CN115326846B - Quality evaluation method for additive manufacturing component - Google Patents
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- 239000000654 additive Substances 0.000 title claims abstract description 131
- 230000000996 additive effect Effects 0.000 title claims abstract description 131
- 238000000034 method Methods 0.000 title claims abstract description 29
- 238000013441 quality evaluation Methods 0.000 title claims abstract description 20
- 238000004519 manufacturing process Methods 0.000 title claims description 75
- 238000011156 evaluation Methods 0.000 claims abstract description 50
- 230000007547 defect Effects 0.000 claims abstract description 37
- 238000009826 distribution Methods 0.000 claims abstract description 34
- 238000009659 non-destructive testing Methods 0.000 claims abstract description 7
- 238000001514 detection method Methods 0.000 claims description 21
- 239000000463 material Substances 0.000 claims description 18
- 238000005516 engineering process Methods 0.000 claims description 11
- 238000012360 testing method Methods 0.000 claims description 10
- 238000000342 Monte Carlo simulation Methods 0.000 claims description 8
- 230000001066 destructive effect Effects 0.000 claims description 2
- 238000007689 inspection Methods 0.000 claims description 2
- 238000012216 screening Methods 0.000 abstract description 3
- 238000004364 calculation method Methods 0.000 description 8
- 238000002591 computed tomography Methods 0.000 description 7
- 238000005315 distribution function Methods 0.000 description 4
- 238000002844 melting Methods 0.000 description 4
- 230000008018 melting Effects 0.000 description 4
- 238000004088 simulation Methods 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 3
- 238000007656 fracture toughness test Methods 0.000 description 3
- 239000007769 metal material Substances 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 238000009864 tensile test Methods 0.000 description 3
- 238000012937 correction Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 230000005855 radiation Effects 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- 238000010998 test method Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000005266 casting Methods 0.000 description 1
- 238000005520 cutting process Methods 0.000 description 1
- 238000006073 displacement reaction Methods 0.000 description 1
- 238000010894 electron beam technology Methods 0.000 description 1
- 238000005242 forging Methods 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 238000000691 measurement method Methods 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000000704 physical effect Effects 0.000 description 1
- 238000001303 quality assessment method Methods 0.000 description 1
- 239000002994 raw material Substances 0.000 description 1
- 238000000110 selective laser sintering Methods 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N23/00—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00
- G01N23/02—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material
- G01N23/04—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material and forming images of the material
- G01N23/046—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material and forming images of the material using tomography, e.g. computed tomography [CT]
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N23/00—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00
- G01N23/02—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material
- G01N23/04—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material and forming images of the material
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Abstract
The invention discloses a quality evaluation method of an additive manufactured component, which comprises the steps of firstly, rapidly realizing preliminary quality evaluation of the additive manufactured component by adopting a nondestructive testing method, completing preliminary screening of the additive manufactured component, then comprehensively considering the actual bearing condition of the additive manufactured component, the internal defect distribution condition of the additive manufactured component and the mechanical property of the additive manufactured component, evaluating the reliability of the component based on fracture mechanics theory, and evaluating the quality of the additive manufactured component according to the result of the reliability evaluation.
Description
Technical Field
The invention relates to the field of material detection, in particular to a quality evaluation method for an additive manufacturing component.
Background
The additive manufacturing technology is proposed in the 80 th century of 20, and compared with the traditional processing technology, the additive manufacturing technology gets rid of the processing modes of raw material removal, cutting and assembly, and is a manufacturing technology capable of accumulating materials from bottom to top. The additive manufacturing technology can realize rapid and precise manufacturing of parts with any complex structure on one piece of equipment, omits cutters, clamps and a plurality of processing procedures of the traditional process, and can reduce the weight of the parts, shorten the production period, reduce the number of parts required by components, thereby saving the cost and improving the reliability of the components. However, additive manufacturing processes have complex physical properties, typically requiring millions of cycles of melting and resolidification in a localized range (20-50 μm), thereby making the microstructure of the additive manufactured component different from that of castings or forgings of the same metallic material. The above-mentioned differences are mainly represented by: anisotropy of material properties and regional non-uniformity; various types of defects, such as holes, cracks, and unfused, are randomly present inside the member, which are difficult to avoid. The above-described additive manufacturing microscopic defects inevitably affect the performance of the component, and the additive manufactured component performance is unstable due to the randomness of the defects. Therefore, the quality of the additive manufactured component can be accurately evaluated, and the application of the additive manufacturing in the related industry field can be further expanded.
