An online sample mechanical property quantitative evaluation method, device and readable storage medium for direct energy deposition additive manufacturing
Patent Information
- Application Number
- CN202610931459.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-06-26
- Publication Date
- 2026-10-27
AI Technical Summary
然而，增材制造过程涉及复杂的非平衡物理冶金，极易产生气孔、未熔合等缺陷，导致构件力学性能退化，严重威胁极端服役工况下的结构完整性与安全性
[0015]本发明提供的一种用于直接能量沉积增材制造的在线样品力学性能定量评估方法、设备及可读存储介质，利用边缘共振、零群速度共振及厚度共振三种模态，实现了样品局部泊松比、波速及杨氏模量的多参数联合评估。该方法具有非接触、高空间分辨率的优点，相比于传统方法无需大范围扫描获取平均信息，仅需在局部检测点进行一次激励与接收即可完成定量评估，显著提升了检测效率与准确性。该方法可直接集成于直接能量沉积增材制造设备中，为功能梯度材料增材制造过程的实时在线力学性能监测提供了切实可行的解决方案。
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Figure CN122983223A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of nondestructive testing technology, and in particular to an online quantitative evaluation method, equipment, and readable storage medium for mechanical properties of samples used in direct energy deposition additive manufacturing. Background Technology
[0002] Functionally graded materials (FJCTs), with their spatially continuous variations in composition and microstructure, can synergistically optimize multiple conflicting properties, making them highly promising for applications in high-end manufacturing fields such as aerospace. Additive manufacturing technology, particularly direct energy deposition (DED), provides a novel pathway for their efficient and precise fabrication. However, the additive manufacturing process involves complex non-equilibrium physical metallurgy, which easily generates defects such as porosity and incomplete fusion, leading to degradation of the mechanical properties of components and seriously threatening structural integrity and safety under extreme service conditions. Existing optical, temperature, and acoustic monitoring methods for additive manufacturing are mostly limited to qualitative analysis and indirect observation. Parameters measured by traditional ultrasonic bulk wave or guided wave dispersion methods reflect the overall average along the propagation path, which cannot meet the current demand for accurate evaluation of Poisson's ratio, wave velocity, and Young's modulus of printed layers. Therefore, there is an urgent need for a method that can achieve quantitative characterization of multiple local parameters, enabling real-time online monitoring of the manufacturing process.
[0003] It should be noted that the information disclosed in this background section is intended only to enhance the understanding of the overall background of the present invention, and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention
[0004] To address the aforementioned issues, this invention provides an online quantitative evaluation method for the mechanical properties of samples used in direct energy deposition additive manufacturing. This method solves the problems in the prior art by utilizing local resonant frequencies to perform precise quantitative evaluation of additive manufacturing samples, thereby enabling real-time online monitoring of the manufacturing process.
[0005] This invention provides an online quantitative evaluation method for the mechanical properties of samples used in direct energy deposition additive manufacturing. The method includes the following steps: S100: On the current deposited layer in the additive manufacturing process, a broadband ultrasonic excitation is applied to stimulate the ultrasonic guided wave response in the sample; S200: Acquires ultrasonic guided wave signals from a local area of the sample, obtains time-domain waveforms containing multiple resonance modes, and performs short-time Fourier transform processing on the acquired ultrasonic guided wave signals to extract edge resonance frequencies, S1 mode zero group velocity resonance frequencies, and thickness resonance frequencies. S300: Combine the edge resonance frequency with the zero group velocity resonance frequency or thickness resonance frequency of the S1 mode respectively, and calculate the local Poisson's ratio of the sample by comprehensive inversion. S400: Obtain the local thickness of the sample, and calculate the local shear wave velocity and longitudinal wave velocity of the sample based on the relationship between Poisson's ratio, edge resonance frequency, S1 mode zero group velocity resonance frequency, thickness resonance frequency, shear wave velocity and longitudinal wave velocity. S500: Obtain the sample density and calculate the local Young's modulus of the sample based on the theoretical relationship between shear wave velocity, Poisson's ratio, sample density and Young's modulus.
[0006] Furthermore, in step S100, before exciting the ultrasonic guided wave response, the top surface of the sample is milled with a milling cutter to ensure the flatness of the sample surface.
[0007] Furthermore, in step S200, the extraction method of the edge resonance frequency, the zero group velocity resonance frequency of the S1 mode, and the thickness resonance frequency includes: identifying the energy accumulation peak corresponding to each resonance mode on the short-time Fourier transform spectrum, and using it as the resonance frequency of the current detection point.
