A comprehensive evaluation method for the corrosion resistance of coated steel bars

Abstract

The present invention belongs to the technical field of material property analysis, and particularly relates to a comprehensive evaluation method for the corrosion resistance of clad steel bars, which comprises the following steps: first, obtain a first clad steel bar specimen and a second clad steel bar specimen; then, perform electrochemical corrosion treatment on the first clad steel bar specimen, and calculate the self-corrosion potential, the self-corrosion current density, and the difference in surface roughness before and after the treatment; then, perform salt spray corrosion treatment on the second clad steel bar specimen, calculate the weight loss rate, count the number of corrosion pits on the circumferential side wall surface, and detect the maximum corrosion width value of the end face, the maximum depth value and the maximum width value of the corrosion pits on the circumferential side wall surface; then, calculate the subjective weight and the objective weight for each evaluation index; finally, weight the subjective weight and the objective weight to construct a comprehensive evaluation model for the corrosion resistance of clad steel bars. This method comprehensively evaluates the corrosion resistance of clad steel bars based on salt spray corrosion and electrochemical corrosion, and can provide guidance for the prediction of the subsequent service performance of steel bars.

Description

Technical Field

[0001] The present invention belongs to the technical field of material property analysis, and particularly relates to a comprehensive evaluation method for the corrosion resistance of clad steel bars. Background Art

[0002] Clad steel bars are a new type of composite steel bars with high-strength low-alloy steel as the base material and an austenitic stainless steel or duplex stainless steel cladding. The corrosion resistance of this type of steel bar is close to that of stainless steel bars, but the cost is low, and it has received extensive attention in recent years. Since clad steel bars are composed of two metals, the bonding performance of the composite surface will greatly affect the service life of clad steel bars. Moreover, the bonding performance is affected by the corrosion resistance. The worse the corrosion resistance of clad steel bars, the more likely pitting corrosion will occur during service, which will further lead to the expansion of corrosion cracks along the composite surface, reducing the bonding strength of the composite surface and shortening the service life of clad steel bars.

[0003] For improving the corrosion resistance of traditional steel bars, scientists have proposed two methods. One is to delay the start time of steel bar corrosion, such as adding corresponding rust inhibitors to concrete, but this solution will increase the quality of the concrete itself and the corresponding cost. The other is to extend the corrosion cycle of steel bars, mainly including the selection of corrosion-resistant steel bars and the cathodic protection method, etc. However, at present, the detection of the corrosion resistance of clad steel bars is still in the exploratory stage. The existing patent with the application number CN202310501966.2 discloses a steel bar corrosion resistance test device and its use method, which mainly improves the salt spray spraying device to enable the steel bars to be in full contact with the acidic mist during the corrosion resistance test. The existing patent with the application number CN201811590112.1 discloses an admixture for improving the corrosion resistance of concrete steel bars and its preparation method, which mainly prepares a corrosion-resistant solvent to improve the corrosion resistance of concrete steel bars and extends the service life of the reinforced concrete structure. In addition, the existing patent with the application number CN201811361431.5 discloses a method for testing the corrosion resistance of steel bars used in concrete structures in a tropical marine atmospheric environment. The method places the steel bars in a salt spray corrosion environment and measures the corrosion rate of the steel bars in the form of weight loss method, and uses this rate to evaluate the corrosion resistance.

[0004] The above-mentioned existing patent technologies only target the corrosion resistance detection of traditional carbon steel bars. In addition, the evaluation of corrosion resistance is only based on salt spray corrosion experiments. However, clad steel bars are mainly used in marine environments. In addition to salt spray corrosion, there is also certain electrochemical corrosion in the marine environment. Therefore, it is necessary to develop a comprehensive detection method for the corrosion resistance of clad steel bars. Summary of the Invention

[0005] The present invention provides a method for comprehensively evaluating the corrosion resistance of coated steel bars. The method comprehensively evaluates the corrosion resistance of coated steel bars based on salt spray corrosion and electrochemical corrosion, and can provide guidance for predicting the subsequent service performance of steel bars.

[0006] The method comprises the following steps:

[0007] S1. Obtain a first covered steel bar specimen and a second covered steel bar specimen, wherein the length of the second covered steel bar specimen is greater than the length of the first covered steel bar specimen;

[0008] S2, electrochemically corroding the first coated steel bar specimen, and calculating the self-corrosion potential i of the first coated steel bar specimen corr and the self-corrosion current density E corr , and measure the surface roughness difference R of the first coated steel bar specimen before and after the electrochemical corrosion treatment a ;

[0009] S3, subjecting the second coated steel bar specimen to salt spray corrosion treatment, and calculating the weight loss rate Z of the second coated steel bar specimen s , count the number of corrosion pits A on the side wall surface of the second coated steel bar specimen, and detect the maximum corrosion width D of the end surface of the second coated steel bar specimen k , and detect the maximum depth value L of the corrosion pit on the side wall surface of the second coating steel bar specimen h and the maximum width of the corrosion pit L k ;

[0010] S4, the self-corrosion potential i corr , self-corrosion current density E corr , surface roughness difference R a , weight loss rate Z s , the number of corrosion pits on the side wall surface A, the maximum depth of the corrosion pits on the side wall surface L h , the maximum width of the corrosion pit on the side wall surface L k And the maximum corrosion width D of the end face k Calculating subjective weights and objective weights, wherein the objective weight calculation step further includes calculating the conflict coefficient of each evaluation index;

[0011] S5. Weighting the subjective weight and the objective weight calculated in step S4 to construct a model for comprehensive evaluation of the corrosion resistance of the coated steel bars.

