Method for evaluating quality of 1000MPa-grade medium-thickness steel plate for water and electricity based on FAHP method

Abstract

The invention discloses a method for evaluating the quality of a 1000MPa-grade medium-thickness steel plate for water and electricity based on an FAHP method, belongs to the technical field of steel plate quality evaluation, and aims at solving the problems that in the prior art, a stable and objective quality evaluation method for a 1000MPa-grade water and electricity steel plate is lacked, is mostly limited to surface and size detection, and cannot be used for evaluating the quality of the 1000MPa-grade medium-thickness steel plate. And main indexes such as strength and low-temperature impact performance are difficult to comprehensively examine. According to the method, main factors of steel plate quality evaluation are determined, five hierarchical evaluation models based on FAHP are constructed, weight vectors are calculated, a bottom layer index membership function is set, data acquisition and discrete degree calculation are carried out, bottom layer index evaluation vectors are obtained, and finally hierarchical calculation is carried out according to the evaluation vectors and the weight vectors to obtain a final comment set. According to the method for evaluating the quality of the 1000MPa-grade medium-thickness steel plate, the requirement for evaluating the quality of 1000MPa-grade high-strength steel in water-power engineering can be met.

Description

Technical Field

[0001] The invention relates to a method for evaluating the quality of 1000MPa-grade medium-thick steel plates for hydropower based on a FAHP method, and belongs to the technical field of steel plate quality evaluation. Background Art

[0002] As my country continues to promote the adjustment of industrial structure and energy structure, it vigorously develops renewable energy. In the current renewable energy power, hydropower accounts for more than half. With the demand for high-head and large-capacity hydropower projects, the use of 1000MPa-grade medium-thick steel plates for key electromechanical equipment such as pressure steel pipes and steel bifurcated pipes has increased sharply, and the thickness of hydropower steel plates is generally in the range of 40-120mm. With the increase in strength level and thickness of steel plates, the construction process will be difficult, and quality accidents have occurred. The quality of the steel plate affects the operation of the entire hydropower station.

[0003] At present, there are many methods for testing the quality of steel plates, but most of them are aimed at testing and judging indicators such as steel plate surface quality and steel plate size. For 1000MPa hydropower steel plates, the main indicators such as strength and low-temperature impact performance are mainly assessed. How to evaluate its quality stably and objectively is particularly important. Therefore, there is an urgent need for an evaluation method that can be used for the quality of 1000MPa medium and thick steel plates to meet the quality assessment of 1000MPa high-strength steel in hydropower projects. Summary of the invention

[0004] The present invention proposes a method for evaluating the quality of 1000MPa medium and thick steel plates for hydropower based on the FAHP method. By determining chemical composition, grain size, mechanical properties and thickness as main evaluation factors, a five-layer evaluation model is established and the weight of indicators at each layer is calculated. Related indicator data at different thickness positions are collected and the membership is calculated. Finally, the evaluation result is obtained according to the maximum membership principle, thereby solving the problem that there is a lack of stable and objective quality evaluation method for 1000MPa hydropower steel plates in the prior art, which is mostly limited to surface and size detection and is difficult to conduct comprehensive assessment of main indicators such as strength and low-temperature impact performance.

[0005] A method for evaluating the quality of 1000MPa medium and thick steel plates for hydropower based on the FAHP method, the method for evaluating the quality of 1000MPa medium and thick steel plates for hydropower based on the FAHP method comprises the following steps:

[0006] S100. Determine the main factors for evaluating steel plate quality;

[0007] S200. Based on the main factors of steel plate quality evaluation, an evaluation model for medium and thick steel plate quality based on FAHP is established, and the weight vector between various indicators is calculated;

[0008] S300, setting the membership function between the underlying indicators;

[0009] S400, calculating the evaluation vector of the underlying indicator according to the calculation result of the discrete degree of the underlying indicator and combining the membership function;

[0010] S500, collecting data of the bottom-level indicators of each indicator and calculating the degree of dispersion;

[0011] S600, calculating the evaluation vector of the underlying indicator according to the calculation result of S500 and combining the membership function;

[0012] S700: Perform hierarchical calculation based on the evaluation vector and the weight vector to obtain a final comment set.

[0013] Furthermore, in S100, the main factors for evaluating the quality of steel plates are chemical composition, grain size, mechanical properties and thickness.

[0014] Furthermore, in S200, the following steps are included:

[0015] S210, constructing a five-level evaluation model, wherein the first level is the final comment set, which is divided into five levels: excellent, good, medium, poor, and bad, and the sum of the five levels is 1, which is used to analyze the final evaluation results according to the maximum membership principle;

[0016] S220, the second level includes chemical composition, grain size, mechanical properties, and thickness;

[0017] S230, the third level is a subset of the second level, where the chemical composition corresponds to important elements, other alloying elements and impurity elements, the grain size corresponds to the grain size grade and grain size stability, and the mechanical properties correspond to tensile, impact and 5% strain aging impact;

[0018] S240, the fourth level is the evaluation results of each element in each group corresponding to important elements, other alloy elements and impurity elements, the tensile strength, yield strength and elongation corresponding to the tensile properties, and the level corresponding to the impact properties;

[0019] S250, the fifth level is the mean content corresponding to each element and the degree of dispersion at different positions.

