A Sampling Method for Comprehensive Performance Testing of TA5 Titanium Alloy Sheets

Abstract

The present invention discloses a sampling method for comprehensive performance testing of TA5 titanium alloy plates, which relates to the field of metal material performance testing. This method realizes the comprehensive detection of multiple indexes such as tensile properties, hardness, and impact toughness of the plates by scientifically dividing the plate area, optimizing the sampling size and quantity, and combining with dynamic adaptive wire cutting technology. The specific steps include: evenly dividing the plate into five regions A-E in the width direction, and dividing the rolling direction into three sections: front, middle, and rear. Priority is given to sampling in the middle sections B and D; determining the specimen size according to the performance test requirements, such as tensile splines, hardness specimens, and impact splines; using wire cutting technology, combining finite element stress prediction, machine vision defect recognition, and parameter dynamic compensation algorithms to ensure that the cutting path avoids high stress areas and surface defects and reduces damage; ensuring the specimen quality through grinding and surface treatment.

Description

Technical Field

[0001] The present invention relates to the field of performance testing of metal materials, and specifically to a sampling method for comprehensive performance testing of TA5 titanium alloy plates. Background Art

[0002] Due to its advantages such as low density, high strength, and good corrosion resistance, TA5 titanium alloy is widely used in many fields such as aerospace, shipbuilding, and chemical engineering. In practical applications, the performance of TA5 titanium alloy plates directly affects the quality and service life of products. For example, in the aerospace field, if TA5 titanium alloy plates with unqualified performance are used for the fuselage structural components of an aircraft, serious accidents may occur during flight due to the inability to withstand pressure; in the chemical engineering field, if the TA5 titanium alloy plates used to manufacture reaction kettles have insufficient corrosion resistance, it will cause leakage of the reaction kettle, leading to safety problems and economic losses.

[0003] At present, there are many deficiencies in the sampling methods for performance testing of TA5 titanium alloy plates. Traditional sampling methods often only focus on the testing of a few specific performances. For example, only the tensile performance is concerned, while other important performances such as hardness and impact toughness are ignored. In this way, the performance of TA5 titanium alloy plates cannot be comprehensively and accurately evaluated, resulting in problems that may be caused by certain performance defects of the plates in practical applications. At the same time, the existing sampling methods lack scientific and systematic standards in determining the sampling position, size, and quantity, and there are randomness and blindness. Different sampling positions may lead to large differences in test results, affecting the accurate judgment of material performance. Moreover, non-standard sampling quantities may make the test results unrepresentative and unable to truly reflect the performance of the entire batch of plates. In addition, traditional sampling methods cause greater damage to the plates during the sampling process, affecting the subsequent use of the remaining plates and resulting in waste of resources.

[0004] For example, a sampling method for comprehensive performance testing of titanium alloy plates with the publication number CN118329498A, although it adopts systematic planning, integrated calculation, and hierarchical numbering, its utilization rate of the central position of titanium alloy plates is relatively low. When performing tensile performance testing, yield performance testing, ductility performance testing, and strength testing on titanium alloy plates, the distribution area of its sampling positions is relatively concentrated, and it cannot comprehensively and accurately reflect the performance of the entire batch of plates, and the available utilization rate of the remaining plates is relatively low.

[0005] Moreover, the traditional wire cutting method uses fixed paths and parameters and cannot adapt to the problem of uneven internal stress distribution of the plates. When the cutting path passes through the rolling stress concentration area, microcracks are easily generated, resulting in distorted test results. In addition, the existing methods cannot automatically avoid surface defects. According to statistics, about 15% of the specimens need to be resampled due to defect interference, resulting in waste of resources.

[0006] Therefore, it is of great practical significance to develop a scientific, comprehensive, and standardized sampling method for the comprehensive performance testing of TA5 titanium alloy plates with less damage to the plates. Summary of the Invention

[0007] Aiming at the problems in the prior art, the present invention provides a sampling method for the comprehensive performance testing of TA5 titanium alloy plates to comprehensively and accurately evaluate the performance of TA5 titanium alloy plates, while reducing the damage to the plates and improving the resource utilization rate.

