Method and system for safety monitoring of a metal component

Abstract

The application relates to a metal component safety monitoring method and system, wherein the method comprises the following steps: establishing a mathematical correlation model among the Brinell hardness, yield strength and work hardening index of a metal material; detecting the Brinell hardness and work hardening index of a metal component manufactured based on the metal material, calculating the yield strength of the metal component through the mathematical correlation model; and determining whether the metal component meets the safety service requirement of a unit component according to the yield strength of the metal component. Through the application, the problem of how to accurately monitor the service safety of a metal component in actual production practice is solved, the influence of the Brinell hardness and work hardening index of the metal material on the yield strength is comprehensively considered, the mathematical correlation model is constructed, the yield strength of the metal component is accurately calculated based on the model, and whether the safety service requirement is met is judged.

Description

Technical Field

[0001] This application relates to the field of mechanical properties of metallic materials, and in particular to a method and system for safety monitoring of metallic components. Background Technology

[0002] In industrial production practice, the yield strength of metal structural materials during service must meet the component design requirements. If plastic deformation occurs during service, failure often results, leading to major accidents. Therefore, to ensure safe production, it is essential to monitor changes in the microstructure and properties of metal materials during service. However, considering the service life of the unit, destructive testing of metal materials during service is generally not possible; only non-destructive testing is permitted.

[0003] Currently, regularly testing the hardness of metal components is one of the important means of monitoring the service safety of metal structural materials. For example, for steel materials widely used in thermal power generating units, regulations stipulate that their hardness must be tested regularly to monitor changes in their microstructure and properties during service, thereby ensuring the safe operation of the generating unit. In actual production practice, in order to ensure the safe operation of thermal power generating units, it is necessary to regularly test the hardness of the unit's metal components and assess the service safety of the metal components based on the empirical relationship between hardness and the strength of the metal material.

[0004] Currently, no effective solution has been proposed for the problem of how to accurately monitor the service safety of metal components during actual production practices in related technologies. Summary of the Invention

[0005] This application provides a method and system for safety monitoring of metal components, which at least solves the problem in the related art of how to accurately monitor the service safety of metal components in actual production practice.

[0006] In a first aspect, embodiments of this application provide a safety monitoring method for metal components, the method comprising:

[0007] Establish a mathematical correlation model between Brinell hardness, yield strength, and work hardening index of metallic materials;

[0008] The Brinell hardness and work hardening index of the metal component manufactured based on the metal material are detected, and the yield strength of the metal component is calculated using the mathematical correlation model.

[0009] Based on the yield strength of the metal component, determine whether the metal component meets the requirements for safe service of unit components.

[0010] In some embodiments, establishing a mathematical correlation model between the Brinell hardness, yield strength, and work hardening index of metallic materials includes:

[0011] Establish a mathematical correlation model R p0.2 = (5.772 / n)*A - (0.00338 / n) 2 )*A 2 -1821.8, where R p0.2 is the yield strength of the metallic material, A is the Brinell hardness of the metallic material, and n is the work hardening index of the metallic material.

[0012] In some embodiments, the method further includes, prior to establishing a mathematical correlation model between the Brinell hardness, yield strength, and work hardening index of the metallic material:

[0013] According to GB / T 228-2002 standard, the metal material is cut to obtain tensile test specimens and hardness test specimens of the metal material;

[0014] Based on the tensile specimen and the hardness test specimen, the Brinell hardness, yield strength and work hardening index of the metallic material are determined.

[0015] In some embodiments, determining the Brinell hardness of the metallic material based on the tensile specimen and the hardness test specimen includes:

[0016] Based on the tensile specimen and the hardness test specimen, the Brinell hardness of the metallic material was determined by a standard hardness tester in accordance with GB / T 231.4-2009 standard.

[0017] In some embodiments, determining the yield strength of the metallic material based on the tensile specimen and the hardness test specimen includes:

[0018] Based on the tensile specimen and the hardness test specimen, the yield strength of the metallic material was determined in accordance with GB / T 228-2002 standard.

[0019] In some embodiments, determining the work hardening index of the metallic material based on the tensile specimen and the hardness test specimen includes:

[0020] Based on the tensile specimen and the hardness test specimen, the work hardening index of the metallic material is determined by a tensile testing machine and an extensometer in accordance with GB / T 16825.1 and GB / T 12160 standards.