[0020] Furthermore, after S250, it also includes:

[0021] S260. Establish the corresponding priority relationship matrix of indicators at each level, calculate the priority relationship matrix using the additive consistency principle, construct a fuzzy consistency matrix, and calculate the weight vector between each indicator.

[0022] Furthermore, the weight vectors include weight vectors corresponding to composition, grain size, mechanical properties and thickness, weight vectors corresponding to important elements, alloy elements and impurity elements in the composition, weight vectors corresponding to C and Ni in the important elements, weight vectors corresponding to Si, Mn, Cr and Mo in the alloy elements, weight vectors corresponding to S, P, O, N and H in the impurity elements, weight vectors corresponding to the mean and deviation of grain size, weight vectors corresponding to tensile properties, impact properties and strain aging properties, weight vectors corresponding to tensile strength, yield strength and elongation in tensile properties, weight vectors corresponding to surface layer, 1 / 4 plate thickness and 1 / 2 plate thickness in impact properties, and weight vectors corresponding to the mean and variance in the underlying indicators.

[0023] Furthermore, in S400, the following steps are included:

[0024] S410, test the thickness of the steel plate and the composition, grain size, tensile strength, -60℃ impact, 5% strain aging -40℃ performance at the 1 / 4 plate thickness and 1 / 2 plate thickness positions, and determine the specific values ​​of each index;

[0025] S420. Calculate the mean and variance of C, Ni, S, P, O, N, and H at different thickness positions in the chemical composition of the steel plate, the maximum deviation and variance of Si, Mn, Cr, and Mo at different thickness positions, the mean and variance of tensile strength, yield strength, and elongation at different thickness positions, the mean and variance of impact properties at different thickness positions, and the mean and variance of strain aging properties at different thickness positions;

[0026] S430, calculating the underlying indicators according to the fuzzy membership function, and obtaining the evaluation set {ab cde} of the underlying indicators through the TS fuzzy model calculation.

[0027] Further, in S430, a to e represent specific numerical values ​​corresponding to excellent, good, medium, poor, and bad respectively obtained by calculation.

[0028] Furthermore, in S700, in the order from the fifth level to the first level, the evaluation set of the previous level is calculated according to the evaluation set of the bottom level and the weight vector of the previous level, and the evaluation result of the quality of the medium and thick steel plate is finally obtained by calculating layer by layer, and the final evaluation result is obtained according to the maximum membership principle.

[0029] A storage medium stores a computer program, which, when executed by a processor, implements the above-mentioned method for evaluating the quality of 1000MPa-grade medium-thick steel plates for hydropower based on the FAHP method.

[0030] A computer device comprises: a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-mentioned method for evaluating the quality of 1000MPa medium-thick steel plates for hydropower based on the FAHP method.

[0031] Beneficial effects of the present invention: The present invention provides a method for evaluating the quality of 1000MPa medium and thick steel plates for hydropower based on the FAHP method, which assesses the main indicators such as the strength and low-temperature impact performance of the 1000MPa hydropower steel plates, objectively evaluates their quality stability, and obtains an evaluation method that can be used for the quality of 1000MPa medium and thick steel plates, which meets the quality assessment of 1000MPa high-strength steel in hydropower projects. DETAILED DESCRIPTION

[0032] The present invention proposes an embodiment of a method for evaluating the quality of 1000MPa medium and thick steel plates for hydropower based on the FAHP method. The method for evaluating the quality of 1000MPa medium and thick steel plates for hydropower based on the FAHP method comprises the following steps:

[0033] S100. Determine the main factors for evaluating steel plate quality;

[0034] S200. Based on the main factors of steel plate quality evaluation, an evaluation model for medium and thick steel plate quality based on FAHP is established, and the weight vector between various indicators is calculated;

[0035] S300, setting the membership function between the underlying indicators;

[0036] S400, calculating the evaluation vector of the underlying indicator according to the calculation result of the discrete degree of the underlying indicator and combining the membership function;

[0037] S500, collecting data of the bottom-level indicators of each indicator and calculating the degree of dispersion;

[0038] S600, calculating the evaluation vector of the underlying indicator according to the calculation result of S500 and combining the membership function;

[0039] S700: Perform hierarchical calculation based on the evaluation vector and the weight vector to obtain a final comment set.

