CN110286046A - A kind of DED process Hardness Prediction method and device based on temperature field - Google Patents
A kind of DED process Hardness Prediction method and device based on temperature field Download PDFInfo
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- CN110286046A CN110286046A CN201910340374.0A CN201910340374A CN110286046A CN 110286046 A CN110286046 A CN 110286046A CN 201910340374 A CN201910340374 A CN 201910340374A CN 110286046 A CN110286046 A CN 110286046A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N3/00—Investigating strength properties of solid materials by application of mechanical stress
- G01N3/40—Investigating hardness or rebound hardness
- G01N3/54—Performing tests at high or low temperatures
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2203/00—Investigating strength properties of solid materials by application of mechanical stress
- G01N2203/0058—Kind of property studied
- G01N2203/0076—Hardness, compressibility or resistance to crushing
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2203/00—Investigating strength properties of solid materials by application of mechanical stress
- G01N2203/02—Details not specific for a particular testing method
- G01N2203/022—Environment of the test
- G01N2203/0222—Temperature
- G01N2203/0228—Low temperature; Cooling means
Abstract
The present invention provides a kind of DED process Hardness Prediction method and device based on temperature field, can predict the hardness distribution situation of entire part to be measured.The described method includes: the characteristics of being directed to heat mechanical periodicity in DED technique print procedure exposure cycles, temperature field key temperatures feature；In DED forming process, according to determining temperature field key temperatures feature, the temperature field data of the fractional-sample point of part to be measured is obtained；According to the shape of part to be measured, three-dimensional system of coordinate is established；According to temperature changing regularity of the key temperatures feature of temperature field data on three dimension directions of part to be measured, part hardness prediction is carried out from three dimensions, obtains the hardness distribution situation of entire part to be measured.The present invention relates to non-destructive monitoring fields.
Description
Technical field
The present invention relates to non-destructive monitoring field, particularly relate to a kind of DED process Hardness Prediction method based on temperature field and
Device.
Background technique
DIRECT ENERGY deposition (DED) be using laser technology, CAD and manufacture (CAD/CAM), robot,
The interdisciplinary technology of sensor and control and powder metallurgy.DED technology is a kind of metallic addition manufacture (AM) method, is passed through
The raw material (wire or powder) of fusing is deposited to required spatial position by deposition head, so that material be made quickly to solidify.With powder
Unlike last bed precinct laser fusion metal (SLM) technology, DED technology can protect gold independent of pressure chamber, pressure chamber
Belong to print procedure to exempt to be affected by the surrounding environment.For SLM print procedure, working region must be first filled with inert gas, this
It is a time-consuming process.And for the laser metal powder deposition technique in DED technique classification, because inert gas is straight
It connects and powder stream and molten bath is flowed out and surrounded from laser head, printing process can be immediately begun to.DED is received greatly in recent years
Concern, because it can be used for a variety of materials processing activity, such as metal coating, high value element reparation, raw basin, in addition it is small quantities of
Amount production.But may be excessively inconsistent and unreliable using the part that DED technology manufactures, it is unable to satisfy many industrial applications
Hardness requirement.In DED forming process, hardness is the important indicator of verifying printing design of part integrality and assembly quality, with
It determines if the characteristic for having specified use requirement, thus prediction in real time is carried out with important to part hardness in process
Meaning.
Currently, Chinese patent literature (application number: 201811202776.6, the applying date: 2018.10.16, application publication number:
109409271 A of CN) one kind is disclosed based on reverse transmittance nerve network (Back Propagation Neural
Network, BP neural network) innovatory algorithm Testing of Ferromagnetic Material Hardness prediction algorithm.The algorithm acquires bar of ferromagnetic material first
Ke Haosen signal divides signal collection, obtains Barkhausen noise training set and Barkhausen noise test set；Then right
The signal of acquisition carries out autoregressive spectrum (Autoregression spectrum, AR spectrum) analysis, selects 5 order expansion, respectively
It is 4,8,16,32,64 ranks, asks second order to lead the signal of expansion, and wide with the paddy that second order leads signal, paddy is deeply and where valley point
Position carries out distance using K mean value (k-means) algorithm as feature, to these paddy, encodes to signal, so as to complete
The unification of characteristic dimension；Then BP neural network model is optimized and training.Emulation shows the result of the invention predicted very
Good, mean square error only has 80, that is, the error of each Hardness Prediction can guarantee in 9 Vickers hardnesses, and Time-Domain algorithm
Mean square error is 229, that is, is greater than 15 Vickers hardnesses, so demonstrating algorithm validity.But there is no needles for the algorithm
To the characteristics of heat mechanical periodicity, carrying out distribution non-destructive prediction to part hardness in DED technique print procedure exposure cycles.
