Optimized manufacturing method and device for gradient zirconium alloy hip joint implant

Abstract

The invention discloses an optimized manufacturing method and device for a gradient zirconium alloy hip joint implant, and the method comprises the steps: obtaining a design demand of the hip joint implant, carrying out the matching analysis of bearing performance and bone tissue mechanics, and building a gradient structure constraint condition covering the strength demand and low modulus constraint; optimal structure parameters are screened through strength-porosity-elastic modulus collaborative optimization, and partition boundaries of a core compact area, a gradient transition area and an outer porous area are delimited; double-powder-feeder selective laser melting equipment is configured, the mixing proportion of titanium powder and zirconium alloy powder is determined, and a partition manufacturing instruction is generated through energy density matching; molten pool state identification defect risk points are monitored in real time in the forming process, and laser power and scanning speed are dynamically adjusted to generate compensation parameters; and the continuity of interlayer components is detected, a layer-by-layer gradual change scheme is configured, a forming control instruction is output, and the manufacturing requirements of personalized gradient implants can be met.

Description

Technical Field

[0001] This invention relates to the field of additive manufacturing technology for medical metal materials, and in particular to an optimized manufacturing method and apparatus for gradient zirconium alloy hip joint implants. Background Technology

[0002] The long-term stability of implants after hip replacement surgery is limited by the degree of mechanical fit between the implant and bone tissue. Human bone exhibits heterogeneous mechanical properties; the elastic modulus of cortical bone is approximately 15-20 GPa, while that of cancellous bone is only 0.1-2 GPa. In contrast, the elastic modulus of traditional titanium alloy or cobalt-chromium alloy implants can exceed 100 GPa. This difference in stiffness means that the load is primarily transmitted through the implant rather than distributed to the surrounding bone tissue. Over long periods, the bone tissue degenerates due to a lack of mechanical stimulation. Gradient structural design is considered an effective way to address this problem. By constructing a continuous transition from dense to porous within the implant, a spatially gradual distribution of the elastic modulus can be achieved, allowing the stiffness of each region of the implant to match that of the adjacent bone tissue.

[0003] Currently, the manufacturing of gradient implants mainly relies on additive manufacturing technologies such as selective laser melting. However, there are still three challenges in practical applications: the determination of gradient structure parameters lacks quantitative correlation with individual bone mechanical properties, and empirical values ​​or literature reference values ​​are mostly used; it is difficult to control the compositional jump when transitioning between two or more materials, and brittle phases or microcracks are easily generated at the interface; and the process parameters are fixed during the forming process, which cannot adapt to the differences in melting characteristics of different composition regions, resulting in local overheating or undermelting defects. Summary of the Invention

[0004] This invention discloses an optimized manufacturing method and apparatus for gradient zirconium alloy hip implants. The aim is to establish a quantitative matching relationship between gradient structural parameters and the mechanical properties of bone tissue, achieve smooth transition control of titanium-zirconium dual material composition, and ensure the consistency of forming quality through real-time monitoring of the molten pool state and dynamic compensation of process parameters. Finally, it outputs forming control commands that can be directly used by the equipment, providing technical support for the precise manufacturing of personalized hip implants and the quality control of orthopedic implants.

[0005] The first aspect of this invention provides an optimized manufacturing method for a gradient zirconium alloy hip implant, comprising the following steps: Obtain the design requirements for the hip joint implant, and perform load-bearing performance and bone tissue mechanics matching analysis on the design requirements to establish gradient structural constraints. The gradient structure constraint conditions are subjected to strength-porosity-elastic modulus co-optimization to identify the optimal solution set. The optimal structural parameters are generated by mechanical performance adaptation screening of the optimal solution set. The optimal structural parameters are then delineated by gradient partition boundary to establish a partition parameter table. Based on the partition parameter table, a preliminary configuration is established for the laser selective melting equipment with dual powder feeders. The partition parameter table is converted into a mixing ratio requirement for titanium powder and zirconium alloy powder. The energy density matching degree of the preliminary configuration is screened through the mixing ratio requirement to generate a usable configuration. A partition manufacturing instruction is generated for the usable configuration. Based on the partitioned manufacturing instructions, the molten pool status is monitored in real time to identify forming defect risk points. The forming defect risk points trigger the dynamic adjustment of laser power and scanning speed to generate a set of compensation parameters. The interlayer composition continuity detection is performed on the partition manufacturing command and the compensation parameter group to identify the connection section. The connection section and the mixing ratio requirement are configured layer by layer to generate a gradient transition configuration. Based on the gradient transition configuration, the process parameters of the partition parameter table are refined and forming control commands are output.

[0006] A second aspect of the present invention provides an optimized manufacturing apparatus for gradient zirconium alloy hip implants, comprising: The requirements analysis module is used to obtain the design requirements of the hip joint implant, and to perform load-bearing performance and bone tissue mechanics matching analysis on the design requirements to establish gradient structural constraints. The optimization design module is used to identify the optimal solution set by performing strength-porosity-elastic modulus collaborative optimization on the gradient structure constraints, to filter the optimal solution set by mechanical performance adaptability to generate the optimal structural parameters, and to delineate the gradient partition boundary of the optimal structural parameters to establish a partition parameter table. The process configuration module is used to establish a preliminary configuration for a laser selective melting equipment with dual powder feeders based on the partition parameter table, convert the partition parameter table into a mixing ratio requirement for titanium powder and zirconium alloy powder, screen the preliminary configuration for energy density matching degree based on the mixing ratio requirement to generate an available configuration, and generate a partition manufacturing instruction for the available configuration. The real-time monitoring module is used to monitor the molten pool status in real time and identify forming defect risk points according to the partition manufacturing instructions. The forming defect risk points trigger the dynamic adjustment of laser power and scanning speed to generate a compensation parameter set. The gradient forming module is used to detect and identify the connection section between the interlayer composition of the partition manufacturing command and the compensation parameter group, generate a gradient transition configuration by gradually configuring the connection section and the mixing ratio requirement layer by layer, and refine the process parameters of the partition parameter table according to the gradient transition configuration and output forming control commands.

[0007] The beneficial effects of this invention are reflected in the following points: 1. Based on the stress intensity distribution and stress shielding effect evaluation results of the implant bearing area, the upper and lower limits of modulus constraints for each region are determined. Multi-objective optimization is used to search for the optimal solution in the design space composed of strength, porosity, and elastic modulus. The combination of structural parameters that takes into account both load-bearing capacity and bone tissue matching is screened through fit scoring. The core dense area retains sufficient strength to bear the main load, the outer porous area reduces the modulus to promote bone ingrowth, and the transition area achieves a smooth connection between the two. This mechanical analysis-based zoning design method replaces the traditional empirical parameter selection. 2. A dual powder feeder configuration is used to achieve adjustable mixing of titanium powder and zirconium alloy powder. The required powder ratio is deduced based on the modulus requirements of each zone, and corresponding energy density parameters are set for the melting temperature differences of powders with different ratios. The compositional jumps at the zone boundaries are smoothed through a layer-by-layer gradual configuration. The compositional differences between adjacent layers are controlled within the interface bonding safety threshold, avoiding the interface embrittlement problem caused by abrupt compositional changes. 3. During the forming process, the temperature field and morphological characteristics of the molten pool are simultaneously collected by an infrared thermal imager and a high-speed camera. Based on temperature gradient analysis, overheated and under-melted areas are identified. Energy reduction or energy enhancement compensation parameters are generated for different types of defect risk points. The compensated process parameters are superimposed on the zonal manufacturing instructions and executed to ensure that each area can obtain a stable molten pool state and consistent forming quality. Attached Figure Description

[0008] The accompanying drawings illustrate specific examples of the technical solutions described in this invention and, together with the detailed embodiments, form part of the specification, serving to explain the technical solutions, principles, and effects of this invention.

[0009] Figure 1 This is a schematic flowchart of an optimized manufacturing method for a gradient zirconium alloy hip implant according to the present invention.

[0010] Figure 2 This is a schematic diagram of the gradient implant partition structure of the present invention.

[0011] Figure 3 This is a schematic diagram of the structure of the dual-powder-feeder laser selective melting device of the present invention.

[0012] Figure 4 This is a structural block diagram of an optimized manufacturing device for gradient zirconium alloy hip joint implants according to the present invention.

[0013] Among them: 1-Laser, 2-Scanning galvanometer, 3-Powder feeder A, 4-Powder feeder B, 5-Powder mixer, 6-Powder spreading scraper, 7-Forming substrate, 8-Forming chamber, 9-Coaxial thermal imager, 10-Coaxial high-speed camera, 11-Control system, 2a-Core dense area, 2b-Gradient transition area, 2c-Outer porous area. Detailed Implementation

[0014] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0015] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0016] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0017] The technical solutions of the embodiments of this application will be described below.

[0018] like Figure 1 As shown, this embodiment of the invention provides an optimized manufacturing method for a gradient zirconium alloy hip implant, including the following steps S110-S150: Step S110: Obtain the design requirements of the hip joint implant, and perform load-bearing performance and bone tissue mechanics matching analysis on the design requirements to establish gradient structural constraints.

[0019] Specifically, the design requirements for hip implants are determined. Clinicians propose customized requirements for the implant based on the patient's CT images and bone mineral density test results, including the implant's external dimensions, expected lifespan, and the patient's daily activity level. The external dimensions are determined based on a 3D reconstruction model of the patient's acetabulum, with an acetabular cup diameter ranging from 48-62 mm, a cup depth from 22-28 mm, and a wall thickness from 3-8 mm. The expected lifespan is set at 15-20 years, corresponding to approximately 50 million load cycles. This lifespan requirement determines the lower limit of the implant's fatigue strength. The patient's daily activity level is categorized into three levels: low activity, moderate activity, and high activity. Low activity corresponds to a peak load less than twice the body weight, moderate activity corresponds to a peak load of 2-4 times the body weight, and high activity corresponds to a peak load greater than 4 times the body weight. The design requirements also include biocompatibility requirements; the implant material must meet the ISO 10993 biological evaluation standard, and the surface treatment must promote bone cell adhesion and proliferation.

