A method and system for surface modification based gate valve wear resistance strengthening

Abstract

This invention relates to the field of metal material strengthening technology, specifically a method and system for enhancing the wear resistance of gate valves based on surface modification. The method includes: receiving a gate valve strengthening command; determining a target gate valve based on the command; identifying a set of target modification regions based on the target gate valve; performing surface pretreatment on multiple target modification regions within the target modification region set to obtain multiple pretreated modification regions; setting multiple powder mass ratios; constructing multiple laser cladding parameters; obtaining multiple cladding samples based on the laser cladding parameters and powder mass ratios; performing cladding performance testing on the multiple cladding samples to obtain multiple performance scores; determining a target cladding parameter combination based on the performance scores; and performing laser cladding on the multiple pretreated modification regions using the target cladding parameter combination to obtain a wear-resistant strengthened gate valve. This invention can improve the wear resistance of gate valves and extend their service life.

Description

Technical Field

[0001] This invention relates to the field of metal material strengthening technology, and in particular to a method and system for strengthening the wear resistance of gate valves based on surface modification. Background Technology

[0002] Gate valves are key fluid shut-off control components in the petroleum, chemical, water conservancy, and thermal power industries, and their application demands and strengths are increasing. By preparing multiple sets of cladding samples with different laser cladding parameters, the parameters were quantitatively evaluated from multiple dimensions such as microstructure uniformity, phase stability, and mechanical wear resistance, and a weighted comprehensive score was calculated to select the optimal cladding parameters for the preparation of high-performance wear-resistant and reinforced gate valves.

[0003] Currently, existing methods for strengthening the wear resistance of gate valves mainly employ welding and spraying reinforcement layers. While these processes are simple, they suffer from drawbacks such as weak coating adhesion, uneven microstructure, numerous internal pores and cracks, and poor phase stability. Furthermore, traditional processes cannot quantitatively evaluate the microstructure, phase structure, and mechanical wear resistance of the cladding layer. Process parameters rely on manual experience for adjustment, leading to strong subjectivity and poor repeatability, which cannot guarantee the performance consistency of large-scale gate valve products. Therefore, optimizing the wear resistance strengthening methods for gate valves is of great significance for improving their wear resistance and extending their service life. Summary of the Invention

[0004] This invention provides a method for enhancing the wear resistance of gate valves based on surface modification and a computer-readable storage medium. Its main purpose is to improve the wear resistance of gate valves and extend their service life.

[0005] To achieve the above objectives, the present invention provides a method for enhancing the wear resistance of gate valves based on surface modification, comprising: Receive a gate valve reinforcement command and determine the target gate valve based on the gate valve reinforcement command; The target modification region set is identified based on the target gate valve; Multiple target modification regions within the target modification region set are subjected to surface pretreatment to obtain multiple pretreated modification regions; Multiple powder mass ratios were set to construct multiple laser cladding parameters; Multiple cladding samples were obtained based on multiple laser cladding parameters and multiple powder mass ratios; Multiple cladding samples were tested for cladding performance, and multiple test performance scores were obtained. The target cladding parameter combination is determined based on multiple test performance scores; Laser cladding is performed on multiple pre-treated modified areas using the target cladding parameter combination to obtain a wear-resistant and reinforced gate valve.

[0006] Optionally, the surface pretreatment of multiple target modification regions within the target modification region set to obtain multiple pretreated modification regions includes: For each of the multiple target modification regions, perform the following operation: The target modified region is subjected to surface roughening treatment to obtain a roughened modified region; The roughened and modified area is degreased and cleaned to obtain the degreased and modified area; The de-oiled modified area is cleaned to remove the oxide layer, resulting in a purified modified area; The surface condition of the purified and modified area is detected to obtain a set of surface detection parameters, which includes surface residual oxygen content, surface roughness and surface cleanliness. The surface detection parameter set is compared with the preset surface detection threshold set to obtain the surface condition determination result, wherein the surface condition determination result includes qualified or unqualified. If the surface condition determination result is unqualified, the purified modified area is regarded as the roughened modified area, and the above steps of degreasing and cleaning the roughened modified area are returned until the surface condition determination result is qualified. If the surface condition determination result is qualified, then the purification and modification area is used as the pretreatment modification area; By summarizing the preprocessed modified regions, multiple preprocessed modified regions are obtained.

[0007] Optionally, the surface condition detection of the purified and modified area to obtain a surface detection parameter set includes: Three element detection points were selected based on the purification and modification area; Perform the following operation on each of the three element detection points: Elemental energy spectrum signals are acquired at element detection points to obtain elemental characteristic peak intensity data; The oxygen mass fraction is calculated based on the characteristic peak intensity data of the elements. By summing up the oxygen element mass fractions, three oxygen element mass fractions are obtained; The residual oxygen content on the surface was calculated using the mass fractions of three oxygen elements. Surface roughness parameters are obtained based on the purified and modified region; Images were acquired from the purified and modified area to obtain surface microscopic images; The surface microscopic image is preprocessed to obtain a preprocessed microscopic image; The preprocessed microscopic image is divided into pixels using a preset grayscale threshold to obtain multiple clean substrate areas and multiple contaminant areas; The clean pixel area and the contaminant pixel area are obtained based on multiple clean substrate areas and multiple contaminant areas. Surface cleanliness is calculated using the area of ​​clean pixels and the area of ​​contaminated pixels. By summarizing the surface residual oxygen content, the surface roughness parameters, and the surface cleanliness, a set of surface detection parameters is obtained.

[0008] Optionally, obtaining multiple cladding samples based on multiple laser cladding parameters and multiple powder mass ratios includes: To obtain iron-3 aluminum-based alloy powder and chromium carbide powder; For each of the multiple powder mass ratios, perform the following operation: Iron-aluminum alloy powder and chromium carbide powder were mixed according to the powder mass ratio to obtain the test cladding powder; By summing up the tested cladding powders, multiple test cladding powders were obtained; Multiple modified reaction systems were obtained based on multiple test cladding powders and multiple laser cladding parameters; Multiple laser cladding substrates were obtained based on multiple modified reaction systems, wherein each laser cladding substrate corresponds one-to-one with a modified reaction system. Multiple laser cladding substrates were clad using multiple modified reaction systems to obtain multiple cladding samples.

[0009] Optionally, the cladding performance testing of multiple cladding samples yields multiple test performance scores, including: For each of the multiple cladding samples, the following operation shall be performed: The cladding sample was cut and prepared to obtain a metallographic test sample; The metallographic sample is subjected to metallographic pretreatment to obtain the metallographic sample to be tested; Microscopic images of the metallographic sample to be tested are acquired using a pre-confirmed metallographic microscopic imaging device to obtain microstructure images; Tissue uniformity indices are obtained based on the microscopic tissue images; Phase analysis was performed on the cladding sample to obtain phase stability indicators; The mechanical properties of the cladding sample were tested to obtain a mechanical property score. The test performance score is calculated using the tissue uniformity index, the phase stability index, and the mechanical property score. By summing the test performance scores, multiple test performance scores are obtained.

[0010] Optionally, obtaining the tissue uniformity index based on the microscopic tissue image includes: The microscopic tissue image is preprocessed to obtain a preprocessed tissue image; The preprocessed tissue image is subjected to grain boundary segmentation to obtain multiple grain boundary regions; For each of the multiple grain boundary regions, perform the following operation: Obtain the grain pixel area of ​​the grain boundary region; The pixel area of ​​the die is converted into the actual die area using the pre-confirmed pixel ratio; The actual equivalent grain size is obtained by utilizing the actual grain area; By summing up the actual equivalent particle sizes, multiple actual equivalent particle sizes are obtained; The average particle size is calculated using multiple actual equivalent particle sizes; The standard deviation of particle size is calculated using the mean particle size and multiple actual equivalent particle sizes. Based on multiple pre-confirmed particle size intervals, multiple actual equivalent particle sizes are divided into particle size intervals to obtain multiple particle size distribution sets, wherein the particle size distribution sets correspond one-to-one with the particle size intervals. The total grain area is obtained based on multiple grain size distribution sets; For each of the multiple particle size distribution sets, perform the following operation: Obtain the interval grain area of ​​the grain size distribution set; The grain area ratio is calculated using the interval grain area and the total grain area; By summing up the aforementioned grain area percentages, multiple grain area percentages are obtained; Calculate the average area percentage using the area percentages of multiple grains; Calculate the standard deviation of area percentage using the area percentage of multiple grains; The area dispersion coefficient of the particle size range is calculated using the average area proportion and the standard deviation of the area proportion. The uniformity index of the microstructure is calculated using the mean particle size, standard deviation of particle size, and coefficient of variation of the area of ​​the particle size interval.

[0011] Optionally, the phase analysis of the cladding sample to obtain phase stability indicators includes: The cladding sample was pretreated to obtain a phase detection sample. Set the diffraction angle scanning range and angle step size; The phase detection sample is scanned using a pre-confirmed diffractometer according to the diffraction angle scanning range and angle step size to obtain the diffraction pattern; Baseline correction is performed on the diffraction pattern to obtain the corrected pattern; The corrected spectrum is smoothed and filtered to obtain the standard diffraction pattern; Multiple diffraction characteristic peaks were obtained using standard diffraction patterns; For each of the multiple diffraction characteristic peaks, perform the following operation: Obtain the characteristic peak features of the diffraction characteristic peaks, including peak position angle, peak height, and full width at half maximum (FWHM). By summarizing the aforementioned characteristic peak features, multiple characteristic peak features are obtained; Multiple characteristic peak features are compared with a pre-built phase database to obtain multiple matching phases, where each matching phase corresponds one-to-one with a characteristic peak feature. The total peak height is calculated using the peak heights of multiple characteristic peaks. For each of the multiple matching phases, perform the following operation: The relative proportion of the phase is calculated using the peak height and total peak height of the characteristic peaks corresponding to the matched phases; Grain size is calculated using peak angle and full width at half maximum (FWHM). Obtain the standard peak angles of the matching phases; Calculate peak position deviation using standard peak position angle and peak position angle; Calculate the measured lattice spacing using peak position deviation; Obtain the standard lattice spacing, and use the standard lattice spacing and the measured lattice spacing to calculate the degree of lattice distortion; By summarizing the relative proportions of the aforementioned phases, grain sizes, and lattice distortion degrees, multiple relative proportions of phases, multiple grain sizes, and multiple lattice distortion degrees are obtained. Phase stability indices are calculated using the relative proportions of multiple phases, multiple grain sizes, and multiple degrees of lattice distortion.