[0008] The technical solution adopted by the present invention to solve its technical problems is: a sampling method for the comprehensive performance testing of TA5 titanium alloy plates, including the following steps:

[0009] Determination of sampling position: According to the rolling direction and width of the plate, the plate is evenly divided into regions A, B, C, D, and E in the width direction, and equally divided into the front section, middle section, and rear section in the rolling direction. The priority sampling regions are determined as regions B and D in the middle section. The formula for calculating the width of the region is: ; The formula for calculating the length of the section is: ;

[0010] Determination of sampling size: The size of the tensile property test spline is determined as: length L = 200 mm, width W = 20 mm, and thickness T = the actual thickness of the plate; the size of the hardness test specimen is a square with a side length of 30 mm and a thickness of the actual thickness of the plate; the size of the impact toughness test spline is: length l = 55 mm, width w = 10 mm, and thickness t = the actual thickness of the plate;

[0011] Determination of the number of samples: 5 tensile property test splines are taken from different position combinations; 3 hardness test specimens are taken, with 1 in each of regions B, C, and D in the middle section; 5 impact toughness test splines are taken and distributed at different key positions;

[0012] Sampling operation: Sampling is carried out by wire cutting. The cutting speed is controlled at 5 - 10 mm / min, and the cutting current is controlled at 1 - 2 A. After cutting, the specimens are polished, and the grit sizes of the polishing sandpapers are 200 mesh, 400 mesh, 600 mesh, and 800 mesh in sequence;

[0013] Among them, during the wire cutting process, a dynamic adaptive cutting path planning method is adopted, including the following steps:

[0014] a) A plate stress distribution prediction module based on finite element analysis to generate an optimal cutting path in real time;

[0015] b) A machine vision defect recognition module to automatically avoid the surface defect areas;

[0016] c) A cutting parameter dynamic compensation algorithm to adjust the cutting speed and current according to the plate thickness and local stress.

[0017] Specifically, in the step of determining the sampling position, for plates with special requirements, the sampling area is adjusted according to the stress direction and the key attention area during their use.

[0018] Specifically, the different position combinations of the tensile property test spline include different combinations of the front section, middle section, rear section and areas B and D.

[0019] Specifically, after the hardness test specimen is polished, the surface flatness needs to be detected, and the flatness error is controlled within ±0.05 mm.

[0020] Specifically, after the impact toughness test spline is cut, the notch needs to be specially processed, with the notch depth of 2 mm and the notch angle of 45°.

[0021] Specifically, before sampling with the wire cutting equipment, the equipment accuracy needs to be calibrated to ensure that the cutting accuracy error is controlled within ±0.1 mm.

[0022] Specifically, during the grinding process, every time the sandpaper is changed, the surface of the specimen needs to be cleaned to avoid the influence of the grinding particles remaining from sandpapers with different mesh numbers on the grinding effect.

[0023] Specifically, for TA5 titanium alloy plates with a thickness greater than 10 mm, the width W of the tensile property test spline is adjusted according to the formula W = thickness T × 1.5.

[0024] Specifically, when the sampling method is applied to the performance consistency detection of TA5 titanium alloy plates in different production batches, the plates in each batch are sampled and tested according to the same sampling rules.

[0025] Specifically, the dynamic adaptive cutting path planning method includes the following steps:

[0026] a) Based on the plate stress distribution prediction module of finite element analysis, a three-dimensional stress model is established to predict that the cutting deformation amount ≤ 0.03 mm, and a spiral or "Z"-shaped cutting path is generated;

[0027] b) The machine vision defect recognition module uses the YOLO algorithm to detect surface defects. When the defect area > 2 mm², a buffer zone radius R = 2 - 5 mm is generated;

[0028] c) The cutting parameter dynamic compensation algorithm: when the local stress > 800 MPa, the cutting speed is reduced to 3 - 5 mm / min, the current is increased to 2.0 - 2.5 A, and when the thickness T > 15 mm, the current is increased by 0.3 A.

[0029] The beneficial effects of the present invention:

[0030] (1)The sampling method for comprehensive performance testing of TA5 titanium alloy plates according to the present invention can comprehensively consider the performance differences in different regions of the plates by scientifically dividing the sampling positions, test various performances such as tensile performance, hardness, impact toughness, etc., and comprehensively evaluate the performance of TA5 titanium alloy plates.

[0031] (2)The sampling method for comprehensive performance testing of TA5 titanium alloy plates according to the present invention makes the test results more representative through reasonable sampling sizes and quantities, can accurately reflect the performance of the entire batch of plates, and reduces misjudgment caused by test errors.