[0012] In a specific embodiment, the length of the first coated steel bar specimen is 10-25 mm, the length of the second coated steel bar specimen is 300-800 mm, and step S2 comprises:

[0013] S2.1. Place the first clad steel bar specimen under a 3D scanner, scan its surface profile, and use post-processing software to measure its surface roughness R before electrochemical corrosion treatment. y ;

[0014] S2.2. Connect the first clad steel bar specimen as the working electrode to an electrochemical workstation through a wire, connect a saturated calomel electrode as the reference electrode to the electrochemical workstation, and the saturated calomel electrode is connected with a salt bridge structure. Connect a platinum electrode as the auxiliary electrode to the electrochemical workstation.

[0015] S2.3. Inject electrolyte into the electrolytic cell so that the electrolyte completely immerses the first clad steel bar specimen, the saturated calomel electrode, the salt bridge structure and the platinum electrode, and adjust the distance between the tip of the salt bridge structure and the first clad steel bar specimen to a certain value.

[0016] S2.4. Start the potentiodynamic polarization curve test. Draw a polarization curve based on the electrode potential and electrode current obtained from the potentiodynamic polarization curve test, and then use the Tafel straight-line measurement method to calculate the self-corrosion potential i corr and the self-corrosion current density E corr ;

[0017] S2.5. Then place the first clad steel bar specimen under a 3D scanner, scan its surface profile, and use post-processing software to measure its surface roughness R after electrochemical corrosion treatment. h ;

[0018] S2.6. Calculate the difference in surface roughness R of the first clad steel bar specimen before and after electrochemical corrosion treatment a :

[0019] R a =R y -R h .

[0020] In a specific embodiment, step S3 includes:

[0021] S3.1. Grind and remove the scale on the surface of the second clad steel bar specimen, and weigh the second clad steel bar specimen after removing the scale to obtain its weight G1.

[0022] S3.2. Place the second clad steel bar specimen in a salt spray corrosion chamber for corrosion. After corrosion, remove rust, and weigh the second clad steel bar specimen after removing rust to obtain its weight G2.

[0023] S3.3. Calculate the weight loss rate:

[0024] Zs =(G1 - G2) / G1;

[0025] S3.4. Count the number of corrosion pits A on the circumferential sidewall surface of the second clad steel bar specimen after rust removal, and place the end face of the second clad steel bar specimen after rust removal under a 3D scanner. Use post-processing software to detect the maximum corrosion width value D of the end face k ;

[0026] S3.5. Perform wire cutting on the corrosion pits on the circumferential sidewall surface to obtain corrosion pit cross-section specimens. After grinding and polishing the corrosion pit cross-section specimens, perform corrosion treatment using a metallographic corrosion solution;

[0027] S3.6. Place the corrosion pit cross-section specimens under a metallographic microscope. Use post-processing software to detect the maximum depth value L and the maximum width value L of the corrosion pits in the corrosion pit cross-section specimens h and the maximum width value L k .

[0028] In a specific embodiment, the expert scoring method is used to calculate the subjective weight in step S4, which specifically includes the following steps:

[0029] S4.1. Suppose n experts score each evaluation index on a ten-point scale, where the evaluation index is i corr , E corr , R a , Z s , A, L h , L k and D k . The scores of the n experts for the above 8 evaluation indexes form an n×8 matrix, denoted as the scoring matrix. The rows in the scoring matrix represent the scores of a certain expert for each evaluation index, and the columns in the scoring matrix represent the scores of each expert for a certain evaluation index;

[0030] S4.2. Calculate the scoring correlation coefficients between each expert according to the scoring matrix to obtain a scoring correlation coefficient matrix; among them, the formula for calculating the scoring correlation coefficients between each expert is as follows:

[0031]

[0032] In the formula, e represents the e-th evaluation index, a ie represents the score of the i-th expert for the e-th evaluation index, a je represents the score of the j-th expert for the e-th evaluation index, n represents the total number of experts, i represents the i-th expert, j represents the j-th expert, and d ij represents the scoring correlation coefficient between the i-th expert and the j-th expert;

[0033] S4.3. Accumulate the correlation coefficients in each row of the above-mentioned scoring correlation coefficient matrix to obtain the K value of each expert:

[0034]

[0035] In the formula, n represents the total number of experts, j represents the j-th expert, and d ij represents the scoring correlation coefficient between the i-th expert and the j-th expert, and K i represents the K value of the i-th expert;

[0036] Calculate the weight of each expert:

[0037]

[0038] In the formula, n represents the total number of experts, i represents the i-th expert, |K i | represents the absolute value of the K value of the i-th expert, and U i represents the weight of the i-th expert;