[0012] Optionally, the calculation of phase stability indices using multiple phase relative proportions, multiple grain sizes, and multiple lattice distortion degrees includes: The proportion of the hard reinforcing phase was determined by using the relative proportions of multiple phases. The average grain size is calculated using the relative proportions of multiple phases and multiple grain sizes. The average degree of lattice distortion is calculated using the relative proportions of multiple phases and the degree of lattice distortion of multiple phases. The phase stability index is calculated using the proportion of hard reinforcing phase, average grain size, and average lattice distortion. The formula for calculating the phase stability index is shown below:

[0013] in, Indicators of phase stability This indicates the preset hard phase weighting coefficient. Indicates the proportion of hard reinforcing phase. This represents the preset grain size deviation coefficient. Indicates the average grain size. This indicates the preset maximum average grain size. This represents the preset lattice distortion correction factor. Indicates the degree of average lattice distortion. Indicates the preset maximum degree of lattice distortion. This indicates taking the absolute value. It represents the square root.

[0014] Optionally, the mechanical property testing of the cladding sample to obtain a mechanical property score includes: Using cladding specimens to prepare mechanical testing specimens; The wear test parameters are obtained, including the radius of the grinding steel ring, the grinding wheel speed, the test time, and the test load. Friction and wear tests were performed on the mechanical test specimens using a pre-confirmed wear testing machine according to the wear test parameters to obtain the wear track width; The wear rate is calculated using the wear mark width, the radius of the grinding steel ring, the grinding wheel speed, the test time, and the test load. The formula for calculating the wear rate is as follows:

[0015] in, Indicates wear rate, Indicates the radius of the grinding steel ring. Indicates the width of the wear mark. Indicates the grinding wheel speed. Indicates the test time. Indicates that the test load is applied. This represents the preset value of pi. Represents the arcsine function; Mechanical performance scores are calculated using wear rate.

[0016] To achieve the above objectives, the present invention also provides a gate valve wear resistance enhancement system based on surface modification, comprising: The modified area confirmation module is used to receive the gate valve reinforcement command and determine the target gate valve according to the gate valve reinforcement command; The target modification region set is identified based on the target gate valve; The processing parameter setting module is used to perform surface pretreatment on multiple target modification regions in the target modification region set to obtain multiple pretreated modification regions; Multiple powder mass ratios were set to construct multiple laser cladding parameters; The target parameter confirmation module is used to obtain multiple cladding samples based on multiple laser cladding parameters and multiple powder mass ratios. Multiple cladding samples were tested for cladding performance, and multiple test performance scores were obtained. The target cladding parameter combination is determined based on multiple test performance scores; The gate valve wear-resistant strengthening module is used to perform laser cladding on multiple pre-treated modified areas using the target cladding parameter combination to obtain a wear-resistant strengthened gate valve.

[0017] To address the above problems, the present invention also provides an electronic device, the electronic device comprising: A memory that stores at least one instruction; and a processor that executes the instructions stored in the memory to implement the above-described method for enhancing the wear resistance of gate valves based on surface modification.

[0018] To address the aforementioned problems, the present invention also provides a computer-readable storage medium storing at least one instruction, which is executed by a processor in an electronic device to implement the aforementioned method for enhancing the wear resistance of gate valves based on surface modification.

[0019] To address the problems described in the background art, this invention receives a gate valve strengthening command, determines the target gate valve based on the command, and identifies a set of target modification regions based on the target gate valve. This invention, by using a command-based approach to precisely match the target gate valve and automatically delineate the modification regions, avoids the subjectivity and arbitrariness of manual region delineation, thus improving the accuracy, standardization, and automation of selecting modification regions on the gate valve surface. Furthermore, this invention pre-treats multiple target modification regions within the target modification region set to obtain multiple pre-treated modification regions. This standardized surface pre-treatment effectively removes surface oil, scale, and impurities from the target modification regions, resulting in a tighter bond between the subsequent laser cladding coating and the substrate. Simultaneously, it ensures consistent operating conditions across all modification regions, improving the uniformity of the cladding forming quality. Subsequently, this invention constructs multiple laser cladding parameters by setting multiple powder mass ratios. It is evident that by setting multiple sets of powder mass ratios and constructing multiple sets of laser cladding parameters, this invention can cover the performance range of different process combinations, providing sufficient sample support for subsequently selecting the optimal process scheme for wear-resistant strengthening of gate valves. Then, this invention obtains multiple cladding samples based on multiple laser cladding parameters and multiple powder mass ratios, and performs cladding performance testing on these samples, obtaining multiple test performance scores. It is evident that this invention, by preparing multiple sets of cladding samples with different process matching and conducting multi-dimensional performance testing and quantitative scoring, achieves quantifiable comparison and screening of cladding processes and powder ratios, overcoming the limitations of traditional experience-based selection, and providing objective data basis for selecting the strengthening scheme with the best overall performance. Furthermore, this invention determines the target cladding parameter combination based on multiple test performance scores, and uses this target cladding parameter combination to perform laser cladding on multiple pre-treated modified areas to obtain a wear-resistant and reinforced gate valve. It is evident that this invention, through quantitative test performance scoring to optimize the cladding parameter combination and using this optimal parameter for laser cladding processing, can ensure the stability and consistency of the microstructure, phase composition, and mechanical properties of the modified areas of the gate valve, significantly improving the overall wear resistance and service life of the gate valve. Therefore, this invention can improve the wear resistance of gate valves and extend their service life. Attached Figure Description

[0020] Figure 1 A schematic flowchart of a method for enhancing the wear resistance of a gate valve based on surface modification, provided in an embodiment of the present invention; Figure 2 A functional block diagram of a surface-modified gate valve wear resistance enhancement system provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of an electronic device for implementing the surface modification-based method for enhancing the wear resistance of gate valves, as provided in an embodiment of the present invention.

[0021] Explanation of reference numerals in the attached figures: 10. Electronic device; 11. Processor; 12. Memory; 13. Bus.

[0022] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0023] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0024] This application provides a method for enhancing the wear resistance of gate valves based on surface modification. The execution entity of this method includes, but is not limited to, at least one electronic device configured to execute the method provided in this application, such as a server or a terminal. In other words, the method can be executed by software or hardware installed on a terminal device or a server device, where the software may be a blockchain platform. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0025] Reference Figure 1 The diagram shown is a schematic flowchart of a method for enhancing the wear resistance of a gate valve based on surface modification, according to an embodiment of the present invention. In this embodiment, the method for enhancing the wear resistance of a gate valve based on surface modification includes:

[0026] S1. Receive the gate valve reinforcement command and determine the target gate valve according to the gate valve reinforcement command.

[0027] It should be explained that the gate valve strengthening command is issued by personnel who wish to enhance the wear resistance of the gate valve. The target gate valve is identified through the gate valve strengthening command and is the gate valve that requires wear resistance enhancement.

[0028] S2. Confirm the target modification region set based on the target gate valve.

[0029] It should be explained that the target modified region set includes the gate valve plate sealing surface, the valve seat contact surface, and the fluid scouring region. The valve plate sealing surface is the sealing contact area used to achieve a sealing fit during the opening and closing process of the gate valve. The valve plate sealing surface is located on both sides of the gate valve plate at the position where it contacts the valve seat sealing ring. During the opening and closing process of the gate valve, the valve plate sealing surface undergoes sliding friction contact with the surface of the valve seat sealing ring along the opening and closing direction of the gate valve. The valve seat contact surface is the sealing pressure-bearing area used to withstand the contact friction load when the gate valve is closed. The valve seat contact surface is located on the surface of the valve seat sealing ring inside the gate valve body. When the gate valve is closed, a sealing and pressing contact is formed between the valve plate sealing surface and the valve seat contact surface. The fluid scouring region is the flow channel erosion region used to withstand the erosion and wear during the flow of the fluid medium. The fluid scouring region is located at the valve port flow position inside the gate valve flow channel. During the high-speed flow of the fluid medium, the fluid scouring region is continuously subjected to fluid impact and particle erosion.

[0030] S3. Perform surface pretreatment on multiple target modification regions in the target modification region set to obtain multiple pretreated modification regions.

[0031] It should be explained that the surface pretreatment of multiple target modification regions within the target modification region set to obtain multiple pretreated modification regions includes: For each of the multiple target modification regions, perform the following operation: The target modified region is subjected to surface roughening treatment to obtain a roughened modified region; The roughened and modified area is degreased and cleaned to obtain the degreased and modified area; The de-oiled modified area is cleaned to remove the oxide layer, resulting in a purified modified area; The surface condition of the purified and modified area is detected to obtain a set of surface detection parameters, which includes surface residual oxygen content, surface roughness and surface cleanliness. The surface detection parameter set is compared with the preset surface detection threshold set to obtain the surface condition determination result, wherein the surface condition determination result includes qualified or unqualified. If the surface condition determination result is unqualified, the purified modified area is regarded as the roughened modified area, and the above steps of degreasing and cleaning the roughened modified area are returned until the surface condition determination result is qualified. If the surface condition determination result is qualified, then the purification and modification area is used as the pretreatment modification area; By summarizing the preprocessed modified regions, multiple preprocessed modified regions are obtained.

