CN108763801B - Modeling method for geometric characteristics and dilution rate of laser additive remanufacturing cladding layer - Google Patents

Modeling method for geometric characteristics and dilution rate of laser additive remanufacturing cladding layer Download PDF

Info

Publication number
CN108763801B
CN108763801B CN201810562315.3A CN201810562315A CN108763801B CN 108763801 B CN108763801 B CN 108763801B CN 201810562315 A CN201810562315 A CN 201810562315A CN 108763801 B CN108763801 B CN 108763801B
Authority
CN
China
Prior art keywords
cladding layer
cladding
dilution rate
channel
dilution
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201810562315.3A
Other languages
Chinese (zh)
Other versions
CN108763801A (en
Inventor
岳海涛
郭辰光
李强
赵丽娟
王闯
张建卓
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Liaoning Technical University
Original Assignee
Liaoning Technical University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Liaoning Technical University filed Critical Liaoning Technical University
Priority to CN201810562315.3A priority Critical patent/CN108763801B/en
Publication of CN108763801A publication Critical patent/CN108763801A/en
Application granted granted Critical
Publication of CN108763801B publication Critical patent/CN108763801B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/004—Artificial life, i.e. computing arrangements simulating life
    • G06N3/006—Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P10/00—Technologies related to metal processing
    • Y02P10/25—Process efficiency

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Evolutionary Computation (AREA)
  • General Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Health & Medical Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Data Mining & Analysis (AREA)
  • Biophysics (AREA)
  • Biomedical Technology (AREA)
  • Molecular Biology (AREA)
  • Computing Systems (AREA)
  • Computational Linguistics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Health & Medical Sciences (AREA)
  • Computer Hardware Design (AREA)
  • Geometry (AREA)

Abstract

The invention provides a modeling method for geometric characteristics and dilution rate of a laser additive remanufacturing cladding layer, and relates to the technical field of laser additive remanufacturing. Firstly, carrying out single-melting-channel single-factor experiment to obtain a process parameter optimal range and model verification data; performing a single cladding channel orthogonal experiment to obtain a better parameter combination and model modeling data; obtaining a cross section sample of the cladding layer by cutting the test piece, measuring the geometric dimension of the cross section of the cladding layer, and calculating the dilution rate; and finally, establishing a geometric characteristic and dilution rate interactive linear regression relation equation of the cladding layer, solving the relation coefficient through a BreedPSO algorithm, and verifying the fitting and predicting precision of the model. The modeling method for geometric characteristics and dilution rate of the laser additive remanufacturing cladding layer accurately solves the technical problem that the fitting precision between the geometric characteristic forming size of the laser additive remanufacturing single cladding channel and the process parameters is not high, is simple and high in accuracy, and can save production cost.