[0039] S4.4. Multiply the weight of each expert by the corresponding score in the above-mentioned scoring matrix to obtain a weight matrix;

[0040] S4.5. Take the average of each column in the above-mentioned weight matrix to obtain the comprehensive score value of each evaluation index:

[0041]

[0042] In the formula, n represents the total number of experts, i represents the i-th expert, e represents the e-th evaluation index, U i represents the weight of the i-th expert, and a ie represents the score of the i-th expert for the e-th evaluation index, and Y e represents the comprehensive score value of the e-th evaluation index;

[0043] S4.6. Calculate the subjective weight of each evaluation index:

[0044]

[0045] In the formula, ω e represents the subjective weight of the e-th evaluation index, and Y e represents the comprehensive score value of the e-th evaluation index, represents the sum of the comprehensive score values of all evaluation indexes.

[0046] In a specific embodiment, the CRITIC method is used for objective weight calculation in step S4, which specifically includes the following steps:

[0047] S4.7. Obtain N groups of first clad steel bar specimens and second clad steel bar specimens with different diameters and different materials, repeat the operations in steps S2 to S3, obtain N groups of test data on the above 8 evaluation indicators, and form an N×8 objective data matrix; according to the objective data matrix, calculate the standard deviation of each evaluation indicator:

[0048]

[0049] where, σ e represents the standard deviation of the e-th evaluation indicator, N is the number of groups of data, t re represents the value of the e-th evaluation indicator in the r-th group of data, and μ e represents the average value of the e-th evaluation indicator;

[0050] Among them, the calculation formula of μ e is as follows:

[0051]

[0052] S4.8. Refer to the calculation method of the formula in step S4.2, calculate the objective correlation coefficient d fe between each evaluation indicator, where e represents the e-th evaluation indicator, f represents the f-th evaluation indicator, f, e = (1, 2,..., 8), and then calculate the conflict coefficient of each evaluation indicator:

[0053]

[0054] where, C e represents the conflict coefficient of the e-th evaluation indicator, and d fe represents the objective correlation coefficient between the f-th evaluation indicator and the e-th evaluation indicator;

[0055] S4.9. According to the standard deviation σ e of each evaluation indicator calculated in step S4.7 and the conflict coefficient C e of each evaluation indicator calculated in step S4.8, calculate the comprehensive information quantity X e of each evaluation indicator:

[0056] X e = σ e ·C e , e = (1, 2,..., 8);

[0057] Then, according to the comprehensive information quantity of each evaluation indicator calculated, calculate the objective weight of each evaluation indicator:

[0058]

[0059] where, ω e' represents the objective weight of each evaluation index, |X e | represents the absolute value of the comprehensive information quantity of each evaluation index.

[0060] In a specific embodiment, in step S5, the subjective weight and the objective weight are weighted by using the method of non-unique importance. First, the comprehensive weight ω' of each evaluation index is calculated e :

[0061]

[0062] Then, the weighted weight ω″ of each evaluation index is calculated e :

[0063]

[0064] In the formula, v represents the v-th evaluation index; finally, according to the calculated weighted weights of each evaluation index, a comprehensive evaluation model for the corrosion resistance of the clad steel bars is constructed:

[0065] Q = ω″1 × i corr + ω″2 × E corr + ω″3 × R a + ω″4 × Z s + ω″5 × A + ω″6 × L h + ω″7 × L k + ω″8 × D k .

[0066] The present invention has at least the following beneficial effects:

[0067] 1. This method not only considers the corrosion effects of salt spray corrosion and electrochemical corrosion on the clad steel bars, but also combines the physical morphology changes of the clad steel bars before and after corrosion to conduct a comprehensive evaluation of the corrosion resistance, which can provide guidance for predicting the service performance of the subsequent clad steel bars.

[0068] 2. By using clad steel bars with different diameters and materials for experiments, this method ensures the wide applicability and representativeness of the results, and helps to discover the influence laws of material characteristics and structural dimensions on the corrosion behavior.

[0069] 3. This method combines multiple means such as potentiodynamic polarization curve testing, 3D scanner, and metallographic microscope to obtain data, which increases the credibility of the results.

[0070] 4. By calculating parameters such as the conflict coefficient, comprehensive information quantity, and objective weight, this method assigns scientific and reasonable weight values to each evaluation index, making the final evaluation result more fair and objective.

[0071] In summary, through systematic experimental design and data analysis methods, this method evaluates the corrosion performance of coated steel bars more comprehensively and accurately, providing important reference and support for the research and practical engineering applications of coated steel bars. Description of the Drawings

[0072] Figure 1 It is the process schematic diagram of the embodiment of the present invention.

[0073] Figure 2 It is the three-dimensional view of the first coated steel bar specimen in the embodiment of the present invention.

[0074] Figure 3 It is the three-dimensional view of the first coated steel bar specimen covered with plasticine in the embodiment of the present invention.

[0075] Figure 4 It is the three-dimensional view of the first coated steel bar specimen covered with plasticine and connected with wires in the embodiment of the present invention.