[0040] Specifically, the present invention lays a foundation for comprehensively evaluating the quality of steel plates by determining the main factors for evaluating the quality of steel plates; establishes an evaluation model based on FAHP and calculates a weight vector, which can scientifically and reasonably reflect the importance of each indicator and deal with the ambiguity and uncertainty in the evaluation process; sets a membership function to provide a quantitative standard for the evaluation of underlying indicators; performs data collection and discrete degree calculations as well as corresponding underlying indicator evaluation vector calculations to ensure the accuracy and objectivity of the evaluation basis; finally, hierarchical calculations are performed based on the evaluation vector and the weight vector to obtain a final comment set. The entire process comprehensively considers various factors, and can perform a comprehensive, stable and objective quality evaluation on key indicators such as the strength and low-temperature impact performance of 1000MPa-level medium and thick steel plates for hydropower, thereby meeting the quality evaluation requirements of hydropower projects for high-strength steel, helping to ensure the safe operation of hydropower stations, improving the quality control level of steel plates, and providing an effective method for steel plate material selection and quality control in related industries.

[0041] Furthermore, in S100, the main factors for evaluating the quality of steel plates are chemical composition, grain size, mechanical properties and thickness.

[0042] Specifically, this embodiment further clarifies that it is of great significance to use chemical composition, grain size, mechanical properties and thickness as the main factors for evaluating the quality of steel plates in S100. Chemical composition directly affects the basic properties of steel plates such as strength, toughness and corrosion resistance. Accurate consideration can ensure that the steel plates have suitable material properties; grain size plays a key role in mechanical properties. Appropriate grain size can optimize the strength and toughness combination of steel plates and ensure their reliability in use; mechanical properties are the core embodiment of steel plate quality. Comprehensive evaluation of tensile, impact and other properties can intuitively reflect their load-bearing and impact resistance under actual working conditions; thickness factors are not only related to the basic mechanical properties of steel plates, but also closely related to processing technology and specific usage scenarios. Comprehensive consideration of these main factors can accurately and comprehensively evaluate the quality of 1000MPa-level medium and thick steel plates from multiple dimensions, thereby providing reliable quality steel plates for hydropower projects, etc., and effectively avoiding safety hazards caused by steel plate quality problems.

[0043] Furthermore, in S200, the following steps are included:

[0044] S210, constructing a five-level evaluation model, wherein the first level is the final comment set, which is divided into five levels: excellent, good, medium, poor, and bad, and the sum of the five levels is 1, which is used to analyze the final evaluation results according to the maximum membership principle;

[0045] S220, the second level includes chemical composition, grain size, mechanical properties, and thickness;

[0046] S230, the third level is a subset of the second level, where the chemical composition corresponds to important elements, other alloying elements and impurity elements, the grain size corresponds to the grain size grade and grain size stability, and the mechanical properties correspond to tensile, impact and 5% strain aging impact;

[0047] S240, the fourth level is the evaluation results of each element in each group corresponding to important elements, other alloy elements and impurity elements, the tensile strength, yield strength and elongation corresponding to the tensile properties, and the level corresponding to the impact properties;

[0048] S250, the fifth level is the mean content corresponding to each element and the degree of dispersion at different positions.

[0049] Specifically, a five-level evaluation model is constructed. From the clear comment set of the first level and the analysis method of the final evaluation results based on the principle of maximum membership, it provides an intuitive and clear quantitative standard for the quality assessment of steel plates, which can accurately locate the quality grade of steel plates. The second level covers key aspects such as chemical composition, grain size, mechanical properties and thickness, ensuring the comprehensiveness of the evaluation factors and grasping the quality of steel plates from multiple key dimensions. The third level is further refined to clarify the correspondence between specific subsets of chemical composition, grain size and mechanical properties, which helps to deeply analyze the impact of the internal composition of each factor on quality. The fourth level sets specific evaluation results for each element and performance, realizing a more accurate microscopic analysis of the quality of steel plates. The fifth level focuses on the mean content and discreteness of elements, which can effectively reflect the stability and uniformity of steel plate quality. In summary, the evaluation model of the present invention is progressive and logically rigorous, and can conduct a comprehensive, in-depth, detailed and objective evaluation of the quality of 1000MPa-grade medium and thick steel plates for hydropower, providing a scientific, reliable and effective method for steel plate quality control, engineering material selection and ensuring the safe and stable operation of hydropower projects.

[0050] Furthermore, after S250, it also includes:

[0051] S260. Establish the corresponding priority relationship matrix of indicators at each level, calculate the priority relationship matrix using the additive consistency principle, construct a fuzzy consistency matrix, and calculate the weight vector between each indicator.