[0008] Furthermore, in step S300, two Poisson's ratio values are calculated using the combination of edge resonance frequency and zero group velocity resonance frequency, and the combination of edge resonance frequency and thickness resonance frequency, respectively. The average of these two Poisson's ratio values is then taken as the final local Poisson's ratio of the sample.
[0009] Furthermore, based on the combination of the edge resonance frequency and the S1 mode zero group velocity resonance frequency, the first Poisson ratio is obtained by simultaneously solving the following formulas: in, The edge resonant frequency, Poisson's ratio, For transverse wave velocity, The zero-group velocity resonance frequency of mode S1. The proportionality coefficient related to Poisson's ratio. For longitudinal wave velocity, is the wave velocity ratio, and h is the structural thickness.
[0010] Furthermore, based on the combination of the edge resonant frequency and the thickness resonant frequency, the second Poisson ratio is obtained by simultaneously solving the following formulas: in, The edge resonant frequency, Poisson's ratio, For transverse wave velocity, For thickness resonant frequency, For longitudinal wave velocity, is the wave velocity ratio, and h is the structural thickness.
[0011] Furthermore, in step S400, the local shear wave velocity of the sample is calculated using the following formula: in The transverse wave velocity is the local transverse wave velocity of the sample. The local longitudinal wave velocity of the sample can be calculated by reverse calculation using the following formula: in This represents the shear wave velocity in a localized area of the sample.
[0012] Furthermore, in step S500, the Young's modulus of the sample is calculated according to the following formula: in, For Young's modulus, For density.
[0013] The present invention also provides an apparatus comprising: a memory for storing an embedded software program; and a processor for executing the embedded software program stored in the memory, wherein the embedded software program, when executed, implements the steps of the online sample mechanical property quantitative evaluation method for direct energy deposition additive manufacturing as described above.
[0014] The present invention also provides a computer-readable storage medium storing a program for implementing a method for quantitatively evaluating the mechanical properties of a sample. The program for implementing the method for quantitatively evaluating the mechanical properties of a sample is executed by a processor to implement the steps of an online method for quantitatively evaluating the mechanical properties of a sample for direct energy deposition additive manufacturing as described in any one of the above.
[0015] This invention provides a method, device, and readable storage medium for online quantitative evaluation of the mechanical properties of samples in direct energy deposition additive manufacturing. Utilizing three modes—edge resonance, zero-group velocity resonance, and thickness resonance—it achieves multi-parameter joint evaluation of local Poisson's ratio, wave velocity, and Young's modulus of the sample. This method offers advantages such as non-contact operation and high spatial resolution. Compared to traditional methods, it eliminates the need for large-scale scanning to acquire averaging information; quantitative evaluation can be completed with only a single excitation and reception at a local detection point, significantly improving detection efficiency and accuracy. This method can be directly integrated into direct energy deposition additive manufacturing equipment, providing a practical solution for real-time online monitoring of the mechanical properties of functionally graded materials in the additive manufacturing process.
[0016] Other features and beneficial effects of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects of the invention and other beneficial effects may be realized and obtained by means of the structures particularly pointed out in the description, claims, etc. Attached Figure Description
[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Unless otherwise specified, the positional relationships in the drawings described below are based on the direction shown by the components in the figures.
[0018] Figure 1 This is a flowchart illustrating a quantitative evaluation method for the mechanical properties of samples provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the material parameter inversion process provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of a detection system provided in an embodiment of the present invention. Detailed Implementation
[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. The technical features designed in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.
[0020] In the description of this invention, it should be understood that the terms "center," "lateral," "upper," "lower," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or component referred to must have a specific orientation or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more. Additionally, the term "comprising" and any variations thereof mean "at least comprising."
[0021] Please see Figure 1 , Figure 2 , Figure 3 , Figure 1 This is a flowchart illustrating a quantitative evaluation method for the mechanical properties of samples provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the material parameter inversion process provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of a detection system provided in an embodiment of the present invention. To achieve at least one or more of the aforementioned advantages, an embodiment of the present invention provides an online quantitative evaluation method for the mechanical properties of samples used in direct energy deposition additive manufacturing, as shown in the figure. This quantitative evaluation method for the mechanical properties of samples includes the following steps: S100: On the current deposited layer in the additive manufacturing process, a broadband ultrasonic excitation is applied to stimulate an ultrasonic guided wave response in the sample. This current deposited layer can refer to... Figure 3 The current print layer in the current layer.