[0076] Figure 5 It is the three-dimensional view of the first coated steel bar specimen covered with plasticine and connected with wires and placed in a square mold in the embodiment of the present invention.

[0077] Figure 6 It is the three-dimensional view of the first coated steel bar specimen coated with epoxy resin in the embodiment of the present invention.

[0078] Figure 7 It is the electron microscope image of the cross-sectional specimen of the corrosion pit in the embodiment of the present invention.

[0079] Reference numerals: the first coated steel bar specimen 1, plasticine 2, wire 3, square mold 4, epoxy resin 5. Detailed Embodiment

[0080] Please refer to Figure 1 , a comprehensive evaluation method for the corrosion resistance of coated steel bars provided by the present invention specifically includes the following steps:

[0081] S1. Cut the coated steel bars to obtain the first coated steel bar specimen 1 with an axial length of 16 mm as shown in Figure 2 and the second coated steel bar specimen (not shown) with an axial length of 500 mm. Of course, to ensure the accuracy of experimental data, the length of the first coated steel bar specimen can be selected within the range of 10 - 25 mm, and the length of the second coated steel bar specimen can be selected within the range of 300 - 800 mm.

[0082] S2. Perform electrochemical corrosion treatment on the first coated steel bar specimen 1, and calculate the self-corrosion potential i corr and the self-corrosion current density E corr, and measure the surface roughness difference R of the first coated steel bar specimen 1 before and after electrochemical corrosion treatment. a , and the specific operation steps are as follows:

[0083] Place the first coated steel bar specimen 1 under a 3D scanner, scan its surface profile, and use post-processing software to measure its surface roughness R before electrochemical corrosion treatment. y .

[0084] Conduct electrochemical corrosion treatment on the first coated steel bar specimen 1: Refer to Figures 3 - 6 , cover the side wall of the first coated steel bar specimen 1 with plasticine 2, and connect a wire 3 with an insulating outer skin at the center of the side wall opposite to the plasticine 2. Place the first coated steel bar specimen 1 covered with plasticine 2 and connected with the wire 3 in the middle of a square mold 4 through a support column, pour epoxy resin 5 into the square mold 4 until the cross-section of the specimen is completely immersed, wait for it to cure at room temperature, then take it out of the square mold 4, remove the support column and plasticine 2, and fill the hole formed by the support column with hot melt adhesive to obtain the first coated steel bar specimen 1 coated with epoxy resin 5. It should be noted that in other embodiments, the plasticine 2 can also be replaced with Blu Tack. Then connect the first coated steel bar specimen 1 as the working electrode to the electrochemical workstation through the wire 3, connect the saturated calomel electrode as the reference electrode to the electrochemical workstation, and the saturated calomel electrode is connected with a salt bridge structure. Connect the platinum electrode as the auxiliary electrode to the electrochemical workstation and place it in the electrolytic cell. Inject a NaCl solution with a mass concentration of 3.5% into the electrolytic cell as the electrolyte, so that the electrolyte completely immerses the first coated steel bar specimen 1, the saturated calomel electrode, the salt bridge structure and the platinum electrode, and adjust the distance between the tip of the salt bridge structure and the first coated steel bar specimen 1 to 5 mm. Start the potentiodynamic polarization curve test, and use the "Tafel curve" technology in the "linear sweep technique" of the electrochemical workstation. The initial potential is set to -1.0 V, the termination potential is set to 2.0 V, the scanning speed is set to 0.2 V / s, the experimental temperature is 30 °C, and other instrument default values are used. Draw a polarization curve, that is, an E-logi curve, according to the electrode potential and electrode current obtained from the potentiodynamic polarization curve test, and then use the Tafel straight line measurement method to calculate the self-corrosion potential i corr and the self-corrosion current density E corr .

[0085] Then place the first coated steel bar specimen 1 after electrochemical corrosion treatment under the 3D scanner, scan its surface profile, the scanning speed is 50000 pts / s, after scanning, use post-processing software to measure its surface roughness R after electrochemical corrosion treatment. h . Then calculate the surface roughness difference R of the first coated steel bar specimen 1 before and after electrochemical corrosion treatment.a :

[0086] R a = R y -R h 。

[0087] S3. Perform salt spray corrosion treatment on the second clad steel bar specimen, calculate the weight loss rate Z of the second clad steel bar specimen s , count the number of corrosion pits A on the circumferential side wall surface of the second clad steel bar specimen, detect the maximum corrosion width value D of the end face of the second clad steel bar specimen k , and detect the maximum depth value L of the corrosion pits on the circumferential side wall surface of the second clad steel bar specimen h and the maximum width value L of the corrosion pits k , and the specific operation steps are as follows:

[0088] Polish and remove the scale on the surface of the second clad steel bar specimen, and weigh the second clad steel bar specimen after removing the scale to obtain its weight G1.

[0089] Place the second clad steel bar specimen in a salt spray corrosion chamber for corrosion. The corrosion time is 30 days. Use a NaCl solution with a mass concentration of 5% for corrosion. The pH value of the NaCl solution is 6.5 - 7.5. The temperature in the salt spray corrosion chamber is 35°C, and the spray rate of the salt spray corrosion chamber is 1.5 - 2.5 mL / (90 cm 2 ·h). After corrosion, naturally dry the second clad steel bar specimen for 24 h, then remove rust, and weigh the second clad steel bar specimen after removing rust to obtain its weight G2.