For additive manufacturing processes, there is currently no perfect quality evaluation method. In addition to the lack of a relevant standard system, the difficulties in quality assessment of additive manufactured components are mainly the following: 1. and detecting defects. The additive manufacturing technology has developed so far, the internal defect size of the component can be controlled to be even in the micron level, the defect detection difficulty is greatly increased, and the nondestructive detection method is particularly used. 2. Practical experience with additive manufacturing is lacking. In certain industries, such as the aerospace field, there is currently no adequate overall production experience.
Aiming at the lack of an additive manufactured component quality evaluation system at present, the invention provides an additive manufactured component quality evaluation method which can evaluate the reliability of an additive manufactured component.
Compared with the prior art, the invention has the beneficial effects that:
(1) According to the nondestructive testing result, the invention combines the actual conditions of internal defects of the additive manufacturing component to quickly realize the preliminary quality evaluation of the additive manufacturing component, completes the preliminary screening of the additive manufacturing component, and then adopts a reliability evaluation method to further quantitatively evaluate the quality of the additive manufacturing component, thereby having a perfect quality evaluation system.
(2) The random distribution characteristics of the key parameters such as the load, the mechanical property parameters and the defect size of the additive manufacturing component are comprehensively considered, the random distribution characteristics are matched with the essential properties and the actual service environment conditions of the additive manufacturing component, a model of the reliability evaluation method of the additive manufacturing component is established, the accurate evaluation of the reliability of the additive manufacturing component can be realized, and the quality of the additive manufacturing component is quantitatively analyzed.
(3) The reliability evaluation method for the additive manufactured component provided by the invention is applicable to all metal additive manufacturing methods, such as selective laser sintering, selective laser melting, electron beam melting forming, arc wire feeding additive manufacturing technology and the like.
Disclosure of Invention
The invention is realized by adopting the following technical scheme:
A method of evaluating the quality of an additive manufactured component, comprising the steps of:
Step one, detecting an additive manufacturing component by using a ray nondestructive detection technology to obtain a ray nondestructive detection result;
step two, according to the ray nondestructive testing result of the step one, carrying out preliminary acceptance on the additive manufacturing component, wherein the grade of acceptance is classified into grade 1, grade 2 and grade 3;
step three, taking the additive manufacturing components with the acceptance level of 2 and 3 in the step two as unqualified products, and taking the additive manufacturing components with the acceptance level of 1 as primary qualified products;
step four, microscopic defect detection is carried out on the additive manufacturing component with the acceptance level of 1 in the step two, and the distribution characteristic of the defect size of the additive manufacturing component is obtained;
step five, carrying out mechanical property test on the additive manufacturing component with the acceptance level of 1 in the step two to obtain the stress-strain curve and fracture toughness distribution characteristics of the additive manufacturing component material;
Step six, combining the actual working condition of the additive manufacturing component to obtain the load distribution characteristic of the additive manufacturing component;
step seven, calculating a failure evaluation chart according to the stress-strain curve obtained in the step five;
Step eight, adopting a Monte Carlo simulation method, and carrying out reliability evaluation on the additive manufacturing component by combining the random distribution characteristics of the defect size in the step four and the load size in the step five;
And step nine, performing quality evaluation on the additive manufactured component according to the reliability evaluation result of the additive manufactured component in the step eight.
The additive manufactured component quality evaluation method comprises the following steps: the non-destructive testing result of the ray in the first step comprises the type, the size, the position distribution and the like of the internal defects of the additive manufactured component.
The method for evaluating the quality of the additive manufactured component comprises the following steps:
The failure evaluation graph consists of an abscissa L r, an ordinate K r and a failure evaluation curve, wherein the failure evaluation curve is a function curve of K r about L r and is used for defining a safety area, wherein the safety area is positioned below the curve, and the unsafe area is positioned below the curve; the calculation formula of the failure evaluation curve is as follows:
Kr＝0 Lr＞Lrmax
Wherein E is the Poisson's ratio of the material; epsilon ref is the true strain obtained at true stress L rσY by a uni-directional tensile stress-strain curve; σ Y is the yield strength of the material; l rmax is the maximum value of L r, calculated by the following formula:
Wherein σ U is the tensile strength of the material.