[0022] In step S100, before exciting the ultrasonic guided wave response, the top surface of the sample is milled with a milling cutter to ensure the flatness of the sample surface. Specifically, the current deposition layer of the direct energy deposition additive manufacturing can be milled. Because the surface roughness and flatness of the additively manufactured sample are relatively large, direct laser ultrasonic testing will result in the guided wave signal failing to form a clearly discernible resonant energy peak in the short-time Fourier transform time spectrum, thus affecting the accurate extraction of the edge resonant frequency, zero-group velocity resonant frequency, and thickness resonant frequency. Milling the top surface of the sample with a milling cutter provides favorable conditions for subsequent non-contact laser testing.
[0023] A non-contact laser detection system was used to apply broadband ultrasonic excitation. The excitation source of this system was a 532 nm Q-switched Nd:YAG laser pulse emitter, and the applied excitation signal was a pulse signal with an excitation frequency of 10 Hz, used to excite a broadband ultrasonic guided wave response in the sample. This broadband excitation could simultaneously excite multiple guided wave modes, including the edge resonance mode, S1 zero-group velocity resonance mode, and thickness resonance mode required for subsequent processing. The laser pulse was focused on a local area of the sample surface, generating a broadband ultrasonic signal through the thermoelastic effect, without physical contact with the sample, thus avoiding interference from coupling agents in the additive manufacturing process.
[0024] S200: Acquires ultrasonic guided wave signals from a local area of the sample, obtains time-domain waveforms containing multiple resonant modes, and performs short-time Fourier transform processing on the acquired ultrasonic guided wave signals to extract edge resonant frequencies, S1 mode zero group velocity resonant frequencies, and thickness resonant frequencies.
[0025] In step S200, the ultrasonic guided wave signal of a local area of the sample can be acquired using a non-contact laser detection system. Specifically, the ultrasonic guided wave signal of a local area of the sample is acquired using a non-contact laser detection system. The receiving sensor uses a helium-neon (He-Ne) laser Doppler vibrometer with a wavelength of 632.8 nm and a bandwidth of 0 to 3 MHz, enabling non-contact acquisition of the ultrasonic guided wave signal on the sample surface. During acquisition, multiple detection points are set along the sample printing direction to achieve point-by-point scanning and evaluation of the current deposition layer. At each detection point, the receiving sensor records the ultrasonic guided wave response generated by the excitation, acquiring time-domain waveform data containing multiple resonant modes.
[0026] The acquired ultrasonic guided wave signals were processed using a short-time Fourier transform (SFT) to extract three resonant frequencies. Edge resonance, zero-group velocity resonance, and thickness resonance correspond to energy concentration peaks at different frequencies in the time-frequency spectrum. Edge resonance has the lowest frequency, the S1 mode zero-group velocity resonance frequency is in the middle, and thickness resonance has the highest frequency. After identifying the energy concentration peaks corresponding to each resonant mode, frequency values were extracted at multiple time points. Outliers were removed, and the median was taken as the resonant frequency for the current detection point. In other words, the energy concentration peaks corresponding to each resonant mode were identified in the SFT time-frequency spectrum and used as the resonant frequency for the current detection point. This processing effectively suppresses frequency fluctuations caused by local surface roughness or differences in reflectivity, improving the accuracy of resonant frequency extraction.
[0027] S300: Combine the edge resonance frequency with the zero group velocity resonance frequency or thickness resonance frequency of the S1 mode to comprehensively invert and calculate the local Poisson's ratio of the sample.
[0028] In step S300, two Poisson ratio values are calculated by combining the edge resonance frequency with the zero group velocity resonance frequency and the edge resonance frequency with the thickness resonance frequency, respectively. The average of the two Poisson ratio values is then taken as the final local Poisson ratio of the sample.
[0029] Furthermore, based on the combination of the edge resonance frequency and the S1 mode zero group velocity resonance frequency, the first Poisson ratio is obtained by simultaneously solving the following formulas: in, The edge resonant frequency, Poisson's ratio, For transverse wave velocity, The zero-group velocity resonance frequency of mode S1. The proportionality coefficient related to Poisson's ratio. For longitudinal wave velocity, is the wave velocity ratio, and h is the structural thickness.
[0030] Furthermore, based on the combination of the edge resonance frequency and the thickness resonance frequency, the second Poisson's ratio is obtained by simultaneously solving the following formulas: in, The edge resonant frequency, Poisson's ratio, For transverse wave velocity, For longitudinal wave velocity, is the wave velocity ratio, and h is the structural thickness.