Description

Modeling method for geometric characteristics and dilution rate of laser additive remanufacturing cladding layer
Technical Field
The invention relates to the technical field of laser additive remanufacturing, in particular to a modeling method for geometric characteristics and dilution rate of a laser additive remanufacturing cladding layer.
Background
The laser additive remanufacturing technology is an advanced manufacturing technology for accumulating materials layer by layer or point by point to form a finished piece by applying laser. The technology takes the waste parts which lose use value as remanufactured blanks, and then utilizes the advanced manufacturing technology which mainly comprises laser cladding and laser rapid forming technology to repair the damage and improve the performance of the remanufactured blanks, so that the product after laser additive remanufacturing meets the use requirements of new products in quality and use performance. The laser additive remanufacturing technology has the greatest advantages that various advanced manufacturing technologies such as a computer aided design technology, a numerical control processing technology, a material technology, a laser processing technology and the like are fused, a cladding layer superior to the performance of a base material is manufactured by applying the comprehensive advanced technology, and the base material has small dilution rate on the coating material due to high concentration of energy density of laser, so that the structure performance of the coating material can be guaranteed, the processing precision is high, the controllability is strong, and the range of the coating material which can be processed by the high energy performance of the laser is wide.
The single-channel cladding is used as a basic composition unit of a laser additive remanufacturing forming structure, the multi-channel lapping and the lamination forming are realized by lapping and stacking the single-channel cladding one by one, and the forming structure of the laser additive remanufacturing forming structure determines the integral appearance characteristics of lapping and lamination to a great extent. The local shape is just uneven through single-pass cladding, so that structural errors of integral additive remanufacturing forming are caused, and if the structural errors are not controlled, failure of one-time forming processing can be caused. The geometric feature size and internal organization of the single cladding channel represent the overall attributes of laser additive remanufactured formed structures to some extent, and therefore, research on the geometric feature and dilution rate of the single cladding channel is necessary.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a modeling method for geometric characteristics and dilution rate of a laser additive remanufacturing cladding layer, which realizes modeling for the geometric characteristics and the dilution rate of a single cladding channel.
A modeling method for geometric characteristics and dilution rate of a laser additive remanufacturing cladding layer comprises the following steps:
step 1, obtaining an optimal range of process parameters related to geometrical characteristics and dilution rate of a cladding layer and verification data for verifying the geometrical characteristics and dilution rate model of the single cladding channel through a single-factor experiment of laser additive remanufacturing;
The process parameters related to the geometrical characteristics and dilution ratio of the cladding layer comprise laser workRate P, scanning speed VSAnd powder feeding rate VF；
Step 2, obtaining optimal parameter combination of process parameters related to geometrical characteristics and dilution rate of the cladding layer and model modeling data through a single cladding channel orthogonal experiment, wherein the specific method comprises the following steps:
cutting a test piece of a single cladding channel orthogonal experiment to obtain a cladding layer section sample, and measuring geometrical characteristics of the cladding layer by using an optical super-depth-of-field three-dimensional microscope, wherein the geometrical characteristics comprise a cladding height H and a cladding layer cross-sectional area SRAnd the matrix melting area SJ(ii) a And calculating the dilution ratio lambda through the geometrical characteristics of the cladding layer, wherein the formula is as follows:
[SJ/(SR+SJ)]×100％
the measured cladding height H and the cross section area S of the cladding layerRAnd the matrix melting area SJPerforming range analysis on the calculated dilution ratio lambda to determine a better parameter combination of the process parameters related to the geometrical characteristics and the dilution ratio of the cladding layer; and the cladding height H and the cross section area S of the cladding layerRAnd the melting area S of the matrixJAnd the dilution rate lambda is used as the original data of the geometric characteristics of the cladding layer of the single cladding channel and the dilution rate model;
step 3, establishing an interactive linear regression relational expression of the geometric characteristics and the dilution rate of the cladding layer of the single cladding channel, and solving coefficients in the relational expression by a particle swarm BreedPSO algorithm based on a hybridization theory to complete modeling of the geometric characteristics and the dilution rate of the cladding layer of the single cladding channel;
The specific method for establishing the interactive linear regression relation between the geometrical characteristics and the dilution ratio of the cladding layer comprises the following steps:
establishing a regression relation among the process parameters, the geometrical characteristics of the cladding layer and the dilution rate based on a quadratic regression model with interactive effect coefficients, wherein the formula is as follows:
Figure BDA0001683616200000021
Figure BDA0001683616200000022
Figure BDA0001683616200000023
Figure BDA0001683616200000024
wherein, H (P, V)S，VF) Is the height of the cladding layer, SR(P，VS，VF) Is the cross-sectional area of the cladding layer, SJ(P，VS，VF) Is the melting area of the matrix, lambda (P, V)S，VF) To the dilution ratio, alpha0、β0、χ0And delta0Coefficient of constant term, α, both of regression equationsi、βi、χiAnd deltaiCoefficient of first order of regression equation, alphaii、βii、χiiAnd deltaiiCoefficient of quadratic term, α, both regression equationsij、βij、χijAnd deltaijThe coefficient of the interaction effect is a regression equation, i is 1, 2 and 3, j is 1, 2 and 3, i is not equal to j, and epsilon is an error term;