Summary of the invention
The technical problem to be solved in the present invention is to provide a kind of DED process Hardness Prediction method and dress based on temperature field
It sets, to solve present in the prior art without in DED technique print procedure exposure cycles the characteristics of heat mechanical periodicity,
The problem of distribution non-destructive prediction is carried out to part hardness.
In order to solve the above technical problems, the embodiment of the present invention provides a kind of DED process Hardness Prediction side based on temperature field
Method, comprising:
For the characteristics of heat mechanical periodicity, temperature field key temperatures are special in DED technique print procedure exposure cycles
Sign；
In DED forming process, according to determining temperature field key temperatures feature, the fractional-sample point of part to be measured is obtained
Temperature field data；
According to the shape of part to be measured, three-dimensional system of coordinate is established；
According to temperature changing regularity of the key temperatures feature of temperature field data on three dimension directions of part to be measured, from
Three dimensions carry out part hardness prediction, obtain the hardness distribution situation of entire part to be measured.
Further, the fractional-sample point is that every layer of part to be measured fixes the point of position at equal intervals and to represent hardness total
Body distribution situation.
Further, the temperature field key temperatures feature includes: the direction x key temperatures feature, the direction y key temperatures spy
Sign and the direction z key temperatures feature；Wherein,
The direction x key temperatures feature is depositing temperature in sampled point exposure cycles, cooling temperature, cooling rate and averagely sinks
Accumulated temperature degree；
The direction y key temperatures feature is depositing temperature and cooling temperature in sampled point exposure cycles；
The direction z key temperatures feature is depositing temperature in sampled point exposure cycles, cooling temperature, depositing temperature gradient and puts down
Equal depositing temperature.
Further, exposure cycles are that one sampled point of DED process occurs until being capped the time used, but do not include by
When covering；
Depositing temperature is the maximum temperature in an exposure cycles；
Cooling temperature is the minimum temperature in an exposure cycles.
Further, cooling rate indicates in X-direction are as follows:
V=(tX+100)/s
Wherein, v indicates the cooling rate in X-direction, and tX is coordinate y, minimum in the identical sampled point exposure cycles of z
Temperature, s are that sampled point reduces the time required for 100 degree of arrival tX.
Further, average deposition temperature indicates in X-direction are as follows:
Wherein, TX is average deposition temperature in X-direction, TxyzIt is in the sampled point exposure cycles of (x, y, z) for coordinate
Maximum temperature, m, n, l respectively indicate the number of sampling points of x, y, z direction selection.
Further, average deposition temperature indicates in Z-direction are as follows:
Wherein, TZ indicates average deposition temperature in Z-direction, TxyzIt is in the sampled point exposure cycles of (x, y, z) for coordinate
Maximum temperature.
Further, depositing temperature gradient is expressed as in Z-direction:
Wherein, grad indicates depositing temperature gradient in Z-direction, TZn+1With TZnThe respectively identical phase of layer printing starting point
Adjacent 2 layers of average deposition temperature, tinterFor the layer printing starting point time interval that adjacent 2 layers of printing starts when identical.
Further, temperature of the key temperatures feature according to temperature field data on three dimension directions of part to be measured
Changing rule is spent, carries out part hardness prediction from three dimensions, the hardness distribution situation for obtaining entire part to be measured includes:
A1, it is pre- in the regularity of distribution of z-axis according to depositing temperature, cooling temperature, depositing temperature gradient and average deposition temperature
Hardness is surveyed with the increased variation tendency of the number of plies；
A2, the regularity of distribution according to depositing temperature, cooling rate, cooling temperature and average deposition temperature in x-axis are predicted firmly
Spend the trend changed with lengthwise location；
A3 changes in the regularity of distribution prediction hardness of y-axis with width position according to depositing temperature and cooling temperature
Trend；
A4 determines the entire maximum area of part hardness distribution situation and hardness to be measured according to A1, A2 and A3 prediction result
Domain.