[0031] Finally, the average of the first and second Poisson ratios is taken as the final local Poisson ratio of the sample at the current detection point.
[0032] S400: Obtain the local thickness of the sample and calculate the local shear and longitudinal wave velocities based on the relationship between Poisson's ratio, edge resonance frequency, S1 mode zero group velocity resonance frequency, thickness resonance frequency, and shear and longitudinal wave velocities. In other words, calculate the shear and longitudinal wave velocities given the local thickness of the sample. Based on the Poisson's ratio obtained in the previous steps, and the extracted edge resonance frequency and S1 mode zero group velocity resonance frequency, solve for the shear and longitudinal wave velocities respectively.
[0033] In step S400, the local shear wave velocity of the sample is calculated using the following formula: in Let be the local shear wave velocity of the sample. By substituting the known material parameters, the local shear wave velocity of the sample can be calculated.
[0034] The local longitudinal wave velocity of the sample can be calculated by reverse calculation using the following formula: in This represents the local shear wave velocity of the sample. By substituting the known material parameters, the local longitudinal wave velocity of the sample can be calculated. (Two wave velocities) and The consistency between them satisfies the wave speed ratio formula k, which can be used to cross-validate the rationality of the calculation results.
[0035] S500: Obtain the sample density and calculate the local Young's modulus of the sample based on the theoretical relationship between shear wave velocity, Poisson's ratio, sample density and Young's modulus.
[0036] In step S500, the Young's modulus of the sample is calculated locally according to the following formula: in, For Young's modulus, The density is used as the basis for inversion calculations. Based on the obtained Poisson's ratio, density, and shear wave velocity, the Young's modulus of the sample is output. In some embodiments, if either the shear wave velocity or the P-wave velocity is known, the inversion calculation can be performed to output the Young's modulus of the sample.
[0037] To further explain the evaluation method of the present invention, the following is an experimental verification description.
[0038] like Figure 3 As shown, firstly, functionally graded material samples were prepared. Four samples with different powder ratios were prepared using direct energy deposition (DED). The powder materials were iron-based superalloy LC-SR-31 and nickel-based superalloy In625, with ratios of 100% LC-SR-31, 75% LC-SR-31 and 25% In625, 50% LC-SR-31 and 50% In625, and 25% LC-SR-31 and 75% In625, respectively. The sample dimensions were 160 mm long, 5 mm wide, and 60 mm high. The top surface of each sample was milled using an 8 mm diameter milling cutter at a speed of 800 r / min and a feed rate of 80 to ensure the flatness of the test surface.
[0039] Next, detection points were set along the printing direction and ultrasonic guided wave signals were acquired. Four detection points were set within the sampling area of each sample, with adjacent detection points spaced 2.5 mm apart. A non-contact laser detection system was used for point-by-point scanning detection. The excitation source was a Q-switched Nd:YAG laser pulse emitter with a wavelength of 532 nm, applying a single-cycle sinusoidal pulse at a frequency of 10 kHz. The receiving sensor was a helium-neon laser Doppler vibrometer with a wavelength of 632.8 nm and a bandwidth of 0–3 MHz, acquiring the ultrasonic guided wave signals at each detection point.
[0040] Next, the acquired ultrasonic guided wave signal was processed by short-time Fourier transform to identify the energy accumulation peaks corresponding to each resonance mode in the time spectrum, and the edge resonance frequency, the zero group velocity resonance frequency of the S1 mode, and the thickness resonance frequency were extracted.
[0041] Then, the local Poisson's ratio of the sample is inverted using the resonant frequency combination. Two combination methods are used to combine the edge resonant frequency with the S1 mode zero group velocity resonant frequency and the thickness resonant frequency, respectively, to obtain two Poisson's ratio values. The average of the two Poisson's ratio values is taken as the final local Poisson's ratio evaluation result for the current detection point.
[0042] Next, the transverse and longitudinal wave velocities are calculated given the local thickness of the sample. Based on the obtained Poisson's ratio, edge resonance frequency, and S1 mode zero group velocity resonance frequency, the transverse and longitudinal wave velocities are deduced using the formulas.
[0043] Then, the local density of the sample is known, and the Young's modulus is calculated. Based on the obtained transverse wave velocity, Poisson's ratio, and density, the local Young's modulus of the sample is calculated according to the formula.
