample blocks and the aerobic copper sample blocks in the plurality of sample groups; detecting the oxygen content of each sample group; constructing a design matrix, and constructing a measurement value vector according to the oxygen content corresponding to each sample group; solving the parameter estimation vector by using a least square algorithm, and calculating the real oxygen content of the oxygen-free copper through the parameter estimation vector; and verifying the credibility of the sample and the model, if the verification is passed, calculating the uncertainty, and outputting by combining the true oxygen content of the oxygen-free copper. According to the method, the oxygen content of the oxygen-free copper can be more accurately measured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of material detection, and particularly relates to a combined detection method and system for oxygen content of oxygen-free copper. BACKGROUND

[0002] Oxygen-free copper is a kind of high-purity copper, and the content of impurities, especially oxygen, in the oxygen-free copper is extremely low, so the oxygen-free copper has extremely high conductivity and heat conductivity, and is widely used in the field of electronic devices and semiconductor industry which have extremely high requirements on material performance. In order to ensure the performance of the oxygen-free copper, the oxygen content of the produced oxygen-free copper needs to be detected. In the existing detection means, the oxygen-free copper product is usually directly detected, but since the oxygen content in the oxygen-free copper is extremely small, the sensitivity of the detection environment and the detection equipment is extremely high, and the detection result is also prone to large errors under the influence of instrument system deviation and background signal, so a detection method and system capable of more accurately detecting the oxygen content of the oxygen-free copper is needed. SUMMARY

[0003] The present application provides a combined detection method and system for oxygen content of oxygen-free copper, which can effectively solve the problems in the background art.

[0004] The combined detection method for oxygen content of oxygen-free copper provided by the present application comprises the following steps: oxygen-free copper castings and oxygen-containing copper castings are made, and a plurality of oxygen-free copper samples and oxygen-containing copper samples with the same mass are obtained from the oxygen-free copper castings and the oxygen-containing copper castings; a plurality of sample groups are prepared, the oxygen-free copper samples and the oxygen-containing copper samples are mixed in gradient proportions in the plurality of sample groups, and the mass fraction of the oxygen-free copper samples and the oxygen-containing copper samples in each sample group is recorded; the oxygen content of each sample group is detected; a design matrix is constructed according to the mass fraction of the oxygen-free copper samples and the oxygen-containing copper samples in each sample group, and a measurement value vector is constructed according to the oxygen content corresponding to each sample group; a parameter estimation vector is solved by using a least square algorithm, and the real oxygen content of the oxygen-free copper is calculated through the parameter estimation vector; the credibility of the sample and the model is verified, if the verification is passed, the uncertainty is calculated, and the real oxygen content of the oxygen-free copper is output.

[0005] Further, the specific steps of preparing the plurality of sample groups comprise: N+1 sample groups are prepared, and in the jth sample group, N+1-j oxygen-free copper samples and j-1 oxygen-containing copper samples are included.

[0006] Further, the specific construction method of the design matrix and the measurement value vector is: The mass fraction of oxygen-free copper in the jth sample group is aj=(N+1-j) / N, and the mass fraction of oxygen-containing copper is bj=(j-1) / N; The design matrix X is an (N+1) row and 3 column matrix, wherein the elements of the jth row are [1, aj, bj]; The measurement vector O is [o1, o2, …, o(N+1)] T , wherein oj is the oxygen content detected by the jth sample group.

[0007] Further, the specific steps of calculating the true oxygen content of oxygen-free copper include: Constructing a least squares algorithm deformation equation: (X T · W · X + λ · I) · θ = X T · W · O; Wherein, W is a set weight matrix; λ is a regularization coefficient; I is the unit matrix; θ is the parameter estimation vector, denoted as θ=[γ,U,V] T ; Solving the least squares algorithm deformation equation to obtain the specific values of γ, U, and V; The calculation formula of the true oxygen content ou of oxygen-free copper is: ou=U·o(N+1) / V.

[0008] Further, at least three of each sample group are prepared, and when detecting the oxygen content, the average value of the oxygen content detected by all the sample groups corresponding to each sample group is taken as the final oxygen content of the sample group. The oxygen content variance σj2 of the multiple sample groups of the jth sample group is calculated, and the element value of the jth row and the jth column of the weight matrix W is 1 / σj2.