[0021] In some embodiments, determining the Brinell hardness, yield strength, and work hardening index of the metallic material includes:

[0022] The Brinell hardness, yield strength, and work hardening index of the metal material were determined at room temperature.

[0023] In some embodiments, the metal material is steel.

[0024] In some embodiments, the steel material is P91 steel.

[0025] Secondly, embodiments of this application provide a safety monitoring system for metal components, the system including a model construction module, a detection calculation module, and a safety determination module;

[0026] The model building module is used to establish a mathematical correlation model between the Brinell hardness, yield strength and work hardening index of metallic materials.

[0027] The detection and calculation module is used to detect the Brinell hardness and work hardening index of the metal component made based on the metal material, and calculate the yield strength of the metal component through the mathematical correlation model.

[0028] The safety determination module is used to determine whether the metal component meets the safe service requirements of the unit components based on the yield strength of the metal component.

[0029] Compared to related technologies, this application provides a method and system for safety monitoring of metal components. The method establishes a mathematical correlation model between the Brinell hardness, yield strength, and work hardening index of a metal material; detects the Brinell hardness and work hardening index of a metal component manufactured based on the metal material; calculates the yield strength of the metal component using the mathematical correlation model; and determines whether the metal component meets the safe service requirements of the unit components based on its yield strength. This solves the problem of how to accurately monitor the service safety of metal components during actual production practice. It comprehensively considers the influence of the Brinell hardness and work hardening index of the metal material on the yield strength, realizes the construction of a mathematical correlation model, and accurately calculates the yield strength of the metal component based on this model to determine whether it meets the safe service requirements. Attached Figure Description

[0030] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments of this application and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0031] Figure 1 This is a flowchart of the steps of a safety monitoring method for metal components according to an embodiment of this application;

[0032] Figure 2 This is a schematic diagram of the mathematical correlation model according to the preferred embodiment of this application;

[0033] Figure 3This is a structural block diagram of a safety monitoring system for metal components according to an embodiment of this application;

[0034] Figure 4 This is a schematic diagram of the internal structure of an electronic device according to an embodiment of this application.

[0035] Figure descriptions: 31. Model construction module; 32. Detection calculation module; 33. Safety determination module. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of this application clearer, the application is described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. All other embodiments obtained by those skilled in the art based on the embodiments provided in this application without inventive effort are within the scope of protection of this application.

[0037] Obviously, the accompanying drawings described below are merely some examples or embodiments of this application. Those skilled in the art can apply this application to other similar scenarios based on these drawings without any inventive effort. Furthermore, it is understood that although the efforts made in this development process may be complex and lengthy, for those skilled in the art related to the content disclosed in this application, any changes to design, manufacturing, or production based on the technical content disclosed in this application are merely conventional technical means and should not be construed as insufficient disclosure of the content of this application.

[0038] In this application, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment that is mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0039] Unless otherwise defined, the technical or scientific terms used in this application shall have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms “a,” “an,” “an,” “the,” and similar words used in this application do not indicate quantity limitation and may indicate singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units not listed, or may include other steps or units inherent to these processes, methods, products, or devices. The terms “connected,” “linked,” “coupled,” and similar words used in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. “Multiple” used in this application refers to two or more. “And / or” describes the relationship between related objects, indicating that three relationships may exist; for example, “A and / or B” can represent: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following objects are in an "or" relationship. The terms "first," "second," and "third" used in this application are merely to distinguish similar objects and do not represent a specific ordering of the objects.

[0040] The JJF 1011-2006 standard defines hardness as a material's ability to resist one or more of the following: elastic deformation, plastic deformation, scratching, or cracking. This indicates that hardness itself is not a simple physical quantity; under certain conditions, hardness reflects a comprehensive performance index of a material's physical and mechanical properties, and it is related to many factors. There are many ways to determine the hardness of metallic materials, among which the Brinell hardness test is a commonly used method, especially for steel. The principle of the Brinell hardness test is to press a rigid indenter into the surface of the metal being tested with a certain test force, hold it for a specified time, and then unload the test force. The Brinell hardness value HB is then determined based on the ratio of the load to the indentation area. This shows that Brinell hardness reflects the material's resistance to plastic deformation.