[0032] (3)The sampling method for comprehensive performance testing of TA5 titanium alloy plates according to the present invention effectively reduces the damage to the plates and specimens by using wire cutting and controlling cutting parameters, as well as subsequent grinding treatment, improves the availability rate of the remaining plates, and reduces costs.

[0033] (4)The sampling method for comprehensive performance testing of TA5 titanium alloy plates according to the present invention has clear operation standards and procedures, is convenient for popularization and application, and different operators can obtain relatively consistent test results by sampling according to this method, improving the reliability and comparability of the tests.

[0034] (5)The sampling method for comprehensive performance testing of TA5 titanium alloy plates according to the present invention can reduce the incidence of microcracks during cutting through dynamic adaptive cutting path planning, and control the verticality error of the cut to within ±0.05°, significantly improving the quality of the specimens.

[0035] (6)The sampling method for comprehensive performance testing of TA5 titanium alloy plates according to the present invention combines defect recognition and path optimization technologies to improve the effective sampling rate and reduce the material loss cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The present invention will be further described below with reference to the drawings and embodiments.

[0037] Figure 1 is a schematic diagram of the plate area division provided by the present invention;

[0038] Figure 2 is a flow chart of the dynamic adaptive cutting path planning provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0039] In order to make the technical means, creative features, achieved purposes and effects of the present invention easy to understand, the present invention will be further described below in conjunction with specific embodiments.

[0040] As Figure 1 - Figure 2 shown, the sampling method for comprehensive performance testing of TA5 titanium alloy plates according to the present invention includes the following steps:

[0041] Sampling location determination: For TA5 titanium alloy plates, the plates are divided into multiple regions according to the rolling direction and width of the plates. In the width direction of the plate, 5 regions are evenly divided from the edge to the center, and are respectively marked as regions A, B, C, D, and E; in the rolling direction, the plate is equally divided into 3 segments, namely the front segment, the middle segment, and the rear segment. The sampling location is preferably selected in regions B and D of the middle segment because the deformation in these two regions is relatively uniform during rolling and the performance is more representative. The formula for calculating the region width is: ; The formula for calculating the segment length is: . For plates with special requirements, the sampling regions can be flexibly adjusted according to the stress direction and the key attention regions during their use.

[0042] Sampling size determination: The dimensions of the tensile property test specimen are set as: length L = 200 mm, width W = 20 mm, and thickness T = the actual thickness of the plate. It also includes the adjustment method for the width of the tensile property test specimen. For TA5 titanium alloy plates with a thickness greater than 10 mm, the width W of the tensile property test specimen is adjusted according to the formula W = thickness T × 1.5. The dimensions of the hardness test specimen are a square with a side length of 30 mm and a thickness of the actual thickness of the plate. The dimensions of the impact toughness test specimen are: length l = 55 mm, width w = 10 mm, and thickness t = the actual thickness of the plate.

[0043] Sampling quantity determination: 5 tensile property test specimens are taken, from different position combinations respectively, such as 1 in region B of the middle segment, 1 in region D of the middle segment, 1 in region B of the front segment, 1 in region D of the front segment, and 1 in region D of the rear segment. 3 hardness test specimens are taken, with 1 in each of regions B, C, and D of the middle segment respectively. 5 impact toughness test specimens are taken, also distributed at different key positions. When this sampling method is applied to the performance consistency detection of TA5 titanium alloy plates in different production batches, the plates of each batch are sampled and tested strictly according to the same sampling rules.

[0044] Sampling operation: Advanced slow wire electrical discharge machining is used for sampling. The cutting speed is precisely controlled at 5 - 10 mm / min, and the cutting current is stably controlled at 1 - 2 A to minimize the thermal influence and mechanical damage to the specimen during the cutting process. Before cutting, a high-precision laser calibration device is used to calibrate the cutting equipment to ensure that the cutting precision error is controlled within ±0.1 mm. After cutting, the specimen is finely polished. Sandpapers with 200 mesh, 400 mesh, 600 mesh, and 800 mesh are used in sequence to remove the cutting marks and oxide layers on the surface. During the polishing process, every time the sandpaper is changed, an ultrasonic cleaning device is used to clean the surface of the specimen to avoid the influence of residual polishing particles of different mesh numbers on the polishing effect. For the impact toughness test specimen, the notch needs to be specially processed after cutting. A high-precision electrical discharge machining equipment is used to make the notch with a depth of 2 mm and an angle of 45°. After the hardness test specimen is polished, a high-precision laser flatness detector is used to detect the surface flatness to ensure that the flatness error is controlled within ±0.05 mm. In addition, before and during sampling, non-destructive testing techniques such as ultrasonic flaw detection are used to detect the plate and the sampled specimen to timely discover possible internal defects and ensure the accuracy of the test results.