[0044] Next, based on the relationship curve established by the orthogonal mode decomposition method, combined with the measured Poisson's ratio and the position coordinates of the first amplitude minimum point, the local thickness of the sample is calculated.
[0045] Then, tensile tests were used to verify the accuracy of the Poisson's ratio assessment results. Dog bone specimens were cut from the measurement area of each sample, and tensile tests were performed on a universal testing machine. Strain gauges were attached to measure the Poisson's ratio. The average Poisson's ratio measured by this method was compared with the tensile test results. The measurement results for the four powder formulations are as follows: 100% LC-SR-31 sample: 0.2669 measured by this method, 0.266 in tensile test, relative error 0.35%; 75% LC-SR-31 and 25% In625 sample: 0.2772 measured, 0.277 in tensile test, relative error 0.06%; 50% LC-SR-31 and 50% In625 sample: 0.2703 measured, 0.270 in tensile test, relative error 0.09%; 25% LC-SR-31 and 75% In625 sample: 0.2855 measured, 0.285 in tensile test, relative error 0.16%.
[0046] Next, an ultrasonic probe was used to measure the longitudinal and transverse wave velocities in the detection area to verify the accuracy of the wave velocity assessment results. The wave velocity results obtained by this method were compared with the probe measurement results. The overall average deviation of the longitudinal wave velocity was approximately 1.47%, and the overall average deviation of the transverse wave velocity was approximately 1.72%.
[0047] Finally, tensile tests were used to verify the accuracy of the Young's modulus assessment results. The same dog bone specimens were used for the Poisson's ratio test, and the Young's modulus and Poisson's ratio were obtained through a single tensile test. The stress-strain curves from the tensile tests were measured, and the slope of the elastic phase was calculated. The average Young's modulus calculated using this method was compared with the Young's modulus measured by the tensile tests. For a 100% LC-SR-31 sample, the measured strength was 187.035 GPa, and the tensile test strength was 185.04 GPa, with a relative error of 1.08%. For a 75% LC-SR-31 and 25% In625 sample, the measured strength was 218.7875 GPa, and the tensile test strength was 210.04 GPa, with a relative error of 4.16%. For a 50% LC-SR-31 and 50% In625 sample, the measured strength was 206.435 GPa, and the tensile test strength was 200.36 GPa, with a relative error of 3.03%. For a 25% LC-SR-31 and 75% In625 sample, the measured strength was 195.16 GPa, and the tensile test strength was 188.15 GPa, with a relative error of 3.72%. These validation results demonstrate that the method proposed in this application can accurately assess the local Poisson's ratio, wave velocity, and Young's modulus of the sample.
[0048] The present invention also provides an apparatus comprising: a memory for storing an embedded software program; and a processor for executing the embedded software program stored in the memory, wherein the embedded software program, when executed, implements the steps of an online sample mechanical property quantitative evaluation method for direct energy deposition additive manufacturing as described above.
[0049] The present invention also provides a computer-readable storage medium storing a program for implementing a method for quantitatively evaluating the mechanical properties of a sample, the program being executed by a processor to implement the steps of an online method for quantitatively evaluating the mechanical properties of a sample for direct energy deposition additive manufacturing as described in any of the preceding claims.
[0050] In summary, this invention provides a method, device, and readable storage medium for online quantitative evaluation of the mechanical properties of samples in direct energy deposition additive manufacturing. Utilizing three modes—edge resonance, zero-group velocity resonance, and thickness resonance—it achieves multi-parameter joint evaluation of local Poisson's ratio, wave velocity, and Young's modulus of the sample. This method offers advantages such as non-contact operation and high spatial resolution. Compared to traditional methods, it eliminates the need for large-scale scanning to acquire average information; quantitative evaluation can be completed with only a single excitation and reception at a local detection point, significantly improving detection efficiency and accuracy. This method can be directly integrated into direct energy deposition additive manufacturing equipment, providing a practical solution for real-time online monitoring of the mechanical properties of functionally graded materials in the additive manufacturing process.
[0051] Furthermore, those skilled in the art should understand that although many problems exist in the prior art, each embodiment or technical solution of the present invention can be improved in only one or a few aspects, without necessarily solving all the technical problems listed in the prior art or the background art simultaneously. Those skilled in the art should understand that any content not mentioned in a claim should not be construed as a limitation on that claim.
[0052] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.