[0032] Furthermore, surface roughening refers to the process of roughening the surface of the target modified area using a sandblasting machine to remove surface deposits and improve surface bonding activity. The roughened modified area is the target modified area after surface roughening. Degreasing and cleaning is the process of removing oil and processing residues from the surface of the roughened modified area, with the aim of removing surface oil, cutting fluid, dust, and other organic contaminants. Optionally, ultrasonic cleaning is used as the degreasing and cleaning method. The degreasing modified area is the roughened modified area after degreasing and cleaning. Oxide layer removal cleaning refers to the process of removing the oxide layer from the surface of the degreasing modified area. Specifically, the degreasing modified area is immersed in a 5% (v / v) nitric acid solution at room temperature (25°C) for 30 minutes to remove the oxide film, rust layer, and metal oxide impurities from the surface of the degreasing modified area. The purified modified area is the degreasing modified area after oxide layer removal cleaning.

[0033] It should be explained that the surface detection parameter set refers to a set of multiple quantitative indicators obtained after surface condition detection of the purified and modified area. This set includes residual oxygen content, surface roughness, and surface cleanliness, used to characterize the surface cleanliness, oxidation degree, and microstructure of the purified and modified area. The surface detection threshold set is a set of critical parameters that meet the process quality requirements of laser cladding, including residual oxygen content threshold, surface roughness threshold, and surface cleanliness threshold. Specifically, the residual oxygen content threshold is 0.5 wt.%, the surface roughness threshold is 3.0 μm, and the surface cleanliness threshold is 98%, used as the criterion for determining whether the surface quality is acceptable. This surface detection threshold set was obtained through extensive historical experiments and will not be elaborated further here. The step of comparing the surface detection parameter set with a preset surface detection threshold set to obtain the surface condition judgment result refers to comparing the surface residual oxygen content, surface roughness, and surface cleanliness in the surface detection parameter set with the corresponding surface residual oxygen content threshold, surface roughness threshold, and surface cleanliness threshold in the surface detection threshold set one by one; if the surface residual oxygen content, surface roughness, and surface cleanliness are all less than or equal to the corresponding surface residual oxygen content threshold, surface roughness threshold, and surface cleanliness threshold, the surface condition is judged to be qualified; if any parameter is greater than the corresponding threshold, the surface condition is judged to be unqualified.

[0034] Understandably, the surface condition assessment result refers to the conclusion made on the quality of the cleaned and modified area surface after comparing the surface residual oxygen content, surface roughness, and surface cleanliness with the surface detection threshold set. It includes two categories: qualified and unqualified. A qualified surface condition assessment result means that the surface residual oxygen content, surface roughness, and surface cleanliness of the cleaned and modified area all meet the process requirements of laser cladding. A unqualified surface condition assessment result means that at least one of the surface residual oxygen content, surface roughness, and surface cleanliness of the cleaned and modified area exceeds the corresponding threshold, and the surface has oxidation, oil residue, or abnormal roughness, failing to meet the process requirements of laser cladding. The pre-treated modified area refers to the target modified area that, after surface pretreatment, meets the process standards for laser cladding and is ready for laser cladding.

[0035] It should be explained that the surface state detection of the purified and modified area to obtain a set of surface detection parameters includes: Three element detection points were selected based on the purification and modification area; Perform the following operation on each of the three element detection points: Elemental energy spectrum signals are acquired at element detection points to obtain elemental characteristic peak intensity data; The oxygen mass fraction is calculated based on the characteristic peak intensity data of the elements. By summing up the oxygen element mass fractions, three oxygen element mass fractions are obtained; The residual oxygen content on the surface was calculated using the mass fractions of three oxygen elements. Surface roughness parameters are obtained based on the purified and modified region; Images were acquired from the purified and modified area to obtain surface microscopic images; The surface microscopic image is preprocessed to obtain a preprocessed microscopic image; The preprocessed microscopic image is divided into pixels using a preset grayscale threshold to obtain multiple clean substrate areas and multiple contaminant areas; The clean pixel area and the contaminant pixel area are obtained based on multiple clean substrate areas and multiple contaminant areas. Surface cleanliness is calculated using the area of ​​clean pixels and the area of ​​contaminated pixels. By summarizing the surface residual oxygen content, the surface roughness parameters, and the surface cleanliness, a set of surface detection parameters is obtained.

[0036] Furthermore, the selection of three element detection points based on the purification and modification area refers to randomly selecting three locations within the purification and modification area as element detection points, ensuring comprehensive coverage, random distribution, and avoiding edge effects. These element detection points are randomly selected locations within the purification and modification area for subsequent elemental energy spectrum signal acquisition. Elemental energy spectrum signal acquisition utilizes an X-ray photoelectron spectroscopy (XPS) analyzer to excite surface elements and acquire corresponding characteristic energy spectrum signals at each element detection point. The elemental characteristic peak intensity data is the quantified data of the peak areas of target elements such as oxygen, iron, carbon, and chromium in the elemental energy spectrum signal, used to calculate the relative content of each element. This elemental characteristic peak intensity data can be obtained through an X-ray photoelectron spectroscopy analyzer and will not be elaborated further here. The oxygen element mass fraction is the percentage of the characteristic peak area of ​​oxygen at a single element detection point relative to the sum of the characteristic peak areas of all detected elements, used to characterize the relative content of surface oxygen at that element detection point. The surface residual oxygen content is obtained by summing the oxygen element mass fractions of the three element detection points and taking the arithmetic mean, used to characterize the overall degree of residual oxidation in the area.

[0037] Understandably, obtaining surface roughness parameters based on the purification and modification region refers to acquiring the surface micro-profile of the purification and modification region and outputting roughness values. Optionally, a roughness meter is used as the device for obtaining the surface roughness parameters. The surface roughness parameters are the roughness directly read and output by the roughness meter, used to characterize the degree of micro-roughness of the surface of the purification and modification region.

[0038] Furthermore, image acquisition involves using a microscopic imaging device to photograph and acquire images of the cleaned and modified area, obtaining images of the area's surface microstructure, oil stains, particulate impurities, and residual deposits. Optionally, a microscope camera is used as the image acquisition device. The surface microscopic image is an image obtained after image acquisition that can completely reflect the surface microstructure and impurity distribution characteristics of the cleaned and modified area. Preprocessing involves sequentially performing grayscale conversion and noise reduction filtering on the surface microscopic image to eliminate image noise and facilitate subsequent pixel segmentation. The preprocessed microscopic image is the surface microscopic image after preprocessing. The grayscale threshold is a reference value used to determine the clean area and contaminated area of ​​the substrate, for example, 128. Pixel segmentation involves comparing the grayscale value of each pixel in the preprocessed microscopic image with the grayscale threshold one by one. Pixels with a grayscale value greater than 128 are determined to be clean areas of the substrate, and pixels with a grayscale value less than or equal to 128 are determined to be contaminated areas, thus dividing the preprocessed microscopic image into multiple clean areas of the substrate and multiple contaminated areas. The clean substrate area is a pixel area, after pixel division, where the grayscale value is greater than the grayscale threshold of 128, consistent with the normal brightness and darkness of the metal substrate, and free from oil stains, particulate impurities, and oxide residues. The contaminated area is a pixel area, after pixel division, where the grayscale value is less than or equal to the grayscale threshold of 128, differing from the normal brightness and darkness of the metal substrate, and containing residual oil stains, dust particles, metal debris, and oxide deposits. Obtaining the clean pixel area and contaminated pixel area based on multiple clean substrate areas and multiple contaminated areas refers to summing the number of pixels in all clean substrate areas to obtain the clean pixel area, and summing the number of pixels in all contaminated areas to obtain the contaminated pixel area.

[0039] Understandably, surface cleanliness is a parameter used to quantitatively characterize the degree of cleanliness of a purified and modified area's surface, free from impurities and oil residues. The formula for calculating surface cleanliness is as follows:

[0040] in, Indicates surface cleanliness. Indicates the clean pixel area. This indicates the area of ​​the contaminant pixel.

[0041] S4. Set multiple powder mass ratios to construct multiple laser cladding parameters.

[0042] It should be explained that setting multiple powder mass ratios refers to establishing multiple sets of different mass ratio schemes for the iron-aluminum-based alloy powder and chromium carbide powder, used for subsequent laser cladding parameter optimization. For example, among the multiple powder mass ratios, the first powder mass ratio is: 100% iron-aluminum-based alloy powder and 0% chromium carbide powder; the second powder mass ratio is: 80% iron-aluminum-based alloy powder and 20% chromium carbide powder; and the third powder mass ratio is: 60% iron-aluminum-based alloy powder and 40% chromium carbide powder. The powder mass ratio refers to the mass percentage relationship between the alloy powders participating in laser cladding (e.g., iron-aluminum-based alloy powder and chromium carbide powder). Constructing multiple laser cladding parameters means keeping other process parameters (scanning rate, powder feeding rate) constant, and only adjusting the laser power to set multiple sets of different laser power parameters, forming multiple sets of differentiated laser cladding process conditions. Laser cladding parameters refer to the power of the laser emitted during laser cladding, such as 1200W, 1500W, or 1800W.

[0043] S5. Multiple cladding samples were obtained based on multiple laser cladding parameters and multiple powder mass ratios.