step 4, verifying the fitting precision and the prediction precision of the geometric characteristics of the cladding layer of the single cladding channel and the dilution rate model, wherein the specific method comprises the following steps:
and (3) calculating the fitting precision of the geometric characteristics of the cladding layer of the single cladding channel and the dilution rate model by applying a re-determination coefficient R shown in the following formula:
Figure BDA0001683616200000031
wherein n is the sample number of the test piece used in the single cladding channel orthogonal experiment, yiIs the measured value of the single cladding channel orthogonal experiment,
Figure BDA0001683616200000033
is single meltingFitting values of geometric characteristics of the cladding layer and a dilution rate model, i' is 1, 2 … and n;
Substituting the geometrical characteristics of the cladding layer obtained by a single-cladding-channel single-factor experiment and the process parameters related to the dilution rate into a model of the geometrical characteristics and the dilution rate of the cladding layer of the single cladding channel, comparing the obtained geometrical characteristic size and the dilution rate of the cladding layer with data obtained by actual measurement, and verifying the prediction accuracy of the geometrical characteristics and the dilution rate model of the cladding layer of the single cladding channel by a prediction coefficient shown in the following formula:
Figure BDA0001683616200000032
where η is the prediction coefficient.
According to the technical scheme, the invention has the beneficial effects that: the modeling method for the geometric characteristics and the dilution rate of the laser additive remanufacturing cladding layer provided by the invention overcomes the limitation of determining a regression relation between the geometric characteristics and the dilution rate of the cladding layer and the process parameters by the existing method, accurately solves the technical problem of low fitting precision between the geometric characteristic forming size and the process parameters of the laser additive remanufacturing single cladding channel, is simple and high in accuracy, can save the production cost, and can provide theoretical support for lapping and laminated cladding.
Drawings
Fig. 1 is a flowchart of a modeling method for geometric characteristics and dilution ratio of a laser additive remanufacturing cladding layer according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a test piece used in a single-melting-channel single-factor experiment provided in an embodiment of the present invention;
FIG. 3 is a schematic cross-sectional geometry of a single cladding channel provided in accordance with an embodiment of the present invention;
FIG. 4 is a diagram of an actual measurement result of a test piece No. DD-02 provided by the embodiment of the present invention;
FIG. 5 is a graph of a comparison result of orthogonal experimental measurement calculated values of geometrical characteristics and dilution ratio of a single cladding pass cladding layer provided by an embodiment of the invention and model fitting values;
fig. 6 is a comparison result graph of the orthogonal test measurement calculation value of the geometric characteristic and the dilution ratio of the cladding layer of the single cladding channel and the model prediction value provided by the embodiment of the invention.
In the figure, 1, cladding layer; 2. a substrate material; 3. area of matrix melting SJ(ii) a 4. A heat affected zone; 5. cladding height H; 6. cross sectional area S of cladding layerR(ii) a 7. Measuring the section of a DD-02 test piece;
Detailed Description
The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
A modeling method for geometric characteristics and dilution ratio of a laser additive remanufacturing cladding layer is shown in figure 1 and comprises the following steps:
step 1, obtaining an optimal range of process parameters related to geometrical characteristics and dilution rate of a cladding layer and verification data for verifying the geometrical characteristics and dilution rate model of the single cladding channel through a single-factor experiment of laser additive remanufacturing;
The process parameters related to the geometrical characteristics and dilution ratio of the cladding layer include laser power P and scanning speed VSAnd powder feeding rate VF。
In this embodiment, 34GrNiMO6 is selected as a base material, the prepared ferrochrome powder is used as a cladding material, and an initial range of process parameters related to geometrical characteristics and dilution rate of the cladding layer is selected according to characteristics of processing equipment, wherein the initial range of laser power P is 900-1400W, and the scanning speed V is set as the scanning speed VSThe initial range of (A) is 700-1200 mm/min, and the powder feeding rate VFThe initial range of (a) is 3.2-4.1 rad/min, the specific single factor experimental protocol data is shown in table 1, and the preferred process parameter range is determined according to the experimental results shown in fig. 2 as follows: 1100-1400W, VS＝700～1000mm/min，VF＝3.2～4.1rad/min。
Table 1 single factor experimental protocol data
Figure BDA0001683616200000041
Figure BDA0001683616200000051
Step 2, obtaining optimal parameter combination of process parameters related to geometrical characteristics and dilution rate of the cladding layer and model modeling data through a single cladding channel orthogonal experiment, wherein the specific method comprises the following steps:
cutting a test piece of a single cladding channel orthogonal experiment to obtain a cladding layer section sample, and measuring geometrical characteristics of the cladding layer by using an optical super-depth-of-field three-dimensional microscope, wherein the geometrical characteristics comprise a cladding height H and a cladding layer cross-sectional area SRAnd the melting area S of the matrixJ(ii) a And calculating the dilution ratio lambda through the geometrical characteristics of the cladding layer, wherein the formula is as follows:
[SJ/(SR+SJ)]×100％
The measured cladding height H and the cross section area S of the cladding layerRAnd the matrix melting area SJPerforming range analysis on the calculated dilution ratio lambda to determine a better parameter combination of the process parameters related to the geometrical characteristics and the dilution ratio of the cladding layer; and the cladding height H and the cross section area S of the cladding layerRAnd the matrix melting area SJAnd the dilution rate lambda is used as the original data of the geometric characteristics of the cladding layer of the single cladding channel and the dilution rate model;