[0045] Furthermore, a dynamic adaptive cutting path planning method is adopted:

[0046] Before cutting, a three-dimensional stress model of the plate is established through finite element analysis to predict the deformation amount caused by stress release during cutting (error ≤ 0.03 mm);

[0047] Based on the stress cloud map, a "Z"-shaped cutting path is automatically generated, preferentially avoiding high stress gradient areas;

[0048] An industrial camera is integrated to real-time collect the surface image of the plate, and defects (such as scratches and pits) are identified through the YOLO algorithm. When the defect area exceeds 2 mm², the path is automatically adjusted;

[0049] A fuzzy control algorithm is used to dynamically adjust the cutting parameters: when the detected local stress > 800 MPa, the cutting speed is reduced to 3 mm / min and the current is increased to 2.5 A;

[0050] After cutting, the perpendicularity of the cut is detected by a laser displacement sensor. When the deviation > 0.1°, secondary corrective cutting is triggered.

[0051] Among them, Figure 2 is the flow chart of dynamic adaptive cutting path planning, showing how to dynamically adjust the cutting path according to the stress distribution of the plate and the surface defect situation in the sampling operation step S4, and Figure 1 is closely coordinated with the plate area division and other sampling operation processes.

[0052] For the module of predicting the stress distribution of sheet metal in finite element analysis:

[0053] Among them, 3D modeling:

[0054] Based on the geometric parameters of the sheet metal (length × width × thickness), a 3D solid model is established. Tetrahedral mesh division is adopted (element size ≤ 2 mm), and the mesh is refined in the key area (element size ≤ 0.5 mm).

[0055] Input the material parameters of TA5 titanium alloy: elastic modulus E = 110 GPa, Poisson's ratio ν = 0.34, coefficient of thermal expansion α = 8.6×10⁻ 6 / °C.

[0056] Boundary condition setting

[0057] Constraints for simulating the rolling process: Fix the nodes at the bottom of the sheet metal and apply a displacement load in the rolling direction (speed 5 - 15 mm / s).

[0058] Consider the influence of the temperature field: Set the initial temperature to 20°C, and the heat flux density q = 5×10 6 W / m² during the cutting process.

[0059] Solution and post-processing

[0060] Use ANSYS Mechanical APDL for explicit dynamic analysis, with a time step Δt = 1×10⁻ 5 s.

[0061] Extract the equivalent plastic strain (PEEQ) and the Mises stress nephogram, and identify the high-stress area (σ ≥ 850 MPa).

[0062] Generate the stress gradient distribution curve and determine the sensitive area of the cutting path (gradient > 150 MPa / mm).

[0063] Output the 3D stress field distribution matrix of the sheet metal in real time (accuracy ±3%), and automatically generate the cutting path optimization coefficient K (K = σ / σ0, where σ0 is the average stress).

[0064] For the machine vision defect recognition module:

[0065] Among them, image acquisition and preprocessing:

[0066] Use a linear array CCD camera, combined with a parallel light source (wavelength 532 nm) to obtain the surface image of the sheet metal.

[0067] Adopt median filtering to eliminate noise, and extract contour features through Canny edge detection.

[0068] Defect classification and localization

[0069] Build a defect recognition model based on YOLOv5. The training set contains a large number of annotated images (5 types of defects such as scratches, pits, and inclusions).

[0070] The defect location accuracy reaches ±0.1 mm, and the detection speed is ≥20 frames per second.

[0071] Path avoidance algorithm

[0072] Establish a defect buffer model: when the defect diameter d ≤ 2 mm, the buffer radius R = 3 mm; when d > 2 mm, R = 2d.

[0073] Use the Dijkstra algorithm to generate a collision-free path, ensuring that the distance between the cutting path and the defect edge is ≥ R.

[0074] The defect recognition accuracy is 98.7%, the false alarm rate is <0.5%, and the path planning time is <0.5 seconds per meter.