The embodiment of the present invention also provides a kind of DED process Hardness Prediction device based on temperature field, comprising:
Determining module is used for the characteristics of being directed to heat mechanical periodicity in DED technique print procedure exposure cycles, temperature
Field key temperatures feature；
Module is obtained, for according to determining temperature field key temperatures feature, obtaining to be measured zero in DED forming process
The temperature field data of the fractional-sample point of part；
Module is established, for the shape according to part to be measured, establishes three-dimensional system of coordinate；
Prediction module, for temperature of the key temperatures feature according to temperature field data on three dimension directions of part to be measured
Changing rule is spent, part hardness prediction is carried out from three dimensions, obtains the hardness distribution situation of entire part to be measured.
The advantageous effects of the above technical solutions of the present invention are as follows:
In above scheme, in DED technique print procedure exposure cycles the characteristics of heat mechanical periodicity, temperature field
Key temperatures feature；In DED forming process, according to determining temperature field key temperatures feature, the part of part to be measured is obtained
The temperature field data of sampled point；According to the shape of part to be measured, three-dimensional system of coordinate is established；According to the key temperatures of temperature field data
Temperature changing regularity of the feature on three dimension directions of part to be measured carries out part hardness prediction from three dimensions, obtains whole
The hardness distribution situation of a part to be measured.In this way, by the efficient and inexpensive realization of temperature changing regularity energy to part hardness
Overall distribution non-destructive prediction will not cause any destruction to part.
Detailed description of the invention
Fig. 1 is the flow diagram of the DED process Hardness Prediction method provided in an embodiment of the present invention based on temperature field；
Fig. 2 is three-dimensional system of coordinate schematic diagram provided in an embodiment of the present invention；
Fig. 3 is key temperatures characterizing definition schematic diagram in temperature field provided in an embodiment of the present invention；
Fig. 4 is the schematic illustration of the DED process Hardness Prediction method provided in an embodiment of the present invention based on temperature field；
Fig. 5 is the structural schematic diagram of the DED process Hardness Prediction device provided in an embodiment of the present invention based on temperature field.
Specific embodiment
To keep the technical problem to be solved in the present invention, technical solution and advantage clearer, below in conjunction with attached drawing and tool
Body embodiment is described in detail.
The present invention is directed to existing no the characteristics of being directed to heat mechanical periodicity in DED technique print procedure exposure cycles,
The problem of carrying out distribution non-destructive prediction to part hardness provides a kind of DED process Hardness Prediction method and dress based on temperature field
It sets.
Embodiment one
As shown in Figure 1, the DED process Hardness Prediction method provided in an embodiment of the present invention based on temperature field, comprising:
S101, for the characteristics of heat mechanical periodicity, temperature field is crucial warm in DED technique print procedure exposure cycles
Spend feature；
S102, according to determining temperature field key temperatures feature, obtains the part of part to be measured in DED forming process
The temperature field data of sampled point；
S103 establishes three-dimensional system of coordinate according to the shape of part to be measured；
S104 is advised according to temperature change of the key temperatures feature of temperature field data on three dimension directions of part to be measured
Rule carries out part hardness prediction from three dimensions, obtains the hardness distribution situation of entire part to be measured.
DED process Hardness Prediction method described in the embodiment of the present invention based on temperature field, for DED technique print procedure
In exposure cycles the characteristics of heat mechanical periodicity, temperature field key temperatures feature；In DED forming process, according to determination
Temperature field key temperatures feature, obtain the temperature field data of the fractional-sample point of part to be measured；According to the shape of part to be measured,
Establish three-dimensional system of coordinate；According to temperature change of the key temperatures feature of temperature field data on three dimension directions of part to be measured
Rule carries out part hardness prediction from three dimensions, obtains the hardness distribution situation of entire part to be measured.In this way, passing through temperature
The efficient and inexpensive realization of changing rule energy will not cause any broken part hardness overall distribution non-destructive prediction to part
It is bad.
In the present embodiment, the fractional-sample point is that every layer of part to be measured fixes the point of position at equal intervals and can represent hardness
Overall distribution situation.
In the present embodiment, as shown in Fig. 2, three dimensions are the suitable three-dimensionals established according to part concrete shape to be measured
The x, y, z direction of coordinate system.