[0090] Calculate the weight loss rate:

[0091] Z s =(G1 - G2) / G1.

[0092] Count the number of corrosion pits A on the circumferential side wall surface of the second clad steel bar specimen after removing rust, and place the end face of the second clad steel bar specimen after removing rust under a 3D scanner, and use post-processing software to detect the maximum corrosion width value D of the end face k 。

[0093] Use a wire cutting machine to perform wire cutting at the center of the corrosion pits on the circumferential side wall surface of the second clad steel bar specimen to obtain a cross-sectional specimen of the corrosion pits. It should be noted that to reduce the experimental workload, only some of the corrosion pits can be sampled for wire cutting to obtain a cross-sectional specimen of the corrosion pits. Then, polish and polish the cross-sectional specimen of the corrosion pits with 150#, 400#, 800#, 1200# sandpaper and nylon cloth in sequence, and then use a nitric acid alcohol solution with a mass concentration of 4% as a metallographic corrosion solution for corrosion treatment.

[0094] Please refer to Figure 7 and place the cross-sectional specimen of the corrosion pit under a metallurgical microscope. Use post-processing software to detect the maximum depth value L of the corrosion pit in the cross-sectional specimen of the corrosion pit h and the maximum width value L k of the corrosion pit.

[0095] S4. Calculate the subjective weight and objective weight for the 8 evaluation indicators, namely the self-corrosion potential i corr , the self-corrosion current density E corr , the surface roughness difference R a , the weight loss rate Z s , the number of corrosion pits A on the circumferential sidewall surface, the maximum depth value L of the corrosion pits on the circumferential sidewall surface h , the maximum width value L of the corrosion pits on the circumferential sidewall surface k , and the maximum corrosion width value D of the end face k .

[0096] First, calculate the subjective weight using the expert scoring method. It should be noted that although each expert is a technical person engaged in steel corrosion, due to different working hours, their experiences are also different. To improve the reliability and rigor of the subjective weight, this method improves the expert scoring method using the matrix correlation coefficient. The specific operation is as follows:

[0097] Suppose there are 6 experts who score the 8 evaluation indicators, namely the self-corrosion potential i corr , the self-corrosion current density E corr , the surface roughness difference R before and after electrochemistry a , the weight loss rate Z s , the number of corrosion pits A on the circumferential sidewall surface, the maximum depth value L of the corrosion pits on the circumferential sidewall surface h , the maximum width value L of the corrosion pits on the circumferential sidewall surface k , and the maximum corrosion width value D of the end face k . The scoring range is 0 - 10 points, indicating the importance of the evaluation indicator for the corrosion resistance performance. 0 points means the evaluation indicator is not important for the corrosion resistance performance evaluation, and 10 points means the evaluation indicator is very important for the corrosion resistance performance evaluation. The scores of these 6 experts form a 6×8 matrix, denoted as the scoring matrix. The rows in the scoring matrix represent the scores of a certain expert for each evaluation indicator, and the columns in the scoring matrix represent the scores of each expert for a certain indicator. For example, the obtained scoring matrix is as follows:

[0098]

[0099] In the matrix, a 11 represents the score of the 1st expert for the self-corrosion potential, and so on.

[0100] The scoring correlation coefficients between each expert are calculated based on the scoring matrix, and the calculation formula is as follows:

[0101]

[0102] In the formula, e represents the e-th evaluation index, a ie represents the score of the i-th expert for the e-th evaluation index, a je represents the score of the j-th expert for the e-th evaluation index, n represents the total number of experts, i represents the i-th expert, j represents the j-th expert, d ij represents the scoring correlation coefficient between the i-th expert and the j-th expert, and the scoring correlation coefficient matrix is obtained as follows:

[0103]

[0104] The following formula is used to accumulate the correlation coefficients in each row of the scoring correlation coefficient matrix to obtain the K value of each expert:

[0105]

[0106] In the formula, n represents the total number of experts, j represents the j-th expert, d ij represents the scoring correlation coefficient between the i-th expert and the j-th expert, K i represents the K value of the i-th expert, and the K value of each expert is calculated as shown in Table 1.

[0107] Table 1

[0108] Expert 1 Expert 2 Expert 3 Expert 4 Expert 5 Expert 6 K value 0.291 0.46 0.155 -0.716 0.368 -0.354

[0109] The following formula is used to calculate the weight of each expert:

[0110]

[0111] In the formula, n represents the total number of experts, i represents the i-th expert, |K i | represents the absolute value of the K value of the i-th expert, U i represents the weight of the i-th expert, and the calculation results are shown in Table 2.