in this example, data of the single cladding lane orthogonal experimental scheme are shown in table 2, and the cladding height H and the cross-sectional area S of the cladding layer obtained by measurement are measuredRAnd the melting area S of the matrixJAnd performing range analysis on the calculated dilution ratio lambda to determine the optimal parameter combinations of the process parameters related to the geometric characteristics and dilution ratio of the cladding layer, namely the laser power P is 1300W, and the scanning speed VS700mm/min, powder feed rate VF3.5 rad/min; and the cladding height H and the cross section area S of the cladding layerRAnd the matrix melting area SJ and the dilution ratio lambda are used as the original data of the geometric characteristics of the cladding layer of the single cladding channel and the model of the dilution ratio.
Table 2 data of single cladding lane orthogonal experimental protocol
Figure BDA0001683616200000052
Figure BDA0001683616200000061
Step 3, establishing an interactive linear regression relational expression of the geometric characteristics and the dilution rate of the cladding layer of the single cladding channel, and solving coefficients in the relational expression by a particle swarm BreedPSO algorithm based on a hybridization theory to complete modeling of the geometric characteristics and the dilution rate of the cladding layer of the single cladding channel;
The specific method for establishing the interactive linear regression relation between the geometrical characteristics of the cladding layer and the dilution rate comprises the following steps:
establishing a regression relation among the process parameters, the geometrical characteristics of the cladding layer and the dilution rate based on a quadratic regression model with interactive effect coefficients, wherein the formula is as follows:
Figure BDA0001683616200000062
Figure BDA0001683616200000063
Figure BDA0001683616200000064
Figure BDA0001683616200000065
wherein, H (P, V)S，VF)、SR(P，VS，VF)、SJ(P，VS，VF) And λ (P, V)S，VF) Respectively comprises the height of a cladding layer, the cross section area of the cladding layer and the melting of a matrixArea and dilution ratio, alpha0、β0、χ0And delta0Coefficient of constant term, α, both of regression equationsi、βi、χiAnd deltaiCoefficient of first order of regression equation, alphaii、βii、χiiAnd deltaiiCoefficient of quadratic term, α, both regression equationsij、βij、χijAnd δ ijThe coefficients of the interaction are regression equations, i ≠ 1, 2, 3, j ≠ 1, 2, 3, and ≠ j, and ∈ is the error term.
In this embodiment, the geometric characteristics of the cross section of the cladding track are shown in fig. 3, the actual measurement result of the test piece No. DD-02 is shown in fig. 4, the single-factor experimental measurement calculation data is shown in table 3, and the orthogonal experimental measurement calculation data is shown in table 4.
TABLE 3 Single factor Experimental measurement calculation data
Figure BDA0001683616200000066
Figure BDA0001683616200000071
TABLE 4 orthogonal experimental measurement calculation data
Figure BDA0001683616200000072
In this example, the cladding height H and the cladding layer cross-sectional area SRThe melting area S of the matrixJAnd the dilution ratio λ as follows:
Figure BDA0001683616200000081
Figure BDA0001683616200000082
Figure BDA0001683616200000083
Figure BDA0001683616200000084
step 4, verifying the fitting precision and the prediction precision of the geometric characteristics of the cladding layer of the single cladding channel and the dilution rate model, wherein the specific method comprises the following steps:
And (3) calculating the fitting precision of the geometric characteristics of the cladding layer of the single cladding channel and the dilution rate model by applying a re-determination coefficient R shown in the following formula:
Figure BDA0001683616200000085
wherein n is the sample number of the test piece used in the single cladding channel orthogonal experiment, yiIs the measured value of the single cladding channel orthogonal experiment,
Figure BDA0001683616200000086
fitting values of geometric characteristics of the cladding layer of the single cladding channel and a dilution rate model, i' is 1, 2 … and n;
substituting the process parameters related to the geometrical characteristics and the dilution rate of the cladding layer obtained by the single-cladding-channel single-factor experiment into a geometrical characteristics and dilution rate model of the cladding layer of the single-cladding channel, comparing the obtained geometrical characteristic size and dilution rate of the cladding layer with data obtained by actual measurement, and verifying the prediction accuracy of the geometrical characteristics and the dilution rate model of the cladding layer of the single-cladding channel by a prediction coefficient shown in the following formula:
Figure BDA0001683616200000087
where η is a prediction coefficient.
In this example, the model calculation fitting values based on the orthogonal test process parameter combination are shown in table 5, and the cladding height H and the cladding layer cross sectionProduct SRThe melting area S of the matrixJModel fitting with dilution ratio λ the coefficient R was determined computationally, as shown in FIG. 520.9995, 0.9992, 0.9990 and 0.9998 respectively.
TABLE 5 model calculated fit values based on orthogonal test Process parameter combinations
Figure BDA0001683616200000088
Figure BDA0001683616200000091
In this embodiment, the combination of the process parameters of the single-cladding single-factor experiment is substituted into the mathematical model, the geometric feature size and the dilution ratio fitting value obtained as shown in table 6 are compared with the actual measurement calculation data of the single-factor experiment, and the prediction accuracy of the mathematical model is verified by a prediction coefficient formula.
In this embodiment, the established cladding height H and the cladding layer cross-sectional area S are displayed through the verification resultRBase melting area SJAnd the prediction accuracy of the interactive linear regression model of the dilution ratio lambda reaches 95.08%, 92.02%, 88.32% and 96.94% respectively, and the model verification pair is shown in figure 6.
TABLE 6 geometric feature size and dilution ratio fit values for single cladding pass
Figure BDA0001683616200000092
Figure BDA0001683616200000101
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions and scope of the present invention as defined in the appended claims.