[0052] Specifically, the corresponding priority relationship matrix of indicators at each level is established, so that the relative importance of each indicator can be clearly presented, providing a basic framework for subsequent precise quantitative evaluation. The calculation based on the additive consistency principle effectively avoids the logical contradictions that may occur in the process of determining the importance of indicators, ensuring the rationality and scientificity of weight determination. By constructing a fuzzy consistency matrix, the fuzziness and uncertainty factors in the evaluation process are fully considered, so that the weight vectors between the calculated indicators are more in line with the actual situation, and more accurately reflect the true importance of each indicator in evaluating the quality of 1000MPa medium and thick steel plates for hydropower.

[0053] Furthermore, the weight vectors include weight vectors corresponding to composition, grain size, mechanical properties and thickness, weight vectors corresponding to important elements, alloy elements and impurity elements in the composition, weight vectors corresponding to C and Ni in the important elements, weight vectors corresponding to Si, Mn, Cr and Mo in the alloy elements, weight vectors corresponding to S, P, O, N and H in the impurity elements, weight vectors corresponding to the mean and deviation of grain size, weight vectors corresponding to tensile properties, impact properties and strain aging properties, weight vectors corresponding to tensile strength, yield strength and elongation in tensile properties, weight vectors corresponding to surface layer, 1 / 4 plate thickness and 1 / 2 plate thickness in impact properties, and weight vectors corresponding to the mean and variance in the underlying indicators.

[0054] Specifically, clarifying the weight vectors corresponding to composition, grain size, mechanical properties and thickness can accurately grasp the relative importance of each major factor in the evaluation of steel plate quality from a macro level, and provide a reasonable framework for comprehensive evaluation. Further subdividing the weight vectors corresponding to various elements in the composition, grain size related parameters, various aspects of mechanical properties, and the mean and variance of the underlying indicators, allows the evaluation of steel plate quality to go deep into the micro level and carefully consider the contribution of each element and performance indicator. For example, determining the weight vectors of important elements such as C and Ni can help to focus on the impact of key components on the performance of steel plates; understanding the weight vectors of impact properties at different thickness positions can more accurately evaluate the impact resistance of steel plates at different locations.

[0055] Furthermore, in S400, the following steps are included:

[0056] S410, test the thickness of the steel plate and the composition, grain size, tensile strength, -60℃ impact, 5% strain aging -40℃ performance at the 1 / 4 plate thickness and 1 / 2 plate thickness positions, and determine the specific values ​​of each index;

[0057] S420. Calculate the mean and variance of C, Ni, S, P, O, N, and H at different thickness positions in the chemical composition of the steel plate, the maximum deviation and variance of Si, Mn, Cr, and Mo at different thickness positions, the mean and variance of tensile strength, yield strength, and elongation at different thickness positions, the mean and variance of impact properties at different thickness positions, and the mean and variance of strain aging properties at different thickness positions;

[0058] S430, calculating the underlying indicators according to the fuzzy membership function, and obtaining the evaluation set {ab cde} of the underlying indicators through the TS fuzzy model calculation.

[0059] Specifically, by conducting comprehensive tests at multiple key locations and determining the specific values ​​of each indicator through S410, detailed performance data of steel plates at different locations can be obtained, truly reflecting the overall quality and internal differences of steel plates, and providing rich basic information for accurate evaluation. S420 calculates the mean and variance of various indicators at different thickness positions, further quantifies the data characteristics, and helps to deeply analyze the stability and uniformity of steel plate quality. For example, the mean variance of chemical composition elements can reflect their distribution law, and the mean variance of mechanical properties can reflect the overall performance level and degree of discreteness. Finally, S430 calculates the underlying indicator evaluation set based on the fuzzy membership function and TS fuzzy model, effectively dealing with the ambiguity and uncertainty of the data, and converting the underlying indicators into intuitive evaluation results, making the evaluation more practical and scientific, thereby providing an accurate basis for subsequent hierarchical calculations.

[0060] Further, in S430, a to e represent specific numerical values ​​corresponding to excellent, good, medium, poor, and bad respectively obtained by calculation.

[0061] Specifically, in S430, it is clarified that ae represents the specific values ​​corresponding to excellent, good, medium, poor and bad calculated respectively, which has a significant beneficial effect. This setting enables the evaluation results of the underlying indicators to be clearly quantified, converts the fuzzy quality evaluation into a specific numerical range, and enhances the accuracy and objectivity of the evaluation. On the one hand, it provides a standardized and comparable data basis for subsequent hierarchical calculations, facilitates comprehensive trade-offs and analysis between different indicators, and makes the entire evaluation process more logical and scientific. On the other hand, this presentation of specific values ​​is easy to understand and apply. Whether it is used by steel plate manufacturers for quality improvement or by users such as hydropower projects for material selection decisions, they can intuitively judge the quality level of steel plates in each underlying indicator based on these values, thereby accurately locating problems or advantages, taking targeted measures, and further improving the effectiveness of steel plate quality control, ensuring the safety and reliability of steel plate use in application scenarios such as hydropower projects, and effectively promoting the high-quality development of related industries.