[0020] In some embodiments, the step of performing load-bearing performance and bone tissue mechanics matching analysis to establish gradient structural constraints for the design requirements includes: determining the load-bearing parts and force directions of the implant based on the design requirements to establish load-bearing characteristics; performing stress strength analysis on the load-bearing characteristics to generate a strength requirement distribution; evaluating the stress shielding effect of the strength requirement distribution to determine a low-modulus constraint range; and constructing gradient structural constraints based on the strength requirement distribution and the low-modulus constraint range.

[0021] Based on design requirements, the load-bearing areas and force directions of the implant are determined, establishing load-bearing characteristics. The primary load-bearing area of ​​the acetabular cup is located in the upper lateral quadrant of the cup body. This area bears concentrated pressure from the femoral head during standing and walking. The patient's activity level directly affects the load amplitude setting in this area according to the design requirements. The load-bearing characteristics define the spatial range of the primary load-bearing area as a fan-shaped region extending 45 degrees outward from the top of the acetabular cup, with an area of ​​approximately 30% of the outer surface of the cup. The force direction is represented in vector form in the load-bearing characteristics. In the standing posture, the primary load direction is inclined inward at approximately 15 degrees along the axis of the acetabular cup. In the walking posture, the load direction oscillates periodically with the gait cycle, with an anterior-posterior swing amplitude of approximately ±10 degrees. In the design requirements, the force direction changes more drastically for patients with high activity levels, and the load-bearing characteristics correspondingly expand the coverage of the load direction. In addition to the primary load-bearing area, the load-bearing characteristics also define secondary load-bearing areas and low-load areas. The secondary load-bearing areas are located in the anterior and posterior edge regions of the acetabular cup and bear shear forces, while the low-load areas are located in the central region of the cup bottom and mainly bear uniformly distributed pressure. The load-bearing characteristics are presented in the form of a three-dimensional cloud map, showing the load intensity level and force direction distribution of each part. Red indicates the high load area, yellow indicates the medium load area, and green indicates the low load area.

[0022] A strength requirement distribution is generated by performing stress and strength analysis on the load-bearing characteristics. The main load-bearing parts are marked as high-load areas in the load-bearing characteristics. The peak stress in this area reaches 180-250 MPa according to finite element calculations. The strength requirement distribution accordingly sets the lower limit of material strength in this area to 450 MPa to ensure a safety factor of 2. The finite element model sets boundary conditions based on the load direction and load amplitude in the load-bearing characteristics. The mesh uses second-order tetrahedral elements, and the element size is refined to 0.2 mm in the high-load area to improve calculation accuracy. The strength requirement distribution divides the implant into several strength level regions. The first-level strength region corresponds to the main load-bearing parts in the load-bearing characteristics, requiring a material yield strength greater than 450 MPa; the second-level strength region corresponds to the secondary load-bearing parts, requiring a material yield strength greater than 300 MPa; and the third-level strength region corresponds to the low-load parts, requiring a material yield strength greater than 150 MPa. The periodic change of the load direction in the load-bearing characteristics is converted into fatigue strength requirements in the strength requirement distribution. The fatigue limit of the high-load area is set to 350 MPa to meet the requirement of 50 million cycle life. The strength requirement distribution also considers the impact of stress concentration. Regions with abrupt changes in load direction in the load-bearing characteristics are given a strength margin of 1.5 times in the strength requirement distribution. The spatial boundaries of each strength level region are marked in the form of isosurfaces in the strength requirement distribution, forming a strength gradient that gradually decreases from the outer surface of the implant to the interior.

[0023] A stress shielding effect assessment was conducted on the strength requirement distribution to determine the low modulus constraint range. An excessively high elastic modulus of the implant causes loads to be preferentially transferred through the implant rather than through the surrounding bone tissue. The strength requirements of each region in the strength requirement distribution need to be considered in conjunction with modulus constraints. The elastic modulus range of bone tissue is 15-20 GPa for cortical bone and 0.1-2 GPa for cancellous bone. The elastic modulus of traditional titanium alloy implants is approximately 110 GPa, a difference of 5-10 times, which is the fundamental cause of stress shielding. The low modulus constraint range sets upper modulus limits for different strength levels within the strength requirement distribution. The upper modulus limit for the first-level strength zone is set at 30 GPa to ensure load-bearing capacity; the upper modulus limit for the second-level strength zone is set at 15 GPa to approximate the cortical bone modulus; and the upper modulus limit for the third-level strength zone is set at 5 GPa to approximate the cancellous bone modulus. The third-level strength zone in the strength requirement distribution is mainly located at the contact interface between the implant and cancellous bone. The low modulus constraint range sets the strictest modulus limit in this region to promote stress transfer to the bone tissue. The low-modulus constraint zone also sets a lower modulus limit to ensure minimum load-bearing capacity. The lower modulus limit for the first-level strength zone is 15 GPa, for the second-level strength zone it is 8 GPa, and for the third-level strength zone it is 1 GPa. The strength requirement distribution corresponds spatially to the low-modulus constraint zone. The high-strength zone allows for higher modulus, while the low-strength zone requires lower modulus. Together, they constrain the mechanical performance window of each region of the implant.

[0024] Gradient structural constraints are constructed based on the strength requirement distribution and the low modulus constraint range. In the strength requirement distribution, the primary strength zone requires a material yield strength greater than 450 MPa, while the low modulus constraint range allows a modulus range of 15-30 GPa. These two constraints are integrated into the design window of the core dense zone within the gradient structural constraints. Zirconium alloy has a yield strength of approximately 900 MPa, possesses good load-bearing capacity and biocompatibility, and its equivalent modulus can be controlled to a target range matching bone tissue through reasonable material proportions and pore structure design. The gradient structural constraints set target parameters according to the load-bearing and modulus matching requirements of each region. The target porosity range for the core dense zone is 0-30%, and the target modulus range is 15-30 GPa to ensure load-bearing capacity. This region, located in the inner layer of the implant, primarily bears the load transfer function. The target porosity range for the transition zone is 30-60%, and the target modulus range is 5-15 GPa to approach the cortical bone modulus. This region achieves a smooth transition of mechanical properties between the core dense zone and the outer porous zone. The target porosity range for the outer porous region is 60-80%, and the target modulus range is 1-5 GPa, approaching the modulus of cancellous bone. This region is in direct contact with bone tissue, and the low modulus design can effectively alleviate stress shielding and promote bone ingrowth. The fatigue strength requirement in the strength demand distribution is transformed into a minimum wall thickness constraint under the gradient structure constraint conditions. The wall thickness of the porous structure must not be less than 150 micrometers to ensure fatigue life. The above target parameters will be achieved in subsequent process optimization steps through the coordinated adjustment of material ratio and porous structure design. The matrix modulus is adjusted by the mixing ratio of zirconium alloy and titanium alloy, and the equivalent modulus is further reduced by the design of porosity and pore size. The gradient structure constraint conditions ultimately output four types of constraint parameters for each region: porosity range, modulus range, lower strength limit, and lower wall thickness limit.

[0025] Step S120: Perform strength-porosity-elastic modulus co-optimization on the gradient structure constraints to identify the optimal solution set, perform mechanical property fit screening on the optimal solution set to generate the optimal structural parameters, and delineate the gradient partition boundary to establish a partition parameter table for the optimal structural parameters.

[0026] Specifically, a collaborative optimization of strength, porosity, and elastic modulus is performed to identify the optimal solution set for the gradient structure constraints. There are complex coupling relationships among the three design variables. Increased porosity leads to a decrease in the equivalent modulus, which helps alleviate stress shielding, but simultaneously reduces strength, which is detrimental to load-bearing safety. The four types of constraint parameters in the gradient structure constraints limit the boundaries of the feasible design space. The multi-objective genetic algorithm NSGA-II is used to search for the Pareto optimal solution within the feasible space. The optimization objectives are set as minimizing the deviation between the equivalent modulus and the target bone tissue modulus, maximizing the structural strength safety factor, and maximizing pore connectivity. The optimal solution set is generated after the algorithm iterative convergence and contains 200-500 non-dominated solutions, each corresponding to a set of porosity-modulus-strength parameter combinations. The constraints on the core dense region in the gradient structure constraints are selected from the optimal solution set, with parameters ranging from 5-25% porosity, 20-30 GPa modulus, and 2.0-3.5 strength safety factor. The optimized solution set for the transition zone exhibits a parameter range of 35-55% porosity, 6-14 GPa modulus, and a strength safety factor of 1.5-2.5. The modulus value in this region falls near the cortical bone modulus. Among the gradient structure constraints, the low modulus constraint in the outer porous region is the most stringent. In the optimized solution set, the porosity in this region is concentrated at 65-75%, the modulus is 2-4 GPa, and the strength safety factor is 1.2-1.8. The optimized solution set is visualized as a three-dimensional scatter plot, with the horizontal axis representing porosity and the vertical axis representing the equivalent modulus. The color intensity indicates the magnitude of the strength safety factor.

[0027] The optimal structural parameters are generated by screening the mechanical properties of the optimized solution set. The fit evaluation index comprehensively considers three factors: modulus matching degree, strength margin, and manufacturing feasibility. The fit score of each solution in the optimized solution set is calculated and ranked. Modulus matching degree is defined as the reciprocal of the ratio of the equivalent modulus to the target bone tissue modulus; the closer the ratio is to 1, the higher the matching degree. The target bone tissue in the core dense region is cortical bone with a modulus of 17 GPa, and the target bone tissue in the outer porous region is cancellous bone with a modulus of 1.5 GPa. Solutions in the optimized solution set with a modulus matching degree higher than 0.8 are entered into the candidate pool. Approximately 35% of the solutions in the core dense region and approximately 50% of the solutions in the outer porous region meet this condition. Strength margin is defined as the difference between the strength safety factor and the minimum required value of 1.2. Solutions in the optimized solution set with a strength margin greater than 0.3 are given priority in the candidate pool. Manufacturing feasibility is assessed based on the minimum characteristic size of the pore structure. Solutions with a wall thickness less than 150 micrometers or a pore size less than 200 micrometers are marked as difficult to manufacture and have their priority reduced. Optimal structural parameters are selected from the candidate pool of each region, choosing the solution with the highest fit score. The optimal structural parameters for the core dense region are: porosity 15%, equivalent modulus 28 GPa, and strength safety factor 2.8; for the transition region, porosity 45%, equivalent modulus 9 GPa, and strength safety factor 2.0; and for the outer porous region, porosity 70%, equivalent modulus 3 GPa, and strength safety factor 1.5. The corresponding pore size and wall thickness are recorded simultaneously with the optimal structural parameters. The core dense region has a pore size of 200 micrometers and a wall thickness of 400 micrometers to ensure structural continuity and load-bearing strength under low porosity. The pore size and wall thickness of the transition region are adjusted gradually with changing porosity. The outer porous region has a pore size of 500 micrometers and a wall thickness of 180 micrometers.