In the present embodiment, in DED technique print procedure exposure cycles the characteristics of heat mechanical periodicity, temperature field
Key temperatures feature；Temperature field key temperatures are characterized in being chosen from the direction x, the direction y, three, the direction z dimension, wherein
The temperature field key temperatures feature includes: the direction x key temperatures feature, the direction y key temperatures feature and the direction z key temperatures
Feature.
In the present embodiment, the direction x key temperatures feature is depositing temperature, cooling temperature, cooling in sampled point exposure cycles
Rate and average deposition temperature；The direction y key temperatures feature is depositing temperature and cooling temperature in sampled point exposure cycles；The side z
It is depositing temperature, cooling temperature, depositing temperature gradient and average deposition temperature in sampled point exposure cycles to key temperatures feature.
In the present embodiment, as shown in figure 3, exposure cycles are that one sampled point of DED process occurs when capped used
Between, but do not include when being capped；Depositing temperature is the maximum temperature in an exposure cycles；Cooling temperature is an exposure cycles
Interior minimum temperature.
In the present embodiment, part hardness prediction is carried out from three dimensions of x, y, z, wherein needing to illustrate following temperature feature meter
Calculation method:
1) in Z-direction average deposition temperature calculation formula are as follows:
Wherein, TZ indicates average deposition temperature in Z-direction, TxyzIt is in the sampled point exposure cycles of (x, y, z) for coordinate
Maximum temperature, m, n, l respectively indicate x, y, z direction selection number of sampling points.
2) in Z-direction depositing temperature gradient calculation formula are as follows:
Wherein, grad indicates depositing temperature gradient in Z-direction, TZn+1With TZnThe respectively identical phase of layer printing starting point
Adjacent 2 layers of average deposition temperature, tinterFor the layer printing starting point time interval that adjacent 2 layers of printing starts when identical.
3) calculation formula of average deposition temperature indicates in X-direction are as follows:
Wherein, TX is average deposition temperature in X-direction, TxyzIt is in the sampled point exposure cycles of (x, y, z) for coordinate
Maximum temperature.
4) calculation formula of cooling rate indicates in X-direction are as follows:
V=(tX+100)/s
Wherein, v indicates the cooling rate in X-direction, and tX is coordinate y, minimum in the identical sampled point exposure cycles of z
Temperature, s are that sampled point reduces the time required for 100 degree of arrival tX.
In the present embodiment, formula v=(tX+100)/s is only used for sampled point exposure cycles approximation, and tX is approximate, and s difference is obvious
The case where, wherein approximation refers to that the temperature difference is less than preset first threshold, and difference obviously refers to that time difference is greater than preset second threshold
Value.
In the specific embodiment of the aforementioned DED process Hardness Prediction method based on temperature field, further, described
According to temperature changing regularity of the key temperatures feature of temperature field data on three dimension directions of part to be measured, from three dimensions into
The prediction of row part hardness, the hardness distribution situation for obtaining entire part to be measured include:
A1, it is pre- in the regularity of distribution of z-axis according to depositing temperature, cooling temperature, depositing temperature gradient and average deposition temperature
Hardness is surveyed with the increased variation tendency of the number of plies；
A2, the regularity of distribution according to depositing temperature, cooling rate, cooling temperature and average deposition temperature in x-axis are predicted firmly
Spend the trend changed with lengthwise location；
A3 changes in the regularity of distribution prediction hardness of y-axis with width position according to depositing temperature and cooling temperature
Trend；
A4 determines the entire maximum area of part hardness distribution situation and hardness to be measured according to A1, A2 and A3 prediction result
Domain.
As shown in figure 4, the DED process Hardness Prediction method described in the embodiment of the present invention based on temperature field, for DED work
Temperature field key temperatures feature the characteristics of heat mechanical periodicity in printing process process exposure cycles, real-time monitoring and obtain to
The temperature field data of the fractional-sample point of part is surveyed, and the temperature field data obtained carries out Gaussian smoothing denoising, in conjunction with
Changing rule of the key temperatures feature on three dimension directions of part to be measured, from three dimensions (direction x, the direction y, the direction z)
Part hardness prediction is carried out, relationship between temperature profile and hardness is obtained in three dimensions, according to temperature in three obtained dimension
Relationship between feature and hardness further obtains the hardness distribution situation of entire part, to realize to DED forming part hardness point
The non-destructive prediction of cloth, and it is at low cost, easy to operate；Predict that obtained hardness distribution situation is verifying printing design of part integrality
With the important indicator of assembly quality, facilitate following process control, improvement and optimization.