[0062] Furthermore, in S700, in the order from the fifth level to the first level, the evaluation set of the previous level is calculated according to the evaluation set of the bottom level and the weight vector of the previous level, and the evaluation result of the quality of the medium and thick steel plate is finally obtained by calculating layer by layer, and the final evaluation result is obtained according to the maximum membership principle.

[0063] Specifically, the hierarchical calculation is carried out in the order from the fifth level to the first level, which can make full use of the logical relationship between the indicators at each level, systematically integrate the detailed evaluation information of the bottom layer with the weight distribution of the upper layer, so that the evaluation results are gradually summarized from the bottom layer indicators at the micro level to the macro overall quality evaluation of the steel plate. This progressive calculation method ensures the comprehensiveness and accuracy of the evaluation and avoids information omission or one-sided evaluation. By accurately calculating the bottom layer evaluation set and the weight vector to obtain the upper layer evaluation set, the gradual abstraction and comprehensive quantification of the complex steel plate quality evaluation is realized. The evaluation results finally obtained based on the maximum membership principle are concise and intuitive, with clear decision-making direction. Whether it is used by steel plate production enterprises for quality grading and product improvement, or used for material selection and quality acceptance in application fields such as hydropower engineering, the quality grade of steel plates can be clearly determined based on this, which effectively improves decision-making efficiency, ensures that the quality of steel plates meets engineering requirements, and promotes the standardization and normalization of steel plate production and application.

[0064] A storage medium stores a computer program, which, when executed by a processor, implements the above-mentioned method for evaluating the quality of 1000MPa-grade medium-thick steel plates for hydropower based on the FAHP method.

[0065] Specifically, the computer program stored on the storage medium implements a quality evaluation method for 1000MPa-grade medium and thick steel plates for hydropower based on the FAHP method. On the one hand, it makes the evaluation process more standardized and automated, reduces the subjectivity and errors of manual evaluation, and improves the accuracy and reliability of the evaluation. Through the efficient operation of the computer program, a large amount of steel plate quality data can be processed quickly, saving time and cost for manufacturers and users. On the other hand, this storage medium facilitates the storage and management of data, and historical evaluation data can be called up at any time for analysis and comparison, which helps to track the changing trend of steel plate quality and provide a strong basis for quality improvement. At the same time, the application of this method helps to improve the control level of the quality of medium and thick steel plates in fields such as hydropower engineering, ensure the safety and stability of the project, and promote technological progress and sustainable development in related industries.

[0066] A computer device comprises: a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-mentioned method for evaluating the quality of 1000MPa medium-thick steel plates for hydropower based on the FAHP method.

[0067] Specifically, the computer program is stored in the memory, and the processor executes the program to implement the FAHP method-based quality evaluation method for 1000MPa medium-thick steel plates for hydropower, making the evaluation process more efficient, accurate and objective. The computer equipment can quickly process a large amount of complex data, accurately calculate the weight vectors of indicators at each level, the evaluation vectors of the bottom-level indicators, etc., avoiding errors and deviations that may occur in manual calculations. At the same time, it can realize the automated operation of the evaluation method, improve the evaluation efficiency, and save manpower and time costs.

[0068] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0069] The above method is used to evaluate the quality of a 1000MPa grade medium and thick plate, as follows:

[0070] The composition, grain size, mechanical properties and thickness of the steel plate were measured. The thickness result was 120 mm. The other chemical composition test results are shown in Table 1, the grain size grade is shown in Table 2, and the mechanical property test results are shown in Table 3.

[0071]

[0072]

[0073] Table 1

[0074] Grain size grade Measured surface Level 7 Measured 1 / 4 plate thickness Level 7 Measured 1 / 2 plate thickness Level 7

[0075] Table 2

[0076]

[0077] Table 3

[0078] 1. The deviation values ​​of chemical elements, tensile properties, impact and strain aging results were calculated. The mean and variance are shown in Table 4-Table 7.

[0079] Table 4 shows the calculation results of composition data

[0080]

[0081] Table 4 and Table 5 are the calculation results of mechanical properties data

[0082]

[0083]

[0084] Table 5 and Table 6 are the calculation results of impact performance data

[0085] Measured surface Measured 1 / 4 plate thickness Measured 1 / 2 plate thickness Mean 92.3 110.3 130.0 variance 288.9％ 2422.2％ 1800.0％

[0086] Table 6 and Table 7 are the calculation results of strain aging performance

[0087] Mean 76.7 variance 911.1％

[0088] Table 7

[0089] 2. Based on the importance of each indicator, a priority relationship matrix is ​​established, as shown in Tables 8 to 17.