[0112] Table 2

[0113] Expert 1 Expert 2 Expert 3 Expert 4 Expert 5 Expert 6 Weight 0.12 0.2 0.07 0.31 0.16 0.14

[0114] Then, the weight of each expert in Table 2 is multiplied by the corresponding score in the above scoring matrix to obtain the following weight matrix:

[0115]

[0116] The average of each column in the above weight matrix is calculated:

[0117]

[0118] In the formula, n represents the total number of experts, i represents the i-th expert, e represents the e-th evaluation index, and U i represents the weight of the i-th expert, and a ie represents the score of the i-th expert for the e-th evaluation index, and Y e represents the comprehensive score value of the e-th evaluation index. The comprehensive score values of each evaluation index are obtained as shown in Table 3.

[0119] Table 3

[0120]

[0121] Then, the following formula is used to calculate the subjective weight of each evaluation index:

[0122]

[0123] In the formula, ω e represents the subjective weight of the e-th evaluation index, and Y e represents the comprehensive score value of the e-th evaluation index, represents the sum of the comprehensive score values of all evaluation indexes. The calculation results are shown in Table 4.

[0124] Table 4

[0125]

[0126] Then, the CRITIC method is used to calculate the objective weight. Compared with the independent objective weight, the CRITIC method not only considers the volatility of the data but also considers the correlation relationship between the data. The specific steps are as follows:

[0127] Obtain 20 first clad steel bar specimens 1 and second clad steel bar specimens with different diameters and different materials, repeat the salt spray corrosion and electrochemical corrosion treatments in steps S2 - S3, obtain 20 groups of test data on the above 8 evaluation indexes, and form a 20×8 objective data matrix; according to this objective data matrix, calculate the standard deviation of each evaluation index:

[0128]

[0129] In the formula, σ e represents the standard deviation of the e-th evaluation index, N is the number of data groups, t re represents the value of the e-th evaluation index in the r-th group of data, and μ e represents the average value of the e-th evaluation index;

[0130] Among them, the calculation formula of μ e is as follows:

[0131]

[0132] The standard deviations of the calculated evaluation indicators are shown in Table 5.

[0133] Table 5

[0134]

[0135] Referring to the above formula for calculating the scoring correlation coefficient between experts, calculate the objective correlation coefficient d between each evaluation indicator fe , where e represents the e-th evaluation indicator, f represents the f-th evaluation indicator, f, e = (1, 2,..., 8).

[0136] Then use the following formula to calculate the conflict coefficient of each evaluation indicator:

[0137]

[0138] In the formula, C e represents the conflict coefficient of the e-th evaluation indicator, d fe represents the objective correlation coefficient between the f-th evaluation indicator and the e-th evaluation indicator. The calculated conflict coefficients of each evaluation indicator are shown in Table 6.

[0139] Table 6

[0140]

[0141] Then, according to the calculated standard deviation σ e of each evaluation indicator and the conflict coefficient C e of each evaluation indicator, calculate the comprehensive information quantity X e of each evaluation indicator:

[0142] X e = σ e ·C e , e = (1, 2,..., 8);

[0143] The calculation results of the comprehensive information quantity X e of each evaluation indicator are shown in Table 7.

[0144] Table 7

[0145]

[0146] Then, according to the calculated comprehensive information quantity of each evaluation indicator, use the following formula to calculate the objective weight of each evaluation indicator:

[0147]

[0148] In the formula, ωe ′ represents the objective weight of each evaluation index, |X e | represents the absolute value of the comprehensive information volume of each evaluation index,

[0149] The objective weight results of each evaluation index calculated are shown in Table 8.

[0150] Table 8

[0151]

[0152] S5. Weight the subjective weight and objective weight calculated in step S4 to construct a comprehensive evaluation model for the corrosion resistance performance of the clad steel bars. Specifically, use the non-unique importance method to weight the subjective weight and objective weight, and first calculate the comprehensive weight ω′ of each evaluation index e :

[0153]

[0154] The calculation results are shown in Table 9.

[0155] Table 9

[0156]

[0157] Then calculate the weighted weight ω″ of each evaluation index e :

[0158]

[0159] In the formula, v represents the vth evaluation index, and the calculation results are shown in Table 10.

[0160] Table 10

[0161]

[0162] Finally, according to the weighted weights of each evaluation index calculated, construct a comprehensive evaluation model for the corrosion resistance performance of the clad steel bars:

[0163] Q = 0.11×i corr + 0.10×E corr + 0.08×R a + 0.09×Z S + 0.16×A + 0.15×L h + 0.21×L K + 0.09×D K .

[0164] The above content is a further detailed description of the present invention in combination with specific preferred embodiments. It cannot be determined that the specific implementation of the present invention is only limited to these descriptions. For those of ordinary skill in the technical field to which the present invention pertains, without departing from the concept of the present invention, several simple deductions and substitutions can still be made, and all should be regarded as belonging to the protection scope of the present invention.