[0075] For the cutting parameter dynamic compensation algorithm:

[0076] Among them, the speed compensation model:

[0077] The calculation formula for the cutting speed V: ;

[0078] Among them:

[0079] (benchmark speed)

[0080] (stress sensitivity coefficient)

[0081] (thickness compensation coefficient)

[0082] (material ultimate stress)

[0083] T is the thickness of the sheet (mm)

[0084] Current dynamic adjustment rule

[0085] When σ < 600 MPa, the current I = 1.2 A;

[0086] When 600 MPa ≤ σ < 800 MPa, the current I = 1.5 A;

[0087] When σ ≥ 800 MPa, the current I = 2.0 A;

[0088] When the thickness T > 15 mm, the current increases by 0.3 A.

[0089] Real-time feedback mechanism

[0090] Monitor the cutting resistance through a force sensor with an accuracy of 0.1 N, and trigger adaptive adjustment when the resistance fluctuation > 15%.

[0091] Adopt a fuzzy PID controller, and the adjusted parameters are as follows:

[0092] Proportional coefficient Kp = 1.2, integral coefficient Ki = 0.5, derivative coefficient Kd = 0.3.

[0093] The residual stress is reduced by more than 40%, the surface roughness Ra of the cutting surface ≤ 1.6 μm, and the thickness deviation is ±0.02 mm.

[0094] Module collaborative verification

[0095] Test conditions:

[0096] Plate specifications: 2000mm × 1000mm × 25mm TA5 titanium alloy

[0097] Defect type: Artificially prefabricated scratch (length 5mm, depth 0.3mm)

[0098] Stress concentration area: Central area in the rolling direction (σ = 950 MPa).

[0099] The test results are as follows in the table:

[0100]

[0101] Example 1, Preparation work: Select a batch of TA5 titanium alloy plates with specifications of length 2000mm, width 1000mm, and thickness 5mm. Prepare a slow wire cutting machine, a high-precision laser calibration device, a grinding device, an ultrasonic cleaning device, an electronic universal testing machine, and corresponding measuring tools, and conduct a preliminary non-destructive inspection of the plates using an ultrasonic flaw detector.

[0102] Determine the sampling positions: According to the above method, divide the width direction into 5 regions, each region with a width of 1000 / 5 = 200mm; divide the rolling direction into 3 segments, each segment with a length of 2000 / 3 ≈ 667mm. Mark the B and D regions in the middle section.

[0103] Sampling: Use the wire cutting equipment to cut according to the tensile property test spline size (length 200mm, width 20mm, thickness 5mm). Set the cutting speed to 8mm / min and the current to 1.5A. After cutting, conduct preliminary grinding with 200-mesh sandpaper to remove obvious cutting marks, and then put it into the ultrasonic cleaning device to clean and remove surface impurities.

[0104] Performance test: Conduct a tensile property test on the ground tensile specimen, and use an electronic universal testing machine for the test equipment, with a loading speed of 2mm / min.

[0105] Record data such as yield strength, tensile strength, elongation rate, etc., and organize them into the following table:

[0106]

[0107] Example 2, Preparation: TA5 titanium alloy plates of the same specifications as in Example 1, prepare hardness testing equipment, high-precision laser flatness detector, and ultrasonic cleaning device.

[0108] Determine the sampling location: Mark the positions of hardness testing specimens in areas B, C, and D in the middle section.

[0109] Sampling: Cut out square hardness testing specimens with a side length of 30 mm and a thickness of 5 mm. The cutting parameters are the same as in Example 1. After cutting, polish with 200-mesh, 400-mesh, 600-mesh, and 800-mesh sandpaper in sequence, and clean with the ultrasonic cleaning device after each polishing.

[0110] Performance testing: Use a Rockwell hardness tester for hardness testing. Test each specimen 3 times and take the average value. Use a laser flatness detector to detect the surface flatness of the specimen to ensure that the error is within ±0.05 mm.

[0111] The test results are as follows:

[0112]

[0113] Example 3, Preparation: Select plates of the same specifications, and prepare impact toughness testing equipment, high-precision electric discharge machining equipment, and ultrasonic cleaning device.

[0114] Determine the sampling location: Mark the positions of impact toughness test specimens at different locations such as area B in the front section, area D in the middle section, and area D in the rear section.

[0115] Sampling: Perform wire cutting according to the dimensions of the impact toughness test specimen (length 55 mm, width 10 mm, thickness 5 mm). The cutting parameters are the same as before. After polishing, conduct the test. After cutting, perform electric discharge machining on the notch to machine a notch with a depth of 2 mm and an angle of 45°, and clean with the ultrasonic cleaning device after processing.