[0090] Table 8 is the priority relationship matrix of secondary indicators

[0091] Element Grain size Mechanical properties thickness Element 0.5 0.6 0.8 0.1 Grain size 0.4 0.5 0.6 0.1 Mechanical properties 0.2 0.4 0.5 0.1 thickness 0.9 0.9 0.9 0.5

[0092] Table 8 and Table 9 are the three-level indicator priority relationship matrices corresponding to the components

[0093] Important elements Alloying elements Impurity Elements Important elements 0.5 0.6 0.7 Alloying elements 0.4 0.5 0.6 Impurity Elements 0.3 0.4 0.5

[0094] Table 9 and Table 10 are the four-level indicator priority relationship matrices corresponding to important elements

[0095] element C Ni C 0.5 0.6 Ni 0.4 0.5

[0096] Table 10Table 11Four-level priority relationship matrix corresponding to alloy elements

[0097] element Si Mn Cr Mo Si 0.5 0.6 0.8 0.7 Mn 0.4 0.5 0.7 0.6 Cr 0.2 0.3 0.5 0.4 Mo 0.3 0.4 0.6 0.5

[0098] Table 11 and Table 12 are the four-level priority relationship matrices corresponding to impurity elements.

[0099] element S P O N H S 0.5 0.6 0.7 0.7 0.7 P 0.4 0.5 0.7 0.7 0.7 O 0.3 0.3 0.5 0.4 0.6 N 0.3 0.3 0.4 0.5 0.6 H 0.3 0.3 0.4 0.4 0.5

[0100] Table 12 and Table 13 are the three-level priority relationship matrices corresponding to grain size

[0101] Mean grain size Grain size deviation Mean grain size 0.5 0.6 Grain size deviation 0.4 0.5

[0102] Table 13 and Table 14 are the three-level priority relationship matrices corresponding to the mechanical properties

[0103] index Tensile properties Impact performance Strain aging performance Tensile properties 0.5 0.6 0.7 Impact performance 0.4 0.5 0.6 Strain aging performance 0.3 0.4 0.5

[0104] Table 14 and Table 15 are the four-level priority relationship matrices corresponding to tensile properties.

[0105] index tensile strength Yield Strength Elongation tensile strength 0.5 0.6 0.7 Yield Strength 0.4 0.5 0.6 Elongation 0.3 0.4 0.5

[0106] Table 15 and Table 16 are the four-level priority relationship matrices corresponding to impact performance

[0107] Location surface layer 1 / 4 1 / 2 surface layer 0.5 0.9 0.7 1 / 4 0.1 0.5 0.4 1 / 2 0.3 0.6 0.5

[0108] Table 16 and Table 17 are the five-level priority relationship matrices corresponding to the underlying indicators and tensile impact properties of different indicators

[0109] Mean variance Mean 0.5 0.6 variance 0.4 0.5

[0110] Table 17

[0111] 3. According to the set priority relationship matrix, the fuzzy consistency matrix is ​​constructed through the additive consistency principle, and its weight vector is calculated. The final weight vector is as follows:

[0112] Weight vectors corresponding to composition, grain size, mechanical properties, and thickness: [0.250 0.317 0.383 0.050];

[0113] The weight vectors corresponding to important elements, alloy elements, and impurity elements in the composition: [0.2330.3330.434];

[0114] The weight vectors corresponding to C and Ni among the important elements are: [0.450.55];

[0115] The weight vectors corresponding to Si, Mn, Cr, and Mo in the alloy elements are: [0.1500.2170.3500.283];

[0116] The weight vector corresponding to S, P, O, N, and H in the magazine elements: [0.1300.1500.2200.2200.260];

[0117] Weight vector corresponding to the mean and deviation of grain size: [0.450.55];

[0118] Weight vectors corresponding to tensile properties, impact properties, and strain aging properties: [0.2330.3330.433];

[0119] The weight vectors corresponding to tensile strength, yield strength and elongation in tensile properties: [0.2330.3330.433];

[0120] The weight vectors corresponding to the surface layer, 1 / 4 plate thickness, and 1 / 2 plate thickness in impact performance are: [0.1330.5000.367];

[0121] The weight vector corresponding to the mean and variance in the underlying indicator: [0.4500.550].

[0122] 4. The membership function is calculated using the TS model, where the underlying indicators of the horizontal axis are set according to demand.

[0123] 5. The bottom layer evaluation results are calculated based on the fuzzy membership function. The thickness evaluation result is [00.40.600]. The composition, grain size, tensile, impact and strain performance evaluation results are shown in Tables 18-22.

[0124] Table 18 shows the evaluation results of each element

[0125]

[0126]

[0127] Table 18 and Table 19 are the grain size evaluation results

[0128]

[0129] Table 19 and Table 20 are the tensile performance evaluation results.