Claims

1. A comprehensive evaluation method for the corrosion resistance of clad steel bars, where the clad steel bars are composite steel bars with high-strength low-alloy steel as the base material and an austenitic stainless steel or duplex stainless steel clad layer; characterized in that, It includes the following steps: S1. Obtain a first clad steel bar specimen and a second clad steel bar specimen, where the length of the second clad steel bar specimen is greater than that of the first clad steel bar specimen; S2. Electrochemically corrode the first coated steel bar specimen, plot a polarization curve by using the electrode potential and electrode current obtained from the potentiodynamic polarization curve test, and calculate the self-corrosion potential i corr and the self-corrosion current density E corr of the first coated steel bar specimen, and use a 3D scanner and post-processing software to measure the surface roughness difference R a of the first coated steel bar specimen before and after the electrochemical corrosion treatment; Before the electrochemical corrosion treatment of the first clad steel bar specimen, it includes: covering putty (2) or Blu-Tack on one side wall of the first clad steel bar specimen (1), and connecting a wire (3) with an insulating outer skin at the center of the side wall opposite to the putty or Blu-Tack; placing the first clad steel bar specimen covered with putty or Blu-Tack and connected with the wire in the middle of a square mold (4) through a support column, pouring epoxy resin (5) into the square mold until the cross-section of the specimen is completely immersed, taking it out of the square mold after curing at room temperature, removing the support column and the putty or Blu-Tack, and filling the hole formed by the support column with hot melt adhesive to obtain a first clad steel bar specimen coated with epoxy resin; S3. Perform salt spray corrosion treatment on the second clad steel bar specimen, and calculate the weight loss rate Z of the second clad steel bar specimen s , count the number A of corrosion pits on the surface of the circumferential side wall of the second clad steel bar specimen, and use a three-dimensional scanner and post-processing software to detect the maximum corrosion width value D of the end face of the second clad steel bar specimen k , and use a metallographic microscope and post-processing software to detect the maximum depth value L of the corrosion pits on the surface of the circumferential side wall of the second clad steel bar specimen after corrosion treatment with a metallographic corrosion solution h and the maximum width value L of the corrosion pits k ; S4. Calculate the subjective weight and objective weight of the self-corrosion potential i corr , the self-corrosion current density E corr , the surface roughness difference R a , the weight loss rate Z s , the number of corrosion pits A on the circumferential sidewall surface, the maximum depth value L of the corrosion pits on the circumferential sidewall surface h , the maximum width value L of the corrosion pits on the circumferential sidewall surface k , and the maximum corrosion width value D of the end face k , and calculate the subjective weight and objective weight, wherein, the expert scoring method is used for subjective weight calculation, and the CRITIC method is used for objective weight calculation; and the steps of the objective weight calculation further include calculating the conflict coefficient C e of each evaluation index; during the objective weight calculation, experiments are included using clad steel bars with different diameters and materials; S5. Weight the subjective weight and objective weight calculated in step S4 to construct a comprehensive evaluation model for the corrosion resistance performance of the clad steel bar.

2. The comprehensive evaluation method for the corrosion resistance of the clad steel bars according to claim 1, characterized in that, The length of the first clad steel bar specimen is 10 - 25 mm, and the length of the second clad steel bar specimen is 300 - 800 mm, and step S2 includes: S2.

1. Place the first clad steel bar specimen under a 3D scanner, scan its surface profile, and measure its surface roughness R before electrochemical corrosion treatment using post-processing software y ; S2.

2. Connect the first clad steel bar specimen as the working electrode to the electrochemical workstation through a wire, connect the saturated calomel electrode as the reference electrode to the electrochemical workstation, and the saturated calomel electrode is connected with a salt bridge structure, and connect the platinum electrode as the auxiliary electrode to the electrochemical workstation; S2.

3. Inject electrolyte into the electrolytic cell to completely immerse the first clad steel bar specimen, the saturated calomel electrode, the salt bridge structure and the platinum electrode with the electrolyte, and adjust the distance between the tip of the salt bridge structure and the first clad steel bar specimen to a certain value; S2.

4. Start the potentiodynamic polarization curve test. Draw the polarization curve based on the electrode potential and electrode current obtained from the potentiodynamic polarization curve test, and then use the Tafel linear measurement method to calculate the self-corrosion potential i corr and the self-corrosion current density E corr ; S2.

5. Then, place the first clad reinforcing bar specimen under a 3D scanner to scan its surface profile, and use post-processing software to measure its surface roughness R after electrochemical corrosion treatment h ; S2.

6. Calculate the surface roughness difference R of the first layer of reinforcing bar specimens before and after electrochemical corrosion treatment a : R a = R y - R h 。 3. The comprehensive evaluation method for the corrosion resistance of clad steel bars according to claim 2, characterized in that, Step S3 includes: S3.

1. Grind and remove the scale on the surface of the second clad steel bar specimen, and weigh the second clad steel bar specimen after removing the scale to obtain its weight G1; S3.

2. Place the second clad steel bar specimen in a salt spray corrosion chamber for corrosion, remove rust after corrosion, and weigh the second clad steel bar specimen after removing rust to obtain its weight G2; S3.

3. Calculate the weight loss rate: Z s = (G1 - G2) / G1; S3.

4. Count the number A of corrosion pits on the circumferential side wall surface of the second clad steel bar specimen after derusting, and place the end face of the second clad steel bar specimen after derusting under a 3D scanner, and use post-processing software to detect the maximum corrosion width value D of the end face k ; S3.

5. Perform wire cutting on the corrosion pits on the circumferential side wall surface to obtain a corrosion pit cross-section specimen, polish the corrosion pit cross-section specimen, and then perform corrosion treatment with a metallographic corrosion solution; S3.