Claims
1. A method for quantitative evaluation of the mechanical properties of online samples used in direct energy deposition additive manufacturing, characterized in that: The quantitative evaluation method for the mechanical properties of the sample includes the following steps: S100: On the current deposited layer in the additive manufacturing process, a broadband ultrasonic excitation is applied to stimulate the ultrasonic guided wave response in the sample; S200: Acquires ultrasonic guided wave signals from a local area of the sample, obtains time-domain waveforms containing multiple resonant modes, and performs short-time Fourier transform processing on the acquired ultrasonic guided wave signals to extract edge resonant frequencies, S1 mode zero group velocity resonant frequencies, and thickness resonant frequencies. S300: Combine the edge resonance frequency with the zero group velocity resonance frequency or thickness resonance frequency of the S1 mode respectively, and calculate the local Poisson's ratio of the sample by comprehensive inversion. S400: Obtain the local thickness of the sample, and calculate the local shear wave velocity and longitudinal wave velocity of the sample based on the relationship between Poisson's ratio, edge resonance frequency, S1 mode zero group velocity resonance frequency, thickness resonance frequency, shear wave velocity and longitudinal wave velocity. S500: Obtain the sample density and calculate the local Young's modulus of the sample based on the theoretical relationship between shear wave velocity, Poisson's ratio, sample density and Young's modulus.
2. The method for quantitative evaluation of the mechanical properties of online samples in direct energy deposition additive manufacturing according to claim 1, characterized in that: In step S100, before exciting the ultrasonic guided wave response, the top surface of the sample is milled with a milling cutter to ensure the flatness of the sample surface.
3. The method for quantitative evaluation of the mechanical properties of online samples in direct energy deposition additive manufacturing according to claim 1, characterized in that: In step S200, the extraction method of edge resonance frequency, S1 mode zero group velocity resonance frequency and thickness resonance frequency includes: identifying the energy accumulation peak corresponding to each resonance mode on the short-time Fourier transform spectrum, and using it as the resonance frequency of the current detection point.
4. The method for quantitative evaluation of the mechanical properties of online samples in direct energy deposition additive manufacturing according to claim 1, characterized in that: In step S300, two Poisson ratio values are calculated by combining the edge resonance frequency with the zero group velocity resonance frequency and the edge resonance frequency with the thickness resonance frequency, respectively. The average of the two Poisson ratio values is then taken as the final local Poisson ratio of the sample.
5. The method for quantitative evaluation of the mechanical properties of online samples in direct energy deposition additive manufacturing according to claim 4, characterized in that: Based on the combination of the edge resonance frequency and the S1 mode zero group velocity resonance frequency, the first Poisson ratio is obtained by simultaneously solving the following formulas: in, The edge resonant frequency, Poisson's ratio, For transverse wave velocity, The zero-group velocity resonance frequency of mode S1. The proportionality coefficient related to Poisson's ratio. For longitudinal wave velocity, is the wave velocity ratio, and h is the structural thickness.
6. The method for quantitative evaluation of the mechanical properties of online samples in direct energy deposition additive manufacturing according to claim 5, characterized in that: Based on the combination of edge resonant frequency and thickness resonant frequency, the second Poisson's ratio is obtained by simultaneously solving the following formulas: in, The edge resonant frequency, Poisson's ratio, For transverse wave velocity, For thickness resonant frequency, For longitudinal wave velocity, is the wave velocity ratio, and h is the structural thickness.
7. The method for quantitative evaluation of the mechanical properties of online samples in direct energy deposition additive manufacturing according to claim 6, characterized in that: In step S400, the local shear wave velocity of the sample is calculated using the following formula: in The transverse wave velocity is the local transverse wave velocity of the sample. The local longitudinal wave velocity of the sample can be calculated by reverse calculation using the following formula: in This represents the shear wave velocity in a localized area of the sample.
8. The method for quantitative evaluation of the mechanical properties of online samples in direct energy deposition additive manufacturing according to claim 7, characterized in that: In step S500, the Young's modulus of the sample is calculated locally according to the following formula: in, For Young's modulus, For density.
9. A device, characterized in that: The device includes: Memory, used to store embedded software programs; A processor for executing an embedded software program stored in the memory, wherein the embedded software program, when executed, implements the steps of the online sample mechanical property quantitative evaluation method for direct energy deposition additive manufacturing according to any one of claims 1 to 8.
10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a program for implementing a method for quantitatively evaluating the mechanical properties of a sample. The program for implementing the method for quantitatively evaluating the mechanical properties of a sample is executed by a processor to implement the steps of an online method for quantitatively evaluating the mechanical properties of a sample for direct energy deposition additive manufacturing as described in any one of claims 1 to 8.