[0044] It should be explained that obtaining multiple cladding samples based on multiple laser cladding parameters and multiple powder mass ratios includes: To obtain iron-3 aluminum-based alloy powder and chromium carbide powder; For each of the multiple powder mass ratios, perform the following operation: Iron-aluminum alloy powder and chromium carbide powder were mixed according to the powder mass ratio to obtain the test cladding powder; By summing up the tested cladding powders, multiple test cladding powders were obtained; Multiple modified reaction systems were obtained based on multiple test cladding powders and multiple laser cladding parameters; Multiple laser cladding substrates were obtained based on multiple modified reaction systems, wherein each laser cladding substrate corresponds one-to-one with a modified reaction system. Multiple laser cladding substrates were clad using multiple modified reaction systems to obtain multiple cladding samples.

[0045] Furthermore, the iron-aluminum-iron alloy powder is a powder of iron-aluminum-iron alloy, which possesses high-temperature resistance, wear resistance, and oxidation resistance, serving as the base material powder for laser cladding. Chromium carbide powder is a powder of chromium carbide, which possesses high hardness, high wear resistance, and corrosion resistance, serving as a reinforcing phase additive to improve the mechanical and wear resistance properties of the cladding layer. Powder preparation involves quantitatively weighing the corresponding mass of iron-aluminum-iron alloy powder and chromium carbide powder according to the powder mass ratio, mixing and stirring until uniform, to obtain a mixed powder. The test cladding powder is the alloy powder prepared according to the powder mass ratio after powder preparation, used for subsequent laser cladding. The phrase "obtaining multiple modified reaction systems based on multiple test cladding powders and multiple laser cladding parameters" refers to matching each test cladding powder with the laser cladding parameters corresponding to a single laser power, forming multiple sets of independent, one-to-one matching schemes. The modified reaction system is a process reaction system composed of test cladding powder and laser cladding parameters of a single laser power, used to limit the powder composition and laser process conditions for a single laser cladding. Obtaining multiple laser cladding substrates based on multiple modified reaction systems refers to configuring a separate substrate material to be clad for each modified reaction system, wherein the number of laser cladding substrates and modified reaction systems are equal and matched one-to-one.

[0046] Understandably, the laser cladding substrate is a substrate plate to be clad, made from the same metal substrate as the gate valve substrate, and undergoes surface pretreatment to serve as the substrate carrier for the laser cladding layer. The cladding process involves irradiating the surface of the laser cladding substrate with a laser beam under corresponding laser cladding parameters, causing the test cladding powder and the substrate surface to melt and solidify simultaneously, forming a metallurgically bonded cladding layer on the substrate surface. Optionally, laser cladding is used as the cladding process method. The cladding sample is the laser cladding substrate after the cladding process.

[0047] S6. Perform cladding performance testing on multiple cladding samples to obtain multiple test performance scores.

[0048] It should be explained that the cladding performance testing of multiple cladding samples yields multiple test performance scores, including: For each of the multiple cladding samples, the following operation shall be performed: The cladding sample was cut and prepared to obtain a metallographic test sample; The metallographic sample is subjected to metallographic pretreatment to obtain the metallographic sample to be tested; Microscopic images of the metallographic sample to be tested are acquired using a pre-confirmed metallographic microscopic imaging device to obtain microstructure images; Tissue uniformity indices are obtained based on the microscopic tissue images; Phase analysis was performed on the cladding sample to obtain phase stability indicators; The mechanical properties of the cladding sample were tested to obtain a mechanical property score. The test performance score is calculated using the tissue uniformity index, the phase stability index, and the mechanical property score. By summing the test performance scores, multiple test performance scores are obtained.

[0049] Furthermore, sample preparation involves cutting a small, well-shaped sample from the cross-section of the cladding layer of the cladding sample according to standard metallographic sample preparation size requirements (e.g., 12mm × 12mm × 15mm), obtaining a small sample with regular dimensions and a complete interface between the substrate and the cladding layer. Optionally, metallographic sample preparation can be used as the sample preparation method. The metallographic test sample is a sample whose dimensions meet the requirements for metallographic observation after sample preparation, and which includes both the substrate and the laser cladding layer structure. Metallographic pretreatment involves sequentially performing coarse grinding, fine grinding, polishing, and etching on the metallographic test sample to remove surface cutting marks, scratches, and oxide layers, with the aim of clearly revealing the internal microstructure. The metallographic sample to be tested is a metallographic test sample with a smooth surface, clear microstructure, and ready for direct microscopic observation after metallographic pretreatment. The metallographic microscopic imaging equipment is a metallographic microscope with high magnification and microscopic imaging capabilities, used to observe the microscopic morphology of grains, dendrites, pores, and cracks within the cladding layer. Optionally, a metallurgical microscope may be used as the metallurgical microscopic imaging device.

[0050] Understandably, microscopic image acquisition is the process of taking pictures of the cladding layer of the metallographic sample under test using metallographic microscopic imaging equipment, and acquiring clear images of its microscopic morphology. Microstructure images are microscopic morphological images acquired by metallographic microscopic imaging equipment that can intuitively reflect the grain size, dendrite morphology, porosity, and crack distribution characteristics of the cladding layer.

[0051] Furthermore, the test performance score is a weighted fusion calculation of the tissue uniformity index, phase stability index, and mechanical property score, wherein the calculation formula for the test performance score is as follows:

[0052] in, This indicates the test performance score. This represents the preset uniform weighting coefficient for the organization. This represents the preset phase stability weighting coefficient. This represents the preset mechanical wear resistance weighting coefficient. The microstructure uniformity weighting coefficient is a weighting parameter used to adjust the proportion of influence of microstructure uniformity on the test performance score, for example, 0.35. The phase stability weighting coefficient is a weighting parameter used to adjust the proportion of influence of crystalline phase structure stability on the test performance score, for example, 0.40. The mechanical wear resistance weighting coefficient is a weighting parameter used to adjust the proportion of influence of coating wear resistance mechanical properties on the overall performance of the sample, for example, 0.25. The microstructure uniformity weighting coefficient, phase stability weighting coefficient, and mechanical wear resistance weighting coefficient can be obtained through the analytic hierarchy process (AHP), and will not be elaborated further here.

[0053] It should be explained that obtaining the tissue uniformity index based on the microscopic tissue image includes: The microscopic tissue image is preprocessed to obtain a preprocessed tissue image; The preprocessed tissue image is subjected to grain boundary segmentation to obtain multiple grain boundary regions; For each of the multiple grain boundary regions, perform the following operation: Obtain the grain pixel area of ​​the grain boundary region; The pixel area of ​​the die is converted into the actual die area using the pre-confirmed pixel ratio; The actual equivalent grain size is obtained by utilizing the actual grain area; By summing up the actual equivalent particle sizes, multiple actual equivalent particle sizes are obtained; The average particle size is calculated using multiple actual equivalent particle sizes; The standard deviation of particle size is calculated using the mean particle size and multiple actual equivalent particle sizes. Based on multiple pre-confirmed particle size intervals, multiple actual equivalent particle sizes are divided into particle size intervals to obtain multiple particle size distribution sets, wherein the particle size distribution sets correspond one-to-one with the particle size intervals. The total grain area is obtained based on multiple grain size distribution sets; For each of the multiple particle size distribution sets, perform the following operation: Obtain the interval grain area of ​​the grain size distribution set; The grain area ratio is calculated using the interval grain area and the total grain area; By summing up the aforementioned grain area percentages, multiple grain area percentages are obtained; Calculate the average area percentage using the area percentages of multiple grains; Calculate the standard deviation of area percentage using the area percentage of multiple grains; The area dispersion coefficient of the particle size range is calculated using the average area proportion and the standard deviation of the area proportion. The uniformity index of the microstructure is calculated using the mean particle size, standard deviation of particle size, and coefficient of variation of the area of ​​the particle size interval.

[0054] Furthermore, the preprocessed tissue image is a microscopic tissue image after preprocessing. Grain boundary segmentation is an image processing process that uses edge detection to extract the contours of grain boundaries in the preprocessed tissue image, isolating and distinguishing adjacent different grains. Edge detection is an existing technology and will not be elaborated here. The grain boundary region is the image region corresponding to a complete grain after grain boundary segmentation. Obtaining the grain pixel area of ​​the grain boundary region refers to counting the number of pixels contained in the grain boundary region as the pixel area corresponding to that grain boundary region. The grain pixel area is the total number of pixels occupied by the grain boundary region in the microscopic tissue image. The pixel ratio is the conversion relationship between pixels and actual physical size obtained in advance through a standard micrometer scale under a fixed magnification of a metallurgical microscope. Specifically, after acquiring the microscopic image of the scale, the actual length of the standard scale and the number of image pixels corresponding to that length are read. The actual length is divided by the number of pixels to obtain the actual length corresponding to a unit pixel, which is the pixel ratio, for example, 0.1 μm / pixel. The actual die area is the physical cross-sectional area of ​​the die obtained by converting the die pixel area based on the pixel ratio. The formula for calculating the actual die area is as follows:

[0055]

[0056] in, Indicates the actual grain area. Indicates the pixel area of ​​the grain. Indicates pixel ratio.

[0057] Understandably, obtaining the actual equivalent grain size using the actual grain area refers to transforming irregularly shaped grains into standard circles with the same cross-sectional area, using the diameter of the circle to characterize the true grain size. The purpose is to eliminate measurement errors caused by differences in grain shape. The formula for calculating the actual equivalent grain size is as follows:

[0058] in, Indicates the actual equivalent particle size.