[0116] Performance testing: Use an impact testing machine for testing, and the pendulum energy is 300 J.

[0117] The test results are as follows:

[0118]

[0119] Example 4, Preparation: Prepare multiple batches of TA5 titanium alloy plates produced in different batches with the same specifications. Prepare all relevant equipment, including non-destructive testing equipment.

[0120] Sampling: Samples of different batches of plates are taken according to the method of the present invention, including tensile, hardness, and impact toughness test specimens. Non-destructive testing is carried out before and after sampling.

[0121] Performance testing: The corresponding performance tests are carried out on the specimens of different batches, and the test results are compared with those of the traditional sampling method. It is found that the test results of the method of the present invention have less discreteness and can more accurately reflect the performance differences of different batches of plates. For example, for a certain batch of plates, the difference between the maximum and minimum tensile strengths tested by the traditional method is 50 MPa, while the difference by the method of the present invention is within 20 MPa. Through multi-batch comparative tests, the reliability and superiority of the method of the present invention are verified.

[0122] Example 5, Preparation for verifying the dynamic cutting path: The same as Example 1, a TA5 titanium alloy plate with a specification of 2000 mm × 1000 mm × 20 mm is selected. The plate is subjected to non-destructive testing using an ultrasonic flaw detector to confirm no macroscopic defects. Prepare a slow wire cutting machine (model: Sodick AQ750L), finite element analysis software (ANSYS Workbench 2022), an industrial camera (Keyence LV-4050), and a residual stress detector (Proto iXRD).

[0123] Specific implementation steps

[0124] Finite element stress analysis

[0125] Establish a three-dimensional model of the plate with a mesh size of 1 mm, and the key areas are encrypted to 0.5 mm.

[0126] Input the rolling process parameters: rolling temperature 850 °C, reduction 30%, rolling speed 10 mm / s.

[0127] The simulation results show that there is rolling stress concentration in the central area of the plate (σ_max = 950 MPa, stress gradient 200 MPa / mm).

[0128] Dynamic path planning

[0129] Generate a spiral cutting path based on the stress nephogram to avoid high-stress areas (the path is ≥ 50 mm away from the central area).

[0130] The integrated machine vision system identifies the surface of the plate and no defects that need to be avoided are found (defect area < 0.5 mm²).

[0131] Dynamic adjustment of cutting parameters

[0132] Use a fuzzy PID controller to adjust the parameters in real time:

[0133] Before entering the stress concentration area, the speed is reduced from 8 mm / min to 4 mm / min, and the current is increased from 1.5 A to 2.2 A;

[0134] The cutting fluid flow rate is increased by 20% (from 15 L / min to 18 L / min) to inhibit thermal deformation.

[0135] Testing and comparison

[0136] Cut 5 tensile specimens (dimensions: L = 200 mm, W = 20 mm) along the optimized path.

[0137] The traditional method uses straight-line cutting with parameters fixed at a speed of 8 mm / min and a current of 1.5 A.

[0138] Testing indicators: Residual stress (X-ray diffraction method), elongation (electronic universal testing machine).

[0139] Test results:

[0140]

[0141] Result analysis

[0142] Residual stress control

[0143] Dynamic cutting makes the cutting heat input more uniform by reducing the speed and increasing the current. The depth of the heat-affected zone is reduced from 0.15 mm to 0.09 mm, and the peak value of the residual stress is reduced by 42%.

[0144] Test data stability

[0145] The standard deviation of the elongation is reduced by 38.9%, indicating that the dynamic path planning effectively avoids the interference of stress concentration on the test results, and the data discreteness is significantly reduced.

[0146] Improvement of cut quality

[0147] The perpendicularity error is controlled within ±0.08°, which is better than ±0.15° of the traditional method, verifying the improvement of cutting accuracy by path optimization.

[0148] In this embodiment, by combining finite element analysis and dynamic path planning technology, the sampling problem in the rolling stress concentration area of thick plates (T = 20 mm) is successfully solved. Compared with the traditional method, the residual stress is reduced by 42%, and the test data stability is improved by 39%, demonstrating the significant advantages of the present invention in sampling of plates under complex stress states.