[0041] However, to date, the correlation between the hardness and strength or other physical and mechanical properties of metallic materials remains unclear, and no empirical or mathematical relationship has been established between hardness and strength. In practical research and production, it is common to observe phenomena where the hardness of metallic materials remains constant, but their strength decreases significantly; that is, the hardness and strength of metallic materials do not perfectly satisfy a linear relationship. This poses a potential threat to the monitoring of the service safety of metallic components through regular hardness testing.

[0042] The inventors discovered that the work hardening index also reflects the ability of a metallic material to resist uniform plastic deformation, and that the yield strength is the critical stress at which a material undergoes plastic deformation. In other words, the Brinell hardness value of a metallic material is closely related to its work hardening index and yield strength. Therefore, this invention proposes a mathematical correlation model based on Brinell hardness, work hardening index, and yield strength, and uses this model to achieve safety monitoring of metal components in the unit.

[0043] This application provides a method for safety monitoring of metal components. Figure 1 This is a flowchart of the steps of a safety monitoring method for metal components according to an embodiment of this application, as follows: Figure 1 As shown, the method includes the following steps:

[0044] Step S102: Establish a mathematical correlation model between the Brinell hardness, yield strength, and work hardening index of metallic materials;

[0045] Specifically, step S102 involves establishing a mathematical correlation model R. p0.2 = (5.772 / n)*A - (0.00338 / n) 2 )*A 2 -1821.8, where R p0.2 is the yield strength of the metallic material, A is the Brinell hardness of the metallic material, and n is the work hardening index of the metallic material.

[0046] In addition, before performing step S102, the following steps are also included:

[0047] Step S11: Cut the metal material according to GB / T 228-2002 standard to obtain tensile test specimens and hardness test specimens of the metal material; preferably, the metal material is P91 steel.

[0048] Step S12: The hardness of the metal material is tested using a standard hardness tester. The hardness of the test samples is measured at room temperature according to the GB / T231.4-2009 standard. A total of 5 groups of samples are tested, and each group of samples is tested at least 3 times. The average value is taken to obtain the Brinell hardness of the metal material at room temperature.

[0049] Step S13: Perform room temperature tensile testing on the metallic material. The yield strength is determined at room temperature according to GB / T 228-2002 standard. At least 3 parallel specimens are tested for each group of samples. The average value is taken to obtain the yield strength of the metallic material at room temperature.

[0050] Step S14: Using a tensile testing machine that meets or exceeds Grade 1 of GB / T 16825.1 standard and an extensometer that meets or exceeds Grade 2 of GB / T 12160 standard, the work hardening index of the metallic material is calculated using the least squares method at room temperature.

[0051] From steps S11 to S14, it can be seen that the mathematical correlation model R constructed in step S102 is... p0.2 = (5.772 / n)*A - (0.00338 / n) 2 )*A 2 -1821.8, where R p0.2 The preferred values ​​are the room temperature yield strength of P91 steel, A is preferably the room temperature Brinell hardness of P91 steel, and n is preferably the room temperature work hardening index of P91 steel in the strain range of 0.2% to 3%.

[0052] Step S104: Detect the Brinell hardness and work hardening index of the metal component made of metal material, and calculate the yield strength of the metal component through a mathematical correlation model.

[0053] Step S106: Determine whether the metal component meets the safe service requirements of the unit components based on the yield strength of the metal component.

[0054] Steps S102 to S106 in the embodiments of this application solve the problem of how to accurately monitor the service safety of metal components in actual production practice. The influence of Brinell hardness and work hardening index of metal materials on yield strength is comprehensively considered, and a mathematical correlation model is constructed. Based on the model, the yield strength of metal components is accurately calculated to determine whether the safety service requirements are met.

[0055] It should be noted that the steps shown in the above process or in the flowchart of the accompanying figures can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0056] This application provides a safety monitoring method for metal components, and also includes several preferred embodiments.

[0057] In the preferred embodiment, P91 steel pipes that have been in service for a long time under supercritical conditions, provided by a power plant, are used to determine their Brinell hardness, yield strength, and n-value, and a correlation model is established. The specific implementation steps are as follows:

[0058] Material was cut from different locations on P91 steel pipes that had been in service at 540℃ for an extended period, and then tensile specimens were prepared. Three parallel specimens were used, and tensile tests were conducted at room temperature (25℃±3℃) using a SHIMAZU AG-X 100 electronic universal testing machine. The gauge length of the specimens was 50 mm, and the tensile rate was 1.6 min. -1 The tensile test was conducted according to GB / T228-2002 "Metallic materials, tensile test at room temperature". The yield strength, tensile strength and elongation of P91 steel pipe at different locations at room temperature were obtained.