[0059] Furthermore, the mean particle size is the arithmetic mean of multiple actual equivalent particle sizes, where the mean particle size characterizes the overall coarseness of the cladding layer grains. The standard deviation of the particle size is the standard deviation of multiple actual equivalent particle sizes, where the standard deviation characterizes the degree of dispersion and fluctuation of each grain size relative to the mean particle size, and is used to intuitively reflect the degree of uniformity in grain size. The particle size interval is a continuous size interval divided according to the conventional size range of historical cladding layer grains, used to classify and statistically analyze grains of different sizes. For example, in this embodiment, the grain size is divided into four particle size intervals: 0~2μm, 2~4μm, 4~6μm, and 6~8μm, covering the entire grain size range within the cladding layer. Particle size interval division is the process of matching the actual equivalent particle size of each grain to the corresponding particle size interval; for example, if the actual equivalent particle size of a grain is 3.2μm, it is divided into the 2~4μm particle size interval. The particle size distribution set is a collection containing multiple grains belonging to the same particle size interval. The total grain area is the sum of the areas of all grain pixels. The interval grain area is the sum of the actual grain areas of all grains within a single grain size interval. The grain area percentage is the ratio of the interval grain area to the total grain area, i.e., the interval grain area divided by the total grain area. The average area percentage is the arithmetic mean of the grain area percentages corresponding to all grain size intervals. The standard deviation of the area percentage is the standard deviation of the area percentage of each grain size interval relative to the average area percentage, used to reflect the degree of non-uniformity in the distribution of grain area of ​​different sizes. The grain size interval area dispersion coefficient is the value obtained by dividing the standard deviation of the area percentage by the average area percentage.

[0060] Understandably, the uniformity index is a quantitative score obtained by weighted fusion calculation of the mean particle size, standard deviation of particle size, and area dispersion coefficient of particle size interval. A higher uniformity index value indicates more uniform and evenly distributed grain size within the cladding layer, and better structural stability. The formula for calculating the uniformity index is as follows:

[0061] in, Indicators representing tissue uniformity This represents the preset average particle size coefficient. Indicates the average particle size. This indicates the preset maximum grain size. This represents the preset standard deviation coefficient. Indicates the standard deviation of particle size. This indicates the maximum preset standard deviation of particle size. This represents the preset discrete distribution coefficient. Indicates the area dispersion coefficient within the particle size range. This indicates the preset maximum value of the coefficient of variation.

[0062] Understandably, the average grain size coefficient is a weighted coefficient used to adjust the influence of the average grain size on the uniformity index, for example, 0.2. The maximum grain size is the maximum average grain size preset according to the process characteristics of the gate valve iron-based cladding material, for example, 8 μm, used for reverse dimensionless normalization of the average grain size. The standard deviation coefficient is a weighted coefficient used to adjust the influence of the degree of grain size fluctuation on the uniformity index, for example, 0.4, used to increase the evaluation weight of grain size consistency. The maximum standard deviation of grain size is the maximum allowable standard deviation of grain size in the cladding layer microstructure, a preset value of the process limit, for example, 2.5 μm, used to complete the dimensionless conversion of the standard deviation of grain size. The dispersion distribution coefficient is a preset weighted coefficient used to adjust the influence of the area dispersion index of the grain size interval on the uniformity index, for example, 0.4. The maximum value of the dispersion coefficient is the maximum allowable dispersion limit of the grain area distribution of the cladding layer, which is a general preset value for material microstructure evaluation, for example, 0.85. The maximum value of grain size, the maximum value of grain size standard deviation, and the maximum value of dispersion coefficient can all be obtained through historical production experience, and will not be elaborated here. The mean coefficient of grain size, the standard deviation coefficient, and the dispersion distribution coefficient can be obtained by analyzing historical production experience based on the analytic hierarchy process, and will not be elaborated here.

[0063] It should be explained that the phase analysis of the cladding sample to obtain phase stability indicators includes: The cladding sample was pretreated to obtain a phase detection sample. Set the diffraction angle scanning range and angle step size; The phase detection sample is scanned using a pre-confirmed diffractometer according to the diffraction angle scanning range and angle step size to obtain the diffraction pattern; Baseline correction is performed on the diffraction pattern to obtain the corrected pattern; The corrected spectrum is smoothed and filtered to obtain the standard diffraction pattern; Multiple diffraction characteristic peaks were obtained using standard diffraction patterns; For each of the multiple diffraction characteristic peaks, perform the following operation: Obtain the characteristic peak features of the diffraction characteristic peaks, including peak position angle, peak height, and full width at half maximum (FWHM). By summarizing the aforementioned characteristic peak features, multiple characteristic peak features are obtained; Multiple characteristic peak features are compared with a pre-built phase database to obtain multiple matching phases, where each matching phase corresponds one-to-one with a characteristic peak feature. The total peak height is calculated using the peak heights of multiple characteristic peaks. For each of the multiple matching phases, perform the following operation: The relative proportion of the phase is calculated using the peak height and total peak height of the characteristic peaks corresponding to the matched phases; Grain size is calculated using peak angle and full width at half maximum (FWHM). Obtain the standard peak angles of the matching phases; Calculate peak position deviation using standard peak position angle and peak position angle; Calculate the measured lattice spacing using peak position deviation; Obtain the standard lattice spacing, and use the standard lattice spacing and the measured lattice spacing to calculate the degree of lattice distortion; By summarizing the relative proportions of the aforementioned phases, grain sizes, and lattice distortion degrees, multiple relative proportions of phases, multiple grain sizes, and multiple lattice distortion degrees are obtained. Phase stability indices are calculated using the relative proportions of multiple phases, multiple grain sizes, and multiple degrees of lattice distortion.

[0064] Further, the sample surface pretreatment involves grinding, polishing, alcohol cleaning, and drying the cladding sample. The purpose is to remove oxide scale, scratches, oil stains, and adhering impurities from the cladding sample surface, ensuring a smooth and clean surface, avoiding interference from surface defects with X-ray diffraction signal acquisition, and improving the accuracy of diffraction pattern detection. The phase detection sample is the cladding sample after surface pretreatment. Setting the diffraction angle scanning range and angle step size refers to setting the operating parameters of the diffractometer during scanning, including the diffraction angle scanning range and angle step size. For example, the diffraction angle scanning range is [20°, 90°], and the angle step size is 0.02°, ensuring that all diffraction peaks of the matrix phase and hard reinforcement phase inside the cladding layer can be completely acquired. The diffraction pattern is a two-dimensional curve generated after the diffractometer acquires X-ray diffraction signals. The horizontal axis of the diffraction pattern represents the diffraction angle, and the vertical axis represents the diffraction signal intensity, used to visually reflect the variation of diffraction signal intensity at different diffraction angles. X-ray diffraction signal is the reflection intensity signal formed after X-rays emitted by a diffractometer penetrate the surface crystal structure of a sample and are scattered and interfered with by the crystal lattice. Different phases and different crystal structures have different X-ray reflection capabilities, and the signal is used to characterize the internal structural features of the crystal. The diffraction signal intensity is the reflection intensity of X-rays collected by the diffractometer. The magnitude of the diffraction signal intensity is positively correlated with the content of the corresponding phase; the higher the phase content, the higher the corresponding diffraction signal intensity. The diffraction signal intensity can be obtained through a diffractometer, which will not be elaborated further here.

[0065] Understandably, baseline correction is the process of eliminating baseline drift caused by inherent instrument background, air scattering, and sample surface impurities, reducing stray noise in areas without characteristic peaks, flattening the diffraction peak baseline, and improving the accuracy of data calculation. For example, in the 45° to 50° range where there are no characteristic diffraction peaks, the diffraction pattern should maintain a flat zero baseline. However, due to interference from the detection environment, stray diffraction signal intensities of 20–40 a.u. appear. First, the background baseline of this area without characteristic peaks is fitted. Then, the diffraction signal intensity of the background baseline is subtracted from the diffraction intensity of the diffraction pattern to eliminate stray background interference, correcting the diffraction signal intensity of the area without characteristic peaks to zero, eliminating the tilting and upward floating of the pattern, and finally obtaining a corrected pattern with a horizontal baseline and no background shift. Optionally, linear fitting can be used as the method for fitting the background baseline. The corrected pattern is the diffraction pattern after baseline correction. Smoothing filtering is a noise reduction process used to denoise the calibration spectrum, weakening stray noise while preserving the true diffraction peak contours and avoiding noise interference. Smoothing filtering is an existing technique and will not be elaborated upon here. The standard diffraction spectrum is the calibration spectrum after smoothing filtering.

[0066] Furthermore, the process of obtaining multiple diffraction characteristic peaks using a standard diffraction pattern refers to the process of identifying multiple characteristic peaks in a standard diffraction pattern. Optionally, MDI Jade can be used as the software for obtaining multiple diffraction characteristic peaks. A diffraction characteristic peak is a peak in a standard diffraction pattern that is formed due to diffraction by the crystal, has a complete convex profile, and has a signal intensity significantly higher than nearby flat positions. Characteristic parameters of a diffraction characteristic peak include peak position angle, peak height, and full width at half maximum (FWHM). Peak position angle is the diffraction angle corresponding to the highest point of the diffraction characteristic peak, used to determine the type of phase. Peak height is the diffraction signal intensity corresponding to the apex of the diffraction characteristic peak, measured in au. A larger peak height indicates stronger diffraction and reflection capabilities and a higher relative abundance of the phase. FWHM is the width at half maximum of the diffraction characteristic peak. The phase database is a database storing a large number of standard PDF crystal cards. This database stores inherent parameters such as standard peak positions, standard lattice spacing, and crystal structure types for common phases in cladding layers, including iron-based matrix phases, carbides, and borides. The standard PDF crystal cards are internationally recognized powder diffraction standard cards, each containing diffraction data for a unique crystal; each crystal uniquely corresponds to one standard PDF crystal card. Optionally, the phase database can be obtained via JCPDS. Phase matching involves calculating the similarity between the peak position angle, peak height, and full width at half maximum (FWHM) of a diffraction characteristic peak and the standard peak position angle, standard peak height, and standard FWHM in a standard PDF card database. Optionally, cosine similarity can be used as the similarity calculation method. A feature vector (peak position angle, peak height, FWHM) is constructed using the peak position angle, peak height, and FWHM, and a standard vector (standard peak position angle, standard peak height, standard FWHM) is constructed using the standard peak position angle, standard peak height, and standard FWHM in the standard PDF card. Cosine similarity is calculated using the feature vector and the standard vector. If the cosine similarity is greater than or equal to 92%, then the phase type of the diffraction characteristic peak is the same as the phase type corresponding to the standard PDF card.