Embodiment two
The specific embodiment of the present invention also provides a kind of DED process Hardness Prediction device based on temperature field, due to this
The DED process Hardness Prediction device provided based on temperature field and the aforementioned DED process Hardness Prediction side based on temperature field are provided
The specific embodiment of method is corresponding, and the execution above method can be passed through by being somebody's turn to do the DED process Hardness Prediction device based on temperature field
Process step in specific embodiment achieves the object of the present invention, therefore the above-mentioned DED process hardness based on temperature field is pre-
It is pre- to be also applied for the DED process hardness provided by the invention based on temperature field for explanation in survey method specific embodiment
The specific embodiment for surveying device will not be described in great detail in present invention specific embodiment below.
As shown in figure 5, the embodiment of the present invention also provides a kind of DED process Hardness Prediction device based on temperature field, comprising:
Determining module 11, for warm for the characteristics of heat mechanical periodicity, being determined in DED technique print procedure exposure cycles
Spend field key temperatures feature；
Module 12 is obtained, for according to determining temperature field key temperatures feature, obtaining to be measured in DED forming process
The temperature field data of the fractional-sample point of part；
Module 13 is established, for the shape according to part to be measured, establishes three-dimensional system of coordinate；
Prediction module 14, for the key temperatures feature according to temperature field data on three dimension directions of part to be measured
Temperature changing regularity carries out part hardness prediction from three dimensions, obtains the hardness distribution situation of entire part to be measured.
DED process Hardness Prediction device described in the embodiment of the present invention based on temperature field, for DED technique print procedure
In exposure cycles the characteristics of heat mechanical periodicity, temperature field key temperatures feature；In DED forming process, according to determination
Temperature field key temperatures feature, obtain the temperature field data of the fractional-sample point of part to be measured；According to the shape of part to be measured,
Establish three-dimensional system of coordinate；According to temperature change of the key temperatures feature of temperature field data on three dimension directions of part to be measured
Rule carries out part hardness prediction from three dimensions, obtains the hardness distribution situation of entire part to be measured.In this way, passing through temperature
The efficient and inexpensive realization of changing rule energy will not cause any broken part hardness overall distribution non-destructive prediction to part
It is bad.
It should be noted that, in this document, relational terms such as first and second and the like are used merely to a reality
Body or operation are distinguished with another entity or operation, are deposited without necessarily requiring or implying between these entities or operation
In any actual relationship or order or sequence.
The above is a preferred embodiment of the present invention, it is noted that for those skilled in the art
For, without departing from the principles of the present invention, several improvements and modifications can also be made, these improvements and modifications
It should be regarded as protection scope of the present invention.
Claims (10)
1. a kind of DED process Hardness Prediction method based on temperature field characterized by comprising
For in DED technique print procedure exposure cycles the characteristics of heat mechanical periodicity, temperature field key temperatures feature,
In, DED indicates DIRECT ENERGY deposition；
In DED forming process, according to determining temperature field key temperatures feature, the temperature of the fractional-sample point of part to be measured is obtained
Spend field data；
According to the shape of part to be measured, three-dimensional system of coordinate is established；
According to temperature changing regularity of the key temperatures feature of temperature field data on three dimension directions of part to be measured, from three
Dimension carries out part hardness prediction, obtains the hardness distribution situation of entire part to be measured.
2. the DED process Hardness Prediction method according to claim 1 based on temperature field, which is characterized in that the part
Sampled point is that every layer of part to be measured fixes the point of position at equal intervals and can represent hardness overall distribution situation.
3. the DED process Hardness Prediction method according to claim 1 based on temperature field, which is characterized in that the temperature
Field key temperatures feature includes: the direction x key temperatures feature, the direction y key temperatures feature and the direction z key temperatures feature；Its
In,
The direction x key temperatures feature is depositing temperature, cooling temperature, cooling rate and average deposition temperature in sampled point exposure cycles
Degree；
The direction y key temperatures feature is depositing temperature and cooling temperature in sampled point exposure cycles；
The direction z key temperatures feature is depositing temperature in sampled point exposure cycles, cooling temperature, depositing temperature gradient and averagely sinks
Accumulated temperature degree.