The method for evaluating the quality of the additive manufactured component comprises the following steps:
Setting total evaluation times N for multiple evaluations;
Randomly sampling and obtaining the defect size, fracture toughness and load size in the step four and the step five when each single evaluation is performed to form an evaluation point;
Calculating a coordinate point (L r,Kr) of the evaluation point in the failure evaluation graph in combination with the structural characteristics of the additive manufactured component;
drawing the coordinate point (L r,Kr) obtained by calculation into a failure evaluation graph in the step seven to perform failure evaluation; the calculation formula of the coordinate point (L r,Kr) is as follows:
Wherein, L r represents the degree of the structure approaching plastic yield, and sigma ref is the reference stress; σ Y is the yield strength of the material; p is the load size of the six random extraction steps; p l is the limit load;
Wherein, K r represents the degree of the structure approaching fracture failure, and K mat is the fracture toughness of the material; k I is the stress intensity factor calculated according to the following formula:
Wherein Y is a stress intensity factor correction coefficient; sigma is the stress magnitude; a is the defect size;
Counting the number M of unacceptable evaluation points in Monte Carlo simulation, and calculating the failure probability and reliability of the additive manufactured component through the following formula:
wherein P is the failure probability of the additive manufactured component;
Reliability = 1-P.
The method for evaluating the quality of the additive manufactured component comprises the following steps:
the additive manufactured components with the reliability more than or equal to 99.99 percent are rated as A-grade products; the additive manufactured components with the reliability of more than or equal to 99.99 percent and the reliability of more than or equal to 99.9 percent are rated as B-class products; the additive manufactured components with the reliability of more than or equal to 99.9 percent are rated as products; the additive manufactured components with the reliability of more than or equal to 95 percent are rated as D-grade products; additive manufactured components with reliability < 95% were rated as off-grade products.
Drawings
FIG. 1 is a flow chart of a method of evaluating the quality of an additive manufactured component of the present invention;
FIG. 2 is a cloud plot of finite element numerical modeling results stress distribution for an additive manufactured component;
FIG. 3 is a stress-strain curve of an additive manufactured component;
FIG. 4 is a failure evaluation chart;
FIG. 5 is a flow chart of a Monte Carlo simulation method;
FIG. 6 is a graph of internal defect size distribution of an additive manufactured component;
fig. 7 is a reliability result evaluation result diagram.
Detailed Description
The following describes embodiments of the present invention in detail with reference to FIGS. 1-7.
The invention provides a quality evaluation method of an additive manufacturing component, which is realized by the following technical scheme: as shown in the flow chart of the quality evaluation method of the additive manufactured component in fig. 1, firstly, a nondestructive testing method is adopted to quickly realize the preliminary quality evaluation of the additive manufactured component, the preliminary screening of the additive manufactured component is completed, then, the actual bearing condition of the additive manufactured component, the internal defect distribution condition of the additive manufactured component and the mechanical property of the additive manufactured component are comprehensively considered, the reliability evaluation is carried out on the component based on the fracture mechanics theory, and the quality of the additive manufactured component is evaluated according to the result of the reliability evaluation. The specific implementation steps are as follows:
Step one, detecting an additive manufacturing component by using a radiation nondestructive detection technology to obtain radiation nondestructive detection results including the types, the sizes, the position distribution and the like of internal defects of the additive manufacturing component;
Step two, according to the ray nondestructive testing result of the step one, the additive manufacturing component is subjected to preliminary acceptance, the acceptance grade is divided into 1 grade, 2 grade and 3 grade, according to the types of internal defects of the additive manufacturing component, the acceptance grade dividing standards are different, and according to the actual conditions of the internal defects of the additive manufacturing component, the invention sets an acceptance grade dividing standard table of the additive manufacturing component, see the following table 1:
TABLE 1 nondestructive inspection acceptance grading criteria for additive manufactured components
Step three, taking the additive manufacturing components with the acceptance level of 2 and 3 in the step two as unqualified products, and taking the additive manufacturing components with the acceptance level of 1 as primary qualified products;
Step four, microscopic defect detection is carried out on the additive manufacturing component with the acceptance level of 1 in the step two, and the distribution characteristic of the defect size of the additive manufacturing component is obtained; the microscopic defect detection method mainly comprises metallographic detection and industrial Computer Tomography (CT) detection, wherein detection samples are randomly cut from an additive manufacturing component; the metallographic detection is according to standard GB/T34895-2017, namely general rule of heat treatment metallographic examination, and the industrial Computer Tomography (CT) detection is according to standard GB/T29067-2012, namely a non-destructive detection industrial Computer Tomography (CT) image measurement method; the number of the defect size detection results is not less than 30, and a random probability distribution model of the defect size is built;