[0067] Understandably, the total peak height is the sum of multiple peak heights. The relative proportion of a phase is the percentage of the phase peak height to the total peak height, used to quantitatively characterize the relative content of a single phase within the cladding layer. The formula for calculating the relative proportion of a phase is as follows:

[0068]

[0069] in, Indicates the relative proportion of phases. Indicates peak height. This indicates the total peak height.

[0070] Furthermore, the grain size is the average grain size of the phase corresponding to the diffraction characteristic peak. Optionally, the Scherrer formula can be used as the method for calculating the grain size using peak angle and full width at half maximum (FWHM). Obtaining the standard peak angle of the matching phase refers to retrieving the corresponding standard PDF card of the matching phase from the phase database and reading the diffraction angle of the corresponding peak. Peak position deviation is the difference between the peak angle and the standard peak angle. The measured lattice spacing is the interplanar spacing calculated based on Bragg's law, and the formula for calculating the measured lattice spacing is as follows:

[0071]

[0072] in, Indicates the measured lattice spacing. This indicates the preset diffraction order. This indicates the preset wavelength of the radiation. This indicates peak position deviation. This represents a sinusoidal function. The diffraction order is the reflection level of X-rays after they enter the crystal lattice and undergo diffraction interference; in this embodiment, the diffraction order is set to 1. The X-ray wavelength is the wavelength of the X-rays emitted by the diffractometer, for example, 0.15406 nm.

[0073] Understandably, the acquisition of standard lattice spacing refers to the theoretical interplanar spacing obtained from standard PDF cards in the phase database. Lattice distortion is a dimensionless parameter that quantifies the degree of stretching or compression deformation of crystal planes, used to characterize the degree of internal defects and lattice deformation state of the cladding layer crystal. The formula for calculating lattice distortion is as follows:

[0074]

[0075] in, Indicates the degree of lattice distortion. Indicates the standard lattice spacing.

[0076] It should be explained that the calculation of phase stability indices using the relative proportions of multiple phases, multiple grain sizes, and multiple lattice distortion degrees includes: The proportion of the hard reinforcing phase was determined by using the relative proportions of multiple phases. The average grain size is calculated using the relative proportions of multiple phases and multiple grain sizes. The average degree of lattice distortion is calculated using the relative proportions of multiple phases and the degree of lattice distortion of multiple phases. The phase stability index is calculated using the proportion of hard reinforcing phase, average grain size, and average lattice distortion. The formula for calculating the phase stability index is shown below:

[0077] in, Indicators of phase stability This indicates the preset hard phase weighting coefficient. Indicates the proportion of hard reinforcing phase. This represents the preset grain size deviation coefficient. Indicates the average grain size. This indicates the preset maximum average grain size. This represents the preset lattice distortion correction factor. Indicates the degree of average lattice distortion. Indicates the preset maximum degree of lattice distortion. This indicates taking the absolute value. It represents the square root.

[0078] Furthermore, the proportion of hard reinforcing phases is a value obtained by selecting hard reinforcing phases such as carbides and borides from multiple matched phases and summing the relative proportions of all hard reinforcing phases. Hard reinforcing phases are crystalline phases within the cladding layer that improve hardness and wear resistance. A higher proportion of hard reinforcing phases results in stronger wear resistance for the gate valve coating. The average grain size is calculated by weighting the grain sizes of multiple phases using their relative proportions as weights. The formula for calculating the average grain size is shown below:

[0079]

[0080] in, Indicates the number of multiple grain sizes. Indicates the relative proportion of multiple phases. The relative proportion of each phase Represents the first among multiple grain sizes individual grain size.

[0081] Understandably, the average lattice distortion degree is a value obtained by weighting the lattice distortion degrees of multiple phases using the relative proportions of each phase as weights. The calculation method for the average lattice distortion degree using the relative proportions of multiple phases and multiple lattice distortion degrees is the same as the calculation method for the average grain size using the relative proportions of multiple phases and multiple grain sizes, and will not be repeated here. The phase stability index is an indicator that comprehensively considers the content of the hard phase, grain size, and lattice distortion defects, quantifying the regularity and stability of the internal crystal structure of the cladding layer. The value range of the phase stability index is [0, 1]. The closer the value of the phase stability index is to 1, the more reasonable the phase combination of the cladding layer, the fine and uniform grains, the low degree of lattice deformation, and the better the overall structural stability. The hard phase proportion bias coefficient is a weighting coefficient used to adjust the influence of the hard reinforcing phase proportion on the phase stability index, for example, 0.5. The grain size deviation coefficient is a weighted coefficient used to adjust the influence of the average grain size on the phase stability index, for example, 0.3. The maximum average grain size is the largest grain size that can be processed by the gate valve cladding process, for example, 80 μm. The lattice distortion correction coefficient is a weighted coefficient used to adjust the influence of the average lattice distortion degree on the phase stability index, for example, 0.2. The maximum lattice distortion degree is the maximum value of the lattice distortion degree set in conjunction with the characteristics of iron-based cladding materials, for example, 0.08.

[0082] It should be explained that the mechanical property testing of the cladding sample to obtain a mechanical property score includes: Using cladding specimens to prepare mechanical testing specimens; The wear test parameters are obtained, including the radius of the grinding steel ring, the grinding wheel speed, the test time, and the test load. Friction and wear tests were performed on the mechanical test specimens using a pre-confirmed wear testing machine according to the wear test parameters to obtain the wear track width; The wear rate is calculated using the wear mark width, the radius of the grinding steel ring, the grinding wheel speed, the test time, and the test load. The formula for calculating the wear rate is as follows:

[0083] in, Indicates wear rate, Indicates the radius of the grinding steel ring. Indicates the width of the wear mark. Indicates the grinding wheel speed. Indicates the test time. Indicates that the test load is applied. This represents the preset value of pi. Represents the arcsine function; Mechanical performance scores are calculated using wear rate.

[0084] Furthermore, the mechanical testing specimen is prepared from the cladding specimen by cutting, grinding, and polishing, resulting in a specimen with dimensions of 10mm × 10mm × 14mm. The wear test parameters are the operating parameters of the wear testing machine used in friction and wear testing. The radius of the grinding steel ring is the radius of the GCr15 steel ring that comes into contact with the mechanical testing specimen during the friction and wear test, for example, 25mm. The grinding wheel speed is the rotational speed of the grinding steel ring during the operation of the wear testing machine, for example, 400 r / min. The test time is the duration of the friction and wear test, for example, 30 min, where min refers to minutes. The test load is the positive pressure vertically applied to the surface of the mechanical testing specimen by the wear testing machine, for example, 98N, used to simulate the stress state of a gate valve under contact compression under actual working conditions. The wear testing machine is a specialized testing device used to determine the wear resistance of materials. Friction and wear testing utilizes a hard steel ring to continuously slide and rub against the surface of the mechanical testing specimen, simulating the frictional wear process generated by the repeated opening and closing of a gate valve. The wear track width is the lateral width of the strip-shaped wear groove formed on the sample surface by friction and scraping with a steel ring after the friction and wear test. Optionally, a super depth-of-field microscope can be used as the instrument to obtain the wear track width. Wear rate is an indicator that quantifies the degree of wear resistance of a material. The mechanical property score is a wear resistance score obtained by normalizing the wear rate. The calculation formula for the mechanical property score is as follows:

[0085]

[0086] in, Indicates mechanical performance score. This indicates the preset maximum wear rate. The maximum wear rate is the maximum wear rate that will not affect the operation of the gate valve components. For example, .

[0087] S7. Determine the target cladding parameter combination based on multiple test performance scores, and use the target cladding parameter combination to perform laser cladding on multiple pre-treated modified areas to obtain a wear-resistant and reinforced gate valve.

[0088] It should be explained that determining the target cladding parameter combination based on multiple test performance scores refers to using the modified reaction system corresponding to the test performance score with the highest value among the multiple test performance scores as the target cladding parameter combination. This target cladding parameter combination includes the optimal powder mass ratio and the optimal laser cladding parameters. The optimal powder mass ratio refers to the powder mass ratio used in the modified reaction system corresponding to the test performance score with the highest value among the multiple test performance scores, and the optimal laser cladding parameters refer to the laser cladding parameters used in the modified reaction system corresponding to the test performance score with the highest value among the multiple test performance scores. The target cladding parameter combination determines the optimal combination of process parameters for laser cladding. The wear-resistant reinforced gate valve is obtained by laser cladding multiple pre-treated modified areas of the gate valve substrate using the target cladding parameter combination. The gate valve surface is clad to form a dense, uniform, and highly stable coating with low wear rate, which significantly improves the gate valve's resistance to friction loss under conditions of impurity fluids and reciprocating opening and closing, extending the gate valve's service life and meeting the long-term service requirements under harsh industrial conditions.