[0130]

[0131] Table 20 and Table 21 are the impact performance evaluation results

[0132]

[0133] Table 21 and Table 22 are the strain performance evaluation results

[0134]

[0135] Table 22

[0136] 6. Calculate the indicators at each level. The weight vectors of the bottom-level indicators and the upper-level indicators are multiplied to obtain the comment set vector of the upper-level indicators. The data obtained by calculating layer by layer are shown in Tables 23 to 33.

[0137] Table 23 shows the strain aging performance evaluation results

[0138] excellent good middle inferior Difference Evaluation results 0.000 0.552 0.448 0.000 0.000

[0139] Table 23 and Table 24 are the impact performance evaluation results.

[0140] excellent good middle inferior Difference surface layer 0.441 0.559 0.000 0.000 0.000 1 / 4 0.450 0.000 0.000 0.425 0.125 1 / 2 0.450 0.000 0.330 0.220 0.000

[0141] Table 24 and Table 25 are the results of mechanical property evaluation.

[0142] excellent good middle inferior Difference tensile strength 0.125 0.425 0.000 0.113 0.338 Yield Strength 0.000 0.564 0.436 0.000 0.000 Elongation 0.971 0.029 0.000 0.000 0.000

[0143] Table 25 and Table 26 are the grain size evaluation results

[0144] excellent good middle inferior Difference Grain size 1.000 0.000 0.000 0.000 0.000

[0145] Table 26 and Table 27 show the element evaluation results.

[0146]

[0147]

[0148] Table 27 and Table 28 show the evaluation results of important elements, alloy elements and impurity elements

[0149] excellent good middle inferior Difference Important elements 0.000 0.275 0.516 0.208 0.000 Alloying elements 0.344 0.611 0.045 0.000 0.000 Impurity Elements 0.554 0.225 0.191 0.011 0.000

[0150] Table 28 and Table 29 are the results of chemical composition evaluation.

[0151] excellent good middle inferior Difference chemical composition 0.355 0.365 0.218 0.053 0.000

[0152] Table 29 and Table 30 show the overall impact evaluation results

[0153] excellent good middle inferior Difference chemical composition 0.449 0.075 0.121 0.293 0.063

[0154] Table 30 and Table 31 are the overall evaluation results of tensile strength

[0155] excellent good middle inferior Difference chemical composition 0.450 0.300 0.145 0.026 0.079

[0156] Table 31 and Table 32 are the results of mechanical property evaluation.

[0157] excellent good middle inferior Difference chemical composition 0.255 0.334 0.268 0.104 0.039

[0158] Table 32 and Table 33 show the final evaluation results.

[0159] excellent good middle inferior Difference chemical composition 0.553 0.217 0.169 0.046 0.012

[0160] Table 33

[0161] 7. Final evaluation

[0162] The final evaluation results of the quality of medium and thick steel plates were obtained through calculation, as shown in Table 33. The corresponding values ​​of excellent, good, medium, poor and bad are 0.553, 0.217, 0.169, 0.046 and 0.012 respectively. According to the principle of maximum membership, it is judged to be excellent, and its proportion is above 0.5.

[0163] The present invention discloses a quality evaluation method for 1000MPa medium and thick steel plates for hydropower based on the FAHP method. First, by determining chemical composition, grain size, mechanical properties and thickness as the main evaluation factors, the key aspects affecting the quality of the steel plates are comprehensively covered. A five-level evaluation model is constructed, from a clear set of comments to a detailed index stratification, so that the evaluation system is logically rigorous and hierarchical, and can deeply analyze the quality of the steel plates. The weight vectors of the indicators at each level are calculated to accurately reflect the importance of each indicator in the quality evaluation, while taking into account fuzziness and uncertainty, so that the evaluation results are more in line with reality. The membership function is set for the underlying indicators and data is collected and calculated to ensure the accuracy and objectivity of the evaluation basis. The hierarchical calculations are performed in a specific order and the evaluation results are obtained based on the maximum membership principle, which provides a clear quantitative standard for the quality of the steel plates. In addition, the application of storage media and computer equipment has realized the automation and standardization of the evaluation process, improved the evaluation efficiency and accuracy, facilitated data management and historical analysis, and provided a powerful quality control method for users such as steel plate manufacturers and hydropower projects, ensuring the safe and stable operation of the project and promoting technological progress and sustainable development in related industries.

[0164] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variation thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. .

[0165] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating the quality of 1000MPa medium and thick steel plates for hydropower based on the FAHP method, characterized in that: The method for evaluating the quality of 1000MPa medium and thick steel plates for hydropower based on the FAHP method comprises the following steps: S100. Determine the main factors for evaluating steel plate quality; S200, based on the main factors of steel plate quality evaluation, establish a FAHP-based evaluation model for medium and thick steel plate quality, and calculate the weight vector between various indicators; S300, setting the membership function between the underlying indicators; S400, calculating the evaluation vector of the underlying indicator according to the calculation result of the discrete degree of the underlying indicator and combining the membership function; S500, collecting data of the bottom-level indicators of each indicator and calculating the degree of dispersion; S600, calculating the evaluation vector of the underlying indicator according to the calculation result of S500 and combining the membership function; S700: Perform hierarchical calculation according to the evaluation vector and the weight vector to obtain a final comment set.