Step five, carrying out mechanical property test on the additive manufacturing component with the acceptance level of 1 in the step two to obtain the stress-strain curve and fracture toughness distribution characteristics of the additive manufacturing component material; the stress-strain curve is obtained through a tensile test according to the standard GB/T228.1 section 1 of tensile test of metal materials, room temperature test method and GB/T228.2 section 2 of tensile test of metal materials: high temperature test methods; fracture toughness is obtained through a quasi-static fracture toughness test, which is preferentially cut from the additive manufactured component according to a standard ISO 12135"Metallic materials-Unified method of test for the determination of quasistatic fracture toughness"; mechanical property test sample, and if the component cannot meet the number and the size of the relevant test samples, the test sample with the same material and manufacturing process as the additive manufactured component can be used; the number of the fracture toughness test results is not less than 30, and a random probability distribution model of the fracture toughness is established;
Step six, combining the actual working condition of the additive manufacturing component to obtain the load distribution characteristic of the additive manufacturing component; the load distribution characteristics of the additive manufacturing component are mainly obtained by combining the actual working condition of the additive manufacturing component with the actual working condition of the additive manufacturing component through finite element numerical simulation calculation, and mainly comprise simulation analysis calculation of a temperature field, a flow field and a stress strain field; FIG. 2 is a cloud plot of finite element numerical modeling results stress distribution of an additive manufactured component;
Step seven, calculating a failure evaluation chart according to the stress-strain curve (shown in fig. 3) obtained in the step five; as shown in fig. 4, the failure evaluation graph is composed of an abscissa L r, an ordinate K r, and a failure evaluation curve, wherein the failure evaluation curve is a function curve of K r with respect to L r, and is used for defining a safe area, a safe area is located below the curve, and an unsafe area is located below the curve; the calculation formula of the failure evaluation curve is as follows:
Kr＝0 Lr＞Lrmax
Wherein E is the Poisson's ratio of the material; epsilon ref is the true strain obtained at true stress L rσY by a uni-directional tensile stress-strain curve; σ Y is the yield strength of the material; l rmax is the maximum value of L r, calculated by the following formula:
wherein σ U is the tensile strength of the material;
Step eight, adopting a Monte Carlo simulation method, and carrying out reliability evaluation on the additive manufacturing component according to the random probability distribution model of the defect size obtained in the step four, the random probability distribution model of fracture toughness obtained in the step five and the component load distribution characteristic obtained in the step six; the flow chart of the Monte Carlo simulation method is shown in fig. 5, and the specific implementation method is as follows: setting total evaluation times N to perform multiple evaluations (recommended total evaluation times N is not less than 10000), randomly sampling and acquiring the defect size obtained in the fourth step, the fracture toughness obtained in the fifth step and the load size obtained in the sixth step during each single evaluation to form an evaluation point, and calculating a coordinate point (L r,Kr) of the evaluation point in a failure evaluation graph by combining the structural characteristics of the additive manufacturing component; as shown in fig. 7, the coordinate point (L r,Kr) obtained by the calculation is plotted in the failure evaluation chart in the step seven to perform failure evaluation; the calculation formula of the coordinate point (L r,Kr) is as follows:
Wherein, L r represents the degree of the structure approaching plastic yield, and sigma ref is the reference stress; σ Y is the yield strength of the material; p is the load size of the six random extraction steps; p l is the limit load;
Wherein, K r represents the degree of the structure approaching fracture failure, and K mat is the fracture toughness of the material; k I is the stress intensity factor calculated according to the following formula:
Wherein Y is a stress intensity factor correction coefficient; sigma is the stress magnitude; a is the defect size;
Counting the number M of unacceptable evaluation points in Monte Carlo simulation, and calculating the failure probability and reliability of the additive manufactured component through the following formula:
wherein P is the failure probability of the additive manufactured component;
reliability = 1-P
Step nine, carrying out quality evaluation on the additive manufactured component according to the reliability evaluation result of the additive manufactured component in the step eight; the additive manufactured components with the reliability more than or equal to 99.99 percent are rated as A-grade products; the additive manufactured components with the reliability of more than or equal to 99.99 percent and the reliability of more than or equal to 99.9 percent are rated as B-class products; the additive manufactured components with the reliability of more than or equal to 99.9 percent are rated as products; the additive manufactured components with the reliability of more than or equal to 95 percent are rated as D-grade products; additive manufactured components with reliability < 95% were rated as off-grade products.