[0089] To address the problems described in the background art, this invention receives a gate valve strengthening command, determines the target gate valve based on the command, and identifies a set of target modification regions based on the target gate valve. This invention, by using a command-based approach to precisely match the target gate valve and automatically delineate the modification regions, avoids the subjectivity and arbitrariness of manual region delineation, thus improving the accuracy, standardization, and automation of selecting modification regions on the gate valve surface. Furthermore, this invention pre-treats multiple target modification regions within the target modification region set to obtain multiple pre-treated modification regions. This standardized surface pre-treatment effectively removes surface oil, scale, and impurities from the target modification regions, resulting in a tighter bond between the subsequent laser cladding coating and the substrate. Simultaneously, it ensures consistent operating conditions across all modification regions, improving the uniformity of the cladding forming quality. Subsequently, this invention constructs multiple laser cladding parameters by setting multiple powder mass ratios. It is evident that by setting multiple sets of powder mass ratios and constructing multiple sets of laser cladding parameters, this invention can cover the performance range of different process combinations, providing sufficient sample support for subsequently selecting the optimal process scheme for wear-resistant strengthening of gate valves. Then, this invention obtains multiple cladding samples based on multiple laser cladding parameters and multiple powder mass ratios, and performs cladding performance testing on these samples, obtaining multiple test performance scores. It is evident that this invention, by preparing multiple sets of cladding samples with different process matching and conducting multi-dimensional performance testing and quantitative scoring, achieves quantifiable comparison and screening of cladding processes and powder ratios, overcoming the limitations of traditional experience-based selection, and providing objective data basis for selecting the strengthening scheme with the best overall performance. Furthermore, this invention determines the target cladding parameter combination based on multiple test performance scores, and uses this target cladding parameter combination to perform laser cladding on multiple pre-treated modified areas to obtain a wear-resistant and reinforced gate valve. It is evident that this invention, through quantitative test performance scoring to optimize the cladding parameter combination and using this optimal parameter for laser cladding processing, can ensure the stability and consistency of the microstructure, phase composition, and mechanical properties of the modified areas of the gate valve, significantly improving the overall wear resistance and service life of the gate valve. Therefore, this invention can improve the wear resistance of gate valves and extend their service life.

[0090] like Figure 2 The diagram shown is a functional block diagram of a gate valve wear resistance enhancement system based on surface modification provided in an embodiment of the present invention.

[0091] The surface-modified gate valve wear resistance enhancement system 100 of this invention can be installed in an electronic device. Depending on the functions implemented, the surface-modified gate valve wear resistance enhancement system 100 may include a modification area confirmation module 101, a processing parameter setting module 102, a target parameter confirmation module 103, and a gate valve wear resistance enhancement module 104. The module described in this invention can also be called a unit, referring to a series of computer program segments that can be executed by the processor of an electronic device and perform a fixed function, stored in the memory of the electronic device.

[0092] The modified area confirmation module 101 is used to receive the gate valve strengthening command and determine the target gate valve according to the gate valve strengthening command; The target modification region set is identified based on the target gate valve; The processing parameter setting module 102 is used to perform surface pretreatment on multiple target modification regions in the target modification region set to obtain multiple pretreated modification regions; Multiple powder mass ratios were set to construct multiple laser cladding parameters; The target parameter confirmation module 103 is used to obtain multiple cladding samples based on multiple laser cladding parameters and multiple powder mass ratios; Multiple cladding samples were tested for cladding performance, and multiple test performance scores were obtained. The target cladding parameter combination is determined based on multiple test performance scores; The gate valve wear-resistant strengthening module 104 is used to perform laser cladding on multiple pre-treated modified areas using the target cladding parameter combination to obtain a wear-resistant strengthened gate valve.

[0093] In detail, the modules in the surface-modified gate valve wear resistance enhancement system 100 described in this embodiment of the invention employ the same methods as described above during use. Figure 1 The method used is the same as the surface modification-based gate valve wear resistance enhancement method described above, and can produce the same technical effect, so it will not be repeated here.

[0094] like Figure 3 The diagram shown is a schematic representation of an electronic device that implements a method for enhancing the wear resistance of a gate valve based on surface modification, according to an embodiment of the present invention.

[0095] The electronic device 1 may include a processor 10, a memory 11 and a bus 12, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a method program for enhancing the wear resistance of gate valves based on surface modification.

[0096] The memory 11 includes at least one type of readable storage medium, such as flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 1, such as a portable hard drive. In other embodiments, the memory 11 can be an external storage device of the electronic device 1, such as a plug-in portable hard drive, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the electronic device 1. Furthermore, the memory 11 includes both internal storage units and external storage devices of the electronic device 1. The memory 11 can be used not only to store application software and various types of data installed on the electronic device 1, such as the code of a method for enhancing the wear resistance of a gate valve based on surface modification, but also to temporarily store data that has been output or will be output.

[0097] In some embodiments, the processor 10 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control unit of the electronic device, connecting various components of the entire electronic device through various interfaces and lines. It executes programs or modules stored in the memory 11 (e.g., a method for enhancing the wear resistance of a gate valve based on surface modification), and calls data stored in the memory 11 to perform various functions of the electronic device 1 and process data.

[0098] The bus 12 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus 12 can be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to realize the connection and communication between the memory 11 and at least one processor 10, etc.

[0099] Figure 3 Only electronic devices with components are shown; it will be understood by those skilled in the art that... Figure 3The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0100] For example, although not shown, the electronic device 1 may also include a power supply (such as a battery) to power the various components. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management device, thereby enabling functions such as charging management, discharging management, and power consumption management. The power supply may also include one or more DC or AC power supplies, recharging devices, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device 1 may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0101] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, a Bluetooth interface, etc.), which is typically used to establish communication connections between the electronic device 1 and other electronic devices.

[0102] Optionally, the electronic device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), and optionally, a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen, etc. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the electronic device 1 and to display a visual user interface.

[0103] The program for enhancing the wear resistance of gate valves based on surface modification, stored in the memory 11 of the electronic device 1, is a combination of multiple instructions. When run in the processor 10, it can achieve the following: Receive a gate valve reinforcement command and determine the target gate valve based on the gate valve reinforcement command; The target modification region set is identified based on the target gate valve; Multiple target modification regions within the target modification region set are subjected to surface pretreatment to obtain multiple pretreated modification regions; Multiple powder mass ratios were set to construct multiple laser cladding parameters; Multiple cladding samples were obtained based on multiple laser cladding parameters and multiple powder mass ratios; Multiple cladding samples were tested for cladding performance, and multiple test performance scores were obtained. The target cladding parameter combination is determined based on multiple test performance scores; Laser cladding is performed on multiple pre-treated modified areas using the target cladding parameter combination to obtain a wear-resistant and reinforced gate valve.

[0104] Specifically, the processor 10's implementation method for the above instructions can be found in [reference needed]. Figures 1 to 3 The descriptions of the relevant steps in the corresponding embodiments are not repeated here.

[0105] Furthermore, if the modules / units integrated in the electronic device 1 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0106] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor of an electronic device, can perform the following: Receive a gate valve reinforcement command and determine the target gate valve based on the gate valve reinforcement command; The target modification region set is identified based on the target gate valve; Multiple target modification regions within the target modification region set are subjected to surface pretreatment to obtain multiple pretreated modification regions; Multiple powder mass ratios were set to construct multiple laser cladding parameters; Multiple cladding samples were obtained based on multiple laser cladding parameters and multiple powder mass ratios; Multiple cladding samples were tested for cladding performance, and multiple test performance scores were obtained. The target cladding parameter combination is determined based on multiple test performance scores; Laser cladding is performed on multiple pre-treated modified areas using the target cladding parameter combination to obtain a wear-resistant and reinforced gate valve.

[0107] In the embodiments provided by this invention, it should be understood that the disclosed devices, systems, and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative, and actual implementations may have other classification methods.

[0108] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0109] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0110] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0111] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for enhancing the wear resistance of gate valves based on surface modification, characterized in that, The method includes: Receive a gate valve reinforcement command and determine the target gate valve based on the gate valve reinforcement command; The target modification region set is identified based on the target gate valve; Multiple target modification regions within the target modification region set are subjected to surface pretreatment to obtain multiple pretreated modification regions; Multiple powder mass ratios were set to construct multiple laser cladding parameters; Multiple cladding samples were obtained based on multiple laser cladding parameters and multiple powder mass ratios; Multiple cladding samples were tested for cladding performance, and multiple test performance scores were obtained. The target cladding parameter combination is determined based on multiple test performance scores; Laser cladding is performed on multiple pre-treated modified areas using the target cladding parameter combination to obtain a wear-resistant and reinforced gate valve.

2. The method for enhancing the wear resistance of gate valves based on surface modification as described in claim 1, characterized in that, The surface pretreatment of multiple target modification regions within the target modification region set yields multiple pretreated modification regions, including: For each of the multiple target modification regions, perform the following operation: The target modified region is subjected to surface roughening treatment to obtain a roughened modified region; The roughened and modified area is degreased and cleaned to obtain the degreased and modified area; The de-oiled modified area is cleaned to remove the oxide layer, resulting in a purified modified area; The surface condition of the purified and modified area is detected to obtain a set of surface detection parameters, which includes surface residual oxygen content, surface roughness and surface cleanliness. The surface detection parameter set is compared with the preset surface detection threshold set to obtain the surface condition determination result, wherein the surface condition determination result includes qualified or unqualified. If the surface condition determination result is unqualified, the purified modified area is regarded as the roughened modified area, and the above steps of degreasing and cleaning the roughened modified area are returned until the surface condition determination result is qualified. If the surface condition determination result is qualified, then the purification and modification area is used as the pretreatment modification area; By summarizing the preprocessed modified regions, multiple preprocessed modified regions are obtained.