Claims (2)

1. A modeling method for geometric characteristics and dilution rate of a laser additive remanufacturing cladding layer is characterized by comprising the following steps: the method comprises the following steps:
step 1, obtaining an optimal range of process parameters related to geometrical characteristics and dilution rate of a cladding layer and verification data for verifying the geometrical characteristics and dilution rate model of the single cladding channel through a single-factor experiment of laser additive remanufacturing;
the process parameters related to the geometric characteristics and dilution rate of the cladding layer comprise laser power P and scanning speed VSAnd powder feeding rate VF；
Step 2, obtaining process parameter combination and model modeling data related to geometrical characteristics and dilution rate of a cladding layer through a single cladding channel orthogonal experiment;
cutting a test piece of a single cladding channel orthogonal experiment to obtain a cladding layer section sample, and measuring geometrical characteristics of the cladding layer by using an optical super-depth-of-field three-dimensional microscope, wherein the geometrical characteristics comprise a cladding height H and a cladding layer cross-sectional area SRAnd the matrix melting area SJ(ii) a And calculating the dilution ratio lambda through the geometrical characteristics of the cladding layer, wherein the formula is as follows:
[SJ/(SR+SJ)]×100％
the measured cladding height H and the cross section area S of the cladding layerRAnd the melting area S of the matrixJPerforming range analysis on the calculated dilution ratio lambda to determine a process parameter combination related to the geometric characteristics and the dilution ratio of the cladding layer; and the cladding height H and the cross section area S of the cladding layer RAnd the melting area S of the matrixJAnd the dilution rate lambda is used as the original data of the geometric characteristics of the cladding layer of the single cladding channel and the dilution rate model;
step 3, establishing an interactive linear regression relational expression of the geometric characteristics and the dilution rate of the cladding layer of the single cladding channel, and solving coefficients in the relational expression by a particle swarm BreedPSO algorithm based on a hybridization theory to complete modeling of the geometric characteristics and the dilution rate of the cladding layer of the single cladding channel;
establishing a regression relation among the process parameters, the geometrical characteristics of the cladding layer and the dilution rate based on a quadratic regression model with interactive effect coefficients, wherein the formula is as follows:
Figure FDA0003406650160000011
Figure FDA0003406650160000012
Figure FDA0003406650160000013
Figure FDA0003406650160000014
wherein, H (P, V)S,VF) Is the height of the cladding layer, SR(P,VS,VF) Is the cross-sectional area of the cladding layer, SJ(P,VS,VF) Is the melting area of the matrix, lambda (P, V)S,VF) To the dilution ratio, alpha0、β0、χ0And delta0Coefficient of constant term, α, both of regression equationsi、βi、χiAnd deltaiCoefficient of first order of regression equation, alphaii、βii、χiiAnd deltaiiCoefficient of quadratic term, α, both regression equationsij、βij、χijAnd deltaijThe coefficient of the interaction effect is a regression equation, i is 1, 2 and 3, j is 1, 2 and 3, i is not equal to j, and epsilon is an error term;
and 4, verifying the fitting precision and the prediction precision of the geometric characteristics of the cladding layer of the single cladding channel and the dilution rate model.
2. The laser additive remanufacturing cladding layer geometric feature and dilution ratio modeling method according to claim 1, wherein: the specific method in the step 4 comprises the following steps:
And (3) calculating the fitting precision of the geometric characteristics of the cladding layer of the single cladding channel and the dilution rate model by applying a re-determination coefficient R shown in the following formula:
Figure FDA0003406650160000021
wherein n is the sample number of the test piece used in the single cladding channel orthogonal experiment, yiIs the measured value of the single cladding channel orthogonal experiment,
Figure FDA0003406650160000022
fitting values of geometric characteristics of the cladding layer of the single cladding channel and a dilution rate model, i' is 1, 2 … and n;
substituting the process parameters related to the geometrical characteristics and the dilution rate of the cladding layer obtained by the single-cladding-channel single-factor experiment into a geometrical characteristics and dilution rate model of the cladding layer of the single-cladding channel, comparing the obtained geometrical characteristic size and dilution rate of the cladding layer with data obtained by actual measurement, and verifying the prediction accuracy of the geometrical characteristics and the dilution rate model of the cladding layer of the single-cladding channel by a prediction coefficient shown in the following formula:
Figure FDA0003406650160000023
where η is the prediction coefficient.
CN201810562315.3A 2018-06-04 2018-06-04 Modeling method for geometric characteristics and dilution rate of laser additive remanufacturing cladding layer Active CN108763801B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810562315.3A CN108763801B (en) 2018-06-04 2018-06-04 Modeling method for geometric characteristics and dilution rate of laser additive remanufacturing cladding layer