[0009] Further, the specific steps of sample reliability verification include: Calculate the first-order difference △oj=oj-o(j-1); Calculate the second-order difference △Doj=△oj-△o(j-1); Calculate the average value △oavg and the standard deviation σ△o of all △oj, if σ△o / △oavg<0.05, then the first-order verification is passed; Calculate the average value △Doavg and the standard deviation σ△Do of all △Doj, if |△Doavg|<2σ△Do, then the second-order verification is passed; Only when the first-order and second-order verifications are passed, the sample reliability verification is passed.

[0010] Further, the specific steps of model reliability verification include: Calculate the determination coefficient R = 1-SR / ST; Wherein, SR=(O-X·θ) T ·W·(O-X·θ); ST=(O-omavg) T ·W·(O-omavg); omavg is the weighted average of all measured values o; If the value of R is less than the set threshold, the verification fails.

[0011] Further, the specific algorithm of the uncertainty is: Calculate the residual variance σθ 2 =(O-X·θ) T ·W·(O-X·θ) / (N+1-3); Calculate the covariance matrix Σθ; Σθ=σθ 2 ·(X T ·W·X+λ·I) -1 ·X T ·W·X·(X T ·W·X+λ·I) -1 ; Extract the element of the second row and the second column of the matrix Σθ as uA(U); Extract the element of the third row and the third column of the matrix Σθ as uA(V); Extract the element of the second row and the third column of the matrix Σθ as cov(U,V); The calculation formula of the uncertainty uc is: ; The final output value of the real oxygen content of the oxygen-free copper is ou±uc.

[0012] Further, the specific steps for detecting the oxygen content of each sample group include: Put the sample group to be detected into a graphite measuring cavity; Use pulse current to heat the sample group to melt it, then introduce high-purity nitrogen into the measuring cavity, and pass the gas flowing out of the measuring cavity into a laser cell; After a certain amount of gas is stored in the laser cell, the degree of attenuation of the laser energy in the laser cell at this time is detected, and then converted into the oxygen content.

[0013] The application also provides an oxygen content combined detection system for oxygen-free copper, which comprises a storage and a processor, the storage is used to store one or more program instructions; the processor is used to run one or more program instructions, and is used to execute the steps of the oxygen content combined detection method for oxygen-free copper as described above.

[0014] The technical scheme of the present application can achieve the following technical effects: The present method can solve the problem of measuring the small oxygen content in oxygen-free copper by mixing the oxygen-free copper and the oxygen-containing copper, and converting the problem of measuring the small oxygen content in oxygen-free copper into the problem of using the increment of oxygen content to deduce the quantitative combination relationship between the oxygen-free copper and the oxygen-containing copper, so as to realize high-precision analysis of the oxygen content in oxygen-free copper. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the technical scheme in the embodiments of the present application or the prior art, the drawings needed in the following embodiment or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments described in the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0016] Figure 1 The flowchart of the oxygen content combination detection method of oxygen-free copper in the present application. DETAILED DESCRIPTION

[0017] The basic principles and main features of the technical scheme of the present application will be described below in combination with the drawings in the embodiments of the present application. One or more embodiments will be described to make the description more intuitive, and the described embodiments are only some embodiments of the present application, not all embodiments.

[0018] In the description of the present application, the words indicating the orientation or positional relationship (such as up, down, left, right, etc.) are based on the orientation shown in the drawings or some conventional positional relationship, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the features referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application.

[0019] An oxygen content combination detection method of oxygen-free copper, as shown in Figure 1 The specific contents of each step are as follows: Sample preparation: First, prepare the oxygen-free copper castings and oxygen-containing copper castings required for detection, and the oxygen content of the oxygen-containing copper castings is relatively high; cut the oxygen-free copper castings and oxygen-containing copper castings into a plurality of oxygen-free copper sample blocks and oxygen-containing copper sample blocks with the same mass; Preparation of a plurality of sample groups, the mixing ratio of oxygen-free copper sample and oxygen-containing copper sample in each sample group is different, the oxygen-free copper sample and oxygen-containing copper sample in the plurality of sample groups are mixed in gradient ratio, a series of sample groups with gradually increasing oxygen content are created, since the oxygen content of castings produced in the same furnace is usually consistent, the comparability of oxygen-free copper sample and oxygen-containing copper sample in different sample groups is ensured by obtaining all oxygen-free copper samples from the same oxygen-free copper casting and obtaining all oxygen-containing copper samples from the same oxygen-containing copper casting; The specific steps for preparing a plurality of sample groups are as follows: Suppose if N+1 sample groups are needed in total; In the first sample group, N oxygen-free copper samples and 0 oxygen-containing copper samples are included; In the second sample group, N-1 oxygen-free copper samples and 1 oxygen-containing copper sample are included; … In the jth sample group, N+1-j oxygen-free copper samples and j-1 oxygen-containing copper samples are included; … In the N+1th sample group, 0 oxygen-free copper samples and N oxygen-containing copper samples are included.