3. The method for enhancing the wear resistance of gate valves based on surface modification as described in claim 2, characterized in that, The surface condition detection of the purified and modified area yields a set of surface detection parameters, including: Three element detection points were selected based on the purification and modification area; Perform the following operation on each of the three element detection points: Elemental energy spectrum signals are acquired at element detection points to obtain elemental characteristic peak intensity data; The oxygen mass fraction is calculated based on the characteristic peak intensity data of the elements. By summing up the oxygen element mass fractions, three oxygen element mass fractions are obtained; The residual oxygen content on the surface was calculated using the mass fractions of three oxygen elements. Surface roughness parameters are obtained based on the purified and modified region; Images were acquired from the purified and modified area to obtain surface microscopic images; The surface microscopic image is preprocessed to obtain a preprocessed microscopic image; The preprocessed microscopic image is divided into pixels using a preset grayscale threshold to obtain multiple clean substrate areas and multiple contaminant areas; The clean pixel area and the contaminant pixel area are obtained based on multiple clean substrate areas and multiple contaminant areas. Surface cleanliness is calculated using the area of ​​clean pixels and the area of ​​contaminated pixels. By summarizing the surface residual oxygen content, the surface roughness parameters, and the surface cleanliness, a set of surface detection parameters is obtained.

4. The method for enhancing the wear resistance of gate valves based on surface modification as described in claim 3, characterized in that, The process of obtaining multiple cladding samples based on multiple laser cladding parameters and multiple powder mass ratios includes: To obtain iron-3 aluminum-based alloy powder and chromium carbide powder; For each of the multiple powder mass ratios, perform the following operation: Iron-aluminum alloy powder and chromium carbide powder were mixed according to the powder mass ratio to obtain the test cladding powder; By summing up the tested cladding powders, multiple test cladding powders were obtained; Multiple modified reaction systems were obtained based on multiple test cladding powders and multiple laser cladding parameters; Multiple laser cladding substrates were obtained based on multiple modified reaction systems, wherein each laser cladding substrate corresponds one-to-one with a modified reaction system. Multiple laser cladding substrates were clad using multiple modified reaction systems to obtain multiple cladding samples.

5. The method for enhancing the wear resistance of gate valves based on surface modification as described in claim 4, characterized in that, The cladding performance of multiple cladding samples is tested to obtain multiple test performance scores, including: For each of the multiple cladding samples, the following operation shall be performed: The cladding sample was cut and prepared to obtain a metallographic test sample; The metallographic sample is subjected to metallographic pretreatment to obtain the metallographic sample to be tested; Microscopic images of the metallographic sample to be tested are acquired using a pre-confirmed metallographic microscopic imaging device to obtain microstructure images; Tissue uniformity indices are obtained based on the microscopic tissue images; Phase analysis was performed on the cladding sample to obtain phase stability indicators; The mechanical properties of the cladding sample were tested to obtain a mechanical property score. The test performance score is calculated using the tissue uniformity index, the phase stability index, and the mechanical property score. By summing the test performance scores, multiple test performance scores are obtained.

6. The method for enhancing the wear resistance of gate valves based on surface modification as described in claim 5, characterized in that, The acquisition of tissue uniformity indicators based on the microscopic tissue image includes: The microscopic tissue image is preprocessed to obtain a preprocessed tissue image; The preprocessed tissue image is subjected to grain boundary segmentation to obtain multiple grain boundary regions; For each of the multiple grain boundary regions, perform the following operation: Obtain the grain pixel area of ​​the grain boundary region; The pixel area of ​​the die is converted into the actual die area using the pre-confirmed pixel ratio; The actual equivalent grain size is obtained by utilizing the actual grain area; By summing up the actual equivalent particle sizes, multiple actual equivalent particle sizes are obtained; The average particle size is calculated using multiple actual equivalent particle sizes; The standard deviation of particle size is calculated using the mean particle size and multiple actual equivalent particle sizes. Based on multiple pre-confirmed particle size intervals, multiple actual equivalent particle sizes are divided into particle size intervals to obtain multiple particle size distribution sets, wherein the particle size distribution sets correspond one-to-one with the particle size intervals. The total grain area is obtained based on multiple grain size distribution sets; For each of the multiple particle size distribution sets, perform the following operation: Obtain the interval grain area of ​​the grain size distribution set; The grain area ratio is calculated using the interval grain area and the total grain area; By summing up the aforementioned grain area percentages, multiple grain area percentages are obtained; Calculate the average area percentage using the area percentages of multiple grains; Calculate the standard deviation of area percentage using the area percentage of multiple grains; The area dispersion coefficient of the particle size range is calculated using the average area proportion and the standard deviation of the area proportion. The uniformity index of the microstructure is calculated using the mean particle size, standard deviation of particle size, and coefficient of variation of the area of ​​the particle size interval.

7. The method for enhancing the wear resistance of gate valves based on surface modification as described in claim 6, characterized in that, The phase analysis of the cladding sample to obtain phase stability indicators includes: The cladding sample was pretreated to obtain a phase detection sample. Set the diffraction angle scanning range and angle step size; The phase detection sample is scanned using a pre-confirmed diffractometer according to the diffraction angle scanning range and angle step size to obtain the diffraction pattern; Baseline correction is performed on the diffraction pattern to obtain the corrected pattern; The corrected spectrum is smoothed and filtered to obtain the standard diffraction pattern; Multiple diffraction characteristic peaks were obtained using standard diffraction patterns; For each of the multiple diffraction characteristic peaks, perform the following operation: Obtain the characteristic peak features of the diffraction characteristic peaks, including peak position angle, peak height, and full width at half maximum (FWHM). By summarizing the aforementioned characteristic peak features, multiple characteristic peak features are obtained; Multiple characteristic peak features are compared with a pre-built phase database to obtain multiple matching phases, where each matching phase corresponds one-to-one with a characteristic peak feature. The total peak height is calculated using the peak heights of multiple characteristic peaks. For each of the multiple matching phases, perform the following operation: The relative proportion of the phase is calculated using the peak height and total peak height of the characteristic peaks corresponding to the matched phases; Grain size is calculated using peak angle and full width at half maximum (FWHM). Obtain the standard peak angles of the matching phases; Calculate peak position deviation using standard peak position angle and peak position angle; Calculate the measured lattice spacing using peak position deviation; Obtain the standard lattice spacing, and use the standard lattice spacing and the measured lattice spacing to calculate the degree of lattice distortion; By summarizing the relative proportions of the aforementioned phases, grain sizes, and lattice distortion degrees, multiple relative proportions of phases, multiple grain sizes, and multiple lattice distortion degrees are obtained. Phase stability indices are calculated using the relative proportions of multiple phases, multiple grain sizes, and multiple degrees of lattice distortion.

8. The method for enhancing the wear resistance of gate valves based on surface modification as described in claim 7, characterized in that, The calculation of phase stability indices using the relative proportions of multiple phases, multiple grain sizes, and multiple degrees of lattice distortion includes: The proportion of the hard reinforcing phase was determined by using the relative proportions of multiple phases. The average grain size is calculated using the relative proportions of multiple phases and multiple grain sizes. The average degree of lattice distortion is calculated using the relative proportions of multiple phases and the degree of lattice distortion of multiple phases. The phase stability index is calculated using the proportion of hard reinforcing phase, average grain size, and average lattice distortion. The formula for calculating the phase stability index is shown below: ， in, Indicators of phase stability This indicates the preset hard phase weighting coefficient. Indicates the proportion of hard reinforcing phase. This represents the preset grain size deviation coefficient. Indicates the average grain size. This indicates the preset maximum average grain size. This represents the preset lattice distortion correction factor. Indicates the degree of average lattice distortion. Indicates the preset maximum degree of lattice distortion. This indicates taking the absolute value. It represents the square root.

9. The method for enhancing the wear resistance of gate valves based on surface modification as described in claim 8, characterized in that, The mechanical property testing of the cladding sample to obtain a mechanical property score includes: Using cladding specimens to prepare mechanical testing specimens; The wear test parameters are obtained, including the radius of the grinding steel ring, the grinding wheel speed, the test time, and the test load. Friction and wear tests were performed on the mechanical test specimens using a pre-confirmed wear testing machine according to the wear test parameters to obtain the wear track width; The wear rate is calculated using the wear mark width, the radius of the grinding steel ring, the grinding wheel speed, the test time, and the test load. The formula for calculating the wear rate is as follows: ， in, Indicates wear rate, Indicates the radius of the grinding steel ring. Indicates the width of the wear mark. Indicates the grinding wheel speed. Indicates the test time. Indicates that the test load is applied. This represents the preset value of pi. Represents the arcsine function; Mechanical performance scores are calculated using wear rate.

10. A system for enhancing the wear resistance of gate valves based on surface modification, characterized in that, The system includes: The modified area confirmation module is used to receive the gate valve reinforcement command and determine the target gate valve according to the gate valve reinforcement command; The target modification region set is identified based on the target gate valve; The processing parameter setting module is used to perform surface pretreatment on multiple target modification regions in the target modification region set to obtain multiple pretreated modification regions; Multiple powder mass ratios were set to construct multiple laser cladding parameters; The target parameter confirmation module is used to obtain multiple cladding samples based on multiple laser cladding parameters and multiple powder mass ratios. Multiple cladding samples were tested for cladding performance, and multiple test performance scores were obtained. The target cladding parameter combination is determined based on multiple test performance scores; The gate valve wear-resistant strengthening module is used to perform laser cladding on multiple pre-treated modified areas using the target cladding parameter combination to obtain a wear-resistant strengthened gate valve.

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