[0059] The work hardening index n reflects the ability of a metallic material to resist uniform plastic deformation. Based on the least squares principle, the work hardening index n of the alloy sheet is calculated using equation (2) for different starting and ending strains:

[0060]

[0061] In the formula, n is the number of calculation strain points selected within the calculation strain range; ε i To calculate the instantaneous true strain corresponding to the strain point; σ i To calculate the instantaneous true stress corresponding to the strain point, according to the requirements of GB / T 5028-2008, the starting strain point for the n-value test is σ = 0.2%, and the ending strain value is σ = 3% within the plastic deformation. A portion of P91 steel pipe tensile specimens were selected for the determination of the n-value, and most of the n-values ​​were 0.26.

[0062] Similarly, Brinell hardness test specimens were cut from the same locations on P91 steel where tensile specimens were cut. The specimen surfaces were polished to a smooth finish. Hardness tests were conducted using an HBS300 digital Brinell hardness tester. The specimens were 15mm × 15mm × 5mm cubes. The test force was 1500kg, the indenter diameter was 10mm, and the test force holding time was 15s. Hardness was measured at room temperature (25℃ ± 3℃) according to the national standard GB / T 231.4-2009. Each group of specimens was tested at least 5 times, and the final average value was taken.

[0063] Table 1

[0064] 1 151 390 387 2.368807717 2 153 404 401 2.368807717 3 156 425 422 1.838477631 4 158 438 439 0.989949494 5 163 468 467 0.954594155 6 165 480 481 0.74246212 7 168 497 495 1.13137085 8 169 502 500 1.378858223 9 175 532 528 2.793071786 10 177 541 545 2.722361108 11 179 550 551 0.74246212 12 180 554 560 4.101219331 13 185 574 579 3.570889245 14 189 588 584 2.793071786 15 192 597 597 0.282842712 16 194 603 600 2.2627417 17 198 614 612 1.13137085 18 201 620 614 4.490128061

[0065] Table 1 shows examples of Brinell hardness and yield strength at different test points of P91 steel pipe in preferred embodiment one. In addition, except for test point 14, the work hardening index n value of P91 steel pipe in preferred embodiment one is 0.26.

[0066] Figure 2 This is a schematic diagram of the mathematical correlation model according to the preferred embodiment of this application, such as... Figure 2As shown, the measured Brinell hardness value and measured yield strength value of the preferred embodiment (Example 1) are fitted (e.g.) Figure 2 As shown), the mathematical correlation model (fitting curve of Equation 1) is obtained as R. p0.2 = (5.772 / n)*A - (0.00338 / n) 2 )*A 2 -1821.8.

[0067] When n = 0.26, the yield strength calculated by the mathematical correlation model is basically consistent with the measured yield strength, and the curve fitting determination coefficient R0 is high. 2 The yield strength value reached 0.988, indicating a very good fit between the yield strength value calculated by the mathematical correlation model and the measured value of the P91 steel pipe. However, the Brinell hardness at test point 14 was 190 HB, and the measured yield strength was 540 MPa. If the work hardening index n is taken as 0.26, the yield strength of the steel pipe calculated by the mathematical correlation model should be 588 MPa. The measured value is 48 MPa lower than the calculated value, indicating a phenomenon of high Brinell hardness but low yield strength. By measuring the n value of the P91 steel at test point 14, it was found to be 0.28. After substituting n = 0.28 and A = 190 HB into the mathematical correlation model, the calculated yield strength R... p0.2 =536MPa, which is close to the measured yield strength of 540MPa of the steel pipe at that location.

[0068] Analysis revealed that the higher Brinell hardness and lower yield strength at test point 14 in the preferred embodiment were due to an increase in the work hardening index (n) of the steel pipe. This also indicates that the Brinell hardness of P91 steel is related not only to yield strength but also to the n value. Therefore, relying solely on Brinell hardness values ​​to predict strength changes in service steel pipes can be risky, especially when changes in the microstructure during service alter the work hardening index (n). For P91 steel pipes used in thermal power units, if an anomaly exists between hardness and strength, a change in the work hardening index (n) should be considered. The mathematical correlation model R obtained above... p0.2 = (5.772 / n)*A - (0.00338 / n) 2 )*A 2 -1821.8 takes into account Brinell hardness, yield strength and work hardening index in a good way. That is, after the Brinell hardness and work hardening index of P91 steel are detected, the yield strength of P91 steel can be accurately calculated through mathematical correlation model, so as to determine whether it meets the requirements for safe service.

[0069] Preferred embodiments two to five utilize four sections of P91 steel pipes that have been in service for 89,000 hours, provided by a power plant. Before service, the P91 steel pipes underwent heat treatment at 1050℃ for 1 hour followed by normalizing, and then tempering at 760℃ for 4 hours. These pipes were then used in a domestically produced supercritical unit with an operating temperature of 560℃. The n-value of most of the four P91 steel pipe sections is 0.26. The yield strength, Brinell hardness, and n-value of the P91 steel pipes provided by the power plant after service were used to verify the mathematical correlation model in this invention. Tables 2 and 3 show the measured and calculated yield strength values ​​(obtained from the mathematical correlation model) at different locations corresponding to the Brinell hardness of two of the four P91 steel pipe sections provided by the plant, respectively. It can be seen that the difference between the measured and calculated yield strength values ​​of the P91 steel is very small, and the measured Brinell hardness, yield strength, and n-value of the four steel pipe sections all meet the requirements. Figure 2 The fitting curve of Equation 1 shows that the mathematical correlation model constructed in this invention can be used to monitor the four P91 steel pipes provided by the factory that have been in service for a long time.

[0070] Table 2

[0071]

[0072]

[0073] Table 3

[0074] 1 165 480 476 2.793071786 2 166 486 485 0.424264069 3 168 497 495 1.13137085 4 169 502 500 1.378858223 5 170 507 509 1.272792206 6 172 517 516 0.989949494 7 173 522 524 1.166726189 8 175 532 534 1.449568901 9 176 537 538 0.989949494 10 179 550 550 0.035355339 11 180 554 554 0.141421356 12 181 558 559 0.459619408 13 183 566 564 1.661700936 14 184 570 573 1.979898987 15 185 574 574 0.035355339 16 187 581 581 0.106066017 17 190 591 590 0.848528137 18 193 600 599 0.954594155

[0075] This application provides a safety monitoring system for metal components. Figure 3 This is a structural block diagram of a safety monitoring system for metal components according to an embodiment of this application, such as... Figure 3 As shown, the system includes a model construction module 31, a detection calculation module 32, and a security determination module 33;

[0076] Model building module 31 is used to establish a mathematical correlation model between the Brinell hardness, yield strength and work hardening index of metallic materials.

[0077] The detection and calculation module 32 is used to detect the Brinell hardness and work hardening index of metal components made of metal materials, and calculate the yield strength of the metal components through a mathematical correlation model.

[0078] The safety determination module 33 is used to determine whether the metal component meets the safe service requirements of the unit components based on the yield strength of the metal component.

[0079] The model construction module 31, detection calculation module 32, and safety judgment module 33 in this embodiment solve the problem of how to accurately monitor the service safety of metal components in actual production practice. They comprehensively consider the influence of Brinell hardness and work hardening index of metal materials on yield strength, realize the construction of a mathematical correlation model, and accurately calculate the yield strength of metal components based on the model to determine whether they meet the safety service requirements.

[0080] It should be noted that the above modules can be functional modules or program modules, and can be implemented through software or hardware. For modules implemented through hardware, the above modules can reside in the same processor; or the above modules can be located in different processors in any combination.

[0081] This embodiment also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

[0082] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0083] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementations, and will not be repeated here.

[0084] Furthermore, in conjunction with the safety monitoring method for metal components in the above embodiments, this application embodiment can provide a storage medium for implementation. This storage medium stores a computer program; when executed by a processor, the computer program implements any of the safety monitoring methods for metal components described in the above embodiments.

[0085] In one embodiment, a computer device is provided, which may be a terminal. The computer device includes a processor, memory, a network interface, a display screen, and an input device connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, it implements a method for safety monitoring of metal components. The display screen may be a liquid crystal display (LCD) or an e-ink display. The input device may be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.

[0086] In one embodiment, Figure 4 This is a schematic diagram of the internal structure of an electronic device according to an embodiment of this application, such as... Figure 4 As shown, an electronic device is provided, which can be a server, and its internal structure diagram can be as follows. Figure 4 As shown, the electronic device includes a processor, a network interface, internal memory, and non-volatile memory connected via an internal bus. The non-volatile memory stores an operating system, computer programs, and a database. The processor provides computing and control capabilities, the network interface communicates with external terminals via a network, the internal memory provides an environment for the operation of the operating system and computer programs, the computer programs are executed by the processor to implement a safety monitoring method for metal components, and the database stores data.

[0087] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the electronic device to which the present application is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0088] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0089] Those skilled in the art should understand that the technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments have been described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0090] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for safety monitoring of metal components, characterized in that, The method includes: Using P91 steel pipes supplied by the power plant that operate under supercritical conditions, and based on the principle of least squares, through... Calculate the work hardening index of P91 steel pipe corresponding to different calculation starting strain and calculation ending strain. n ,in, N The number of calculation strain points selected within the calculated strain range; ε i To calculate the instantaneous true strain corresponding to the strain point; σ i To calculate the instantaneous true stress corresponding to the strain point; According to the requirements of GB / T 5028-2008, n The starting strain point for the value test is σ =0.2%, the endpoint strain value is within the plastic deformation range. σ =3%, the work hardening index was determined. n It is 0.26; The Brinell hardness and yield strength of the P91 steel pipe were measured, and the work hardening index was determined. n With a value of 0.26, the measured Brinell hardness value and the measured yield strength value are fitted to obtain the mathematical correlation model R. p0.2 =(5.772 / n)*A-(0.00338 / n²)*A²-1821.8, where, R p0.2 is the yield strength of the metallic material, A is the Brinell hardness of the metallic material, and n is the work hardening index of the metallic material; The Brinell hardness and work hardening index of the metal component manufactured based on the metal material are detected, and the yield strength of the metal component is calculated using the mathematical correlation model. Based on the yield strength of the metal component, determine whether the metal component meets the requirements for safe service of unit components.

2. The method according to claim 1, characterized in that, Before establishing a mathematical correlation model between the Brinell hardness, yield strength, and work hardening index of metallic materials, the method further includes: According to GB / T 228-2002 standard, the metal material is cut to obtain tensile test specimens and hardness test specimens of the metal material; Based on the tensile specimen and the hardness test specimen, the Brinell hardness, yield strength and work hardening index of the metallic material are determined.

3. The method according to claim 2, characterized in that, The Brinell hardness of the metallic material was determined based on the tensile specimen and the hardness test specimen, including: Based on the tensile specimen and the hardness test specimen, the Brinell hardness of the metallic material was determined by a standard hardness tester in accordance with GB / T 231.4-2009 standard.

4. The method according to claim 2, characterized in that, The yield strength of the metallic material is determined based on the tensile specimen and the hardness test specimen, including: Based on the tensile specimen and the hardness test specimen, the yield strength of the metallic material was determined in accordance with GB / T 228-2002 standard.

5. The method according to claim 2, characterized in that, Based on the tensile specimen and the hardness test specimen, the work hardening index of the metallic material is determined as follows: Based on the tensile specimen and the hardness test specimen, the work hardening index of the metallic material is determined by a tensile testing machine and an extensometer in accordance with GB / T 16825.1 and GB / T 12160 standards.

6. The method according to claim 2, characterized in that, The Brinell hardness, yield strength, and work hardening index of the metal material were determined, including: The Brinell hardness, yield strength, and work hardening index of the metal material were determined at room temperature.

7. A safety monitoring system for metal components, characterized in that, The system is used to perform the method according to any one of claims 1 to 6, and the system includes a model construction module, a detection calculation module, and a security determination module; The model building module is used to establish a mathematical correlation model between the Brinell hardness, yield strength and work hardening index of metallic materials. The detection and calculation module is used to detect the Brinell hardness and work hardening index of the metal component made based on the metal material, and calculate the yield strength of the metal component through the mathematical correlation model. The safety determination module is used to determine whether the metal component meets the safe service requirements of the unit components based on the yield strength of the metal component.

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