[0020] When the sample groups are made, the mass fraction of oxygen-free copper samples and oxygen-containing copper samples in various sample groups is recorded, the mass fraction mainly reflects the proportion of oxygen-free copper samples and oxygen-containing copper samples in the sample groups, since the mass of oxygen-free copper samples and oxygen-containing copper samples is consistent, the proportion between oxygen-free copper and oxygen-containing copper is mainly related to the number of samples, that is, the mass fraction of oxygen-free copper is αj=(N+1-j) / N, and the mass fraction of oxygen-containing copper is βj=(j-1) / N.

[0021] The instrument for detecting oxygen content usually has an optimal range smaller than its range, in which the accuracy of the instrument's detection results is higher, therefore, when designing N+1 sample groups, the estimated oxygen content of the sample groups containing oxygen-containing copper samples should be located in the optimal range of the instrument.

[0022] Oxygen content detection: Before detection, the oxygen-free copper sample and the oxygen-containing copper sample are first subjected to pickling (such as immersion in dilute hydrochloric acid or nitric acid solution) to remove the surface oxide layer, and then washed with deionized water and dried, so as to eliminate the interference of surface oxides on the detection of oxygen content; if the sample is contaminated with oil or organic matter, an organic solvent (such as acetone) cleaning step can be added, and then washed with deionized water and dried to remove these oxygen-containing contaminants.

[0023] Detection data analysis and result output: after obtaining the oxygen content of various sample groups, a design matrix is constructed according to the mass fraction of oxygen-free copper sample and oxygen-containing copper sample in various sample groups, the design matrix is used to establish the relationship between the background noise of the detection equipment, the mass fraction of oxygen-free copper and the mass fraction of oxygen-containing copper, and a measurement value vector is constructed according to the corresponding oxygen content of various sample groups; The least square algorithm is used to solve the parameter estimation vector, the least square algorithm is a fitting algorithm, which can inversely deduce the relationship between multiple parameters according to the result; in the method, the principle of the least square algorithm is used, but the relationship between the background noise, the mass fraction of oxygen-free copper and the mass fraction of oxygen-containing copper has been determined in the method, therefore, the method forms a hypothetical parameter estimation vector according to the characteristics of the real oxygen content in the sample group, the hypothetical parameter estimation vector is involved in the operation of the least square algorithm, so that a series of corresponding equations are obtained, the variables in the equations are the elements in the parameter estimation vector, the elements in the parameter estimation vector can be solved through the corresponding equations, and then the real oxygen content of oxygen-free copper is restored.

[0024] Before outputting the calculation result, the real oxygen content of oxygen-free copper is used to verify the credibility of the sample and the model, if the verification is passed, the uncertainty is calculated, and the real oxygen content of oxygen-free copper is combined to output.

[0025] The method converts the problem of measuring the small oxygen content in oxygen-free copper into the problem of inversely deducing the quantitative combination relationship between oxygen-free copper and oxygen-containing copper by using the increment of oxygen content, through a plurality of sample groups manufactured by gradient proportion mixing, so as to realize high-precision analysis of the oxygen content in oxygen-free copper; and the influence of oxygen-containing copper can be eliminated, the oxygen content of oxygen-containing copper itself can also be measured by the method, so that the actual oxygen content of oxygen-containing copper does not need to be too strict, which is convenient for the production of oxygen-containing copper sample, thereby effectively saving the detection cost.

[0026] Preferably, the specific construction method of the design matrix and the measurement value vector is as follows: The mass fraction of oxygen-free copper in the jth sample group is aj=(N+1-j) / N, and the mass fraction of oxygen-containing copper is bj=(j-1) / N; The design matrix X is an (N+1) row and 3 column matrix, wherein the elements of the jth row are [1, aj, bj], each row element considers the background signal (the first column) which is assumed not to change, the proportion of oxygen-free copper in the sample group (the second column) and the proportion of oxygen-containing copper in the sample group (the third column).

[0027] The measurement value vector O=[o1, o2……o(N+1)] Twherein oj is the oxygen content detected by the jth sample group.

[0028] Preferably, the specific steps of calculating the true oxygen content of the oxygen-free copper include: Let θ be the parameter estimation vector, denoted as θ = [γ, U, V] T ; wherein γ represents the systematic deviation of the instrument, including the background signal, zero drift and other systematic influencing factors; U represents the influence degree of the oxygen-free copper on the measurement value; V represents the influence degree of the oxygen-containing copper on the measurement value; at the present step, the above three values are all assumed values.

[0029] Based on the least square algorithm, the measurement value vector O and the weight matrix W are introduced, and the least square algorithm equation is deformed, so that the equation: (X T · W · X + λ · I) · θ = X T · W · O; wherein W is the set weight matrix, which is an (N+1) × (N+1) matrix, the diagonal elements of the matrix are the set weight values, the weight values correspond to the importance of each sample group, and the remaining elements of the matrix are all 0; λ is a regularization coefficient artificially set, and a suitable λ value can minimize the prediction error of the model; I is a 3 × 3 unit matrix, i.e. the diagonal elements of the matrix are 1, and the remaining elements of the matrix are all 0.

[0030] In the above equation, the left side of the equation is the theoretical situation of the oxygen content generated by the background signal of the measuring instrument, the oxygen-free copper and the oxygen-containing copper under the mutual influence, and the right side of the equation is the actual situation of the oxygen content actually detected, so that by corresponding the theoretical situation and the actual situation, the specific values of each element in the parameter estimation vector θ = [γ, U, V] T can be solved.

[0031] Then the true oxygen content ou of the oxygen-free copper is calculated by the calculation formula of the true oxygen content ou of the oxygen-free copper: ou = U · o(N+1) / V, so that the true oxygen content ou of the oxygen-free copper is calculated; wherein o(N+1) is the oxygen content in the N+1th sample group, and since there is no oxygen-free copper in this group, the value can be directly taken as the true oxygen content of the oxygen-containing copper under the condition that the sample verification is passed.

[0032] Preferably, at least three of each sample group are made, and when the oxygen content is detected, the average of the oxygen content detected by all the sample groups corresponding to each sample group is taken as the final oxygen content of the sample group, so that the oxygen content measured by each sample group is closer to the accurate value, and the error is minimized; and the weight matrix W can also be automatically updated in this way, in the weight matrix W, the oxygen content variance of the plurality of sample groups of the jth sample group is σj2, and the element value of the jth row and jth column of the weight matrix W is 1 / σj2, so if the oxygen content variance of the plurality of sample groups in a sample group is smaller, it means that the measurement value of this sample group is more stable, and the corresponding weight value will be larger, thereby improving its influence in the modified equation of the least square algorithm and improving the calculation accuracy.

[0033] Preferably, the sample reliability verification specific steps include: Calculate the first-order difference △oj=oj-o(j-1), where j takes 2~N+1;△oj represents the change gradient of the oxygen content detected by the adjacent two sample groups, since the number of oxygen-free copper and oxygen-containing copper in the sample group changes regularly, the change gradient should be relatively uniform, by calculating the average value△oavg and the standard deviation σ△o of all△oj, if σ△o / △oavg<0.05, it means that the change gradient is uniform, then the first-order verification of the sample group is passed; and if the change gradient is not uniform, it is more likely that the oxygen content of the oxygen-free copper sample or the oxygen-containing copper sample in the sample group is inconsistent, or the instrument detection error is too large, and corresponding adjustment and re-detection are required; Calculate the second-order difference △Doj=△oj-△o(j-1), where j takes 3~N+1;△Doj is mainly used to determine the difference between the change gradients, so as to determine whether the instrument has too large instability in detection; calculate the average value△Doavg and the standard deviation σ△Do of all△Doj, if |△Doavg|<2σ△Do, it means that there is no significant change in the difference between the change gradients, then the second-order verification is passed; and if there is a significant change in the difference between the change gradients, it means that the instrument has problems such as continuous large or small detection results of the sample group, or too large deviation amplitude, and the instrument needs to be adjusted and then re-detected; Only when the first-order and second-order verifications are passed, the sample reliability verification is passed, so as to confirm that the sample group and the instrument have no obvious problems, so that the subsequent model reliability verification has practical significance.

[0034] Preferably, the model reliability verification specific steps include: Calculate the judgment coefficient R=1-SR / ST; Wherein, SR=(O-X·θ) T• W · (O - X · θ), which represents the residual sum of squares of the model, is used to quantify the degree of correspondence between the theoretical values calculated in the model and the measured values; ST= (O - omavg) T • W · (O - omavg), which represents the total sum of squares of the model, is used to quantify the degree of correspondence between the weighted average of the measured values in the model and the total measured values; omavg is the weighted average of all measured values o, and the specific algorithm of omavg is: ; where wj is the element value on the diagonal of the jth row and jth column in the weight matrix W, and oj is the measured value of the jth sample group; The physical meaning of the determination coefficient R is the percentage of the total variation of the data that can be explained in the model. If the results calculated in the model are more perfect, the degree of correspondence will tend to 0 (i.e. the value of SR will tend to 0), and the determination coefficient R will be closer to 1. If the value of R is less than the set threshold value, it means that the results calculated in the model are too poor, and the verification fails, and the values in the model (such as λ) need to be adjusted for recalculation.

[0035] Preferably, the specific algorithm of the uncertainty is: Calculate the residual variance σθ 2 = (O - X · θ) T • W · (O - X · θ) / (N + 1 - 3) ; Calculate the covariance matrix Σθ; Σθ= σθ 2 • (X T • W · X + λ · I) -1 • X T • W · X · (X T • W · X + λ · I) -1 ; If θ is regarded as a hypothetical value, then the final elements of Σθ will be various expressions with γ, U, and V as variables; Extract the element in the 2nd row and 2nd column of the matrix Σθ, denoted as uA(U) ; Extract the element in the 3rd row and 3rd column of the matrix Σθ, denoted as uA(V) ; Extract the element in the 2nd row and 3rd column of the matrix Σθ, denoted as cov(U, V) ; Now in the foregoing calculation process, the specific values of each element in θ = [γ, U, V] T have been obtained, so the uncertainty uc can be calculated; The calculation formula of the uncertainty uc is: ; The final output value of the real oxygen content of the oxygen-free copper is ou±uc.

[0036] Preferably, the specific steps for detecting the oxygen content of each sample group include: Placing the sample group to be detected into a graphite measuring cavity; Heating the sample group to be detected by using pulse current to melt the sample group, and in the process of melting the sample group, oxygen combines with carbon in the graphite measuring cavity to form CO gas and is released; then high-purity nitrogen gas is introduced into the measuring cavity, the nitrogen gas carries the CO gas out of the measuring cavity, and the outflowing gas is introduced into a laser cell; After a certain amount of gas is stored in the laser cell, the CO gas absorbs and blocks the energy of the laser, so that by detecting the degree of attenuation of the laser energy in the laser cell at this time, the analog quantity of the detection signal is converted into digital quantity for integration and various corrections, to indirectly measure the content of O in the laser cell, and then the oxygen content is obtained. Before measuring each sample group, the measuring cavity is flushed with high-purity nitrogen gas to eliminate the influence of residual gas.

[0037] The present application also relates to a system for combined detection of the oxygen content of oxygen-free copper, comprising a storage and a processor, the storage is used for storing one or more program instructions; the processor is used for running one or more program instructions, and is used for executing the steps of the above-mentioned combined detection method of the oxygen content of oxygen-free copper.

[0038] The basic principles, main features and advantages of the present application are shown and described above. It should be understood by those skilled in the art that the present application is not limited by the above-mentioned embodiments, and the above-mentioned embodiments and descriptions in the specification are only to illustrate the principles of the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A method for detecting oxygen and copper content in a combination, characterized by the steps of The method comprises the following steps: Preparation of oxygen-free copper castings and oxygen-containing copper castings, and obtaining a plurality of oxygen-free copper samples and oxygen-containing copper samples with the same mass from the oxygen-free copper castings and oxygen-containing copper castings; Preparation of a plurality of sample groups, in which the oxygen-free copper samples and oxygen-containing copper samples are mixed in gradient proportions, and the mass fractions of the oxygen-free copper samples and oxygen-containing copper samples in each sample group are recorded; Detection of the oxygen content of each sample group; Construction of a design matrix according to the mass fractions of the oxygen-free copper samples and oxygen-containing copper samples in each sample group, and construction of a measured value vector according to the oxygen contents of each sample group; Solving of a parameter estimation vector by using a least square algorithm, and calculation of the real oxygen content of the oxygen-free copper by using the parameter estimation vector; Verification of the credibility of the sample and the model, calculation of the uncertainty if the verification is passed, and output of the real oxygen content of the oxygen-free copper.

2. The method of claim 1, wherein the method is performed without oxygen. The specific steps for preparing a plurality of sample groups comprise: Preparation of N+1 sample groups, in which N+1-j oxygen-free copper samples and j-1 oxygen-containing copper samples are included in the jth sample group.

3. The method of claim 2, wherein the method is performed without oxygen. The specific construction method of the design matrix and the measured value vector comprises: Calculation of the mass fraction of the oxygen-free copper in the jth sample group as aj=(N+1-j) / N, and calculation of the mass fraction of the oxygen-containing copper as bj=(j-1) / N; The design matrix X is a (N+1) row by 3 column matrix, in which the elements of the jth row are [1, aj, bj]; The measured value vector O = [o1, o2... o(N+1)] T where oj is the oxygen content detected by the jth sample group.

4. The method of claim 3, wherein the method is performed without oxygen. The specific steps for calculating the real oxygen content of the oxygen-free copper comprise: Construction of a deformation equation of the least square algorithm: (X T • W · X + λ · I) · θ = X T • W · O; In the equation, W is a set weight matrix, λ is a regularization coefficient, and I is a unit matrix. Solving of the deformation equation of the least square algorithm to obtain the specific values of γ, U and V. The calculation formula of the real oxygen content of the oxygen-free copper ou is: θ is a parameter estimation vector, denoted as θ = [γ, U, V] T ; ou=U·o(N+1) / V. At least three of each sample group are prepared, and the average value of the oxygen contents detected by all the sample groups corresponding to each sample group is taken as the final oxygen content of the sample group. Calculation of the oxygen content variance σj2 of the plurality of sample groups of the jth sample group.

5. The method of claim 4, wherein the method is performed without oxygen. The element value of the jth row and the jth column of the weight matrix W is 1 / σj2. The specific steps for verifying the credibility of the sample comprise: Calculation of the first-order difference △oj=oj-o(j-1); 6. The method of claim 3, wherein the method is performed without oxygen. Calculation of the second-order difference △Doj=△oj-△o(j-1); Calculation of the average value △oavg and the standard deviation σ△o of all △oj, and if σ△o / △oavg<0.05, the first-order verification is passed. Calculation of the average value △Doavg and the standard deviation σ△Do of all △Doj, and if |△Doavg|<2σ△Do, the second-order verification is passed. Only when the first-order and second-order verifications are both passed, the credibility verification of the sample is passed. The specific steps for verifying the credibility of the model comprise: Calculation of the judgment coefficient R=1-SR / ST; 7. The method of claim 5, wherein the method further comprises determining the oxygen content of the copper. omavg is the weighted average value of all measured values o. If the value of R is less than the set threshold value, the verification is not passed. where SR= (O - X θ) T W (O - X θ); ST = (O - omavg) T • W • (O - omavg); The specific algorithm of the uncertainty comprises: Calculation of the covariance matrix Σθ; 8. The method of claim 3, wherein the method is performed without oxygen. Extraction of the element of the second row and the second column of the matrix Σθ, which is denoted as uA(U); Compute residual variance σθ 2 = (O - X · θ) T · W · (O - X · θ) / (N + 1 - 3); Extraction of the element of the third row and the third column of the matrix Σθ, which is denoted as uA(V); ∑θ = σθ 2 • (X T • W · X + λ · I) -1 • X T • W · X · (X T • W · X + λ · I) -1 ; Extraction of the element of the second row and the third column of the matrix Σθ, which is denoted as cov(U,V). ​ ​ The calculation formula of uncertainty uc is: ； The final output value of the real oxygen content of the oxygen-free copper is ou±uc.

9. The method of claim 1, wherein the method is performed without oxygen. The specific steps for detecting the oxygen content of each sample group include: Placing the sample group to be detected into a graphite measuring cavity; Using pulse current to heat the sample group to melt it, then introducing high-purity nitrogen into the measuring cavity, and introducing the gas flowing out of the measuring cavity into a laser cell; After a certain amount of gas is stored in the laser cell, the degree of attenuation of the laser energy in the laser cell at this time is detected, and then converted into the oxygen content.

10. A system for detecting oxygen-free copper and oxygen content combination, characterized by, The device comprises a storage and a processor, the storage is used for storing one or more program instructions; the processor is used for running one or more program instructions, and is used for executing the steps of the combined detection method of the oxygen content of the oxygen-free copper according to any one of claims 1-9.

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