4. the DED process Hardness Prediction method according to claim 3 based on temperature field, which is characterized in that exposure cycles
Occur for one sampled point of DED process until being capped the time used, but does not include when being capped；
Depositing temperature is the maximum temperature in an exposure cycles；
Cooling temperature is the minimum temperature in an exposure cycles.
5. the DED process Hardness Prediction method according to claim 3 based on temperature field, which is characterized in that in X-direction
Cooling rate indicates are as follows:
V=(tX+100)/s
Wherein, v indicates the cooling rate in X-direction, and tX is coordinate y, the lowest temperature in the identical sampled point exposure cycles of z
Degree, s are that sampled point reduces the time required for 100 degree of arrival tX.
6. the DED process Hardness Prediction method according to claim 3 based on temperature field, which is characterized in that in X-direction
Average deposition temperature indicates are as follows:
Wherein, TX is average deposition temperature in X-direction, TxyzIt is the highest in the sampled point exposure cycles of (x, y, z) for coordinate
Temperature, m, n, l respectively indicate the number of sampling points of x, y, z direction selection.
7. the DED process Hardness Prediction method according to claim 3 based on temperature field, which is characterized in that in Z-direction
Average deposition temperature indicates are as follows:
Wherein, TZ indicates average deposition temperature in Z-direction, TxyzFor in sampled point exposure cycles that coordinate is (x, y, z) most
High-temperature.
8. the DED process Hardness Prediction method according to claim 7 based on temperature field, which is characterized in that in Z-direction
Depositing temperature gradient is expressed as:
Wherein, grad indicates depositing temperature gradient in Z-direction, TZn+1With TZnIt is 2 layers adjacent when respectively layer printing starting point is identical
Average deposition temperature, tinterFor the layer printing starting point time interval that adjacent 2 layers of printing starts when identical.
9. the DED process Hardness Prediction method according to claim 3 based on temperature field, which is characterized in that the basis
Temperature changing regularity of the key temperatures feature of temperature field data on three dimension directions of part to be measured is carried out from three dimensions
Part hardness prediction, the hardness distribution situation for obtaining entire part to be measured include:
A1, the regularity of distribution according to depositing temperature, cooling temperature, depositing temperature gradient and average deposition temperature in z-axis are predicted firmly
Degree is with the increased variation tendency of the number of plies；
A2, according to depositing temperature, cooling rate, cooling temperature and average deposition temperature x-axis the regularity of distribution prediction hardness with
The trend of lengthwise location variation；
A3, the trend changed in the regularity of distribution prediction hardness of y-axis with width position according to depositing temperature and cooling temperature；
A4 determines the entire maximum region of part hardness distribution situation and hardness to be measured according to A1, A2 and A3 prediction result.
10. a kind of DED process Hardness Prediction device based on temperature field characterized by comprising
Determining module, for for the characteristics of heat mechanical periodicity, temperature field is closed in DED technique print procedure exposure cycles
Key temperature profile；
Module is obtained, for according to determining temperature field key temperatures feature, obtaining part to be measured in DED forming process
The temperature field data of fractional-sample point；
Module is established, for the shape according to part to be measured, establishes three-dimensional system of coordinate；
Prediction module becomes for temperature of the key temperatures feature according to temperature field data on three dimension directions of part to be measured
Law carries out part hardness prediction from three dimensions, obtains the hardness distribution situation of entire part to be measured.
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| US20210197282A1 (en) * | 2019-12-31 | 2021-07-01 | Korea Advanced Institute Of Science And Technology | Method and apparatus for estimating height of 3d printing object formed during 3d printing process, and 3d printing system having the same |
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| SARAH J. WOLFF 等: "Experimentally validated predictions of thermal history and microhardness in laser-deposited Inconel 718 on carbon steel", 《ADDITIVE MANUFACTURING》 * |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20210197282A1 (en) * | 2019-12-31 | 2021-07-01 | Korea Advanced Institute Of Science And Technology | Method and apparatus for estimating height of 3d printing object formed during 3d printing process, and 3d printing system having the same |
| CN113118456A (en) * | 2019-12-31 | 2021-07-16 | 韩国科学技术院 | Method and apparatus for estimating height of 3D printed object formed in 3D printing process, and 3D printing system |
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| CN110286046B (en) | 2020-06-19 |
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