2. The method for evaluating the quality of 1000MPa medium and thick steel plates for hydropower based on the FAHP method according to claim 1, characterized in that: In S100, the main factors for evaluating the quality of the steel plate are chemical composition, grain size, mechanical properties and thickness.

3. The method for evaluating the quality of 1000MPa medium and thick steel plates for hydropower based on the FAHP method according to claim 2, characterized in that: In S200, the following steps are included: S210, constructing a five-level evaluation model, wherein the first level is the final comment set, which is divided into five levels: excellent, good, medium, poor, and bad, and the sum of the five levels is 1, which is used to analyze the final evaluation results according to the maximum membership principle; S220, the second level includes chemical composition, grain size, mechanical properties, and thickness; S230, the third level is a subset of the second level, where the chemical composition corresponds to important elements, other alloying elements and impurity elements, the grain size corresponds to the grain size grade and grain size stability, and the mechanical properties correspond to tensile, impact and 5% strain aging impact; S240, the fourth level is the evaluation results of each element in each group corresponding to important elements, other alloy elements and impurity elements, the tensile strength, yield strength and elongation corresponding to the tensile properties, and the level corresponding to the impact properties; S250, the fifth level is the mean content corresponding to each element and the degree of dispersion at different positions.

4. The method for evaluating the quality of 1000MPa medium and thick steel plates for hydropower based on the FAHP method according to claim 3 is characterized in that: After S250, it also includes: S260. Establish the corresponding priority relationship matrix of indicators at each level, calculate the priority relationship matrix using the additive consistency principle, construct a fuzzy consistency matrix, and calculate the weight vector between each indicator.

5. The method for evaluating the quality of 1000MPa medium and thick steel plates for hydropower based on the FAHP method according to claim 4, characterized in that: The weight vectors include weight vectors corresponding to composition, grain size, mechanical properties and thickness, weight vectors corresponding to important elements, alloy elements and impurity elements in the composition, weight vectors corresponding to C and Ni in important elements, weight vectors corresponding to Si, Mn, Cr and Mo in alloy elements, weight vectors corresponding to S, P, O, N and H in impurity elements, weight vectors corresponding to the mean and deviation of grain size, weight vectors corresponding to tensile properties, impact properties and strain aging properties, weight vectors corresponding to tensile strength, yield strength and elongation in tensile properties, weight vectors corresponding to surface layer, 1 / 4 plate thickness and 1 / 2 plate thickness in impact properties, and weight vectors corresponding to the mean and variance in underlying indicators.

6. The method for evaluating the quality of 1000MPa medium and thick steel plates for hydropower based on the FAHP method according to claim 5, characterized in that: In S400, the following steps are included: S410, test the thickness of the steel plate and the composition, grain size, tensile strength, -60℃ impact, 5% strain aging -40℃ performance at the 1 / 4 plate thickness and 1 / 2 plate thickness positions, and determine the specific values ​​of each index; S420. Calculate the mean and variance of C, Ni, S, P, O, N, and H at different thickness positions in the chemical composition of the steel plate, the maximum deviation and variance of Si, Mn, Cr, and Mo at different thickness positions, the mean and variance of tensile strength, yield strength, and elongation at different thickness positions, the mean and variance of impact properties at different thickness positions, and the mean and variance of strain aging properties at different thickness positions; S430, calculating the underlying indicators according to the fuzzy membership function, and obtaining the evaluation set {ab cde} of the underlying indicators through the TS fuzzy model calculation.

7. The method for evaluating the quality of 1000MPa medium and thick steel plates for hydropower based on the FAHP method according to claim 6, characterized in that: In S430, a to e represent the calculated specific values ​​corresponding to excellent, good, medium, poor, and bad, respectively.

8. The method for evaluating the quality of 1000MPa medium and thick steel plates for hydropower based on the FAHP method according to claim 7, characterized in that: In S700, in the order from the fifth level to the first level, the evaluation set of the previous level is calculated according to the evaluation set of the bottom level and the weight vector of the previous level, and the evaluation result of the quality of the medium and thick steel plate is finally obtained by calculating layer by layer, and the final evaluation result is obtained according to the maximum membership principle.

9. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements the method for evaluating the quality of 1000MPa grade medium and thick steel plates for hydropower based on the FAHP method as described in any one of claims 1 to 8.

10. A computer device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement a method for evaluating the quality of 1000MPa grade medium and thick steel plates for hydropower based on the FAHP method as described in any one of claims 1 to 8.

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