[0028] In some embodiments, the step of defining the gradient partition boundary and establishing a partition parameter table for the optimal structural parameters includes: selecting a density parameter from the optimal structural parameters to establish a core dense region boundary; selecting a porosity parameter from the optimal structural parameters to establish an outer porous region boundary; defining a gradient transition region between the core dense region boundary and the outer porous region boundary; and performing interface bonding strength constraint verification on the core dense region boundary, the gradient transition region, and the outer porous region boundary to establish a partition parameter table.

[0029] The core-dense zone boundary was established by selecting density parameters from the optimal structural parameters. Density is calculated as 1 minus porosity; in the optimal structural parameters, a porosity of 15% in the core-dense zone corresponds to a density of 85%, ensuring sufficient load-bearing strength while achieving a certain degree of modulus reduction. The spatial range of the core-dense zone boundary was determined based on the spatial coordinates of the main load-bearing components associated with the optimal structural parameters. The inner 2-4 mm thickness of the 45-degree fan-shaped area on the outer side of the acetabular cup was included in the core-dense zone. The equivalent modulus of 28 GPa in the core-dense zone, as defined in the optimal structural parameters, is still higher than the cortical bone modulus of 17 GPa. A 0.5 mm thick transition layer was reserved on the outer surface directly in contact with bone tissue at the core-dense zone boundary for modulus gradient. The core-dense zone boundary was defined using isosurfaces; areas with a density higher than 80% were included within the core-dense zone, while areas with a density between 70-80% were included in the gradient boundary layer of the core-dense zone. The strength safety factor of 2.8 in the optimal structural parameters was uniformly distributed within the core-dense zone boundary, with no local weak points. The geometry of the core dense region boundary is approximately a local slice of an ellipsoidal shell, with the major axis along the main load transmission path and the minor axis perpendicular to the cup wall.

[0030] For example, the step of selecting porosity parameters from the optimal structural parameters to establish the outer porous region boundary includes: setting a target porosity range based on the porosity parameters to establish pore constraints; performing pore size adaptation analysis on the pore constraints to generate a pore size range; using the pore size range to perform connected pore structure control to generate connectivity requirements; and determining the outer porous region boundary based on the pore constraints, the pore size range, and the connectivity requirements.

[0031] Pore ​​constraints are established by setting a target porosity range based on porosity parameters. The porosity parameter is set to 70% in the optimal structural parameters. Considering manufacturing precision fluctuations and batch-to-batch material differences, the target porosity range is set to 65-75%, allowing a deviation of ±5%. The lower limit of 65% porosity is based on the requirement that the equivalent modulus should not exceed 5 GPa; a porosity below 65% will cause the modulus to rise beyond the constraint range. The equivalent strength corresponding to a porosity parameter of 70% is approximately 12% of the strength of dense materials. The porosity constraints verify whether this strength level meets the load-bearing requirements of the outer porous region. The verification results show that the strength safety factor of 1.5 meets the minimum requirement. The porosity constraints also specify the spatial uniformity requirements of the pores; the deviation between the local porosity and the overall porosity within any 10 mm³ volume must not exceed 8%, avoiding pore aggregation or sparse, uneven regions. Pore ​​constraints are written into the optimization model in the form of constraint equations. The porosity variable p must satisfy 0.65≤p≤0.75 and the local deviation Δp≤0.08.

[0032] A pore size adaptation analysis was performed on the pore constraints to generate a pore size range. The optimal pore size range for osteoblast ingrowth into porous structures is 300-800 micrometers, and the porosity of 65-75% in the pore constraints needs to match this biological requirement. There is a geometric relationship between porosity and pore size in the three-period minimal surface structure. The typical pore size of the Gyroid structure at 70% porosity is 480-550 micrometers, and the pore size range is set accordingly to 480-600 micrometers. In the pore constraints, the pore size is smaller (approximately 480-520 micrometers) when the porosity is close to the lower limit of 65%, and larger (approximately 550-680 micrometers) when the porosity is close to the upper limit of 75%. Taking into account the optimal pore size requirements for osteoblast ingrowth and manufacturing feasibility, the pore size range is set to 480-600 micrometers to cover the main operating conditions. The aperture range also needs to consider the forming accuracy limitations of additive manufacturing. The minimum resolvable aperture of laser selective melting (LSM) is approximately 200 micrometers, and the lower limit of the aperture range at 480 micrometers provides ample manufacturing margin. The uniformity requirement in porosity constraints is translated into aperture deviation constraints within the aperture range; the standard deviation of the aperture within the same zone must not exceed 15% of the average aperture. The aperture range is output as a parameter range, including three indicators: a lower aperture limit of 480 micrometers, an upper aperture limit of 600 micrometers, and an upper limit of 15% for aperture deviation.

[0033] The connectivity requirements are generated by controlling the interconnected pore structure within a specific pore size range. Pore connectivity directly affects the ingrowth depth of bone tissue and the efficiency of nutrient transport. Pores with a size range of 480-600 micrometers need to form a three-dimensional interconnected network structure. The connectivity requirements first specify a minimum connectivity rate for the pores; the proportion of pores that can be connected to a depth of 3 mm or more from any position on the implanted surface must not be less than 90%. Within the pore size range, larger pores are easier to connect. The theoretical connectivity rate is approximately 88% for a pore size of 480 micrometers and approximately 96% for a pore size of 600 micrometers. The 90% connectivity requirement can be met through reasonable pore size design. The connectivity requirements also specify a minimum channel cross-sectional area for the connected pores; the minimum channel cross-sectional area on any connected path must not be less than 0.1 mm², ensuring the passage capacity of bone cells and blood vessels. Within the pore size range, the lower limit of 480 micrometers corresponds to a single pore cross-sectional area of ​​0.16 mm². Considering the necking effect between adjacent pores, the minimum channel cross-sectional area is approximately 60% of the single pore cross-sectional area, or 0.1 mm², which just meets the lower limit of the connectivity requirement. The connectivity requirement is to ultimately output two indicators: a lower limit of 90% connectivity rate and a minimum channel cross-sectional area of ​​0.1 mm².

[0034] The boundary of the outer porous region is determined based on a combination of porosity constraints, pore size range, and connectivity requirements. The three indicators—porosity of 65-75%, pore size of 480-600 micrometers, and connectivity of 90%—jointly define the structural characteristics of the outer porous region. The spatial area satisfying these three indicators is the defined boundary of the outer porous region. A thickness range of 1-3 mm from the outer surface to the interior of the acetabular cup allows for the above parameter combination. The outer boundary of the outer porous region coincides with the outer surface of the acetabular cup, while the inner boundary is located 1-3 mm below the outer surface. The uniformity requirement in the porosity constraints dictates that the boundary of the outer porous region cannot extend to areas with abrupt changes in load-bearing characteristics; the position where the edge of the acetabular cup mates with the liner is excluded from the boundary of the outer porous region. The 15% pore size deviation constraint within the pore size range is most difficult to satisfy at the edge of the outer porous region boundary, and the transition between the pore structure at the boundary and adjacent zones requires special design. The required 90% connectivity is most easily achieved in the thickness direction of the outer porous region boundary. The connectivity along the tangential direction is slightly lower, but still meets the minimum requirement of 85%. The outer porous region boundary is ultimately output as a closed surface, and the internal region of the surface satisfies all the indicators of pore constraint, pore size range, and connectivity requirements.

[0035] A gradient transition zone is defined between the boundary of the core dense region and the boundary of the outer porous region. For example... Figure 2As shown, the gradient implant's partitioned structure includes a core dense region 2a, a gradient transition region 2b, and a lateral porous region 2c, distributed sequentially from the inner side to the outer side of the implant. The core dense region 2a, located in the inner layer of the acetabular cup, has a porosity of 15% and an equivalent modulus of 28 GPa, primarily responsible for load transfer. The lateral porous region 2c, located in the outer layer of the acetabular cup and in direct contact with bone tissue, has a porosity of 70% and an equivalent modulus of 3 GPa; its low modulus design helps alleviate stress shielding and promote bone ingrowth. The gradient transition region 2b lies between the two, with a porosity that gradually changes from 15% to 70% and an equivalent modulus that gradually changes from 28 GPa to 3 GPa. The spatial distance between the two boundaries is 5-10 mm, within which the gradient transition region achieves a continuous gradual change in porosity. The gradual change is achieved using linear interpolation, with porosity increasing at equal intervals along the normal direction from the boundary of the core dense region to the boundary of the lateral porous region, increasing by approximately 6-11 percentage points per millimeter of thickness. The equivalent modulus of the gradient transition zone gradually changes from 28 GPa to 3 GPa, with a modulus gradient of approximately 2.5-5 GPa / mm. This gradient value is controlled within a reasonable range to avoid stress concentration at the interface. Under the constraints of optimal structural parameters, the porosity abrupt change at the interface between the core dense zone boundary and the gradient transition zone does not exceed 10%, and the porosity abrupt change at the interface between the outer porous zone boundary and the gradient transition zone is also controlled within 10%. The thickness of the gradient transition zone varies slightly at different locations in the implant. The thickness of the transition zone below the main load-bearing area is 8-10 mm to achieve a smooth gradient, while the thickness of the transition zone in low-load areas is 5-6 mm to save space. The pore size and wall thickness of the gradient transition zone are adjusted according to the porosity gradient; the pore size is smaller and the wall thickness is larger at locations with lower porosity, and the pore size is larger and the wall thickness is smaller at locations with higher porosity.

[0036] A partition parameter table was established to verify the interface bonding strength constraints at the boundaries of the core dense region, the gradient transition region, and the outer porous region. The interface bonding strength between the three partitions determines the structural integrity of the implant during service; interface delamination is one of the main failure modes of porous implants. At the interface between the core dense region boundary and the gradient transition region, the porosity difference is 15%, and the interface bonding strength calculated by finite element analysis is 45 MPa, exceeding twice the safety margin of the interface shear stress. Within the gradient transition region, there is no obvious interface due to the continuous gradual change in porosity; however, stress concentration may occur at locations with excessive porosity gradients. The verification results show that the maximum equivalent stress is 85 MPa, lower than the allowable stress of the material. At the interface between the outer porous region boundary and the gradient transition region, the porosity difference is controlled within 10%, and the interface bonding strength is 38 MPa, meeting the safety requirements. The partition parameter table was formally established after the interface bonding strength verification was passed. The table structure includes seven fields: partition name, spatial boundary coordinates, porosity, pore diameter, wall thickness, equivalent modulus, and strength safety factor. The core dense region in the partitioning parameter table is recorded as follows: boundary coordinates stored in STL mesh format, porosity 15%, pore size 200 μm, wall thickness 400 μm, equivalent modulus 28 GPa, and strength safety factor 2.8. The gradient transition region is subdivided into 5 sub-layers along the thickness direction in the partitioning parameter table, with parameters for each sub-layer recorded independently for subsequent layered manufacturing. The outer porous region is recorded in the partitioning parameter table as follows: porosity 70%, pore size 500 μm, wall thickness 180 μm, equivalent modulus 3 GPa, and strength safety factor 1.5.

[0037] Step S130: Based on the partition parameter table, configure the laser selective melting equipment with dual powder feeders to establish a preliminary configuration, convert the partition parameter table into the mixing ratio requirements of titanium powder and zirconium alloy powder, screen the preliminary configuration for energy density matching degree through the mixing ratio requirements to generate usable configurations, and generate partition manufacturing instructions for usable configurations.

[0038] A preliminary configuration for a laser selective melting equipment with dual powder feeders is established based on a partition parameter table. For example... Figure 3As shown, the dual-powder-feeder laser selective melting equipment includes a laser 1, a scanning galvanometer 2, powder feeders A3 and B4, a powder mixer 5, a powder spreading scraper 6, a forming substrate 7, a forming chamber 8, a coaxial thermal imager 9, a coaxial high-speed camera 10, and a control system 11. Powder feeder A3 is loaded with zirconium alloy powder (Zr-2.5Nb), and powder feeder B4 is loaded with titanium alloy powder (Ti-6Al-4V). The two powders are mixed in a set ratio by the powder mixer 5 and then spread onto the forming substrate 7 by the powder spreading scraper 6. The laser beam emitted by the laser 1 is deflected by the scanning galvanometer 2 and then irradiates the powder bed surface for selective melting. The forming chamber 8 is filled with a high-purity argon protective atmosphere, with the oxygen content controlled below 100 ppm. The coaxial thermal imager 9 and the coaxial high-speed camera 10 share the laser beam path through a beam splitter, acquiring real-time images of the temperature field and morphology of the molten pool. The differentiated parameter requirements for the core dense zone, gradient transition zone, and outer porous zone in the partition parameter table are achieved by adjusting the powder feeding ratio of powder feeders A3 and B4 through control system 11. The initial configuration sets the basic process parameters of the equipment: laser power range of 150-400W, scanning speed range of 600-1200mm / s, layer thickness of 30 micrometers, and scanning spacing of 80 micrometers. The porosity and wall thickness parameters of each zone in the partition parameter table determine the scanning path planning method. The core dense zone uses a reciprocating scanning strategy to fill the solid area, while the outer porous zone uses a contour scanning strategy to delineate the pore boundaries. The initial configuration sets the maximum powder feeding rate of the powder feeders to 50g / min, and the two powder feeders can be controlled independently or in proportional linkage. After the initial configuration is completed, an equipment parameter file is generated, containing four modules: laser parameters, scanning parameters, powder feeding parameters, and atmosphere parameters.

[0039] The partitioning parameter table is converted into the mixing ratio requirements for titanium powder and zirconium alloy powder. The elastic modulus of titanium alloy is approximately 110 GPa, and that of zirconium alloy is approximately 95 GPa. Mixing them in different ratios can obtain an equivalent modulus between the two. Combining this with the porosity structure can further reduce the modulus to the target range. The target equivalent modulus of the core dense region in the partitioning parameter table is 28 GPa, with a porosity of 15%. The modulus requirement of the dense material can be derived by back-calculating the Gibson-Ashby formula: E_s = E / (1-p)^n, where E_s is the elastic modulus of the dense matrix material, E is the equivalent elastic modulus of the porous structure, p is the porosity, and n is the structure-related index, which is approximately 2. Substituting the values, we get E_s = 28 / (1-0.15)^2 = 38.8 GPa. This modulus value is lower than that of pure titanium and pure zirconium, requiring high porosity or the addition of a low-modulus phase. The mixing ratio requirement is to use 100% zirconium alloy powder in the core dense region to obtain a lower matrix modulus. The target equivalent modulus of the outer porous region in the zoning parameter table is 3 GPa, and the porosity is 70%. This leads to the required modulus of the dense material: E_s = 3 / (1-0.7)^2 = 33.3 GPa. The mixing ratio requirement is to use an 8:2 mixture of zirconium alloy and titanium alloy in the outer porous region to fine-tune the matrix modulus and improve biocompatibility. For the gradient transition region in the zoning parameter table, a gradual mixing ratio scheme is required, transitioning from 100% zirconium alloy at the boundary of the core dense region to 85% zirconium alloy + 15% titanium alloy at the end of the gradient transition region. The outer porous region uses a fixed ratio of 80% zirconium alloy + 20% titanium alloy. The mixing ratio requirement is output as a mapping table with the zoning index as the key and the powder ratio as the value. The core dense region corresponds to Zr:Ti = 100:0, the gradient transition region corresponds to Zr:Ti gradually changing from 100:0 to 85:15, and the outer porous region corresponds to Zr:Ti = 80:20.

[0040] In some embodiments, the step of using the mixing ratio requirement to screen the preliminary configuration for energy density matching to generate an available configuration includes: obtaining the powder ratio of each zone according to the mixing ratio requirement to establish a powder characteristic distribution; performing melting temperature analysis on the powder characteristic distribution to generate zone melting requirements; performing linear gradient control of energy density on the preliminary configuration according to the zone melting requirements to generate zone energy density configurations; and performing equipment adaptation screening based on the zone energy density configurations to generate available configurations.

[0041] The powder composition of each zone was determined based on the mixing ratio requirements to establish the powder characteristic distribution. For the core dense zone, with a powder composition of Zr:Ti = 100:0, the powder characteristic distribution recorded a powder density of 6.5 g / cm³, a thermal conductivity of 22 W / (m·K), and a specific heat capacity of 280 J / (kg·K). For the outer porous zone, with a powder composition of Zr:Ti = 80:20, the mixed powder characteristics were calculated using mass fraction weighting, and the powder characteristic distribution recorded a powder density of 5.9 g / cm³, a thermal conductivity of 19 W / (m·K), and a specific heat capacity of 310 J / (kg·K). The gradual mixing ratio in the gradient transition zone was transformed into a continuous change in characteristic parameters in the powder characteristic distribution, with the powder density gradually changing from 6.5 g / cm³ to 5.9 g / cm³ and the thermal conductivity gradually changing from 22 W / (m·K) to 19 W / (m·K). The powder characteristic distribution also includes powder flowability parameters. The Hall flow rate of zirconium alloy powder is 28 s / 50 g, and that of titanium alloy powder is 25 s / 50 g. The flow rate of the mixed powder falls between these two values. The flow rates corresponding to each proportion in the mixing ratio requirements all meet the requirements of the powder feeder. The powder characteristic distribution is stored in a three-dimensional field, and the powder characteristic parameters at each spatial location are determined according to the zone it belongs to and the proportions in the mixing ratio requirements.

[0042] Melting temperature analysis of the powder property distribution was used to generate zonal melting requirements. The melting point of zirconium alloy Zr-2.5Nb is 1855℃, and that of titanium alloy Ti-6Al-4V is 1660℃. The equivalent melting temperature of the mixture of these two powders falls between these two. The core dense region of the 100% zirconium alloy in the powder property distribution requires the highest melting temperature; therefore, the minimum molten pool temperature for this region is set at 2000℃ to ensure complete melting and good fusion quality. The equivalent melting temperature of the outer porous region of the 80% zirconium alloy + 20% titanium alloy in the powder property distribution is approximately 1815℃; therefore, the minimum molten pool temperature for this region is set at 1950℃. The equivalent melting temperature of the gradient transition region changes continuously with the gradual change in the powder property distribution; correspondingly, a temperature curve with a linear gradient from 2000℃ to 1950℃ is set for the zonal melting requirements. The zoned melting requirement also sets upper limits on the molten pool temperature to avoid excessive material evaporation and splashing. The upper limit for the zirconium alloy zone is 2400℃, and the upper limit for the mixed powder zone is 2300℃. The zoned melting requirement translates the temperature requirement into a preliminary estimate of the energy density range. The theoretically required energy density is calculated using the formula E_req=ρ×c×ΔT / (η×δ), where E_req is the minimum energy density required to melt the powder, ρ is the powder density, c is the specific heat capacity, ΔT is the temperature rise from room temperature to the melting temperature, η is the laser absorptivity (approximately 0.4), and δ is the melting depth (approximately 1.5 times the layer thickness).

[0043] Based on the zoned melting requirements, the initial configuration is linearly and gradually controlled to generate zoned energy density configurations. The volumetric energy density E_v = P / (v × h × t) is a key parameter characterizing the laser melting process, where P is the laser power, v is the scanning speed, h is the scanning interval, and t is the layer thickness. E_v must not be lower than the theoretically required energy density E_req calculated in the zoned melting requirements to ensure complete powder melting. In the zoned melting requirements, the core dense region needs to reach a melt pool temperature above 2000℃, corresponding to an energy density range of 120-160 J / mm³. The zoned energy density configuration selects 140 J / mm³ as the nominal value for this zone. In the initial configuration, combinations of laser power range of 150-400 W, scanning speed range of 600-1200 mm / s, layer thickness of 30 μm, and scanning interval of 80 μm are selected from the zoned energy density configurations. An energy density of 140 J / mm³ can be achieved through a combination of power of 280 W and speed of 833 mm / s. In the zoned melting requirement, the outer porous zone needs to reach a melt pool temperature of 1950℃, corresponding to an energy density range of 100-140 J / mm³. The zoned energy density configuration selects 120 J / mm³ as the nominal value, corresponding to a power of 230 W and a speed of 800 mm / s. The energy density of the gradient transition zone is set in the zoned energy density configuration to a linear gradient from 140 J / mm³ to 120 J / mm³, with a gradient step size of approximately 4 J / mm³ / layer. The energy density switching is completed in approximately 5 layers in the transition zone. The zoned energy density configuration is stored in a two-dimensional table format with the zone index and layer number as keys and power-speed parameter pairs as values.

[0044] Available configurations are generated through equipment adaptation screening based on partitioned energy density configurations. Equipment adaptation screening verifies whether the parameter combinations in the partitioned energy density configurations are within the equipment's operating range and checks whether the response speed of parameter switching meets real-time control requirements. The power of 280W and the speed of 833mm / s in the core dense region of the partitioned energy density configuration fall within the initially configured laser power range of 150-400W and scanning speed range of 600-1200mm / s; this parameter combination passes the adaptation screening. The power of 230W and the speed of 800mm / s in the outer porous region also meet the equipment range constraints, and this parameter combination is included in the available configuration. The gradual change in energy density in the gradient transition region is achieved by adjusting the power layer by layer in the partitioned energy density configuration. The power change rate from 280W to 230W is 10W / layer, and the equipment's power response time is less than 1ms; the available configuration confirms that this gradient rate is achievable. There is a risk of abrupt parameter changes at the boundary between high-energy-density and low-energy-density regions in the partitioned energy density configuration; the available configuration inserts 2-3 layers of buffer transition at the boundary to avoid drastic fluctuations in the molten pool state. The available configuration outputs a complete set of filtered and optimized parameters, including the power, speed, nominal energy density values ​​for each partition, and transition strategies at partition boundaries.

[0045] A partition manufacturing instruction is generated for the available configuration. The process parameters of each partition in the available configuration are converted into instruction codes executable by the equipment. The instruction format follows the control protocol of the laser selective melting equipment. The partition manufacturing instruction first defines the spatial boundary coordinates of the partition. The boundaries of the core dense region, gradient transition region, and outer porous region are inherited from the spatial boundary data associated with the available configuration and embedded in the instruction file in the form of an STL mesh. The power of 280W and the speed of 833mm / s for the core dense region in the available configuration are written into the parameter segment of the partition manufacturing instruction. The scanning path adopts a 67-degree rotational reciprocating strategy to homogenize the residual stress distribution. The power of 230W and the speed of 800mm / s for the outer porous region are associated with the scanning path of the pore structure in the partition manufacturing instruction. The pore boundary adopts a contour-first scanning strategy to ensure boundary clarity. The gradient parameters of the gradient transition region in the available configuration are expanded into a layer-by-layer instruction sequence in the partition manufacturing instruction. The power and speed of each layer are set independently, and the correspondence between the layer number and the parameter value is stored in the form of a lookup table. The zone manufacturing instruction also includes powder feeding control instructions, which set the powder feeding rate ratio of powder feeder A and powder feeder B in each zone according to the powder ratio recorded in the available configuration. The zone manufacturing instruction is finally output as two parts: a G-code file and a parameter configuration file. The G-code controls the scanning path and laser switch, while the parameter configuration file controls process parameters such as power, speed, and powder feeding ratio.

[0046] Step S140: Real-time monitoring of the molten pool status is performed according to the partitioned manufacturing instructions to identify forming defect risk points. The laser power and scanning speed are dynamically adjusted to generate a compensation parameter set based on the forming defect risk points.

[0047] In some embodiments, the step of real-time monitoring and identification of forming defect risk points based on the partitioned manufacturing instructions includes: initiating molten pool temperature monitoring and recording a temperature distribution sequence based on the partitioned manufacturing instructions; identifying abnormal temperature regions in the temperature distribution sequence to generate an abnormal temperature distribution; initiating molten pool morphology monitoring and recording a morphological feature sequence based on the partitioned manufacturing instructions; and abnormally associating the abnormal temperature distribution with the morphological feature sequence to generate forming defect risk points.

[0048] The temperature distribution sequence of the molten pool is recorded based on the partitioned manufacturing command. An infrared thermal imager is mounted above the laser scanning path, detecting mid-infrared waves of 3-5 micrometers. The optical window is specially coated to allow infrared light to pass through while blocking laser reflection. The laser activation signal in the partitioned manufacturing command synchronously triggers the thermal imager to acquire data. One frame of temperature image is acquired at each scanning point, with an image resolution of 256×256 pixels and a spatial resolution of approximately 10 micrometers / pixel. The temperature distribution sequence is stored in the scanning order, with each frame recording the temperature distribution of the molten pool area and its surrounding heat-affected zone. A single-layer scan generates approximately 50,000-80,000 frames, with a data volume of approximately 3-5 GB. The temperature distribution sequence corresponding to the scanning path of the core dense area in the partitioned manufacturing command exhibits a higher peak temperature and a wider heat-affected zone, while the temperature distribution sequence corresponding to the scanning path of the outer porous area has a slightly lower peak temperature but a more complex thermal cycle. The temperature distribution sequence is stored using a streaming write method, with raw data written to a high-speed solid-state drive in real time, followed by compression and feature extraction during post-processing. The temperature distribution sequence synchronously records the scanning position coordinates and timestamps corresponding to each frame of the image. This index structure is consistent with the morphological feature data to achieve spatiotemporal registration.

[0049] For example, the step of identifying temperature anomaly regions and generating a temperature anomaly distribution from the temperature distribution sequence includes: obtaining the temperature difference between adjacent sampling points through the temperature distribution sequence to establish a temperature gradient sequence; setting a partitioning temperature threshold for the temperature gradient sequence to generate a partitioning threshold; identifying anomaly regions in the temperature gradient sequence based on the partitioning threshold to generate overheated region markers and undermelted region markers; and integrating the overheated region markers and the undermelted region markers to generate a temperature anomaly distribution.

[0050] A temperature gradient sequence is established by obtaining the temperature difference between adjacent sampling points from the temperature distribution sequence. The spatial temperature gradient reflects the rate of temperature decrease at the edge of the molten pool. A larger gradient value indicates a clearer molten pool boundary and faster heat diffusion, while a smaller gradient value indicates a larger molten pool size and more severe heat accumulation. In each frame of the temperature distribution sequence, the temperature gradient is calculated radially outward from the center of the molten pool. The calculation method is the temperature difference between adjacent pixels divided by the pixel spacing, with the gradient value in °C / μm. The temperature gradient sequence stores two parameters for each frame: the maximum radial gradient and the average radial gradient. The maximum radial gradient of a normal molten pool is approximately 10-20 °C / μm, and the average radial gradient is approximately 5-10 °C / μm. The ratio of these two values ​​reflects the uniformity of the molten pool temperature distribution. Frames with irregularly shaped molten pools exhibit azimuth dependence in the temperature gradient sequence, with larger gradients in some directions and smaller gradients in others. This non-uniformity indicates molten pool stability issues or the coupling effect between the scanning path and the heat conduction direction. The time-temperature gradient is calculated from adjacent frames of the temperature distribution sequence, reflecting the transient rate of change of the molten pool temperature. During normal forming, the time gradient should be maintained within ±100℃ / ms, and this parameter is recorded synchronously in the temperature gradient sequence. The temperature gradient sequence and the temperature distribution sequence use the same frame index structure, and the two sets of data can be directly paired frame by frame and subjected to feature correlation analysis.

[0051] Temperature gradient sequences are divided into zones with set temperature thresholds. The core dense region is scanned using high energy density. With a large molten pool and slow cooling rate, heat conduction paths are continuous within the dense structure. The normal gradient range for this zone in the temperature gradient sequence is 8-15℃ / μm. The zone thresholds are set with an upper limit of 8℃ / μm for overheating (indicating a small gradient and an excessively large molten pool) and a lower limit of 20℃ / μm for underheating (indicating a large gradient and an excessively small molten pool). The outer porous region is scanned using lower energy density and contains numerous pore boundaries. Heat conduction paths are interrupted at these boundaries, leading to heat accumulation. The normal gradient range for this zone in the temperature gradient sequence is 12-22℃ / μm. The zone thresholds are set with an upper limit of 10℃ / μm for overheating and a lower limit of 28℃ / μm for underheating. These threshold ranges are appropriately widened compared to the core dense region to accommodate the heat conduction characteristics of the porous structure. In the temperature gradient sequence, the normal range of the gradient transition zone lies between the core dense zone and the outer porous zone. A gradient threshold is set for this region to accommodate layer-by-layer parameter changes; this threshold is calculated using linear interpolation based on the layer number. The zoning threshold also includes anomaly criteria for the time gradient: a temperature rise rate exceeding 500℃ / ms indicates a sudden increase in energy input possibly caused by defects in the powder bed; a temperature fall rate exceeding 300℃ / ms indicates excessive heat loss possibly caused by disturbances in the protective airflow. Both are considered thermal shock anomalies.

[0052] Based on partition thresholds, abnormal regions are identified in the temperature gradient sequence, generating overheated and undermelted region markers. Locations in the temperature gradient sequence with spatial gradients below the upper limit of the partition threshold for overheating are identified as overheating risk regions. A gradient that is too small indicates an excessively large molten pool size, slow heat diffusion, and potential excessive material evaporation. Overheated region markers record the coordinates, gradient values, and degree of deviation of these locations. In the core dense region, locations with gradients below 8℃ / μm account for approximately 2-5% of the total scan points. These locations are individually registered in the overheated region markers, with the deviation percentage calculated as (threshold - measured value) / threshold × 100%. Locations in the temperature gradient sequence with spatial gradients above the lower limit of the partition threshold for undermelting are identified as undermelting risk regions. An excessively large gradient indicates an excessively small molten pool size, insufficient energy input, and potential incomplete melting of the powder. Undermelted region markers record the coordinates, gradient values, and degree of deviation of these locations. Localized temperature anomalies are prone to occur at the pore boundaries of the outer porous region due to interrupted heat conduction paths. To reduce false alarms, a separate threshold is set for the area within twice the wall thickness of the pore boundary. The upper limit for overheating in this area is relaxed to 7℃ / μm, and the lower limit for undermelting is relaxed to 32℃ / μm. The number and spatial distribution characteristics of abnormal points in each zone are statistically analyzed for overheated and undermelted areas. The anomaly density is characterized by the number of abnormal points per square centimeter. During normal forming, the anomaly density should be less than 50 points / cm².

[0053] Overheated and undermelted area markers are integrated to generate a temperature anomaly distribution. These two types of markers may overlap or be adjacent in space. Overheating may precede undermelting within the same scan track. The temperature anomaly distribution categorizes these complex areas. Isolated anomalies within the overheated area marker are considered random fluctuations if there are no other anomalies within a 3×3 pixel radius. The temperature anomaly distribution downgrades their anomaly level to mild. Mild anomalies do not trigger parameter compensation but are only recorded. Random fluctuations are usually caused by uneven powder particle size distribution. When five or more consecutive adjacent points in the undermelted area marker exhibit undermelting characteristics, it is considered systematic undermelting. The temperature anomaly distribution upgrades its anomaly level to severe and triggers priority compensation. Systematic undermelting is often caused by improper process parameter settings or laser power attenuation. When overheated and undermelted area markers alternate within the same scan track with an alternation frequency exceeding twice per millimeter, it indicates a melt pool stability problem. The temperature anomaly distribution marks this scan track as an unstable region. Unstable regions require checking equipment status or powder bed quality. The temperature anomaly distribution algorithm statistically summarizes various anomalies. Indicators such as the proportion of overheating anomalies, the proportion of undermelting anomalies, and the clustering degree of anomaly spatial distribution are used to assess overall forming quality. The clustering degree is defined as the average area of ​​the connected regions formed by anomaly points. The temperature anomaly distribution algorithm ultimately outputs two parts: an anomaly location list for real-time compensation and an anomaly statistical report for forming quality evaluation.

[0054] The molten pool morphology monitoring and recording sequence is initiated according to the zoning manufacturing command. A coaxial high-speed camera captures visible light images of the molten pool with a resolution of 512×512 pixels and an exposure time of 10 microseconds to freeze the transient morphology of the molten pool. The camera and thermal imager share the same trigger signal to ensure synchronous acquisition. The laser activation signal in the zoning manufacturing command synchronously triggers the camera acquisition, with the acquisition frequency consistent with temperature monitoring at 10000fps. The timestamp deviation between the two sets of data is controlled within 0.1ms. The morphology feature sequence extracts features from each frame of the image, including parameters such as molten pool area, aspect ratio, roundness, and number of spatter particles. The feature extraction algorithm is based on image binarization and connected component analysis. The normal molten pool area in the core dense region is approximately 0.02-0.03 mm², the aspect ratio is approximately 1.2-1.5, and the roundness is approximately 0.7-0.9. The morphology feature sequence records the temporal evolution of these parameters, and the fluctuation range of these parameters reflects the forming stability. In the partitioned manufacturing command, the molten pool morphology of the outer porous zone is affected by the pore boundaries, resulting in large fluctuations in aspect ratio and low roundness. The morphological feature sequence sets differentiated normal ranges for this zone. The number of spatter particles is an important indicator for evaluating forming stability. The morphological feature sequence records the number of spatter particles larger than 20 micrometers in diameter in each frame; the normal value should be less than 5 particles per frame. Exceeding this value indicates excessive energy input or powder bed contamination. The morphological feature sequence and temperature distribution sequence use the same timestamp and location index, allowing for direct multi-source fusion analysis of the two sets of data.

[0055] Anomaly distributions in temperature are correlated with morphological feature sequences to generate forming defect risk points. Anomalies from a single data source may lead to false positives; correlation verification using multi-source data improves defect identification accuracy. The correlation verification employs a spatiotemporal window matching method with a window radius of 3 pixels and a time tolerance of 2 frames. If a location marked as overheated in the temperature anomaly distribution also exhibits increased melt pool area and increased spatter in the morphological feature sequence, the forming defect risk point confirms this location as a genuine overheating defect, and marks it as high confidence. If a location marked as undermelted in the temperature anomaly distribution also exhibits decreased melt pool area and abnormal aspect ratio in the morphological feature sequence, the forming defect risk point confirms this location as a genuine undermelted defect, and marks it as high confidence. Locations exhibiting anomalies in the morphological feature sequence but not marked in the temperature anomaly distribution may be false alarms from morphological monitoring or missed detections from temperature monitoring. The forming defect risk point includes these locations in the observation category, marks them as medium confidence, and does not trigger compensation but records them for future reference. Forming defect risk points classify confirmed defects according to their severity. Severe defects require immediate parameter compensation, moderate defects are recorded and adjusted uniformly before the next layer scan, and minor defects are only recorded without processing. The final output of forming defect risk points is a list of defect locations, with each record containing fields such as coordinates, defect type, severity, confidence level, and associated features.

[0056] In some embodiments, the step of dynamically adjusting the laser power and scanning speed to generate a compensation parameter set by triggering the forming defect risk point includes: identifying the defect type and defect location based on the forming defect risk point to establish a defect feature distribution; generating energy reduction compensation parameters for overheating type defects in the defect feature distribution; generating energy enhancement compensation parameters for undermelting type defects in the defect feature distribution; and integrating the energy reduction compensation parameters and the energy enhancement compensation parameters to generate a compensation parameter set.

[0057] Based on the identification of forming defect risk points, a defect feature distribution is established by identifying defect types and locations. Each record in the forming defect risk point list is classified and statistically analyzed according to defect type, with overheating and undermelting types summarized separately. Statistical indicators include quantity, density, and spatial clustering. The defect feature distribution presents the location of various defects in the form of a spatial distribution map, with overheating defects marked in red and undermelting defects marked in blue. The size of the marker indicates the severity of the defect, and the color intensity indicates the confidence level. Multiple adjacent defects of the same type in the forming defect risk points are merged into a defect region in the defect feature distribution. The region boundary is calculated using the convex hull algorithm, and defects within the region are uniformly compensated using the same strategy. The defect density of each partition is statistically analyzed in the defect feature distribution. The overheating defect density and undermelting defect density in the core dense region are calculated separately, and the outer porous region and gradient transition region are also statistically analyzed independently. The partition statistical results are used to evaluate the rationality of the process parameters for each partition. Forming defect risk points at the partition boundaries are separately marked in the defect feature distribution. Defects at these locations are often related to parameter switching rather than problems with the process parameters themselves, and need to be addressed by optimizing the transition strategy. The defect feature distribution is output in two forms: spatial distribution map and statistical report. The spatial distribution map is used for visual analysis, and the statistical report is used for quantitative evaluation.

[0058] Energy reduction compensation parameters are generated for overheating defects in the defect feature distribution. The essence of overheating defects is excessive energy input causing the molten pool temperature and size to exceed the normal range. The compensation strategy is to reduce laser power or increase scanning speed to reduce energy input per unit area. The energy reduction compensation parameters determine the compensation range based on the severity of the overheating defects in the defect feature distribution: mild overheating corresponds to a 5% reduction in power or a 5% increase in speed; moderate overheating corresponds to a 10% reduction in power or a 10% increase in speed; and severe overheating corresponds to a 15% reduction in power or a 15% increase in speed. A buffer transition zone is set at the boundary of the overheating defect region in the defect feature distribution within the energy reduction compensation parameters. The transition zone width is approximately 3-5 scan tracks. The compensation parameters gradually decrease from the defect center to the boundary to avoid abrupt parameter changes that could trigger new defects. Power reduction is preferred for compensation because power adjustment has a faster response time than speed adjustment and has no impact on the scanning path; a response time of less than 1ms allows for point-by-point compensation. If an isolated mild overheating defect occurs only once in the defect feature distribution, the energy reduction compensation parameter can be set to zero, i.e., no compensation is performed, to avoid over-adjustment leading to undermelting. The energy reduction compensation parameters are output in the form of a mapping table with the defect location as the key and the compensation amount as the value. The compensation amount records two items: the percentage change in power and the percentage change in velocity.

[0059] Energy compensation parameters are generated for undermelting defects in the defect feature distribution. The essence of undermelting defects is insufficient energy input leading to incomplete melting or poor fusion of the powder. The compensation strategy is to increase laser power or decrease scanning speed to increase energy input per unit area. The compensation parameters are determined based on the severity of the undermelting defects in the defect feature distribution: mild undermelting corresponds to a 5% increase in power or a 5% decrease in speed; moderate undermelting corresponds to a 10% increase in power or a 10% decrease in speed; and severe undermelting corresponds to a 15% increase in power or a 15% decrease in speed. For regions with continuous undermelting defects in the defect feature distribution, an overall compensation strategy is set in the energy compensation parameters. All scanning points within this region use the same compensation amount to ensure consistent forming, and a transition zone is also set at the region boundary. The upper limit of the energy compensation parameters is constrained by the maximum power of the equipment and the material evaporation threshold. The power must not exceed the initial configuration upper limit of 400W, and the energy density must not exceed the critical value corresponding to material evaporation, approximately 180J / mm³. If the upper limit is exceeded, the dwell time is extended or a remelting scan is added. In the defect feature distribution, undermelting defects located at pore boundaries may be characteristics of the pore design itself rather than process defects. Energy enhancement compensation parameters should be cautious in these locations, with the compensation magnitude halved to avoid pore blockage. Energy enhancement compensation parameters are output in the same format as energy reduction compensation parameters, maintaining consistent data structures for easy integration and processing.

[0060] The energy reduction compensation parameters and energy enhancement compensation parameters are integrated to generate a compensation parameter group. These two types of compensation parameters do not overlap spatially; it is impossible for the same location to require both energy reduction and energy enhancement compensation simultaneously. Any contradictions indicate a problem with the monitoring data, requiring manual verification. The compensation parameter group merges the energy reduction and energy enhancement compensation parameters into a unified parameter table based on their location index. The compensation type field distinguishes between energy reduction and energy enhancement, and the data format uses sparse matrix storage to save space. In the energy reduction compensation parameters, the power reduction amount is recorded as a negative value in the compensation parameter group, while in the energy enhancement compensation parameters, the power increase amount is recorded as a positive value. The sign convention facilitates parameter superposition calculations. The compensation parameter group also includes the triggering conditions and effective range of the compensation. Compensation for severe defects takes effect immediately and continues until the next inspection update; compensation for moderate defects takes effect before the start of the next scan layer; and compensation for minor defects can be delayed until the next scan track. The compensation parameter group is superimposed with the zonal manufacturing instructions. The original power value plus the compensation amount yields the actual executed power. The original speed value is adjusted accordingly based on the compensation requirements. The superposition calculation is completed in real time in the equipment controller. The historical records of the compensation parameter group are synchronously written to the process log file, supporting the traceability of forming quality and the optimization of process parameters.

[0061] Step S150: Detect and identify the continuity of interlayer components in the partition manufacturing instructions and compensation parameter group, identify the connecting sections, and gradually configure the connecting sections and mixing ratio requirements layer by layer to generate a gradient transition configuration. Based on the gradient transition configuration, refine the process parameters of the partition parameter table and output the forming control instructions.

[0062] Specifically, the interlayer composition continuity of the partitioned manufacturing instructions and compensation parameter groups is detected to identify transition sections. Excessive differences in powder composition between adjacent layers can lead to decreased interfacial bonding strength and residual stress concentration. When the compositional jump exceeds 5%, the interfacial bonding strength decreases by approximately 15%, and the transition section is marked as a layer transition location requiring special treatment. In the partitioned manufacturing instructions, the powder ratio at the boundary between the core dense region and the gradient transition region changes from Zr:Ti=100:0 to Zr:Ti=95:5, with a compositional jump of 5%. The transition section is determined to require a transition at this boundary. Within the gradient transition region, the compositional changes between layers are linearly gradual in the partitioned manufacturing instructions, with a single-layer compositional jump of approximately 4%, which is within an acceptable range; the transition section is not specially marked. Parameter adjustments in the compensation parameter group may alter local energy input, thus affecting fusion quality. When the energy density change exceeds 15%, the molten pool state changes significantly. The transition section is detected at locations where the compensation amplitude in the compensation parameter group exceeds 10% and marked as process transition points. The actual parameter sequence, resulting from the superposition of the zonal manufacturing instructions and the compensation parameter set, is checked layer by layer in the transition section. Interlayer interfaces where the energy density jump exceeds 15% are marked as energy transition points. The final output of the transition section includes a list of component transition points and a list of energy transition points. The two types of transition points require different transition strategies: component transition points are transitioned by adjusting the powder feeding ratio, while energy transition points are transitioned by adjusting the power and speed.

[0063] In some embodiments, the step of generating a gradient transition configuration by progressively varying the connection segment and the mixing ratio requirement includes: determining the number of transition layers based on the connection segment; establishing a ratio interval based on the starting ratio and ending ratio read from the mixing ratio requirement; proportionally allocating the ratio interval according to the number of transition layers to generate a progressive mixing ratio; and performing a component mutation suppression test on the progressive mixing ratio to generate a gradient transition configuration.

[0064] The number of transition layers is determined based on the transition zone. The abrupt change in composition at the transition point and the interfacial bonding characteristics of the material jointly determine the required number of transition layers. The larger the abrupt change, the more transition layers are required. The number of transition layers N = ΔC / 2, where ΔC is the percentage of compositional abrupt change. In the transition zone, at the core-dense region-transition region interface with a compositional abrupt change of 5%, the number of transition layers is set to 3, with each layer showing a compositional change of approximately 1.7%, which is within the safe range of material interfacial bonding. In the transition zone, at the transition region-porous region interface with a compositional abrupt change of 5%, the number of transition layers is set to 3, with each layer showing a compositional change of approximately 1.67%, which is within the safe range of material interfacial bonding. The number of transition layers at the energy transition point is determined based on the energy density abrupt change. An abrupt change of 15-20% corresponds to 2 transition layers, and an abrupt change of 20-30% corresponds to 3-4 transition layers. At the location where the compositional transition point and the energy transition point coincide in the transition zone, the number of transition layers is the larger of the two values ​​to simultaneously meet the requirements of compositional and energy transition. The physical thickness of the transition zone is obtained by multiplying the number of gradient layers by the layer thickness of 30 micrometers. The three layers at the core dense region-transition zone interface correspond to 90 micrometers, and the three layers at the transition zone-porous region interface also correspond to 90 micrometers. Both are within the allowable transition zone thickness range. If the transition zone thickness is too large, it will affect the mechanical property distribution of the partition.

[0065] Based on the mixing ratio requirements, a ratio range is established by reading the initial and final ratios. The initial ratio at the core dense region-transition region interface is read from the mixing ratio requirements as Zr:Ti=100:0, and the final ratio is Zr:Ti=95:5. The ratio range is defined as a 5 percentage point jump as the zirconium alloy percentage decreases from 100% to 95%. In the mixing ratio requirements, the initial ratio at the transition region-porous region interface is Zr:Ti=85:15, and the final ratio is Zr:Ti=80:20. The ratio range is defined as a decrease in the zirconium alloy percentage from 85% to 80%, and an increase in the titanium alloy percentage from 15% to 20%. The ratio range is stored in the form of interval endpoints and jump directions. The initial ratio corresponds to the lower layer number side of the transition section, and the final ratio corresponds to the higher layer number side. The jump direction determines the gradual increasing or decreasing trend. Although the ratios within the gradient transition region in the mixing ratio requirements change continuously, the ratio range is only established at the transition section. The ratios of each layer within the region follow the original gradual change pattern without additional settings. The ratio range and the number of gradient layers are used to determine the ratio increment of each layer. The ratio increment of the core dense area-transition area interface is (100%-95%) / 3 layers≈1.67% / layer. This increment value is less than the interface bonding safety threshold of 3%.

[0066] The proportion range is proportionally allocated according to the number of gradient layers to generate a layer-by-layer mixing ratio. The abrupt change in the proportion range is divided by the number of gradient layers to obtain the change in the proportion of a single layer. The change in the proportion of a single layer at the core dense region-transition region interface is 1.67%, which is less than the interface bonding safety threshold of 3%. The layer-by-layer mixing ratio starts from the initial ratio, and the change in the proportion of a single layer increases or decreases with each layer until the final ratio is reached. The three gradients at the core dense region-transition region interface are as follows: Layer 1 Zr:Ti=98.3:1.7, Layer 2 Zr:Ti=96.7:3.3, Layer 3 Zr:Ti=95:5. The three-layer transition region-porous region interface unfolds into three proportion values ​​in the layer-by-layer mixing ratio, gradually transitioning from Zr:Ti=85:15 to Zr:Ti=80:20, with the proportion of zirconium alloy decreasing by 1.67% and the proportion of titanium alloy increasing by 1.67% in each layer. The layer-by-layer mixing ratio is output as a sequence indexed by the layer number and the powder ratio as the value. The sequence length is equal to the number of gradient layers, and the corresponding suggested energy density value is also recorded in the sequence. Within the ratio range, when the transition direction is a decrease in the zirconium alloy proportion, the layer-by-layer mixing ratio follows a decreasing sequence; when the transition direction is an increase in the zirconium alloy proportion, the layer-by-layer mixing ratio follows an increasing sequence. The accuracy of the layer-by-layer mixing ratio is limited by the powder feeder resolution. The minimum adjustment step for the powder feed ratio is 1%. Amounts less than 1% in the layer-by-layer mixing ratio are rounded off, and the accumulated error after rounding is corrected in the last layer.

[0067] A compositional abruptness suppression test is performed on the layer-by-layer mixing ratio to generate a gradient transition configuration. This test ensures that the compositional difference between adjacent layers does not exceed the safety threshold of 3% for material interface bonding; exceeding this threshold may lead to the formation of brittle intermetallic compounds at the interface. The compositional difference between any two adjacent layers in the layer-by-layer mixing ratio is calculated one by one. The difference between layer 1 and layer 2 is 1.67%, and the difference between layer 2 and layer 3 is also 1.67%, both less than the safety threshold of 3%, thus passing the test. If the difference between any adjacent layer in the layer-by-layer mixing ratio exceeds 3%, the number of gradient layers is automatically increased, and the layer-by-layer mixing ratio is recalculated until the test passes. The upper limit for increasing the number of layers is twice the original value. The gradient transition configuration is established after passing the test and includes the complete sequence of layer-by-layer mixing ratios, the corresponding layer number range, and spatial coordinates. The compositional differences between the first and last layers and adjacent non-transition layers in the layer-by-layer mixing ratio are also included in the test. The difference between the first layer and the initial ratio should be less than 1.5 times the single-layer variation, and the difference between the last layer and the final ratio also meets this condition. The gradient transition configuration is output in the form of structured data, with fields including the transition segment identifier, number of gradient layers, layer-by-layer mixing ratio sequence, layer number range, test results, and recommended energy density value.

[0068] Based on the gradient transition configuration, the process parameters of the partition parameter table are refined to output forming control commands. The gradient layers in the gradient transition configuration are inserted at the partition boundaries of the partition parameter table, transforming the original abrupt boundaries into continuous gradient boundaries. The interface between the core dense region and the gradient transition region in the partition parameter table, originally a single-layer abrupt change, is expanded into a three-layer gradient after gradient transition configuration, and the forming control commands correspondingly add three layer parameter records. The layer-by-layer mixing ratio in the gradient transition configuration is converted into powder feeder control commands; Zr:Ti=98.3:1.7 corresponds to a powder feeder A rate of 49.2 g / min, a powder feeder B rate of 0.8 g / min, and the total powder feeding rate remains unchanged at 50 g / min. The energy density parameters are simultaneously refined according to the gradient transition configuration, and the power and speed of each gradient layer are set according to the melting requirements of the corresponding proportion in the powder characteristic distribution. The forming control commands expand the partition-level parameters of the partition parameter table into layer-by-layer parameters, with each layer record including five fields: layer number, powder proportion, laser power, scanning speed, and scanning path file index. The gradient transition strategy and compensation amount in the compensation parameter group are superimposed in the forming control command. The final power value is the base power plus gradient compensation plus defect compensation. The forming control command is output in two formats: G-code file and JSON parameter file. The G-code is used for equipment execution layer control, and the JSON file is used for host computer parameter monitoring and recording.

[0069] To implement the above-described method embodiments, a graded zirconium alloy hip implant optimization manufacturing method is proposed to achieve the corresponding functional and technical effects. See also... Figure 4 , Figure 4 This diagram illustrates a structural block diagram of a gradient zirconium alloy hip joint implant optimization manufacturing apparatus 400 provided in an embodiment of this application. For ease of explanation, only the parts relevant to this embodiment are shown. The gradient zirconium alloy hip joint implant optimization manufacturing apparatus 400 provided in this embodiment includes: The requirements analysis module 401 is used to obtain the design requirements of the hip joint implant, and to perform load-bearing performance and bone tissue mechanics matching analysis on the design requirements to establish gradient structural constraints. The optimization design module 402 is used to identify the optimal solution set by performing strength-porosity-elastic modulus collaborative optimization on the gradient structure constraints, to filter the optimal solution set by mechanical performance adaptability to generate the optimal structural parameters, and to delineate the gradient partition boundary of the optimal structural parameters to establish a partition parameter table. The process configuration module 403 is used to establish a preliminary configuration for the laser selective melting equipment with dual powder feeders based on the partition parameter table, convert the partition parameter table into a mixing ratio requirement for titanium powder and zirconium alloy powder, perform energy density matching degree screening on the preliminary configuration through the mixing ratio requirement to generate an available configuration, and generate a partition manufacturing instruction for the available configuration. The real-time monitoring module 404 is used to monitor the molten pool status in real time and identify forming defect risk points according to the partition manufacturing instructions, and to trigger the dynamic adjustment of laser power and scanning speed to generate a compensation parameter set through the forming defect risk points. The gradient forming module 405 is used to detect and identify the connection section between the interlayer composition of the partition manufacturing command and the compensation parameter group, generate a gradient transition configuration by gradually changing the connection section and the mixing ratio requirement layer by layer, and refine the process parameters of the partition parameter table according to the gradient transition configuration and output forming control commands.

[0070] The aforementioned gradient zirconium alloy hip implant optimization manufacturing apparatus 400 can implement a gradient zirconium alloy hip implant optimization manufacturing method according to the above method embodiments. The options in the above method embodiments are also applicable to this embodiment, and will not be detailed here. The remaining content of this application embodiment can be referred to the content of the above method embodiments, and will not be repeated in this embodiment.

[0071] The purpose of the above embodiments is to reproduce and derive the technical solution of the present invention by way of example, and to fully describe the technical solution, purpose and effect of the present invention. The purpose is to enable the public to have a more thorough and comprehensive understanding of the disclosure of the present invention, and not to limit the scope of protection of the present invention.

Claims

1. A method for optimizing the manufacturing of a gradient zirconium alloy hip implant, characterized in that, include: Obtain the design requirements for the hip joint implant, and perform load-bearing performance and bone tissue mechanics matching analysis on the design requirements to establish gradient structural constraints. The gradient structure constraint conditions are subjected to strength-porosity-elastic modulus co-optimization to identify the optimal solution set. The optimal structural parameters are generated by mechanical performance adaptation screening of the optimal solution set. The optimal structural parameters are then delineated by gradient partition boundary to establish a partition parameter table. Based on the partition parameter table, a preliminary configuration is established for the laser selective melting equipment with dual powder feeders. The partition parameter table is converted into a mixing ratio requirement for titanium powder and zirconium alloy powder. The energy density matching degree of the preliminary configuration is screened through the mixing ratio requirement to generate a usable configuration. A partition manufacturing instruction is generated for the usable configuration. Based on the partitioned manufacturing instructions, the molten pool status is monitored in real time to identify forming defect risk points. The forming defect risk points trigger the dynamic adjustment of laser power and scanning speed to generate a set of compensation parameters. The interlayer composition continuity detection is performed on the partition manufacturing command and the compensation parameter group to identify the connection section. The connection section and the mixing ratio requirement are configured layer by layer to generate a gradient transition configuration. Based on the gradient transition configuration, the process parameters of the partition parameter table are refined and forming control commands are output.

2. The method according to claim 1, characterized in that, The step of establishing gradient structural constraints by performing load-bearing performance and bone tissue biomechanical matching analysis on the design requirements includes: Based on the design requirements, the load-bearing parts and force directions of the implant are determined, and load-bearing characteristics are established. The load-bearing characteristics are subjected to stress strength analysis to generate a strength requirement distribution; The stress shielding effect of the strength requirement distribution is evaluated to determine the low modulus constraint range; Gradient structure constraints are constructed based on the intensity requirement distribution and the low modulus constraint interval.

3. The method according to claim 1, characterized in that, The step of defining gradient partition boundaries and establishing a partition parameter table for the optimal structure parameters includes: The density parameters are selected from the optimal structural parameters to establish the boundary of the core dense region; The porosity parameter is selected from the optimal structural parameters to establish the boundary of the outer porous region; A gradient transition region is defined between the boundary of the core dense region and the boundary of the outer porous region. A partition parameter table is established by verifying the interface bonding strength constraint of the boundary of the core dense region, the boundary of the gradient transition region and the boundary of the outer porous region.

4. The method according to claim 1, characterized in that, The step of filtering the initial configuration for energy density matching based on the mixing ratio requirements to generate usable configurations includes: Based on the required mixing ratio, the powder proportions for each zone are obtained to establish the powder characteristic distribution; The melting temperature analysis of the powder characteristic distribution generates the zonal melting requirements; Based on the zoned melting requirements, the initial configuration is subjected to linear gradient control of energy density to generate a zoned energy density configuration; Based on the partition energy density configuration, device adaptation screening is performed to generate available configurations.

5. The method according to claim 1, characterized in that, The step of real-time monitoring and identification of forming defect risk points based on the partitioned manufacturing instructions includes: The molten pool temperature monitoring and recording sequence is initiated according to the partition manufacturing instruction; Temperature anomaly regions are identified in the temperature distribution sequence to generate a temperature anomaly distribution; The molten pool morphology monitoring and recording sequence is initiated according to the partition manufacturing instruction; The abnormal temperature distribution is correlated with the morphological feature sequence to generate forming defect risk points.

6. The method according to claim 1, characterized in that, The method of dynamically adjusting the laser power and scanning speed to generate a compensation parameter set by triggering the forming defect risk point includes: Based on the identified forming defect risk points, defect types and locations are determined to establish a defect feature distribution. Energy reduction compensation parameters are generated for overheating type defects in the defect feature distribution; Generate energy-enhancing compensation parameters for under-melting type defects in the aforementioned defect feature distribution; The energy reduction compensation parameters and the energy increase compensation parameters are integrated to generate a compensation parameter group.

7. The method according to claim 1, characterized in that, The step of generating a gradient transition configuration by progressively varying the connection segment and the mixing ratio requirement includes: The number of gradient layers is determined based on the connecting section; Based on the required mixing ratio, the starting and ending ratios are read to establish a ratio range; The proportional range is proportionally and progressively allocated according to the number of gradient layers to generate a layer-by-layer mixing ratio. The component mutation suppression test is performed on the layer-by-layer mixing ratio to generate a gradient transition configuration.

8. The method according to claim 3, characterized in that, The step of selecting porosity parameters from the optimal structural parameters to establish the outer porous region boundary includes: Establish pore constraints by setting a target porosity range based on the porosity parameters; A pore size adaptation analysis is performed on the pore constraints to generate a pore size range; The required connectivity is generated by controlling the interconnected pore structure within the specified aperture range. The outer porous region boundary is determined based on the pore constraint, the pore size range, and the connectivity requirement.

9. The method according to claim 5, characterized in that, The step of identifying temperature anomaly regions and generating a temperature anomaly distribution from the temperature distribution sequence includes: A temperature gradient sequence is established by obtaining the temperature difference between adjacent sampling points using the temperature distribution sequence; The temperature gradient sequence is partitioned, and a partition threshold is generated by setting a partition temperature threshold. Based on the partitioning threshold, abnormal regions are identified in the temperature gradient sequence to generate overheated region markers and undermelted region markers. The overheated region markers and the undermelted region markers are integrated to generate an abnormal temperature distribution.

10. An optimized manufacturing apparatus for gradient zirconium alloy hip implants, characterized in that, include: The requirements analysis module is used to obtain the design requirements of the hip joint implant, and to perform load-bearing performance and bone tissue mechanics matching analysis on the design requirements to establish gradient structural constraints. The optimization design module is used to identify the optimal solution set by performing strength-porosity-elastic modulus collaborative optimization on the gradient structure constraints, to filter the optimal solution set by mechanical performance adaptability to generate the optimal structural parameters, and to delineate the gradient partition boundary of the optimal structural parameters to establish a partition parameter table. The process configuration module is used to establish a preliminary configuration for a laser selective melting equipment with dual powder feeders based on the partition parameter table, convert the partition parameter table into a mixing ratio requirement for titanium powder and zirconium alloy powder, screen the preliminary configuration for energy density matching degree based on the mixing ratio requirement to generate an available configuration, and generate a partition manufacturing instruction for the available configuration. The real-time monitoring module is used to monitor the molten pool status in real time and identify forming defect risk points according to the partition manufacturing instructions. The forming defect risk points trigger the dynamic adjustment of laser power and scanning speed to generate a compensation parameter set. The gradient forming module is used to detect and identify the connection section between the interlayer composition of the partition manufacturing command and the compensation parameter group, generate a gradient transition configuration by gradually configuring the connection section and the mixing ratio requirement layer by layer, and refine the process parameters of the partition parameter table according to the gradient transition configuration and output forming control commands.

Images