In embodiment 1, the quality evaluation is performed on a structural member of an aeroengine produced by a laser selective melting additive manufacturing technology, the structure and bearing analysis finite element numerical simulation results are shown in fig. 2, the conditions of vibration, overload and the like in the actual working process of the structural member are considered in the finite element numerical simulation results, and the maximum load of the structural member is assumed to be in accordance with normal distribution, so that a load distribution function can be obtained, and the load distribution function is shown in the following formula:
In the fifth step, the mechanical property test is a test sample having the same material and manufacturing process as the additive manufactured member because the member has a thin-wall structure. From the mechanical property test results, a stress-strain curve is obtained as shown in fig. 3. Multiple groups of fracture toughness tests are carried out, the random probability distribution characteristics of the fracture toughness accord with the normal distribution characteristics, and the fracture toughness can be described by the distribution function of the following formula:
Wherein CTOD is crack tip opening displacement in mm;
In this embodiment, the distribution characteristics of defects inside the additive manufacturing structure are detected by using a nanoscale industrial computer tomography (μ -CT) detection technique, and by reconstructing the defects and performing statistical analysis, a defect size distribution diagram as shown in fig. 6 is obtained, and it can be seen that the defect size distribution also satisfies the normal distribution, so that a distribution function of the defect size can be obtained, as shown in the following formula:
From the stress-strain curve of fig. 3, a failure evaluation graph is calculated, as shown in fig. 4. According to the eighth step, reliability analysis is performed on the additive manufacturing member by using a monte carlo simulation method, in this embodiment, the number of evaluation times N is set to 10000, the evaluation results are shown in fig. 7, wherein 2 unacceptable evaluation points, 9998 acceptable evaluation points are used, and the failure probability is calculated to be 0.02%, and the reliability is 99.98%. According to step nine, the quality grade of the additive manufactured member of the present embodiment is grade B.
The above embodiments are only for the purpose of more clearly illustrating the present invention, not for the purpose of limiting the same, and one of ordinary skill in the relevant art may
Other changes and modifications may be made in accordance with the teachings of the present disclosure without departing from the spirit and scope thereof, and equivalents thereof should be considered to fall within the scope of the invention, which is defined by the appended claims.
Claims (2)
1. The quality evaluation method of the additive manufactured component is characterized by comprising the following steps of:
Step one, detecting an additive manufacturing component by using a ray nondestructive detection technology to obtain a ray nondestructive detection result;
step two, according to the ray nondestructive testing result of the step one, carrying out preliminary acceptance on the additive manufacturing component, wherein the grade of acceptance is classified into grade 1, grade 2 and grade 3;
step three, taking the additive manufacturing components with the acceptance level of 2 and 3 in the step two as unqualified products, and taking the additive manufacturing components with the acceptance level of 1 as primary qualified products;
step four, microscopic defect detection is carried out on the additive manufacturing component with the acceptance level of 1 in the step two, and the distribution characteristic of the defect size of the additive manufacturing component is obtained;
step five, carrying out mechanical property test on the additive manufacturing component with the acceptance level of 1 in the step two to obtain the stress-strain curve and fracture toughness distribution characteristics of the additive manufacturing component material;
Step six, combining the actual working condition of the additive manufacturing component to obtain the load distribution characteristic of the additive manufacturing component;
step seven, calculating a failure evaluation chart according to the stress-strain curve obtained in the step five;
Step eight, adopting a Monte Carlo simulation method, and carrying out reliability evaluation on the additive manufacturing component by combining the random distribution characteristics of the defect size in the step four and the load size in the step five;
And step nine, performing quality evaluation on the additive manufactured component according to the reliability evaluation result of the additive manufactured component in the step eight.
2. The additive manufactured component quality evaluation method according to claim 1, characterized in that: the non-destructive inspection result of the ray in step 1 comprises the type, size and position distribution of the internal defects of the additive manufactured component.
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| 金属增材制造数值模拟;陈嘉伟;熊飞宇;黄辰阳;廉艳平;;中国科学:物理学 力学 天文学(第09期);全文 * |
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