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810562315.3A CN108763801B (en) 2018-06-04 2018-06-04 Modeling method for geometric characteristics and dilution rate of laser additive remanufacturing cladding layer

Publications (2)

Publication Number Publication Date
CN108763801A CN108763801A (en) 2018-11-06
CN108763801B true CN108763801B (en) 2022-06-03

Family

ID=64002424

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810562315.3A Active CN108763801B (en) 2018-06-04 2018-06-04 Modeling method for geometric characteristics and dilution rate of laser additive remanufacturing cladding layer

Country Status (1)

Country Link
CN (1) CN108763801B (en)

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109473145A (en) * 2018-11-07 2019-03-15 桂林电子科技大学 A kind of electron beam cladding process parameter optimizing method and system based on Orthogonal Method
CN112857271B (en) * 2021-01-08 2022-03-11 中国科学院力学研究所 Method for judging stability of laser cladding process
CN113059186B (en) * 2021-03-19 2022-09-16 沈阳工业大学 Low-carbon modeling and process parameter optimization method in laser additive manufacturing process
CN114003003A (en) * 2021-08-04 2022-02-01 上海航天设备制造总厂有限公司 Technological parameter optimization and stability control method in laser cladding process
CN114346260B (en) * 2022-01-04 2022-10-21 大连理工大学 Geometric feature prediction method for laser melting deposition layer
CN115945698B (en) * 2023-03-13 2023-05-23 西安石油大学 Metal cladding layer forming quality optimization method based on CMT additive remanufacturing