[0149] The basic principles, main features and advantages of the present invention have been shown and described above. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and the descriptions in the specification only illustrate the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and all these changes and improvements fall within the scope of the present invention claimed. The scope of the present invention claimed is defined by the appended claims and their equivalents.

Claims

1. A sampling method for comprehensive performance testing of TA5 titanium alloy plates, characterized in that, It includes the following steps: S1. Sampling position determination: According to the rolling direction and width of the sheet, the sheet is evenly divided into regions A, B, C, D, and E in the width direction, and equally divided into the front section, middle section, and rear section in the rolling direction. The priority sampling regions are determined as regions B and D in the middle section. The calculation formula for the region width is: The calculation formula for the section length is: S2. Sampling size determination: Determine the sizes of the tensile property test splines as follows: length L = 200 mm, width W = 20 mm, and thickness T = the actual thickness of the sheet; the size of the hardness test specimen is a square with a side length of 30 mm and a thickness of the actual thickness of the sheet; the size of the impact toughness test spline is: length l = 55 mm, width w = 10 mm, and thickness t = the actual thickness of the sheet; S3. Sampling quantity determination: Take 5 tensile property test splines from different position combinations; take 3 hardness test specimens, with 1 in each of regions B, C, and D in the middle section; take 5 impact toughness test splines distributed at different key positions; S4. Sampling operation: Use wire cutting for sampling, control the cutting speed at 5 - 10 mm / min, control the cutting current at 1 - 2 A. After cutting, polish the specimens, and the grit sizes of the polishing sandpapers are 200 mesh, 400 mesh, 600 mesh, and 800 mesh in sequence; Among them, during the wire cutting process, a dynamic adaptive cutting path planning method is adopted, which includes the following steps: a) A module for predicting the stress distribution of the sheet based on finite element analysis, which generates the optimal cutting path in real time; b) A machine vision defect recognition module, which automatically avoids the surface defect areas; c) A cutting parameter dynamic compensation algorithm, which adjusts the cutting speed and current according to the sheet thickness and local stress; In the S1 step, when determining the sampling position, for sheets with special requirements, the sampling area is adjusted according to the stress direction and key attention areas during their use; After polishing, the hardness test specimens also need to be subjected to surface flatness detection, and the flatness error is controlled within ±0.05 mm; After cutting, the impact toughness test splines need to be specially processed for the notches, with the notch depth of 2 mm and the notch angle of 45°; During the polishing process, each time the sandpaper is changed, the surface of the specimen needs to be cleaned to avoid the influence of the residual grinding particles of different grit sizes on the polishing effect; When the sampling method is applied to the performance consistency detection of TA5 titanium alloy sheets in different production batches, the sheets in each batch are sampled and tested according to the same sampling rules.

2. The sampling method for comprehensive performance testing of TA5 titanium alloy plates according to claim 1, wherein: The different position combinations of the tensile property test splines include different combinations of the front section, middle section, rear section, and regions B and D.

3. The sampling method for comprehensive performance testing of a TA5 titanium alloy sheet according to claim 1, characterized in that: In the S4 step, before sampling, the wire cutting equipment needs to be calibrated for equipment accuracy to ensure that the cutting accuracy error is controlled within ±0.1 mm.

4. A sampling method for comprehensive performance testing of TA5 titanium alloy plates according to claim 1, characterized in that: In the S2 step, it also includes the adjustment method for the width of the tensile property test splines: For TA5 titanium alloy sheets with a thickness greater than 10 mm, the width W of the tensile property test splines is adjusted according to the formula W = thickness T × 1.

5.

5. The sampling method for comprehensive performance testing of TA5 titanium alloy plates according to claim 1, characterized in that: In the S4 step, a dynamic adaptive cutting path planning method is adopted, which includes the following steps: a) A module for predicting the stress distribution of the sheet based on finite element analysis, which establishes a three-dimensional stress model, predicts that the cutting deformation amount ≤ 0.03 mm, and generates a spiral or "Z"-shaped cutting path; b) Machine vision defect recognition module, using the YOLO algorithm to detect surface defects, generating a buffer radius R = 2 - 5 mm when the defect area > 2 mm 2 ; c) Dynamic compensation algorithm for cutting parameters. When the local stress > 800 MPa, the cutting speed is reduced to 3 - 5 mm / min, the current is increased to 2.0 - 2.5 A, and when the thickness T > 15 mm, the current is increased by 0.3 A.

Images