6. Place the cross-sectional specimen of the corrosion pit under a metallurgical microscope, and use post-processing software to detect the maximum depth value L and the maximum width value L of the corrosion pits in the cross-sectional specimen of the corrosion pit. h and the maximum width value L k .

4. The comprehensive evaluation method for the corrosion resistance of clad steel bars according to claim 3, characterized in that, In step S4, the expert scoring method is used to calculate the subjective weight, and specifically includes the following steps: S4.

1. Let n experts score each evaluation index on a ten-point scale, where the evaluation index is i corr 、E corr 、R a 、Z s 、A、L h 、L k and D k . The scores given by n experts for the above 8 evaluation indexes form an n×8 matrix, denoted as the scoring matrix. The rows in the scoring matrix represent the scores given by a certain expert for each evaluation index, and the columns in the scoring matrix represent the scores given by each expert for a certain evaluation index; S4.

2. Calculate the scoring correlation coefficient between each expert according to the scoring matrix to obtain a scoring correlation coefficient matrix; among them, the formula for calculating the scoring correlation coefficient between each expert is as follows: where e represents the e-th evaluation index, and a ie represents the score given by the i-th expert for the e-th evaluation index, and a je represents the score given by the j-th expert for the e-th evaluation index, n represents the total number of experts, i represents the i-th expert, j represents the j-th expert, and d ij represents the score correlation coefficient between the i-th expert and the j-th expert; S4.

3. Accumulate the correlation coefficients in each row of the scoring correlation coefficient matrix to obtain the K value of each expert: where n represents the total number of experts, j represents the j-th expert, and d ij represents the scoring correlation coefficient between the i-th expert and the j-th expert, and K i represents the K value of the i-th expert; Calculate the weight of each expert: where n represents the total number of experts, i represents the i-th expert, and |K i | represents the absolute value of the K value of the i-th expert, and U i represents the weight of the i-th expert; S4.

4. Multiply the weight of each expert by the corresponding score in the scoring matrix to obtain a weight matrix; S4.

5. Average each column of the weight matrix to obtain the comprehensive score value of each evaluation index: Wherein, n represents the total number of experts, i represents the i-th expert, e represents the e-th evaluation index, and U i represents the weight of the i-th expert, and a ie represents the score given by the i-th expert to the e-th evaluation index, and Y e represents the comprehensive score value of the e-th evaluation index; S4.

6. Calculate the subjective weight of each evaluation index: where ω e represents the subjective weight of the e-th evaluation index, and Y e represents the comprehensive score value of the e-th evaluation index, represents the sum of the comprehensive score values of all evaluation indexes.

5. The comprehensive evaluation method for the corrosion resistance of the clad steel bars according to claim 4, characterized in that, In step S4, the CRITIC method is used to calculate the objective weight, which specifically includes the following steps: S4.

7. Obtain N groups of first clad steel bar specimens and second clad steel bar specimens with different diameters and different materials, repeat the operations in steps S2 to S3, obtain N groups of test data on the above 8 evaluation indexes, and form an N×8 objective data matrix; according to the objective data matrix, calculate the standard deviation of each evaluation index: Where, σ e represents the standard deviation of the e-th evaluation index, N is the number of groups of data, and t re represents the value of the e-th evaluation index in the r-th group of data, and μ e represents the average value of the e-th evaluation index; Among them, μ e is calculated as follows: S4.

8. Calculate the objective correlation coefficient d between each evaluation index according to the calculation method of the formula in step S4.2 fe , where e represents the e-th evaluation index, f represents the f-th evaluation index, f, e = (1, 2,..., 8), and then calculate the conflict coefficient of each evaluation index: where C e represents the conflict coefficient of the e-th evaluation index, and d fe represents the objective correlation coefficient between the f-th evaluation index and the e-th evaluation index; S4.

9. Calculate the comprehensive information quantity X of each evaluation index based on the standard deviation σ of each evaluation index calculated in step S4.7 e and the conflict coefficient C of each evaluation index calculated in step S4.8 e , and calculate the comprehensive information quantity X of each evaluation index e : X e = σ e · C e , e = (1, 2, …… 8); Then, according to the comprehensive information amount of each evaluation index calculated, calculate the objective weight of each evaluation index: where ω e′ represents the objective weight of each evaluation index, and |X e | represents the absolute value of the comprehensive information quantity of each evaluation index.

6. The comprehensive evaluation method for the corrosion resistance of clad steel bars according to claim 5, characterized in that, In step S5, the subjective weight and the objective weight are weighted by the non-unique importance method, and the comprehensive weight ω′ of each evaluation index is calculated first. e : Then calculate the weighted weight ω″ of each evaluation index e : In the formula, v represents the vth evaluation index; Finally, according to the weighted weights of each evaluation index calculated, a comprehensive evaluation model for the corrosion resistance of the clad steel bars is constructed: Q = ω″1 × i corr + ω″2 × E corr + ω″3 × R a + ω″4 × Z s + ω″5 × A + ω″6 × L h + ω″7 × L k + ω″8 × D k .

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