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106484968A (en) * 2016-09-23 2017-03-08 西安交通大学 A kind of method for quick predicting of the heat exchange Correlations based on response surface
CN106529129A (en) * 2016-10-21 2017-03-22 武汉理工大学 Cladding layer cross section contour curve under broadband laser effect and modeling method
EP3316156A1 (en) * 2016-11-01 2018-05-02 Xometry, Inc. Methods and apparatus for machine learning predictions of manufacture processes
CN108036735A (en) * 2017-11-29 2018-05-15 武汉理工大学 A kind of broadband laser cladding molten bath contour curve and its modeling method
CN108062433A (en) * 2017-11-26 2018-05-22 中国人民解放军陆军装甲兵学院 The gradient curved surface layered approach of point cloud model is remanufactured based on increasing material

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106484968A (en) * 2016-09-23 2017-03-08 西安交通大学 A kind of method for quick predicting of the heat exchange Correlations based on response surface
CN106529129A (en) * 2016-10-21 2017-03-22 武汉理工大学 Cladding layer cross section contour curve under broadband laser effect and modeling method
EP3316156A1 (en) * 2016-11-01 2018-05-02 Xometry, Inc. Methods and apparatus for machine learning predictions of manufacture processes
CN108062433A (en) * 2017-11-26 2018-05-22 中国人民解放军陆军装甲兵学院 The gradient curved surface layered approach of point cloud model is remanufactured based on increasing material
CN108036735A (en) * 2017-11-29 2018-05-15 武汉理工大学 A kind of broadband laser cladding molten bath contour curve and its modeling method

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
pindle static and dynamic characteristics analysis of precision CNC turning center;Chenguang Guo 等;《ydraulic equipment and support systems for mining, IWHEM2012》;20121231;47-51 *
面向绿色再制造的单道激光熔覆几何特征的研究;许波;《中国优秀硕士学位论文全文数据库（工程科技Ⅰ辑）》;20111105;B022-52 *

Also Published As

Publication number Publication date
CN108763801A (en) 2018-11-06

Similar Documents

Publication Publication Date Title
CN108763801B (en) Modeling method for geometric characteristics and dilution rate of laser additive remanufacturing cladding layer
Di Angelo et al. Surface quality prediction in FDM additive manufacturing
García Plaza et al. Analysis of PLA geometric properties processed by FFF additive manufacturing: Effects of process parameters and plate-extruder precision motion
Galantucci et al. Analysis of dimensional performance for a 3D open-source printer based on fused deposition modeling technique
Ahn et al. Quantification of surface roughness of parts processed by laminated object manufacturing
CN102962452B (en) Metal laser deposition manufactured scan route planning method based on infrared temperature measurement images
AU2014204284B2 (en) Object production using an additive manufacturing process and quality assessment of the object
Yehorov et al. Balancing WAAM production costs and wall surface quality through parameter selection: a case study of an Al-Mg5 alloy multilayer-non-oscillated single pass wall
CN107102061A (en) Metal material high energy beam increases and decreases the online laser ultrasonic detection combined machining method of material
CN106770634A (en) A kind of metal material high energy beam increases and decreases the online EDDY CURRENT combined machining method of material
Almabrouk Mousa Experimental investigations of curling phenomenon in selective laser sintering process
US20190001655A1 (en) Systems and method for advanced additive manufacturing
Gurrala et al. DOE based parametric study of volumetric change of FDM parts
CN112214864B (en) Multichannel multilayer laser cladding layer size prediction method
CN109145453B (en) Method for calculating thermal field for electric arc additive manufacturing of complex characteristic structural member
CN106529051A (en) Method for determining heat source model parameters of single wire submerged arc welding numerical simulation
Patel et al. Parametric optimization of the process of fused deposition modeling in rapid prototyping technology-a review
Ni et al. Forming optimization for WAAM with weaving deposition on curved surfaces
Alsoufi et al. From 3D models to FDM 3D prints: Experimental study of chemical treatment to reduce stairs-stepping of semi-sphere profile
Tang et al. Arc length identification based on arc acoustic signals in GTA-WAAM process
Saqib et al. Investigation of the transient characteristics for laser cladding beads using 420 stainless steel powder
Chen et al. Prediction of multi-bead profile of robotic wire and arc additive manufactured components recursively using axisymmetric drop shape analysis
McMillan et al. SLM lattice thermal fields acquired by wide-field thermal camera
Wang et al. Remanufacturing oriented multilayer cladding morphology prediction using a new second order fitting method
Huang et al. Effect of fabrication parameters and material features on surface roughness of fdm build parts

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant